St. Petersburg University
Graduate School of Management
Master in Management Program
DIGITALIZATION AND WAREHOUSE MANAGEMENT IN RUSSIA:
AN APPROACH FOR IMPLEMENTATION OF DIGITAL SOLUTIONS
Master’s Thesis by the 2nd year student
Concentration – International Logistics
and
Supply Chain Management
Karina Naumova
Research advisor:
Axel Theo Schulte,
Dr./PhD, Associate Professor
St. Petersburg
2016
ЗАЯВЛЕНИЕ О САМОСТОЯТЕЛЬНОМ ХАРАКТЕРЕ ВЫПОЛНЕНИЯ
ВЫПУСКНОЙ КВАЛИФИКАЦИОННОЙ РАБОТЫ
Я , Наумова Карина Владимировна, студентка второго курса магистратуры
направления «Менеджмент», заявляю, что в моей магистерской диссертации на тему
«Цифровые технологии для складской логистики в России: алгоритм внедрения цифровых
технологий», представленной в службу обеспечения программ магистратуры для
последующей передачи в государственную аттестационную комиссию для публичной
защиты, не содержится элементов плагиата.
Все прямые заимствования из печатных и электронных источников, а также из
защищенных ранее выпускных квалификационных работ, кандидатских и докторских
диссертаций имеют соответствующие ссылки.
Мне известно содержание п. 9.7.1 Правил обучения по основным образовательным
программам высшего и среднего профессионального образования в СПбГУ о том, что
«ВКР выполняется индивидуально каждым студентом под руководством назначенного ему
научного руководителя», и п. 51 Устава федерального государственного бюджетного
образовательного учреждения высшего образования «Санкт-Петербургский
государственный университет» о том, что «студент подлежит отчислению из СанктПетербургского университета за представление курсовой или выпускной
квалификационной работы, выполненной другим лицом (лицами)».
(Подпись студента)
26.05.2016 (Дата)
STATEMENT ABOUT THE INDEPENDENT CHARACTER OF
THE MASTER THESIS
I, Karina Naumova, second year master student, program «Management», state that my
master thesis on the topic «Digitalization and warehouse management in Russia: an approach for
implementation of digital solutions», which is presented to the Master Office to be submitted to
the Official Defense Committee for the public defense, does not contain any elements of
plagiarism.
All direct borrowings from printed and electronic sources, as well as from master theses,
PhD and doctorate theses which were defended earlier, have appropriate references.
I am aware that according to paragraph 9.7.1. of Guidelines for instruction in major
curriculum programs of higher and secondary professional education at St. Petersburg University
«A master thesis must be completed by each of the degree candidates individually under the
supervision of his or her advisor», and according to paragraph 51 of Charter of the Federal State
Institution of Higher Education Saint-Petersburg State University «a student can be expelled
from St. Petersburg University for submitting of the course or graduation qualification work
developed by other person (persons)».
(Student’s signature)
26.05.2016 (Date)
2
АННОТАЦИЯ
Автор
Название магистерской
Наумова Карина Владимировна
Цифровые технологии для складской логистики в России:
диссертации
Факультет
Направление подготовки
Год
Научный руководитель
Описание цели, задач и
алгоритм внедрения цифровых технологий
Высшая Школа Менеджмента
Международная логистика и управление цепями поставок
2016
Шульте Аксель Тео, PhD, доцент
Цифровые решения в складской логистике могут быть
основных результатов
конкурентным преимуществом для улучшения точности
компоновки заказа, снижения затрат на персонал и
повышения производительности труда работников склада.
Многие компании стремятся понять, как внедрить цифровые
решения в складской логистике. Целью данного
исследования является разработка алгоритма внедрения
цифровых решений для складской логистики в российских
компаниях. В рамках исследования были выявлены
цифровые решения в области управления складом и изучены
кейсы российских и международных компаний, которые
внедряли цифровые решения в складской логистике. На
основе анализа были выявлены цифровые решения, которые
в дальнейшем были сопоставлены между собой с точки
зрения их актуальности, затрат и простоты реализации. В
результате было выявлено, что система управления складом
и технология голосового управления являются наиболее
распространенными и актуальными технологиями в
складской логистике в России. Лучшие практики внедрения
цифровых решений в складской логистике были
исследованы с помощью анализа кейсов. Был разработан
алгоритм с указанием стадий внедрения, их содержания и
длительности для системы управления складом и технологии
Ключевые слова
голосового управления для российских компаний.
Цифровые технологии, складская логистика, система
управления складом, технология голосового управления
ABSTRACT
Master Student's Name
Karina V. Naumova
3
Master Thesis Title
Digitalization and warehouse management in Russia: an
Faculty
Main field of study
Year
Academic Advisor's Name
Description of the goal, tasks
approach for implementation of digital solutions
Graduate School of Management
International Logistics and Supply Chain Management
2016
Axel Theo Schulte, Dr./PhD, Associate Professor
Digital solutions for warehouses can be a great competitive
and main results
advantage to improve order-picking accuracy, decrease
personnel costs and increase warehouse employees’
productivity. Сompanies are struggling to understand how to
implement digital solutions in warehouse management. The
research goal of the thesis was to develop an algorithm of
implementing digital solutions in warehouse management for
Russian companies. For achieving this goal digital solutions
in warehouse management were determined and multiple case
study analysis was carried out. Based on the analysis digital
solutions in warehouse management were revealed and
compared in terms of their relevance, costs and ease of
implementation. As a result, it was found out that Warehouse
Management System (WMS) and pick-by-voice are the most
widely applied and relevant technologies in warehouse
management in Russia. Best practices of implementing digital
solutions in warehouse management in Russian and
international companies were investigated using within-case
and cross-case analyses. Finally, an algorithm with stages of
implementation, their duration and content of implementing
WMS and pick-by-voice was developed for Russian
Keywords
companies.
Digitalization, warehouse management, Warehouse
Management System, pick-by-voice
4
Table of contents
Introduction..................................................................................................................................8
CHAPTER 1. DIGITALIZATION AND WAREHOUSE MANAGEMENT............................12
1.1. Digitalization in warehouse management .......................................................................12
1.2. Warehouse Management System and Pick-by-voice ......................................................26
1.3. Research gap...................................................................................................................33
1.4. Summary of Chapter 1.....................................................................................................35
CHAPTER 2. METHODOLOGY OF RESEARCH .................................................................36
2.1. Research strategy.............................................................................................................36
2.2. Data collection.................................................................................................................38
2.3. Data analysis....................................................................................................................43
2.4. Research quality ..............................................................................................................44
2.5. Summary of Chapter 2.....................................................................................................45
CHAPTER 3. APPLICATION AND BEST PRACTICES OF DIGITALIZATION IN
WAREHOUSE MANAGEMENT .............................................................................................47
3.1. Within-case analysis ........................................................................................................48
3.2. Cross-case analysis..........................................................................................................75
3.3. Algorithm of implementing digital solutions in warehouse management for Russian
companies ..............................................................................................................................85
3.4. Summary of Chapter 3.....................................................................................................98
3.5. Discussion and conclusions.............................................................................................98
Conclusion................................................................................................................................102
References................................................................................................................................106
Appendices...............................................................................................................................114
List of tables and figures
5
Tables
Table 1. Digital solutions in warehouse management ………….………………………22
Table 2. Comparison of digital solutions in warehouse management…………………..25
Table 3. Menu of features of a Warehouse Management System………………………28
Table 4. Semi-structured interviews respondents……………………………………….41
Table 5. Coding procedure……………………………………………………………...44
Table 6. Cases overview………………………………………………………………...47
Table 7. Results of cross-case study analysis for Warehouse Management System…....81
Table 8. Results of cross-case study analysis for pick-by-voice technology…………....83
Table 9. Algorithm of implementing WMS in warehouse management for Russian
companies……………………………………………………………………………….87
Table 10. Algorithm of implementing pick-by-voice technology in warehouse
management for Russian companies……………………………………………………92
Figures
Figure 1. Warehouse operations flow…………………………………………………...15
Figure 2. Technology trends in logistics industry………………………………………20
Figure 3. Technology trends in supply chain management……………………………..21
Figure 4. The five-stage research process model……………………………………….38
Figure 5. Data collection process……………………………………………………….39
Figure 6. Gantt chart WMS implementation in warehouse management for Russian
companies……………………………………………………………………………….96
Figure 7. Gantt chart Pick-by-voice implementation in warehouse management for
Russian companies………………………………………………………………………97
6
List of abbreviations
The list of abbreviations used by the author in the master thesis is provided in order to
avoid misinterpretations.
3PL – third-party logistics
CRP - conference room pilot
DC – distribution center
EDI - electronic data interchange
ERP - enterprise resource planning
Industry 4.0 – fourth industrial revolution
IRD - implementation requirements document
IT – information technology
KPIs – key performance indicators
MRP - material resource planning
RFID – radio frequency identification
ROI – return on investment
SRD - systems requirement document
UAV - unmanned aerial vehicles
VDT – voice direct technologies
WMS – warehouse management system
7
Introduction
Digitalization has already entered our lives and has made significant changes in our
society (Dedrick et al., 2008; Fitzgerald et al., 2013). Digitalization has a significant impact on
all economic sectors and revolutionizes industries, as it refers to the fourth industrial revolution,
which is happening in 21st century. In today’s age of digitalization to stay competitive and
increase profit more and more companies are inclined to apply digital solutions in their
operations, including warehouse management (Pfohl et al., 2015). This tendency can be
explained by the fact that currently traditional warehouses, which do not use digital tools, do not
always meet warehouse customers’ needs. In addition, complexity of supply chains has reached a
level, where conventional warehouse systems are not efficient anymore (McKinsey Digital,
2014). Thus, there appears a necessity to use innovative technologies in warehouse management.
Companies face the need of integrating information technology management and warehouse
management, i.e. digital solutions and warehouses.
Warehouses are considered as a vital link within company’s supply chain. Warehouses
are no longer perceived as only costs centers, which rarely can add value (Faber et al., 2002;
Motorola Solutions report, 2013). This development can be explained by the movement from
linear to complex supply chains, digitalization, major shifts in customer demographics and
buying patterns, globalization, increasingly demanding customer and supplier requirements as
well as evolving regulations. Therefore, warehouses can drive competitive differentiation and, by
doing so, increase company profit.
Under the influence of digitalization and globalization, warehouses today are being
asked to increase order-picking accuracy and productivity of warehouse employees, execute
more transactions, offer more value-added services and process more returns. At the same time
warehouses have less time to process orders, more demanding customers, less time to process
returns, higher level of environmental and staffing pressures (Ramaa et al. 2012). Thus, under the
above mentioned rising expectations and requirements for warehouses, digital solutions for
warehouses can be a great competitive advantage to overcome these challenges and increase
company profit and its key performance indicators. However, many companies are struggling to
understand how to integrate and implement digital solutions in warehouse management
(Accenture, 2014).
There are some studies in the field of automation solutions (Warehouse Management
System, Enterprise Resource Planning, Client Relationship Management system etc.) in
warehouse management (Autry et al. 2005; Ramaa et al. 2012; Legutko et al. 2012); however,
there is a lack of research, which is focused on investigating digital solutions in warehouse
management both in international and Russian companies. Moreover, there is no research on
8
developing a n algorithm of implementing digital solutions in warehouse management . An
algorithm in this case means a set of stages to follow in order to implement digital solutions in
warehouse management. Algorithm consists of specific steps with stages of implementation,
their duration and content of implementing digital solutions for Russian companies. Algorithm
and approach terms in the study are considered as synonyms and further algorithm term is used.
This proves that extant studies on warehouse management and its digitalization have
limitations, since there are no studies dedicated to investigating digital solutions in warehouse
management and there isn’t any research among extant studies regarding developing an
algorithm of implementing digital solutions in warehouse management. Hence, the problem of
lack of an algorithm of implementing digital solutions in warehouse management is raised.
All of the above mentioned indicates that there is a research gap, which this thesis will
close. Thus, the research gap consists of lack of research among extant studies regarding
development of an algorithm of implementing digital solutions in warehouse management.
Despite the fact that digital solutions have only recently started to appear in warehouses of
Russian companies, plenty of companies understand the importance and potential of applying
digital solutions in warehouses and its positive impact on warehouse efficiency (Pfohl et al.,
2015).
Taking into consideration all the above mentioned, this research has relevance and
managerial implications for companies. The results of this thesis will be useful for a wide
audience: for supply chain managers, warehouse managers, warehouse specialists, IT managers
and for all managers, who are involved in implementation of digital solutions in warehouse
management. The developed algorithm for implementation of digital solutions can be useful not
only for Russian, but also for foreign companies, which intend to introduce digital solutions in
warehouse management.
The following research goal was formulated:
To develop an algorithm of implementing digital solutions in warehouse management for
Russian companies based on best practices of international and Russian companies
The following research objectives were formulated:
1) To review digitalization phenomenon and its implications for warehouse management
2) To identify digital solutions in warehouse management
3) To analyze best practices of implementing digital solutions in warehouse management
4) To develop an algorithm of implementing digital solutions in warehouse management for
Russian companies
9
Research object in this thesis are digital solutions in warehouse management in Russian
and international companies. Research subject is the algorithm of implementing digital
solutions in warehouse management in Russian and international companies.
Research problem of this study consists of lack of an approach of implementing digital
solutions in warehouse management in Russian companies.
Research questions are the following:
(RQ1) Which digital tools are used in warehouse management?
(RQ2) How digital solutions should be implemented in warehouse management?
The study is based on a qualitative approach, and the main research method is multiple
case study. Both primary and secondary data are used. Secondary data includes journals, internal
documents of the company and textbooks. Regarding primary sources, in the research qualitative
semi-structured interviews and consultations with digital solutions’ integrators are conducted.
Thus, triangulation principle is fulfilled, since different research methods and data from different
sources are used. This allows to reduce the level of subjectivism, which is typical for qualitative
research.
The master thesis consists of three stages of research. The first stage is the theoretical
chapter, which reviews phenomenon of digitalization, warehouse operations, digitalization
implications for warehouse management. Moreover, in the first chapter it is identified which
digital solutions are applied in warehouse management and what impact do they have on
warehouse management. Further, Warehouse Management System (WMS) and pick-by-voice
solutions are analyzed in terms of their functionality, benefits and drawbacks of these
technologies and implementation recommendations. The second chapter includes research
methodology. Case study is the major method, which is used in the thesis. For achieving research
goal semi-structured interviews with companies’ managers and consultations with digital
solutions’ integrators are conducted. The third chapter includes analysis of the best practices of
implementation of digital solutions in warehouse management. For the research within-case and
cross-case study analyses are applied. Based on the conducted analyses, an algorithm of
implementing digital solutions in warehouse management for Russian companies is developed.
The research is conducted on the basis of around a hundred sources, which include
scientific articles, books, industry reports and conference papers. The sources were found in such
databases as EBSCO, Emerald, JSTOR, Elsevier, Taylor & Francis, Wiley Interscience.
The study has both theoretical and practical implications. From the theoretical
perspective the thesis provides contribution to the sphere of digital solutions in warehouse
management, which is quite uninvestigated. Based on the literature review analysis digital
solutions in warehouse management were determined, reviewed and compared. Moreover, it was
inferred that the most widely spread and relevant technologies in warehouse management in
Russian companies are Warehouse Management System (WMS) and pick-by-voice. Regarding
10
practical implications, an algorithm of implementing digital solutions (WMS and pick-by-voice)
in warehouse management was developed, which can be applied by Russian and international
companies, which intend to introduce digital solutions in warehouse management. The algorithm
with the stages of implementation, their duration and content and responsible employees will be
especially useful for warehouse managers, IT managers and other employees, who are involved
in implementation of digital solutions in warehouse management.
11
CHAPTER 1. DIGITALIZATION AND WAREHOUSE MANAGEMENT
The chapter is concentrated on investigating digitalization in warehouse management.
The aim of the conducted literature review is to provide a comprehensive overview of extant
studies regarding digitalization in warehouse management and to identify digital solutions
applied in warehouse management. Since the topic of the master thesis includes both
digitalization and warehouse management, the literature review combines both spheres.
Therefore, the review is organized thematically and consists of two parts: digitalization in
warehouse management and Warehouse Management System (WMS) and pick-by-voice. First of
all, phenomenon of digitalization is traced over time. Afterwards warehouse operations and
future trends should be established. Then, digitalization implications for warehouse management
are explained and consequently digital solutions in warehouse management are revealed based
on academic articles and latest industry reports. Impact of digital solutions on warehouse
management is investigated and as a result it is revealed that WMS and pick-by-voice are the
most widely applied and relevant digital solutions in warehouse management in Russia.
Consequently, these two solutions are investigated in detail, i.e. their functionality, benefits and
drawbacks and implementation recommendations. Eventually research gap is defined after the
conducted literature review.
1.1.
Digitalization in warehouse management
1.1.1. The phenomenon of digitalization
To begin with, digitalization concept should be introduced. The terms of digitalization
and digitization are sometimes used interchangeably in the literature (Yichang, 2001; Sohn et al.,
2002; Geschke, 2006; McKinsey Digital, 2014; Hirsch-Kreinsen, 2016), since they are closely
interrelated.
The first use of digitalization and digitization terms is attributed to the mid 1950-s in
conjunction with the computers (Haigh, 2001). Digitization means the conversion of analogue
data into digital form (Houissa, 1999), while digitalization refers to increase in usage or adoption
of digital or computer technology by the company, industry (Gartner, 2016). It can be inferred
that digitization refers to the material process, while digitalization attributes to the phenomenon
of spreading and adoption of digital technologies. Further, digitalization phenomenon is
scrutinized among the extant studies.
The term ‘digitalization’ appeared in its contemporary usage in an essay of Wachal
(1971). In conjunction with computerization Wachal (1971) shared his view on the social
implications of the ‘society’s digitalization’ in terms of research referred to computer-assisted
humanities. The scholar discussed objections and potential of such kind of research. It can be
12
noted that after 1971 digitalization has become a widely discussed topic among the researchers
and focus of the research has been shifted more to studying ways that digitalization influences
and shapes contemporary world (Williamson, 1975; Naisbitt, 1984; Wijnhove and Wassenaar,
1990; Chareonwongsak, 2002; Cetina and Bruegger, 2002; Verhulst, 2002; Van Dijk, 2005).
Williamson (1975) addressed digitalization in the context of governance mechanisms. During the
decade from the middle 1970s till the middle 1980s there were scholars, who have explored
impact of computerization from the buyer-seller perspective. Significant contribution regarding
this area was done by Mathews et al. (1974) and Mathews et al. (1977), who studied how
computerization influenced selling and buying process to the computer assisted buyers.
As Naisbitt (1984, p.22) argued ‘computer technology is to the information age what
mechanization was to the Industrial Revolution’. Thus, the author claimed the significance of
digitalization and its solutions in the information age. Wijnhove and Wassenaar (1990) studied
digitalization from the perspective of organizational usage of information technology.
Brynjolfsson and Hitt (1998) examined productivity and information technology uptake in terms
of digitalization.
Moreover, scholars have explored that digitalization has been facilitated by and facilitated
the rise of globalization (Chareonwongsak, 2002). Hence, there can be observed a mutual
influence between digitalization and globalization. Further, researchers have explored the impact
of the digitalization and globalization on national sovereignty, culture, people, capital and
commodities. For example, Cetina and Bruegger (2002) have examined that digital media has
become an essential element of global capital flows. Several researchers (Verhulst, 2002; Van
Dijk, 2005) have analyzed digitalization further in terms of communications. Verhulst (2002)
claimed that the new communication system is facilitated by devices, which are able to manage
digital signals. Van Dijk (2005) added that there appeared a single communications infrastructure
which connects all activities in society. As Castells (2011) emphasized digitalization has become
one of the defining characteristics in the modern society. Digitalization allows to reveal new
technologies, which can significantly impact social and economic spheres (Avent, 2014).
Following Avent (2014) there has been a research by Evangelista (2014), who studied the
economic impact of digital technologies in Europe. Hirsch-Kreinsen (2016) pointed out that no
other issue as digitalization has been discussed so often in professional circles and underlined
major role of digitalization in future economic and social development.
According to Hirsch-Kreinsen (2016) two phases of digitalization can be defined. The
first phase can be attributed to the end of the 1990s, when digitalization has been already
established in various industry sectors, where production and communication were based on the
data and information usage and intangible transactions. Zuboff (2010) added that during the first
phase of digitalization influenced not only companies and industries, but also triggered changes
13
in individual business models. The second phase of digitalization refers to the period since the
end of the 1990s till the present day and this phase is oriented to digitalization of physical objects
of all kinds (Hirsch-Kreinsen, 2016). Zuboff (2010) denoted this phase as a ‘second-wave
mutation’, which has an impact on economic and technological spheres. It is interesting to
mention that from the technological perspective second phase of digitalization can be called as
‘Internet of things’ (Hirsch-Kreinsen, 2016). Comparing the mentioned two phases of
digitalization it can be inferred the second phase is far more complex due processes’ materiality
(Zuboff, 2010).
As was shown in McKinsey Digital (2014) digitalization allows companies to grow
quickly and enter new markets at low cost. Moreover, digitalization facilitates companies’
growth through creating network effects and decreasing to a great extent marginal costs, such as
storage costs, transportation costs etc.
Along with the digitalization concept fourth industrial revolution (or Industry 4.0) term
should be defined since these phenomena are closely connected. Pfohl et al. (2015) defined
Industry 4.0 as the sum of all disruptive innovations, which can be obtained and implemented in
a value chain. In Industry 4.0 term Pfohl et al. (2015) include the following trends: digitalization,
modularization, transparency, automatization, mobility, network-collaboration and socializing of
products and processes. As Pfohl et al. (2015) note digitalization is the most important element
of the fourth industrial revolution and enables development of all other features.
In this paper digitalization and more specifically digital solutions in terms of warehouse
management are examined, since the goal of current research is to develop an algorithm of
implementing digital solutions in warehouse management. Further, the warehouse operations and
warehouse trends are examined.
1.1.2. Warehouse operations and trends
Warehouses serve as an essential connection among suppliers, distributors and customers
in the supply chain (Chen and Wu, 2005). According to Motorola Solutions report (2013) a
warehouse is no longer perceived as a cost center, but as a growth center, which can be a
powerful company’s asset for driving profitable growth and improving warehouse operations.
There is a classical definition of a warehouse by Bartholdi and Hackman (2006), according to
whom a warehouse is a facility in the supply chain for consolidating company’s products,
reducing transportation costs and achieving economies of scale. Gong (2008) explored a pollingbased dynamic order picking system for online retailers and added that warehouse can also
provide value enhancing processes and decrease response time. As Hwang and Cho (2006)
evaluated, warehousing costs account for 2-5% of total cost of sale of a company and
consequently minimizing warehousing costs has become a formidable issue for companies.
14
There exist different classifications of warehouse operations, but basically they resemble
each other and have a general pattern. Basic classifications of warehouse operations were
developed by Frazelle (2002) and Tompkins et al. (2003). These classifications include division
of warehouse operation into inbound and outbound processes. Based on scholars’ classifications
a scheme of warehouse operations was developed, which is presented below.
Figure 1. Warehouse operations flow
Source: Based on Frazelle (2002); Tompkins et al. (2003)
Further, to understand how digital solutions can affect warehouse management,
warehouse operations should be explained. The first inbound process is receiving. It includes
activities related to consistent receiving of the items which come in warehouses, checking the
quantity of quality of received items and allocating items to storage (Gu et al., 2007). Receiving
process accounts for about 10% of operating costs in a warehouse (Druri, 1988).
The subsequent inbound process is put away. This activity consists of material handling,
location verification and product placement (Gong and De Koster, 2011). Put away process
usually accounts for about 15% of operating costs in a warehouse (Druri, 1988).
The next process is processing customer orders, which is the first outbound process.
During this stage warehouse personnel verifies that inventory is available to ship, produces pick
lists, prepares necessary shipping documentation schedules order-picking and shipping processes
(Gong and De Koster, 2011).
Order-picking is the process of removing items from storage to meet a specific demand
(Gong and De Koster, 2011). This process is the most time-consuming among all the warehouse
operations, since it accounts for about 55% of warehouse operating costs (Druri, 1988). Orderpicking can be divided into four processes: travelling (55% of order-picking time), searching
(15% of order-picking time), extracting (10% of order-picking time) and paperwork and other
activities (20% of order-picking time) (Bartholdi, 2006).
15
Further outbound processes as checking and packing are presented together, since they
frequently happen simultaneously. Packing is rather labor-intensive process, which requires
handling each customer order. During that time checking process can be carried out to provide
accuracy of customer order. Packed product may be scanned to register the customer order
availability for shipping (Varila et al., 2007).
The last outbound process is shipping. During shipping product probably is staged and as
a result staged freight must be double-handled. Before actual shipping product is likely to be
scanned to register its departure from the warehouse. Corresponding shipping documents,
including the packing list, address label and bill of lading should be prepared. Moreover,
shipments are weighed to determine shipping charges (Van den Berg and Zijm, 1999).
Having analyzed warehouse operations, several conclusions were made. In a typical
warehouse most of the expenses occur in labor, to be exact in an order-picking process. The most
time-consuming and therefore the most expensive process is order-picking and in an orderpicking process the most time consuming process is travelling. That is why companies should
invest resources to reduce unproductive travel time in the first place and digital technologies can
be a suitable solution for that.
Changing market environment has significantly affected companies’ warehouses (Van
Den Berg, 1999; Selen, 2002). Chen and Wu (2005) added that customers have gained more
power to impact market structure and consequently warehouse employees should be able to react
to regular changes. Moreover, Chen and Wu (2005) showed that there has been a market trend in
supply chain management, which consisted of pursuing a demand-driven organization with
certain characteristics such as short response time, high product variety and small order sizes.
Apart from more demanding customers as the main challenges warehouses face, Ramaa et al.
(2012) mentioned deeper and shorter integration of supply chains, globalized operations and
rapid technological changes. Thus, to cope with the rising difficulties companies are inclined to
adopt innovative solutions in warehouse management (Ramaa et al., 2012). Gu et al. (2007)
confirmed this earlier by arguing that implementation of digital solutions allows companies to
improve warehouse processes.
To get a deeper understanding of warehouse management, warehouse trends of the future
are further presented. According to Hurdock (2000) the warehouse trends of the future will focus
on the following aspects: customer-centric supply chain, operations and time compression,
continuous flow, electronic transactions, customized warehouses, cross-docking, third-party
warehousing, complete automation, standardization, continued upskilling of the workforce to
keep in touch with technological advancements in the industry. Capgemini (2010) elaborates
warehouse trends further and adds that in future there will be collaborative warehouses, where
multiple manufacturers store their products. Moreover, Capgemini (2010) states that warehouse
16
locations on the cities’ outskirts will function as hubs for cross-docking final distribution.
Regarding non-urban areas, they will have regional consolidation centers for cross-docking final
distribution. Regarding the specific figures of warehouse future trends according to Motorola
Solutions report (2013) till 2018 35% of the surveyed companies intend to increase number of
warehouses and distribution centers (DCs) and 38% plan to expand the size of warehouses and
DCs. In 2018 use of multimodal voice and screen guidance will increase by more than 2,5 times
and 67% of companies are going to take inventory using mobile handheld computers or tablets
(Motorola Solution report, 2013). Furthermore, 66% of companies are going to equip their staff
with technology and 70% of companies intend to conduct automation of warehouse processes
(Motorola Solution report, 2013).
It can be inferred that some of these mentioned trends have already penetrated into
today’s warehouses such as cross-docking, third-party warehousing, fully automated warehouses.
It is noteworthy to mention that majority of the warehouse trends are closely connected with
digital technologies, which reflect the current and future significance of digitalization in
warehouse management.
1.1.3. Digitalization implications for warehouse management
As mentioned earlier implementation of digital solutions provides opportunities for
companies to improve their warehouse processes (Gu et al., 2007). Fitzgerald et al. (2013) in
MIT Sloan report argue that using digital technologies enable companies to streamline their
operations and improve customer experience. Both aspects are extremely significant for
warehouse management, since streamlining operations can facilitate increasing warehousing
efficiency and high customer service level can increase customer satisfaction. In customer
experience category the most prominent elements, where digitalization had the greatest impact,
were improving overall customer experience and enhancing existing products and services in
customer-friendly ways (Fitzgeral et al., 2013). Considering the operational improvement
category all elements had been influenced by digitalization more or less equally and these
elements include improving internal communications, automating operational processes and
enhancing workers’ productivity (Fitzgeral et al., 2013). It should be noted that fourth industrial
revolution and digitalization are inevitable and real for supply chain management and warehouse
management for several reasons (Schulte, 2013). Firstly, fourth industrial revolution and
digitalization are urgently necessary since traditional methods which were used earlier in supply
chain management cannot meet increasing demands and external requirements anymore.
Moreover, every day new technologies are developed all over the world and there are enough
resources to further innovations development (Pfohl et al., 2015), which means that fourth
17
industrial revolution and digitalization are technically possible. Lastly, due to emergence of new
business-models and markets most of the fields, including warehouse management are
influenced by e-commerce, IT technologies and innovations, such as integrated IT solutions for a
warehouse, innovative order-picking technologies etc. (Schulte, 2013).
In the report of McKinsey Global Institute (2013) it is stated that digitalization has the
potential to decrease or even eliminate transportation and marginal production costs of virtual
goods. As discussed in the report digitalization can decrease costs in three major ways. The first
way consists of creation of purely digital goods that can be easily transported. Considering
warehouse management such digital goods can be created as bills of lading, regular reports,
receipts etc. It is interesting to mention that digitalization can transform even some physical
flows of people into virtual flows by allowing employees to work remotely using digital
technologies. The second way includes using ‘digital wrappers’ for increasing value of physical
flows. In warehouse management digital wrappers can be computers, mobile terminals, tablets,
headphones, etc. As emphasized by McKinsey Global Institute (2013) potential of digital
enablers has been revealed for some time, but their use has been increased only recently. The
third way consists of digitalization acting as a counter by transforming value chains and thus
physical components flow can be made directly to consumers.
Pfohl et al. (2015) added that disruptive innovations are able to influence companies’
supply chain processes, including warehouse operations. For instance, delivery information of
transported goods can be changed in real-time and whenever needed (Whang, 2010).
Consequently, digital technologies (such as RFID technologies in this case) allow to carry out
problem management online and centrally (Pfohl et al., 2015).
As it was shown in McKinsey Digital (2014) companies consider the main improvement
areas in warehouse management those areas, which are connected with operational effectiveness,
namely with labor and quality. Thus, digitalization will facilitate changes in these areas using
advanced digital technologies. Corresponding point of view is reflected in the report Deloitte
Industry 4.0 (2015), where it is claimed that the manufacturing companies perceive substantial
potential of digitalization in warehousing logistics (74% of respondents). In McKinsey Digital
(2014) it is pointed out that digital technologies work as an enabler in warehouse management,
notably they ease information exchange, can visualize and control the processes via digital tools
such as tablets, mobile terminals etc. and simplify communications between warehouse
employees. Moreover, digital technologies are able to facilitate stronger cross-functional
integration in companies and cooperation along the product lifecycle, thus significantly
increasing value for the whole company (McKinsey Digital, 2014). It is noteworthy to mention
that digital technologies will be especially useful if company has remote multiple sites and
digitalization in this case will play a major role.
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McCrea (2015) shares her view on the increased usage of mobile solutions in warehouse
management. According to David Krebs, president of enterprise mobility and connected devices
at VDC Research, more and more warehouse managers intend to apply mobile solutions on a
regular basis to streamline warehouse processes and increase warehouse employees’ productivity
(McCrea, 2015). Leading applications in warehouse management according to Krebs’ view
include receiving/shipping and put-away/picking applications and there is also a growing interest
in additional applications around load planning, cross-docking, and parcel and item
dimensioning. Krebs evaluated investment environment for mobile warehouse technology as a
robust one, and according to his estimation, in 2015 mobile budgeting regarding warehouse
solutions has been risen by 8,7% (McCrea, 2015).
Hirsch-Kreinsen (2016) pointed out that digitalization as an element of fourth industrial
revolution will enable completely new level of automation through using highly flexible data
enabled by Internet. At the same time in Hirsch-Kreinsen (2016) research it is indicated that with
the digitalization proliferation foreseeable consequences might have not seen yet in terms of
socioeconomic structures, namely in labor. For instance, some companies might downsize their
personnel due to usage of digital technologies and subsequent increased worker productivity.
Based on the above mentioned analysis of digitalization implications on warehouse
management it can be inferred that digital technologies facilitate warehouse management
efficiency through interaction with data and establishing collaboration among warehouse
employees and other departments’ personnel. Regarding operations with data, digital solutions
are able to capture data, provide access to the data (allow data visibility) and analyze or
contribute to the data analysis.
1.1.4. Digital solutions in warehouse management
While searching through the academic articles it was found out that there is no defined set
of digital solutions specifically for warehouse management. However, there exist determined
digital technologies in logistics, supply chain management and business and separate studies of
some digital technologies, which are used in warehouse management. As mentioned earlier,
digital solutions represent specific technologies, which can be included in automated solutions.
Thus, taking into account earlier conducted analysis of digitalization and warehouse operations
and industry reports on digital technologies in logistics and supply chain management, digital
solutions in warehouse management are identified.
Extant major reports on digital solutions in logistics, supply chain management and
business include Disruptive technologies (McKinsey Global Institute, 2013), Logistics Trend
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Radar (DHL, 2014), Industry 4.0 How to navigate digitization of the manufacturing sector
(McKinsey Digital, 2014), Industry 4.0 – The Capgemini Consulting View: Sharpening the
Picture beyond the Hype (Capgemini Consulting, 2015), The Impact of Industry 4.0 on the
Supply Chain (Pfohl et al., 2015) and Three Paths to Advantage with Digital Supply Chain (BCG
Perspectives, 2016). Despite the fact that the reports have different classifications of digital
technologies, all reports emphasize significance of intersection of supply chain management and
digitalization at the present. Logistics Trend Radar (DHL, 2014) proposes the following
technologies, which are expected to affect logistics in the following decade.
Figure 2. Technology Trends in Logistics Industry
Source: DHL Logistics Trend Radar, 2014
It is noteworthy to mention that the above presented figure has both technology trends
(e.g. autonomous logistics) and digital solutions (e.g. 3D printing). Based on established earlier
warehouse operations (receiving, put-away, processing customer orders, order picking, checking
and packing, shipping) among the revealed by DHL technologies the following digital solutions
can be attributed to warehouse management: robotics and automation, 3D printing and
augmented reality.
Pfohl et al. (2015) propose another classification of digital technologies and concepts in
the report ‘The Impact of Industry 4.0 on the Supply Chain’. Thus, the authors identified the
most discussed technologies and concepts within the relevant literature. This classification
includes technologies and concepts for all elements of Industry 4.0 (digitalization,
modularization, mobility etc.), that is why this classification was adopted specifically for
digitalization and only elements referring to digitalization are left.
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Figure 3. Technology Trends in Supply Chain Management
Source: Pfohl et al. (2015), The Impact of Industry 4.0 on the Supply Chain
It can be noted that apart from the technologies, which were revealed based on DHL
report (2014), the following technologies can be also attributed to warehouse management: RFID
(radio frequency identification) and voice recognition. In McKinsey reports ‘Industry 4.0 How to
navigate digitization of the manufacturing sector (2014) and ‘Disruptive technologies: Advances
that will transform life, business and the global economy’ (2013), Capgemini Consulting report
‘Industry 4.0 – The Capgemini Consulting View: Sharpening the Picture beyond the Hype’
(2015) and BCG report ‘Three Paths to Advantage with Digital Supply Chain’ (2016) there were
observed similar technologies and trends, therefore they are not presented further.
To get a more comprehensive understanding which digital solutions can be used in
warehouse management articles in logistics journals were also analyzed. One of the leading and
most widely used systems in warehouse management is Warehouse Management System (WMS)
(Harrington, 2001; Patterson et al., 2004; Autry et al., 2005; Morton, 2009; McCrea, 2012;
Napolitano, 2012; Hoffman, 2013; McCrea, 2014; Bond, 2015). Despite the fact that WMS is
more an automated software solution than the digital one, this technology is widely spread in
warehouse management and attributed to digitalization and Industry 4.0 (DHL, 2014). Therefore,
WMS is included further in digital solutions in warehouse management.
Another digital solution, which was found in warehouse management, is pick-to-light
technology (Qiang, 2008; Trebilcock, 2008; McCrea, 2015). This technology is intensively used
in order-picking process in warehouse management (McCrea, 2015). Pick-to-light allows to
increase order-picking accuracy and boost warehouse employees’ productivity.
Thus, having observed industry reports and academic articles regarding digital solutions
in warehouse management, the following digital solutions in warehouse management were
identified. Further, each of the digital solution in warehouse management is reviewed.
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Table 1. Digital solutions in Warehouse Management
Digital solution
Warehouse Management System (WMS)
Pick-by-voice
Pick-to-light
Radio Frequency Identification (RFID)
3D printing
Augmented reality
Robotics
As mentioned earlier WMS is more an automated solution then a digital one since it is a
software program for managing warehouse operations. Currently, WMS is the most widely
applied solution in warehouse management (McCrea, 2012; Napolitano, 2012; Hoffman, 2013).
WMS is oriented to monitor materials movement and storage and carry out corresponding
transactions in a warehouse. The main company goal of WMS implementation is to improve
warehouse efficiency by cutting costs and managing warehouse transactions (Ramaa et al.,
2012). Napolitano (2012) underlined that WMS systems have started to support much more
sophisticated operations than just core warehouse functions such as receiving, picking and
shipping. As John Hill, director for supply chain and logistics consulting firm, St. Onge
Company noted that WMS functionality is used by no more than 60% to 65% (Napolitano,
2012), which means that large potential of WMS is not employed.
Pick-by-voice technology or how it is also called in the literature Voice Direct
Technologies (VDT) (Sowinski, 2005; Phillips, 2013) provides direct voice control tool for order
picking. As Sowinski (2005) showed pick-by-voice technology can boost warehouse productivity
and at the same time improve company’s bottom line. Based on the conducted analysis of the
articles referred to pick-by-voice technology (Terreri, 2007; McCrea, 2015) it was concluded that
this technology is the second most widely applied solution in a warehouse after WMS. It should
be mentioned that pick-by-voice technology is one of the applications of WMS since it is directly
connected to the system (Cork, 2005). As Barrows (2006) noted early adopters of pick-by-voice
technology are able to improve order accuracy to more than 99,7%. As observed by McCrea
(2015) pick-by-voice technology is one of the most affordable solutions in terms of costs. For
instance, even in comparison of pick-by-voice with pick-by-light, the latter solution is more
expensive, since every single location requires light in this case (McCrea, 2015).
Another technology, which is also used for order-picking in warehouse management is
pick-to-light. As well as pick-by-voice technology pick-to-light solution is connected to WMS
system. Ken Ruehrdanz, manager of the distribution systems market for Dematic characterized
pick-to-light technology as a potentially transformational tool in warehouse management (Bond,
2013). Pick-to-light technology with automated data entry allows to improve order-pickers’
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productivity by 10% and decrease human errors by 95% (Andriolo et al., 2016). Importance of
pick-to-light is underlined also by Chris Castaldi, manager of business development at W&H
Systems, who stated that pick-to-light technology ‘is a game of seconds, which turn into minutes,
hours and dollars’ (Bond, 2013).
During the past decade radio frequency identification (RFID) is widely applied in supply
chain management and particularly in warehouse management (Wang et al., 2010). However,
RFID technology is not a new one, since it was used since 1940s (Attaran, 2011). RFID
technology has been intensively researched by plenty of scholars (Kärkkäinen, 2003; Lee et al.,
2004; Chow et al., 2006; Goodrum et al., 2006; Delen et al., 2007; Bottani and Rizzi, 2008; Ngai
et al., 2008; Poon et al., 2009). Radio frequency identification (RFID) system is a system
whereby a portable computer used by an order picker communicates with a host computer from
anywhere in the warehouse (Chen et al., 2013). Companies use RFID technology to improve
both material and information flows via automatic identification of goods using radio frequency
tags (Wang et al., 2010). In Jones et al. (2004) it is indicated that RFID tags are able to store
much more information about goods than traditional barcodes. RFID system allows to
substantially increase productivity, since the warehouse workers are given directions of all
activities by the host computer, which tells them location of products and verifies that they
picked the correct order. In spite of the all benefits of RFID, this technology is rather costly in
comparison with other solutions, since RFID requires tag reader, communication costs and some
infrastructure costs (Gu et al., 2007).
The next digital solution is 3D printing, which is denoted as a disruptive technology and
is able to change future logistics industry. 3D printing or additive manufacturing is defined as a
process, during which a three-dimensional object is produced from a digital model (DHL, 2014).
McKinsey Global Institute (2013) in the report ‘Disruptive technologies’ estimated that
economic impact from 3D printing will grow in the future and will reach up to $550 billion per
year by 2025. Xiao-dong and Fan (2016) underlined that 3D printing has plenty of advantages
such as personalization, miniaturization and intelligence. Furthermore, currently possibilities of
3D printers have been extended in terms of used materials (from titanium up to food and stem
cells) and consequently produce more functional tools such as batteries, transistors etc. (DHL,
2014). Regarding warehouse management 3D printing reveals great potential for companies,
since it allows to produce goods on-site or outsource this task to small fabricators (DHL, 2014).
Augmented reality is another digital solution, which can boost productivity of warehouse
operations and streamline processes in a warehouse (DHL, 2014). Augmented reality is a
combination of the real scene, which the user can view, and a virtual scene, which is generated
by the computer augmenting the real scene with additional information (Novak-Marcincin et al.,
2013). Augmented reality is especially useful in order-picking warehouse process and this
23
solution allows to apply development and path finding techniques, which help workers to greatly
increase their productivity while picking orders (Cirulis and Ginters, 2013). DHL Logistics
Trend Radar (2014) added that usage of augmented reality would be also beneficial for
companies during such warehouse operations as loading and unloading. Moreover, augmented
reality enables warehouse employees to work hands-free using smart glasses (DHL, 2014), thus
such picking method as pick-by-vision is applied in this case.
The last identified digital solution in warehouse management is robotics. As Galuzzo
(2015) argued supply chain management area will be one of the first industries to derive benefits
from robotics. Robotics can offer an attractive alternative in the future for material handling
(DHL, 2014), since robots can provide zero-defect processes and enhanced sensing capabilities.
Potkonjak et al. (2000) claimed that robots can decrease production costs to a great extent since
dwell-time can be reduced and automated processes can be accelerated. In warehouse
management drones or unmanned aerial vehicles (UAV) can provide a game-changing
alternative to some traditional methods, for instance drones can be used as security tools and for
inventory in warehouses (Vyas, 2016). It is estimated that by 2017 20% of logistics companies
will use drones on a regular basis for monitoring their warehouse operations, searching and event
management (Vyas, 2016). Apart from that robots have plenty of advantages, for instance they
enable more personal flexibility, since they are able to provide 24/7 service. In addition, robotics
can adapt to chaotic and changing warehouse environment due to its self-learning systems
(McKinsey Global Institute, 2013). Despite all mentioned advantages, robots remain one of the
most expensive solutions in warehouse management. McKinsey Global Institute (2013)
determined that industrial robots cost tens or hundreds of thousands of dollars per robot.
Furthermore, adoption of robots requires additional investments, which are estimated from $1.1
trillion to $1.6 trillion by 2025 (McKinsey Global Institute, 2013). Nevertheless, there can be
observed a positive trend in terms of robots’ costs, notably in recent decades prices for robots
have decreased annually by 10% and are expected to decline at a similar or faster rate till 2025
(McKinsey Global Institute, 2013).
Having investigated digital solutions in warehouse management it can be spotted that
majority of the solutions are referred to such warehouse process as order-picking, which is the
most time-consuming process in warehouse management.
1.1.5. Impact of digital solutions on warehouse management
In the previous section digital solutions in warehouse management were identified. The
research goal of the thesis is to develop an algorithm for implementing digital solutions in
warehouse management for Russian companies and to achieve more relevant results it was
decided to focus on several digital solutions for the algorithm development. For that the
24
following table was made, in which all earlier discussed digital solutions in warehouse
management are compared using scale from ‘very low’ to ‘very high’. The analysis is based on
reviewed academic articles of digital solutions in warehouse management (Potkonjak et al.,
2000; Sowinski, 2005; Gu et al., 2007; Wang et al., 2010; McCrea, 2012; Napolitano, 2012;
Ramaa et al., 2012; Bond, 2013; Novak-Marcincin et al., 2013; Phillips, 2013; Xiao-dong and
Fan, 2016) and industry reports (DHL, Capgemini, McKinsey, BCG).
Table 2. Comparison of digital solutions in warehouse management
Criteria
Digital solution
Costs
(implementation and
WMS
Pick-by-voice
Pick-to-light
RFID
3D printing
Augmented reality
Robotics
maintaining)
Medium
Very low
Low
Medium
High
High
Very high
Relevance in <5
Ease of
years
implementation
Very high
Very high
High
Medium
Low
Low
Very low
High
High
High
Medium
Medium
Medium
Low
Source: Author’s analysis based on articles (Potkonjak et al. ,2000; Sowinski, 2005; Gu et
al., 2007; Wang et al., 2010; McCrea, 2012; Napolitano, 2012; Ramaa et al., 2012; Bond, 2013;
Novak-Marcincin et al., 2013; Phillips, 2013; Xiao-dong and Fan, 2016) and industry reports
(DHL, Capgemini, McKinsey, BCG)
It can be observed from the table that WMS, pick-by-voice and pick-to-light have the best
values in terms of costs, relevance and ease of implementation. Since the research goal is to
develop an algorithm for Russian companies, it is relevant to review technologies, which are
used most widely in Russian warehouse logistics. As analyzed earlier the most popular digital
solutions in warehouse management at the present in Russia are WMS and pick-by-voice
(Kholinov, 2007; Blinov, 2011; Evdokimov, 2012). Moreover, as indicated in McKinsey Digital
(2014) the biggest areas of improvements in majority of industries are referred to labor and
quality issues and WMS and pick-by-voice solutions are able to address gap in workers’
performance and decrease number of errors. For these reasons WMS and pick-by-voice are
further considered for developing an algorithm for their implementing in warehouse management
for Russian companies.
In order to achieve the research goal WMS and pick-by-voice technologies are
investigated in more detail.
1.2. Warehouse Management System and Pick-by-voice solutions
1.2.1. Warehouse Management System
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WMS functionality
At present Warehouse Management System (WMS) is the most popular solution in
warehouse management both in international (McCrea, 2012; Hoffman, 2013) and Russian
companies (Blinov, 2011; Evdokimov, 2012). As mentioned earlier WMS is a software system or
database driven computer application for tracking and managing warehouse processes. McCrea
(2012) fairly characterized WMS as ‘the grandfather of the supply chain software space’ and
WMS continues its reign at the present time. WMS serves as a linking node for integration of
digital solutions (e.g. pick-by-voice, pick-by-light, RFID etc.).
Faber et al. (2002) distinguishes three types of warehouse management systems:
Basic WMS – this type of WMS is the most simplistic, since it is appropriate only for
stock and location control and recording information. The focus of the Basic WMS is on
throughput.
Advanced WMS – apart from the functions of a basic WMS, this type has extended
possibilities such as planning of resources and activities for synchronizing goods’ flow.
The focus of the Advanced WMS is on throughput, stock and capacity analysis.
Complex WMS – this type of WMS is the most sophisticated one, since it allows to
optimize a warehouse or even group of warehouses. In terms of functionality, complex
WMS offers a wide variety of functions such as value added logistics planning,
transportation functions, dock door etc. Moreover, complex WMS provides
comprehensive information about all the goods, notably about their location, further
destination and why these goods are stored in the warehouse.
Another classification of WMS systems is proposed by Vjestica (2012), according to
whom there are three types of WMS:
Standard WMS – this type of system requires a set-up and WMS elements cannot
be changed
Configured WMS – in this system there are opportunities to change options or
parameters of the system
Customized WMS – the most sophisticated WMS, since it has range from
standard modules to project specific modules and WMS elements can be changed
Motorola Solutions (2013) predicts that in 2018 among WMS users there will be a shift
towards Best-of-Breed and Full-featured WMS (or how it was revealed above, Complex WMS).
Thus, there will be an increase by 76% among users to Complex WMS and 40% of users will not
use Basic WMS systems anymore.
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Rama et al. (2012) emphasized that WMS could be separate systems or modules of an
Enterprise Resource Planning system (ERP). Moreover, WMS systems can be applied as paper
based, radio frequency/wireless based or combination of these two methods.
Main components of a WMS system are the following ones (Blinov, 2011):
1) The client part (radio terminals)
2) Mobile workstations of workflow participants (mobile trucks with scales, mobile units for
sorting and distribution of goods, etc.)
3) Stationary workstations of workflow participants (operators, supervisors, employees of
packing area, etc.)
4) Application Server, which can sometimes be integrated at the level of the platform used
with server management database
5) Management server databases
To get a deeper understanding of a WMS functionality, the following table was built with
basic, high-end and advanced features, which include tools for supporting particular supply chain
and mostly warehouse operations (McCrea, 2012; Napolitano, 2012; Ramaa et al., 2012; Bond,
2015).
Table 3. Menu of features of a Warehouse Management System
Basic features
Appointment scheduling
High-end features
Radio frequency-directed
Advanced features
Multiple-Data center view
Receiving
Quality assurance
Put-away
operations
Cycle counting
Carton manifesting
Replenishment
Stock-keeping slotting
Broken-case flow
Electronic data interchange
Location tracking
Work-order management
Picking
Packing and consolidation
Shipping
Value-added services
Vendor/carrier compliance
Trailer manifesting
Configurability
Returns
Pick/put to light
Yard management
Wave management
Labor management
Task interleaving
Flow-through processing
capability
Parcel shipping
Impact analysis
Traffic management
Import/export management
Benefits and drawbacks of WMS
The main advantage of WMS system in comparison with Material Resource Planning
(MRP) system and Enterprise Resource Planning (ERP) system is that while MRP and ERP
focus on storing products in fixed storage areas, which is clearly insufficient for effective
warehouse management processes, whereas WMS systems allow to adjust storage locations
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depending on products conditions (temperature, material etc.) and to make stocks inventory
without interfering with production processes (Legutko et al., 2012).
Apart from this benefit, WMS system also allows to ascertain the accuracy of the orders
and shipments, increase throughput with integration with other solutions (Warehouse Control
System, Transportation Management System etc.) and improve labor productivity by tracking
warehouse employees’ productivity and change of their individual key performance indicators
(Napolitano, 2012; Hoffman, 2013). Another advantage of WMS is that all of the warehouse
transactions are tracked and managed by the system and WMS can display all activities in real
time (Vjestica, 2012; Ramaa et al., 2015). Moreover, WMS system allows to substantially reduce
paperwork, as reports with the system can be managed electronically. In addition, WMS provides
better space utilization due to increased speed of fulfillment processes and consequently holding
costs can be drastically decreased (Hoffman, 2013).
Speaking about particular figures Jones (2006) pointed out that typical range of savings
due to WMS implementation is between 20 and 40%. Thus, WMS is able to reduce operating
expenses by 35%, decrease the costs of carrying inventory by 27%, provide more efficient space
utilization from 10 to 20%, drop of inventory by 50% after about 3 years, increase inventory
accuracy by 20% and improve shipping accuracy by around 5%. Moreover, Jones (2006) noted
that overall WMS can decrease the total costs per unit shipped, customer service and phone
costs, the number of inventory out-of-stocks, improve the accuracy and timeliness of deliveries,
increase profitability per order and per customer and as a result increase sales.
However, apart from merits WMS systems have drawbacks as well. WMS systems focus
on ‘daily, sequential, waterfall style task assignments, and this drawback has proven to be a
crippling shortcoming’ (Bond, 2015, p.34). That is why alternative approaches can be taken into
consideration such as various digital solutions (pick-by-voice, RFID etc.). It should be
mentioned that digital solutions don’t replace WMS systems, but complement them, since they
address specific needs in warehouse management.
WMS implementation
Among extant studies there does not exist an algorithm of implementing WMS in
warehouse management. Based on further conducted research such algorithm is developed.
Harrington (2001) and Finkel (1996) propose some recommendations regarding WMS
implementation. As a first step the author claims creating a project management team and
appointing a project leader. As Frank Camean, senior project manager of consulting and systems
integration firm eSYNC International, notes a project leader should be entirely committed to the
project and it is recommended for him/her to have prior WMS implementation experience
(Harrington, 2001).
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As a next step, author recommends creating a project road map or implementation
requirements document (IRP). This document includes project’s objectives, project team
members and their responsibilities, requirements for implementation (functional, operational,
systems integration, technical) and business mandates such as number of interfacing
applications, budget constraints, project deadlines (including interim deadlines), number of
facilities/DCs involved in the project etc. Usually project team members include project
manager, integration test team leaders, technical functional team leaders and application
specialists (Finkel, 1996).
Further, company should decide whether to implement project using an outside consultant
or independently. In case if company implements as advanced or best-of-breed WMS, it is
advised to involve consultants (Aytaman, 2005).
Next, company should conduct a conference room pilot (CRP), which is a process of
assessment how company’s operations match software package’s capabilities. This stage is
carried out by the company and WMS vendor (in case company decided to acquire WMS).
Depending on the project complexity, CRP development can take from 2 weeks to 2 months
(Harrington, 2001).
If company wants to add any modifications to the system, it can submit these
requirements to WMS provider. At the same time project team has to select and acquire all the
required hardware for the new system such as bar code printers, radio frequency equipment,
readers etc. Then training program and manuals need to be developed and training of internal
staff needs to be started (Finkel, 1996).
After finishing WMS design, the phase of testing starts. As Fricke, principal consultant of
PricewaterhouseCoopers’ logistics/WMS practice, claims testing phase is the most crucial and
complex stage of the WMS implementation and the consultant advises to have 4 types of testing
for the project: functional, integration, volume and business readiness testing (Harrington, 2001).
During the testing project the measurement of the degree to which testing is successful should be
identified by the project manager and agreed by all project members.
Simultaneously with the testing phase training of WMS users should be conducted as
mentioned earlier. As Aichlmayr (2002) asserts training is frequently overlooked by companies
during WMS implementation. PricewaterhouseCoopers’ consultants recommend to create a
team, which will be responsible for training of WMS during the whole project. The training can
be conducted in-house or by third-party consultants/WMS vendors.
The next stage stated by Harrington (2001) is the launch of WMS. Before the actual
launch PricewaterhouseCoopers’ consultants advise to carry out physical inventory of the
warehouse. The launch of the WMS usually takes from 1 to 2 months.
29
The last stage is evaluation of WMS implementation, during which success of the project
is measured as well as its specific processes/elements. Harrington (2001) and Aytaman (2005)
emphasize importance of this stage, especially if WMS is implemented in several sites.
Considering payback period of WMS Trebilcock (2009) argued that for a traditional
WMS it is considered to have a 2-year payback period, however in time of a down economy
manager expect to have a 1-year payback or even less. As Ramaa et al. (2012) noted WMS
implementation requires significant money and time investment and before implementation
companies should conduct cost benefit analysis.
1.2.2. Pick-by-voice
Pick-by-voice functionality
More international and Russian companies have started to apply pick-by-voice
technology for their labor-intensive such order-picking, put-away, crossdocking and cycle
counting processes in a warehouse (Sowinski, 2005; Phillips, 2013; Bezotosnaya, 2013).
Analysis of extant studies of digital solutions in warehouse management revealed that pick-byvoice is the second most widely spread solution in warehouses after WMS and considered as a
proven and reliable technology (Sowinski, 2005; Terreri, 2007; Phillips, 2013; McCrea, 2015).
Pick-by-voice technology is a surprisingly old technology, as it has been introduced in the late
1990s in US warehouses (Jones, 2006; McCrea, 2015). Pick-by-voice technology is one of the
modules, which is included in WMS system (Cork, 2005).
Pick-by-voice applies voice direction and speech recognition software with hardware for
guiding during picking, put-away, crossdocking and other processes (McCrea, 2015). The worker
wears a headset, which is connected to a terminal/wireless computer, which in turn is attached to
the worker’s belt. This terminal is wirelessly connected with the WMS. The worker receives
directions through the headset regarding the location of the next item, which has to be picked
(Jones, 2006). Then the worker confirms the location by mentioning a unique code through the
microphone and after that confirms the quantity of picked items. This process is iterated until the
order is completed and then the next order starts (de Vries et al., 2015). Thus, it can be inferred
that pick-by-voice enables two-way real-time communications between the picker and the
system. It is noteworthy to mention that pick-by-voice requires a short training for order-pickers
so that the system can adapt to the voice of pickers (McCrea, 2015).
Benefits and drawbacks of pick-by-voice
As Terreri (2009) and Phillips (2013) pointed out pick-by-voice can provide a substantial
benefit for warehouse workers, since order-pickers can work hands-free and don’t need to
change their focus. Consequently, pick-by-voice technology is suitable for picking heavy items,
since operations with these items require both hands free (Cork, 2005). Thus, pick-by-voice
technology provides voice verification that the task has been accomplished so that quality and
30
speed of order-picking increases. Phillips (2013) also mentioned pick-by-voice could be also
useful for loading operations, since technology allows forklift drivers to report load information
verbally and better concentrate on their operations, increasing safety of the used equipment and
goods.
Another benefit is noticed by Jones (2006) and Jezierski and Preez (2009), who state that
voice direct technology can be used by workers who speak different languages within the same
warehouse, which can be a major advantage for companies with international personnel.
Furthermore, costs of pick-by-voice implementation are rather low and technology itself
is rather simple, especially in comparison with other digital solutions for warehouse
management, which require more investment and provide comparable results (McCrea, 2015).
Moreover, pick-by-voice technology allows to simplify cycle counts, since the worker
can do a count and generate a replenishment request during order-picking. Voice direct
technology can reduce warehouse costs between 10 and 25% and help to achieve 99,8%, which
is not considered as a rare case (Barrows, 2006; Terreri, 2009). Thus, pick-by-voice is an
inexpensive tool, which can influence company’s bottom line.
Overall, it can be inferred that voice direct technology enables to have an increase of
accuracy rates, productivity rates, safer working conditions since pick-by-voice technology
serves as a step-by step ‘mentor’ for warehouse employees.
Apart from the benefits pick-by-voice has also some disadvantages. De Vries et al. (2015)
observed that order-picker performance still greatly depends on the ability of the worker to use
pick-by-voice technology efficiently. Furthermore, McCrea (2015) noted that companies that use
pick-by-voice technology could face problems in case warehouse employees speak in an unusual
manner. For instance, pick-by-voice technology cannot be used by workers who change their
speaking manner, e.g. at first stutter, then speak very fast etc.
Pick-by-voice implementation
As in the case of WMS, among extant studies there is no algorithm of pick-by-voice
technology implementation in warehouse management. However, there are some
recommendations for the implementation, which are presented below.
Phillips (2013) underlined that to achieve better results companies are advised to
integrate pick-by-voice technology into existing supply chain processes in the company and
investigate its usage in every workflow.
According to Hounsell (2005) before the implementation of pick-by-voice warehouse
processes should be reviewed in order to understand in which ways the new technology can
bring better results and form the requirement for the new tool. Moreover, company needs to
decide whether to modify existing process and equipment or not. As Hounsell (2005) points out
this stage can be one of the most time-consuming during the whole implementation project.
31
In the beginning the project team should be assigned managed by the project leader.
Communications during the all implementation project should be maintained in order to curtail
gossips and misunderstanding of the new technology and deliver clear expectation among the
employees (Luedde and Miller, 2009). Further, training with the all involved parties is
conducted, which usually takes several short sessions (Hounsell, 2005). This stage is a crucial
one, since it facilitates personnel engagement in the project (Luedde and Miller, 2009).
A pilot project for pick-by-voice is advised to be done since it allows to reveal software
and hardware errors and inefficiency before the actual launch of technology (Hounsell, 2005).
The last stage includes measuring performance of the employees after pick-by-voice
implementation (Luedde and Miller, 2009) and this evaluation enables to make more consistent
forecasts regarding workload.
Speaking about financial attractiveness of voice direct technology as observed by
Jezierski and Preez (2009) the average payback period of the technology is around 1 year or less,
although authors also mention examples of companies where pick-by-voice technology’s
payback period was around 3 months.
In order to further investigate digital solutions in warehouse operations, empirical study is
conducted. In the second chapter of this thesis, analysis of the best practices of companies in
warehouse digitalization is carried out. During empirical study, implementation of such digital
solutions as WMS and pick-by-voice is analyzed. After that, based on conducted theoretical and
empirical research, an algorithm for implementing of digital solutions (WMS and pick-by-voice)
is developed for Russian companies.
1.3. Research gap
Having conducted comprehensive literature review of digitalization in warehouse
management it was identified that digitalization has made influential changes in supply chain
management and more specifically in warehouse management. More and more companies apply
digital solutions in warehouse management to stay competitive and increase profit. Moreover, it
was observed that warehouses have become a significant link within the supply chain and
considered as growth centers, which can add value. Thus, digital solutions can be company’s
competitive advantage in warehouse management and companies should understand how to
implement digital solutions in warehouse management.
From the literature review it was determined that there are plenty of studies referring to
automation solutions in warehouse management, such as software programs (WMS, ERP, CRM
etc.). Moreover, in extant studies there are some identified technologies, but they mostly refer to
supply chain management or logistics and not to warehouse management. Additionally, there is
lack of research of developing an algorithm of implementing digital solutions in warehouse
management.
32
Hence, the following research questions were stated:
Which digital tools are used in warehouse management?
How digital solutions can be implemented in warehouse management?
It is noteworthy to mention that the thesis is country specific since the research goal of
the study is to develop an algorithm of implementing digital solutions in warehouse management
for Russian companies based on best practices of international and Russian companies. Thus,
cases of Russian companies and Russian branches of international companies are investigated.
Hence, this thesis adds value and brings originality to the current studies, which are limited in
terms of studying digital solutions in warehouse management in Russia.
Research gap exists in both theoretical and practical perspectives. From the theoretical
perspective the research contributes to the sphere of digitalization in warehouse management,
which is quite uninvestigated. Thus, digitalization implications for warehouse management and
digital solutions in warehouse management were revealed. Additionally, impact of digital
solutions on warehouse management was established. Hence, the study is valuable to the
theoretical spheres.
From the practical perspective during the research an algorithm of implementing digital
solutions (WMS and pick-by-voice) in warehouse management was developed, which can be
used by Russian companies and serve as a base for digital solutions implementation in
warehouse management for international companies. Thus, the study holds value for warehouse
managers, IT managers and other employees, who participate in implementation of digital
solutions in warehouse management.
1.4. Summary of Chapter 1
The literature review of digitalization in warehouse management, which is presented in
the first chapter, is conducted thematically. It consists of two parts: digitalization in warehouse
management and Warehouse Management System and Pick-by-voice. In the first part of the
chapter digitalization in warehouse management was investigated. Thus, phenomenon of
digitalization and its development over time was reviewed, warehouse operations and trends
were identified. Additionally, implications of digitalization for warehouse management were
established as well as specific digital solutions, which are applied in warehouse management. A
table with digital solutions in warehouse management and their impact on warehouse
management was built, which will serve as a basis for further research. Having determined that
33
the most relevant at present days and the most widely spread technologies in Russia in
warehouse management are Warehouse Management System (WMS) and pick-by-voice solution,
these technologies were the basis for further research. The second part of the first chapter
includes review of two digital solutions: WMS and pick-by-voice. During this part functionality
of both technologies was established as well as their benefits, drawbacks and recommendations
for implementation.
Having analyzed articles on digitalization of warehouse management, it was found out
that there are very few studies, which identify digital solutions in warehouse management.
Moreover, there is no research on developing an algorithm for digital solutions implementation
in warehouse management. All of the above mentioned indicates that there is a research gap in
the topic of warehouse management digitalization and this topic can be investigated in this
master thesis.
CHAPTER 2. METHODOLOGY OF RESEARCH
The second chapter includes description of the methodology which has been applied in
the research. For the research multiple case study research strategy was chosen, since it complies
with the research goal and the research questions of the thesis. To begin with, research strategy is
presented, which includes using qualitative research approach and multiple case study strategy.
After that data collection process is described. Further the process of data analysis is elaborated.
Finally, the research quality is discussed, which consists of reliability and validity.
2.1. Research strategy
This study is based on qualitative research approach, which is chosen according to stated
research goal and which allows to investigate research questions. Qualitative research study has
plenty of advantages, for instance observation and measurements in natural settings,
interpretation and rational approach, subjective ‘insider’ view, holistic perspective and others
(Ghauri, 2005). In addition, since the topic of digitalization in warehouse management is
currently under development, especially in Russia, it is early to carry out quantitative research
34
and measure any data. Field of digitalization in warehouse management is quite new and
complex and extant theories are not fully available to explain the phenomenon, that is why a
qualitative approach is the preferred one (Kotzab et al., 2005). Moreover, topic of digitalization
in warehouse management is not well structured in the secondary sources, that is why qualitative
research strategy is more suitable in this study.
In order to apply qualitative approach, various research methods in logistics and supply
chain management can be used, which include surveys, case study, interviews, focus groups,
modelling, experiments etc. (Larson and Halldorsson, 2004). All these methods can be useful
tools for research in supply chain management field (Larson and Poist, 2004), but it is important
to choose a research method, which corresponds with the research problem and research goal of
the study.
After the analysis of the articles and textbooks on the researched topic it was inferred that
case study is the most appropriate research method for achieving master thesis goal. As Stuart et
al. (2002) state case study is an appropriate research method for the field of supply chain
management. One of the advantages of the case method is its ability to address ‘Why?’ and
‘How?’ questions in the research process (Ellram, 1996; Meredith, 1998; Yin, 2003). Since the
main research question of the study is ‘How digital solutions can be implemented in warehouse
management?’, case study is suitable for the research.
According to Yin (2003) a case study is ‘an empirical enquiry that investigates a
contemporary phenomenon within its real life context especially when the boundaries between
phenomenon and context are not clearly evident’. Since the topic of warehouse digitalization is
uninvestigated one and digitalization is considered as a contemporary phenomenon (Pfohl et al.,
2015), case study is particularly helpful in this thesis. Moreover, there exists paucity of theory in
the field of digitalization in warehouse management and lack of well-supported definitions,
notably digitalization and digitization terms are frequently used interchangeably, automated and
digital solutions in warehouse management are not clearly defined. Thus, these factors favor the
usage of case study as a research strategy.
Furthermore, data in supply chain management and warehouse management are quite
unstructured (Kotzab et al., 2005) and case study as a qualitative method is suitable in this study.
Stuart et al. (2002) suggest that case study is an appropriate research method, which allows ‘to
map the field of supply chain management, as they allow identification and description of critical
variables’.
Case study are applied to achieve various goals: to provide description (Kidder, 1982),
test theory (Pinfield, 1986; Anderson, 1983), or generate theory (Gersick, 1988; Harris and
Sutton, 1986). In the master thesis cases study research strategy is used in order to generate
theory using evidence from case studies. As Meredith (1989, 1993) showed in several papers
35
case study can capture conceptual developments, but at the same time not proposing immediate
broad theories (Swamidass,1991; Wacker, 1998). Moreover, case study allows to carry out
continuous analysis and thorough and deep analysis of the objects, but still case study results can
be biased due to the fact that this method is rather subjective and has limited representativeness.
It is worthwhile to mention that results from the case study cannot be statistically generalized.
According to Yin (2003) the goal of case studies is to derive analytical generalizations, not
statistical ones.
Yin (2003) states that there are three types of case studies: exploratory, descriptive and
explanatory. In the research combination of descriptive and exploratory case studies are used,
since these types of case study allow to profoundly describe a phenomenon within its context and
allow to define questions (Kotzab et al., 2005).
According to Yin (2003) there are two classifications of case studies: single case study
and multiple case study and holistic and embedded case study. A single case study is usually used
when it represents a critical case or a unique case. Furthermore, a single case can be chosen if it
is typical or provides an opportunity to observe and analyze a phenomenon which was studied
only by few researchers. Multiple case strategy implies using more than one case study for the
research. In multiple case strategy it is expected that findings of the first case occur in other
cases as well and as a result these findings can be generalized. In this thesis multiple case study
is used, which increase level of results’ accuracy and help to provide a sustained and
comprehensive research. There are certain criteria, which should be taken into account while
selecting case studies. For multiple case study method a replication logic often can be used, but it
is also can be used within a certain domain (Eisenhardt, 1989).
Regarding second classification, it is referred to the unit of analysis. When holistic case
study is used, it means that the research is concerned with the organization as a whole. As for
embedded case study it is applied when there is a need of examining a number of logical subunits within the organization, perhaps departments or work groups, which means that several
units of analysis will be involved for the analysis (Eisenhardt, 1989). An embedded case study is
used in the research, since several units of analysis are involved in the study, such as warehouse
department and IT department.
It should be noted that research process for case studies resembles that of other research
(Yin, 2003; McCutcheon & Meredith, 1993). Stuart et al. (2002) proposed a five-stage research
process, which is presented below.
Stage 1.
Define the
Research
Question
Stage 2.
Instrument
Development
Stage 3.Data
Gathering
Stage 4.
Analyze
Data
Stage 5.
Disseminate
Figure 4. The five-stage research process model
36
This research process model is used in this thesis and for convenience research is
described by three stages. The first stage is the theoretical chapter, which investigates
digitalization in warehouse management and such digital solutions as Warehouse Management
System and pick-by-voice. The second stage includes conducting an empirical study, during
which the analysis of the best practices in warehouse digitalization is accomplished. The third
stage of the research consists of developing an algorithm for implementing digital solutions in
warehouse management for Russian companies.
2.2. Data collection
The case study research strategy may include such data collection methods as interviews,
documentation, archival records, direct observations, participant observations and physical
artifacts. Thus, case study allows to have multiple sources of evidence, which is known also as
data triangulation (Yin, 2003). To carry out comprehensive research both primary and secondary
data are used.
Secondary data are usually used in descriptive and explanatory research, which
corresponds to chosen case study group (Saunders, 2011). Secondary data was extremely
important in the beginning of the empirical study when companies were selected for the case
study analysis. After selecting companies and receiving agreement from them for participation in
the research, data about company’s warehouse logistics and digital solutions in warehouse
management were obtained through the secondary sources. In this master thesis secondary data
includes internal company documents, articles and official companies’ websites.
As for primary sources, in this research in-depth semi-structured interviews and
consultations with digital solutions’ integrators are conducted. In addition, for one of the cases
direct observation is conducted. Qu and Dumay (2011) claimed that the interview is one of the
most important qualitative data collection methods and this method has been widely applied in
various studies. For achieving research goal semi-structured interviews were chosen. This type of
interviews was selected due to its flexibility since it allows to modify questions, their order, flow
of the conversation and obtain hidden insights from the respondents (Qu and Dumay, 2011). At
the same time, semi-structured interviews have the basis of the questions and topics to be
covered during the interviews. Regarding consultations with digital solutions’ integrators several
companies were chosen after conducting interviews in the companies where digital solutions
were implemented. In one of the companies warehouse manager agreed to demonstrate digital
solution in action (WMS) and showed company’s warehouse. Thus, direct observation of
company’s warehouse logistics and digital solution was conducted.
37
The main data collection methods in the thesis are in-depth interviews, consultations with
digital solutions’ integrators and company documentation. Official company websites, and direct
observation are also used for the analysis.
The data collection process consisted of three phases: pre-data collection, data collection
and follow-up data collection. Each of the phase is discussed further in more detail.
Phase I. Pre-data
collection
Cases selection
Approaching companies
Interview guide
formulation
Phase II – Data
collection
Conducting interviews
Consultations with
digital solutions’
integrators
Transcription of
interviews
Phase III – Follow-up
data collection
Analysis of documents
Clarifying questions
with companies via email and telephone
Figure 5. Data collection process
The first phase is pre-data collection. This stage consisted of cases selection, approaching
companies and formulating interview guide. In order to select cases criteria for cases selection
were identified. The following criteria were established chosen for cases selection:
• Companies should be logistics providers (3PL) or distribution companies
• Companies should have experience in implementing digital solutions in warehouse
•
management
Russian companies or Russian branches of international companies
After identifying criteria for cases six companies were found for the research. Five of the
companies are 3PL providers and one company is a distribution company. Based on the data
from secondary sources it was found out that all companies had vast experience in implementing
digital solutions in warehouse management and were either Russian companies or Russian
branches of international companies. Moreover, companies are different in terms of country of
origin and company size, which enhances possibility of making analytical generalizations
through the case study research strategy. After these six companies were reached and an
agreement from them to take part in the research was received, it was possible to move to the
next step of pre-data collection – interview guide formulation.
Interview guide was developed both in English and Russian since several interviewees
from Russian branches of international companies were not native Russian speakers. Interview
questions guide can be found in Appendices 1 and 2.
Phase II
The second phase is actual data collection. During this stage interviews with companies’
representatives were conducted, consultations with digital solutions’ integrators were carried out
and further interviews were transcribed.
38
All interview questions are open and interviews are semi-structured, since there was a list
of questions, which contributed to research investigation, but at the same time the questions were
reformulated or varied during the interviews. The interviews were carried out face-to-face or via
Skype, which provide high level of accuracy and preciseness. Moreover, face-to-face interviews
and Skype interviews allow to provide more comprehensive research, understand processes and
their sequence, which is very beneficial for the qualitative research strategy. Interviews are
conducted with managers of high and medium levels, which allow to understand both strategic
and operational views on asked questions. Below a table with interview respondents can be
found for all six cases.
Table 4. Semi-structured interviews respondents
Case company
Company A
Company B
Company C
Company D
Company E
Company F
1)
2)
3)
4)
1)
2)
3)
4)
1)
2)
3)
1)
2)
3)
4)
1)
2)
3)
4)
1)
2)
Interviewees’ position
Head of Warehousing
Marketing director
Warehouse manager
IT specialist and IT manager
Warehouse manager
IT manager and IT analyst
Sales director
Financial director
Commercial manager
Warehouse Manager
IT manager
Warehouse manager
Director of logistics
IT director
Marketing director
Contract logistics manager
IT manager
Head of corporate sales
Warehouse manager
Warehouse manager
Business applications development
manager
3) Head of competence center project
department
Before the interviews each respondent received the interview questions guide as well as
the brief research structure so that the interviewee has clear expectations regarding the interview
and feels more comfortable during the interview. Interviews were conducted from January till
mid of April 2016. This prolonged period of interviews conducting can be explained by the fact
that reaching some of the companies took several months, since some of the case companies
were reached via telephone or e-mail on official companies’ websites and arranging interviews
39
required confirmation of several managers. The average length of interviews was around one
hour.
The interview questions were divided into several groups depending on the data
collection objectives. The first group of questions includes questions about digital solutions in
warehouse management. The second group consists of questions regarding specific digital
solutions in warehouse management, how these solutions were implemented, who was
responsible during each stage of implementation, which problems company faced during the
implementation etc. Interview questions guide can be found in Appendices 1 and 2.
In one of the researched companies direct observation was accomplished, since
warehouse manager agreed to present digital solution in action (Warehouse Management
System) and gave a tour of company’s several warehouses.
After conducting interviews it was found out that in several cases companies cooperated
with IT integrators or consulting companies to implement digital solutions in warehouse
management. Thus, two companies were reached, which helped case companies to implement
technologies. These companies are IT integrator Ant technologies and consulting company
KORUS Consulting. Additional interviews with these companies were conducted regarding the
specific digital solution implementation (WMS or pick-by-voice). Interview questions were
based on earlier mentioned interview questions guide, but were focused solely on the digital
solution implementation (stages of implementation, responsible employees, problems during
implementation etc.). Moreover, after additional interviews consultations with representatives of
Ant technologies and KORUS Consulting were carried out in order to ensure the accuracy of the
developed algorithm for implementing of digital solutions in warehouse management.
When all the interviews and consultations were conducted, interviews were transcribed.
Manual coding was used for all the collected primary data to provide data accuracy and
transparency. Interviews were transcribed both in Russian and English since interviews were
conducted in both languages.
Phase III
The third stage of data collection process is follow-up data collection. This stage included
collection of company’s documentation and clarifying questions and facts via e-mail with the
companies’ representatives.
Company documentation included internal documents such as presentations, reports,
guides, excel files with tables and graphs. This documentation allowed to derive additional data
regarding digital solutions implementation and ensure quality of the research since analysis is
based on multiple sources.
40
Furthermore, official company websites were used again in order to verify obtained data
from the conducted interviews regarding company’s digital solutions and their implementation.
Such sources within the websites were used as publications, news, press releases and articles.
Moreover, during the follow-up data collection regular e-mails were sent to the
companies’ representatives in order to clarify some questions and verify data. Also, several
telephone calls with interviewees were conducted for data clarification.
2.3. Data analysis
Since the research strategy of the thesis is case study, data analysis procedure is divided
into two categories: within-case study analysis and cross-case study analysis. Both analyses were
conducted during the research.
Within-case analysis includes detailed description of cases based on obtained data from
interviews, consultations, company documentation, official websites, observation. Within-case
analysis was extremely helpful at the beginning of the data analysis since it allowed to structure
enormous volume of received data. Thus, within-case analysis allowed to obtain unique patterns
for each case before making generalizations across cases (Eisenhardt, 1989). Moreover, withincase analysis accelerated cross-case comparison.
Cross-case analysis can be typically performed using two tactics (Eisenhardt, 1989). The
first tactic is to select dimensions and then search for within-group similarities and intergroup
differences. Dimensions can be identified based on the existing literature or research problem or
the researcher can choose them. The second tactic consists of selecting pairs of cases and then
listing similarities and differences between each pair of cases. There is also an extension to this
tactic, which consists of grouping cases into larger groups (more than two cases in a group) for
comparison. As Eisenhardt (1989) pointed out comparison of cases can lead to novel findings
such as new concepts and categories in terms of the research problem. For the research the first
tactic was chosen and dimensions were chosen by the researcher and approved during the
consultations with digital solutions’ integrators.
During the data analysis chain of evidence was demonstrated to provide transparency and
reliability of the research. Moreover, multiple quotations were used in each case and as Pratt
(2009) asserts quotes can serve as a proof of further inferences.
For organizing and exploring data coding was used, which is an essential analytical
procedure used during the research (Strauss and Corbin, 1990). All interviews and additional
data (information obtained from consultations, company websites, observation) were coded
manually. For the data analysis open, axial and selective coding were conducted to investigate
digital solutions implementation in warehouse management. In order to carry out open coding
interview transcripts were analyzed several times not to miss any relevant details. After that
different labels were made, for instance ‘project group during implementation’. Next, axial
41
coding was conducted, which allowed to group open codes into categories (Strauss and Corbin,
1990). Eventually, selective coding was carried out in order to identify broad categories based on
developed axial codes. Thus, the applied codes were summarized in the following table.
Table 5. Coding procedure
Selective codes
Digital solution content
Axial codes
Functionality
Solution elements, required equipment
Responsible employees of managing the
Problems during the digital solution
digital solution
Productivity
Costs
Software errors and bugs
implementation
Human factor
Implementation of the digital solution
Stage duration
Stage content
Number of stages
Economic effect
Peculiarities of implementation in Russia
Responsible employees during each stage of
Reasons of implementing the digital solution
implementation
Four selective codes were developed based on the data analysis: digital solution content,
r e a s o n s of implementing the digital solution, problems during the digital solution
implementation and implementation of the digital solution. In Chapter 3 there are presented
results of within-case and cross-case analyses, where axial codes were taken as a basis for the
analysis.
2.4. Research quality
In order to ensure quality of case studies, it should be verified that case studies meet the
requirements of validity (whether the stated evidence is valid) and reliability (whether the stated
evidence is correct) (Stuart, 2002; Yin, 2003). For case study research, Yin (2003) points out how
validity of the research can be ensured. He proposes three types of validity: construct validity,
internal validity and external validity. These three types of validity are ‘applied during different
stages of the research process, as reliability and validity are ensured by a clearly structured
research process’ (Yin, 2003).
As for the construct validity in the chosen case studies different data sources are used:
interviews, consultations, direct observation, internal company documentation, companies’
websites. Moreover, a chain of evidence is carried out since during the interviews all the
42
respondents answers’ are recorded not to miss any important details. Taking into account all of
the above mentioned it can be concluded that conducted case studies have construct validity.
Since internal validity is useful in explanatory studies, not in descriptive ones, this test is
not considered for case studies (Yin, 2003).
External validity is achieved in this research by using multiple case design whereby
pattern-matching approach is adopted (Mentzer and Kahn, 1995). Thus, replication logic in
multiple case studies is used to achieve external validity.
Reliability is established in the research design by using the protocol consistently across
interviews and a common database for collecting and analyzing data. In addition, the interviews
are audiotaped for subsequent transcription to minimize researcher bias and support data quality
and reliability. In order to increase reliability of the study a chain of evidence was maintained.
For that direct quotations of the interviews’ respondents were presented and specific companies’
documents were referred. Thus, an external observer of the study has the opportunity to trace the
evidence derivation from stated research questions and received raw data to case study
conclusions (Yin, 2003).
2.5. Summary of Chapter 2
The second chapter consisted of the research methodology, which will be the basis for
the research. The thesis is based on qualitative research approach, which is chosen according to
stated research goal and allows to investigate research questions. Since topic of digitalization in
warehouse management is not well structured in the secondary sources, that is why qualitative
research strategy is more suitable in this study.
The primary research strategy is multiple case study. This particular method was chosen
for the research since it allows to address ‘Why?’ and ‘How?’ questions in the research process
and the research is an uninvestigated one. In the research descriptive and exploratory case
studies are applied, since this type of case study presents a complete description of a
phenomenon within its context, i.e. how digital solutions are implemented in warehouse
management. For the analysis of case study within-case analysis and cross-case analysis are
applied in order to identify within-group similarities coupled with intergroup differences. For
that, specific dimensions were chosen by the researcher and approved during the consultations
with digital solutions’ integrators.
Regarding data both primary and secondary sources are used. In this master thesis
secondary data includes internal company documents, companies’ websites. As for the primary
sources, in this research qualitative semi-structured interviews with companies’ managers and
digital solutions’ integrators are conducted. As for the criteria for cases selection, Russian
companies or Russian branches of international companies were chosen, who are third-party
43
logistics providers (5 companies) or distribution companies (1 company). Moreover, as an
obligatory criterion was experience of companies in implementing digital solutions in
warehouse management. Interviews in this study are one of the main parts of case study
strategy. The interviews in some cases were followed by additional consultations with the
interviewees to clarify some aspects and verify data. Moreover, for one of the cases observation
was used. Thus, triangulation principle is fulfilled since data from different sources and
different research methods are used, which allows to decrease level of subjectivism and bias,
which is typical for qualitative research. During the study it was verified that the research has
both construct and external validity and reliability in the thesis is also established.
C H A P T E R 3 . A P P L I C AT I O N A N D B E S T P R A C T I C E S O F
DIGITALIZATION IN WAREHOUSE MANAGEMENT
As it was mentioned in the first chapter the following digital solutions were chosen for
the development of an algorithm of implementing digital solutions in warehouse management:
Warehouse Management System (WMS) and Pick-by-voice.
For the research of automation and digital solutions in warehouse management 6
companies were chosen: Company A, Company B, Company C, Company D, Company E and
Company F. Due to the confidentiality reasons names of the companies are not revealed in the
thesis and further companies are referred as Company A, Company B etc.
The following criteria were chosen for cases selection:
• Logistics providers (3PL) and distribution companies
• Experience in implementing digital solutions in warehouse management
• Russian companies or Russian branches of international companies
Thus, the following table with the cases overview was developed.
44
Table 6. Cases overview
Cases
Industry
Country
Company A
Logistics
Company B
Logistics
Company C
Logistics
Company D
Food
Company E
Logistics
Company F
Logistics
provider
Belgium/
provider
provider
distributor
Denmark/
provider
Germany/
provider
Finland/
Russian
Russia
Russia
Russian
Russian
Russian
branch
Pick-by-
branch
Pick-by-
branch
Pick-by-
voice
voice
voice
2010
2014
2014
branch
Digital solution
WMS
WMS
WMS
2005
2005
2005
Implementation
of the digital
solution
Implementation
approach
Cooperation
Independent
with the
Cooperation
Independent
integrator
with the
Cooperation
Independent
integrator
with the
integrator
Number of
implementation
stages
# interviews
logistics
# interviews IT
# interviews
sales, marketing,
5
6
5
5
5
6
1
1
1
2
2
1
2
1
1
1
1
1
1
2
1
1
1
1
finance
Next, case studies for each company are presented. According to Eisenhardt (1989) one
of the tactics for cross-case patterns searching is selecting categories or dimensions. Since topic
of digital solutions in warehouse management is uninvestigated one and consequently there are
no dimensions considering this topic in the existing literature, the dimensions were chosen by the
researcher and approved during the consultations with digital solutions’ integrators (IT
integrators or consulting companies). For the within-case analysis and the subsequent cross-case
analysis the following dimensions were chosen:
1. Reasons of implementing the digital solution in warehouse management
2. Problems during the digital solution implementation in warehouse management
3. Stages of implementation of the digital solution, duration of each stage
4. Responsible employees during each stage of implementation of the digital solution
The within-case analysis is structured the following way. In the beginning overview of
the company and its warehouse logistics are given. Then existing digital solutions in warehouse
management in the company are identified. Further, each of the earlier mentioned dimensions is
analyzed regarding particular company’s digital solution in warehouse management.
45
3.1. Within-case analysis
3.1.1.Within-case- analysis of companies with Warehouse Management System
Company A
Company overview and its warehouse logistics
Company A is an international logistic provider, which has subsidiaries in 20 countries
Company’s headquarter is located in Antwerp, Belgium. Company A is a full-value transport
company, which is oriented to creating new opportunities for its clients and offering customized
solutions.
Company A has subsidiary in Saint Petersburg, which was the first company’s office
opened in Russia. This office has been existed since 1993 and has developed into a full-value
transport company rendering services such as liner agencies and international forwarding. Total
site surface of company’s warehouses is 200 000 m2 (Official website of Company A, 2015).
In order to investigate company’s digital solutions both primary and secondary data
sources were used. Apart from collecting data from company’s website, articles in newspapers, a
series of interviews with company’s employees were conducted. Interview questions are
presented in Appendix 1. Overall, four semi-structured interviews were conducted with the
following company’s representatives: marketing director, warehouse manager, IT specialist and
IT manager and head of warehousing. Moreover, such method as an observation is applied, since
company agreed to demonstrate all its warehouses and its WMS system.
Existing digital solutions in warehouse management
As it was found out from the interview with the marketing director that company has the
following digital solutions in warehouse management: Warehouse Management System (WMS),
Electronic Data Interchange (EDI), Cargo security and tracking system and 3D printing. Next,
each of the digital solutions is briefly discussed. Considering WMS system Company A has
implemented it without assistance and installed it in warehouses in Saint Petersburg and
Chelyabinsk. WMS system is used in the company on a regular basis in the warehouses and
serves as an inseparable tool of all warehouse operations. EDI system was also implemented by
company’s employees without any assistance and this system is used for data interchange in all
company’s warehouses and for WMS functioning as well. Cargo security and tracking system
was also implemented by Company A by itself and this system is currently used only for
maintenance of the company's customers that require transportation of valuable goods. As for 3D
printing it was found out that this digital solution is at the very early stage of implementation in
the company. At the present company acquired Da Vinci model of 3D printer for the general
testing technology and the understanding of its features. As marketing director stated ‘it’s
46
extremely early to say that digital solution has been implemented’. Moreover, he added that
‘there are many options for the implementation of the 3D printer’. Initially, company sees the
development of this digital solution as offering customers some additional services that will help
them increase the value of their business, for instance quick printing of spare parts for the
customers. It is worth mentioning that most of digital solutions in warehouse management
Company A implemented on its own except 3D printing. Due to implementation of digital
solutions using its internal personnel, Company A has valuable experience of implementing such
solutions.
Further, such digital solution of Company A as WMS is analyzed based on the earlier
chosen dimensions taking into account interviews answers, observation of WMS (visual
demonstration of WMS in the company by head of warehousing), company’s documentation and
website.
Reasons of implementing the digital solution in warehouse management
Regarding reasons of implementing WMS in warehouse management there were several
opinions from company’s managers. For instance, head of warehousing mentioned the following
reason:
‘WMS is an inseparable part of everyday warehouse operations and this system is a part
of Big data’.
Head of Warehousing
Moreover, IT and warehouse managers underlined that WMS helps to keep track of
warehouses’ key performance indicators and make forecasts. One of the greatest benefits of
WMS according to them are savings in terms of personnel, time and expenses. For instance,
WMS helps to improve customer service, increase productivity and reduce overhead costs.
Moreover, the whole documents flow is included in WMS, which is very convenient for the
company to accelerate warehouse operations.
As marketing director stated Company A is going to commercialize WMS and intends to
sell WMS as an independent commercial product in 2016. It should be noted that WMS will be
sold only to production companies and not to logistics providers. Thus, company keeps one of its
competitive advantages, since company’s WMS is considered as one of the best systems on the
market (Marketing director, 2016).
Stages of implementation of the digital solution, duration of stages
As mentioned earlier, WMS system was implemented from within and company
implemented it using only its own personnel. As Head of Warehousing stated WMS
implementation started in February 2005 and was developed gradually. WMS implementation
finished in January 2006, so that implementation took 1 year or 250 working days.
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As a first stage of implementing a WMS company did an initial analysis, which included
development of logistics warehouse model, identifying WMS requirements and making decision
considering acquiring a WMS or developing a WMS on its own. According to Head of
Warehousing initial analysis can also include such additional steps as WMS providers’ selection
and tender arrangement, but since Company A implemented WMS on its own, these steps were
not included in WMS implementation. Warehouse manager stated the following reasons of
development of logistics model:
‘Development of logistics model is necessary to determine the warehouse processes and
required documentation, allocate labor resources and loading equipment, calculate performance
storage for each process area, forecast volumes in the warehouse’.
Warehouse manager
Moreover, the theoretical description of the warehouse interaction with external storage
services was provided. The process of creating a logistics warehouse model is quite complex,
and as warehouse manager noted ‘if the company does not have experienced warehouse
specialists, company should attract external consultants’. The result of this step was the
development of the detailed recommendations regarding warehouse operations and the need for
the implementation of WMS was determined. The development of logistics warehouse model
took around 10 working days and was conducted by director of logistics and warehouse manager.
The next step of the initial analysis was identifying WMS requirements based on the
established logistics warehouse model. This step included determining of how WMS would
describe the goods and packaging, how it would distribute the processing warehouse zones, how
it would work with documents and reports, as well as what would be the interface of the system
and the ability to integrate it with other software programs. The outcome of this step was
Systems Requirement Document (SRD), a document with a detailed description of the required
parameters of the management system for a particular warehouse (in this case – for a warehouse
in Saint Petersburg). This step required around one week or 5 working days. The step was carried
out by director of logistics, warehouse manager and warehouse specialists.
The last step of the initial analysis was making decision considering acquiring a WMS or
developing a WMS on its own. During this step Company A determined that it has sufficient
resources for developing WMS without assistance and it doesn’t have to buy any ready-made
software program. It can be observed that developing a WMS on its own is not generally typical
even for logistics providers, but due to the fact that Company A had experienced warehouse and
IT specialists and also had subsidiaries abroad, which already implemented WMS and could
share their experience, decision about developing a WMS from within was not a hard one for
Company A. The make/buy decision took 2 working days and was accomplished by director of
logistics and warehouse manager.
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As a second stage of implementing a WMS Company A started to plan WMS
implementation. To begin with, company defined WMS implementation framework – goal,
objectives, potential limitations, basic requirements for the system and the expected results of the
project. Definition of the project framework took 2 days. Then, company assigned responsible
employees for WMS implementation. The WMS implementation team consisted of Head of
Warehousing, IT director, warehouse manager, warehouse specialists, IT specialists and an HR
specialist. As a project manager Head of Warehousing was assigned. Also a project coordinator
was assigned who was the warehouse manager of Company A. After assigning the project team,
a budget of warehousing department was adjusted taking into account WMS implementation
expenses. Budget adjustment was carried out by Financial director and Head of Warehousing.
After that existing hardware and software programs in all company’s departments were evaluated
by IT specialists so that WMS can be integrated with the existing systems. Further,
communications among all project team members regarding WMS implementation were
established, for instance frequency of meetings, regular consultations via e-mail and calls etc.
Afterwards, an internal promotion of WMS system has started in the company so that all
personnel would be aware of the new coming system and would be prepared for changes. This
task was accomplished by Marketing director and HR specialist. The planning stage required
around 2 months.
The third stage of WMS implementation consisted of developing of a WMS. This stage
was the most time-consuming since it required determining WMS content, specific modules,
which are to be included in WMS, detailed description of these modules, defining integration of
WMS and existing systems. This stage required around 6 months and was carried out by director
of logistics and IT specialists.
The fourth stage was practical implementation of WMS. This stage included
informational and technical support throughout the whole WMS implementation project. Further,
a pilot version of WMS was launched, which included main WMS functions. After that feedback
about pilot version was received and as a result all shortcomings were corrected. As an example
of a shortcoming Head of warehousing cited an example when a pilot version revealed that
WMS was not integrated with the security system, which could complicate and slow down
warehouse operation to a great extent. When all shortcomings were corrected, WMS was
implemented to the full extent, i.e. all initially approved modules were launched in the system
and WMS was launched. After that trainings for warehouse and IT specialists were carried out.
After the WMS launching the feedback was collected one more time in order to eliminate all the
potential shortcomings. Throughout the whole practical implementation stage monitoring of
WMS usage was carried out. The stage required around 2 months and was accomplished by
49
director of logistics, warehouse manager, IT director, warehouse specialists, IT specialists and
HR specialist.
The fifth stage was the last one and consisted of evaluation of WMS performance. During
this stage key performance indicators (KPIs) of warehousing department were measured from
the date of WMS launch. According to Head of Warehousing KPIs have been greatly improved
since the WMS implementation, for instance stock accuracy, order accuracy, number of incidents
and near misses have been drastically improved. Moreover, amount of control was significantly
reduced, which allowed employees to invest their time in other tasks. However, direct and
precise impact of WMS implementation was hard to measure. As marketing director stated:
‘There were many other factors, which could potentially influence warehousing
department performance (e.g. seasonality, personnel changes etc.), that is why we didn’t
evaluate impact of WMS implementation right away.’
Marketing director
Further, payback period of WMS was evaluated and equaled 1,5 years. The evaluation
stage required around 2 months to identify impact of WMS implementation. The stage was
carried out by warehouse manager, HR director and HR specialist.
Despite the fact that WMS was implemented in 2006, WMS development team in Saint
Petersburg was constantly working on system improvement. Currently, Company A has assigned
a WMS product manager, who is in charge of the entire system. As it was found out from the
interview with IT manager and IT specialist Company A intends to launch plenty of additional
modules in WMS, for instance mobile application WMS SaaS for Android, flexible licensing
module, voice order picking module, module of inventory management for clients and others.
Responsible employees during implementation of the digital solution
As mentioned earlier for the WMS implementation project Company A assigned a team,
which consisted of Head of Warehousing, IT director, Warehouse manager, warehouse
specialists, IT specialists and an HR specialist. As a project manager Head of Warehousing was
assigned and as a project coordinator Warehouse manager was assigned. During some of the
stages other employees were involved, such as Marketing director, but these employees were not
included in the core project team and for that reason were not mentioned earlier.
Problems during the digital solution implementation in warehouse management
During the WMS implementation there were some problems, which further were
eliminated. For instance, as Head of warehousing mentioned the following problem during the
WMS implementation:
‘There was a lack of module-based structure during the implementation and that
complicated tracking and managing warehouse operations’.
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Head of Warehousing
Since company developed a WMS on its own and didn’t have prior experience of
developing such system, the mentioned problem was a quite predictable one. Currently,
Company A WMS does have module-based structure, what is especially beneficial for the
company, since it is going to commercialize WMS in 2016. Another problem during the
implementation was lack of documentation (e.g. how the system was built) and no database
structure. Furthermore, during the implementation company sometimes applied trial and error
approach, for instance when it launched some of the additional modules.
Company B
Company overview and its warehouse logistics
Company B was established in 2005. It was founded with the participation of multimodal American transport company and Company B is pleased to offer its services in the field of
warehouse and transport logistics. The basic principle of Company B is to provide a high level of
services that allow customers to effectively address the challenges.
Company has warehouses of categories A and A +, corresponding to the highest
international standards in the field of storage and handling. The warehouse complex is located in
Moscow and has a total area of over 33,000 m2. Apart from Moscow branch company is going to
establish warehouses in the Moscow region, St. Petersburg and Yekaterinburg (Official website
of Company B, 2015).
The main goal of Company B is to provide integrated logistics services (design,
organization and effective management of supply chain based on customer requirements) at the
level of the national logistics operator with the use of modern business and information
technology in the field of logistics.
For investigating company’s digital solutions both primary and secondary data sources
were used. Secondary data sources included company’s website, internal company
documentation, articles and primary data sources consisted of interviews with company’s
employees. Interview questions are presented in Appendix 1. In total, four semi-structured
interviews were conducted with the following company’s representatives: warehouse manager,
IT manager and IT analyst, sales director and financial director. Moreover, an additional
interview with an expert of WMS implementation was conducted, since this expert is a
consultant from Ant Technologies, who participated in WMS implementation in Company B.
Existing digital solutions in warehouse management
During the interview with the warehouse manager it was found out that Company B has
only WMS among digital solutions. Company B has implemented WMS in warehouse
management in cooperation with the company Ant Technologies. Further, WMS implementation
is analyzed in detail.
51
Reasons of implementing the digital solution in warehouse management
As for the reasons of implementing WMS warehouse manager noted that ‘our company
needed to find and implement the most suitable WMS system, which would help to quickly
reduce costs in the warehouse and get a real economic benefit’.
Warehouse manager added that WMS would allow to have effective and economical use
of specialized storage equipment and storage space, reduce storage costs and handling of goods.
Management of the company will be able to receive full information about the warehouse in real
time, which would allow to manage the company effectively.
In addition, IT manager of Company B pointed out that:
‘WMS would be integrated with existing software programs and as a result accelerate
warehouse operations’.
IT manager
Furthermore, warehouse manager emphasized that in 2005 Company B required
multifunctional management tool that allows to significantly increase employee productivity.
Stages of implementation of the digital solution, duration of stages
WMS implementation in Company B was carried out in cooperation with company Ant
Technologies, which is the leader of the Russian market of IT solutions for logistics. According
to warehouse manager WMS implementation started April 2005 and finished in March 2006.
Thus, implementation took 1 year or 250 working days. As senior consultant of Ant Technologies
noted and Warehouse manager confirmed that currently 3PL providers tend to cooperate with
consulting companies or IT integrators for the digital solutions’ implementation.
The first stage of WMS implementation in Company B was initial analysis, which
consisted of identifying WMS requirements and making decision considering acquiring or
developing WMS on its own. As a first step company identified WMS requirements. Thus, as
warehouse manager clarified, future WMS should be able to keep records of almost all
warehouse operations:
Collecting information about the address storage of goods
Supporting the work with radio terminals and specialized equipment
Organizing work with bar codes
Keeping records of the working time of employees and the number of transactions made
by them
Automatically generating and delivering reports
Implementing handling a variety of options for different clients within one warehouse
Supporting several geographically distributed warehouses
Apart from that, it was found out that as additional requirements company stated that
WMS should have a clear and open architecture with the ability to support and develop the
system by company’s own resources. Moreover, WMS should have a Russian interface.
52
Identifying WMS requirement took around 1 week and was conducted by director of logistics,
warehouse manager and warehouse specialists.
The second step of initial analysis stage was making decision regarding developing a
WMS without assistance or acquiring a WMS. Since in 2005 Company B didn’t have any
experience in digital solutions in warehouse management, company’s management decided to
acquire a WMS from the provider. It is worth mentioning that in 2003-2005 in Russia there was
observed a phase of development among WMS systems (Trotsky, 2009) and it was quite typical
for a logistics provider to attract a third-party provider to implement WMS. Therefore, company
decided to acquire a WMS to make implementation process less time-consuming and less costly.
The make/buy decision took 2 working days and was accomplished by director of logistics and
warehouse manager.
The second stage of WMS implementation included supplier selection of WMS. In case
of Company B it was required to choose a specialized system that would be able to keep records
of almost all warehouse operations at the existing terminal. It should be mentioned that suppliers
of WMS systems can offer either customized WMS system for the specific clients or ready-made
solutions that require insignificant adaptation. As the warehouse manager emphasized:
‘When choosing a supplier, it is necessary to be guided by the following criteria: ability
of the WMS to meet the requirements of the developed logistics warehouse model of the
warehouse, variety of WMS functions, simplicity of the system for the staff, ROI of the system, as
well as reliability of the supplier and quality of supplier’s services’.
Warehouse manager
In addition, the warehouse manager mentioned flexibility of WMS, which is an important
issue since in case of business environment changes, settings of WMS should be able to be
quickly changed to support warehouse operations. The supplier selection stage required around 3
months and was accomplished by director of logistics, warehouse manager, IT director, senior
consultant and junior consultants from Ant Technologies.
The third stage of WMS implementation consisted of tender arranging. Company B
considered several proposals for warehouse automation. First of all, it takes into account factors
such as the complexity, functionality of the system, the possibility of adapting it in commercial
logistics, ease of management and the ability to independently maintain and refine the system.
Only after considering these mentioned factors company turned to the price factor. As a result,
the company chose Ant Technologies provider, which offered such system as Logistic Vision
Suite, which is based on supply chain management system, developed by Mantis International.
According to warehouse managers and IT manager. As senior consultant of Ant technologies
noticed:
53
‘Logistic Vision Suite is a powerful modern solution designed primarily for automation of
logistics business processes of large and medium-sized enterprises and oriented to help working
in the various segments of the companies in the development of their business’.
Senior consultant of Ant technologies
The tender arranging stage took 3 months and was accomplished by director of logistics,
warehouse manager and senior consultant from Ant Technologies.
The fourth stage of WMS implementation was planning of WMS implementation. During
this stage Company B defined project framework, such as goal, objectives, expected results of
the WMS implementation. Then company’s management assigned a project team for WMS
implementation. The project team consisted both of Company B and Ant technologies
employees. From Company B there were warehouse manager, IT director, warehouse specialists,
an IT specialist and an HR specialist. From Ant Technologies there were senior and junior
consultants and an IT specialist. As a project manager Ant Technologies’ senior consultant was
assigned. As a project coordinator the warehouse manager of Company B was assigned. Further,
necessary documentation required for WMS implementation was developed and approved. As a
next step communication among all project team members regarding WMS implementation were
established, for instance frequency of meetings, regular consultations via e-mail and calls etc.
Moreover, for smoother WMS implementation an internal promotion of WMS in Company B
was required. This step was carried out by marketing director and HR specialist. Planning stage
took around 2 months.
The fifth stage was practical implementation of WMS. As it was found out from the
interviews, implementation of WMS implies not only the physical installation of the software on
the server, but also the description of the settings of business processes in the WMS system. To
ensure the efficient cooperation of Ant Technologies and Company B it was important to carry
out integration between the proposed WMS system of Ant Technologies and existing software
programs of Company B. It was also important that customers of Company B felt comfortable
working with the new WMS system.
The practical implementation stage required around 2 months and was accomplished by
director of logistics, warehouse manager, IT director, warehouse specialists, IT specialists, HR
specialist and senior and junior consultants from Ant Technologies.
According to the Ant Technologies consultant the practical implementation stage
consisted of the following steps:
1. Installation of the server software of WMS system and client (Company B) places, tuning
radio terminals for working with the new system
2. Description and configuration of the client business processes
3. Testing of the system and loading the initial data
54
4. Comprehensive training of dispatchers, administrators and other technical staff of the
warehouse
5. Optimization of business processes included in the system
6. Development and maintenance of WMS system
In addition, as part of the implementation optional billing module was installed, which
provided full control over all payments to existing customers and created an account with the
maximum level of detail for any warehouse operations and the units of goods. It also allowed to
bill for the various operations of accommodation, travel, recruitment, selection, packaging and
shipment. It is worth noting that in the entire warehouse Wi-Fi network was set up and radio
terminals and printers for printing labels were installed.
The sixth stage was evaluation of WMS performance. As a result of WMS
implementation it was observed that employee productivity has increased, storage equipment and
storage space has been used more effectively and storage costs were reduced. In addition,
information exchange process was accelerated by several times. Company B didn’t estimate
return on investment of WMS implementation, since it was hard to measure the direct impact of
WMS implementation on warehouse operations efficiency. The evaluation stage required around
2 months to identify performance of warehouse operations after WMS implementation. The
stage was carried out by warehouse manager, HR director and HR specialist and senior
consultant from Ant Technologies.
Responsible employees during implementation of the digital solution
As mentioned earlier the project team consisted both of Company B and Ant technologies
employees. Company B employees included warehouse manager, IT director, warehouse
specialists, an IT specialist and an HR specialist. Ant Technologies consisted of senior and junior
consultants and an IT specialist. As a project manager Ant Technologies’ senior consultant was
assigned. As a project coordinator the warehouse manager of Company B was assigned.
Problems during the digital solution implementation in warehouse management
During the WMS there were revealed some problems. First of all, the disparity of some
aspects of Russian specifics was identified, also there were software bugs and errors in the
system configuration connected with the lack of experience. However, through interaction with
the consultants of Ant Technologies ways of solving arising difficulties were found. The most
important and serious problem during WMS implementation was the human factor. Thus, a link
between the activities of each individual employee in the warehouse and prescribed business
processes of WMS should have been established, thereby building a single mechanism of
information system and personnel formalized rules.
55
Company C
Company overview and its warehouse logistics
Company C was founded in Saint Petersburg in 1997. The company is a Russian thirdparty logistics provider and it provides services in warehouse logistics, transportation logistics
and consulting services. Company is oriented to providing individual approach to its clients and
a simple and transparent billing system for its customers. Moreover, company strives to apply
cutting-edge technologies in its business processes to increase efficiency of the operations and
provide higher level of customer service.
Regarding its warehouse logistics, Company C has started to provide warehouse services
since 1997. Company’s main specialization is custody services (responsible storage of goods). At
present company has a leading position on the St Petersburg market of custody services. Since
2008, company has been operating in the warehouse of category A, which complies with the
highest standards in warehouse management. The total area of the warehouse complex is 25,000
m2 .
In the next 5 years company intends to diversify geographically and develop a network of
branches, operating on the principle of regional distribution centers (warehouses). As potential
location company considers such cities as Rostov, Samara, Nizhny Novgorod, Novosibirsk,
Yekaterinburg, Kaliningrad (Official website of Company C, 2015).
In order to conduct analysis of WMS implementation in the company both primary and
secondary data sources were used. Secondary data sources included company’s website, internal
company documentation, articles and primary data sources consisted of interviews with
company’s employees. Interview questions are presented in Appendix 1. In total, three semistructured interviews were conducted with the following company’s representatives: commercial
manager, warehouse manager and IT manager.
Existing digital solutions in warehouse management
During the interview with commercial manager it was found out that company has only
WMS among digital solutions. Regarding other digital technologies (RFID, pick-by-voice, 3D
printing) commercial director noted that they are rather expensive and company cannot allow
additional expenses due to the current economic downtime. Company has implemented WMS in
warehouse management on its own and didn’t use any outside personnel. Next, WMS
implementation is analyzed in detail.
Reasons of implementing the digital solution in warehouse management
Considering reasons for WMS implementation commercial manager pointed out the
following reasons:
56
‘WMS allowed reducing time for goods’ put-away and order-picking processes,
decreasing number of errors among warehouse employees and reducing overhead costs, notably
decreasing warehouse personnel due to increased warehouse efficiency’.
Commercial manager
Warehouse manager added that WMS was also implemented due to relocation of
company’s warehouse and the old software system wasn’t suitable for the new warehouse, since
this system caused plenty of human errors and didn’t provide required accuracy rates.
Furthermore, IT manager stressed that WMS enabled integration with existing company’s
software programs and consequently this integration helped to eliminate double-checking of data
in different programs.
Stages of implementation of the digital solution, duration of stages
Implementation of WMS in the company was conducted independently so that company
involved only its internal personnel. As warehouse manager stated implementation started in
February 2005 and finished in January 2006. Hence, implementation took 1 year or 250 working
days. According to the commercial manager and warehouse manager nowadays 3PL providers
prefer to cooperate with consulting companies for the digital solutions’ implementation.
As a first stage of WMS implementation company conducted an initial analysis, which
consisted of identifying WMS requirements and making decision considering acquiring or
developing WMS on its own. To begin with, company identified WMS requirements. Identifying
WMS requirements required 5 working days. The step was carried out by director of logistics,
warehouse manager and warehouse specialists.
From the company’s internal documentation it was found out that company expected the
following WMS requirements:
The system should be focused not only on account of warehouse operations, but also on
the preliminary recommendations regarding the implementation of these operations (for
example, recommended cells for goods storage)
The system should store data about all the warehouse transactions performed in the
warehouse
The system should support data exchange of files of different formats (Excel, csv, txt,
html)
The system should support the designated inventory storage location, which allows
locating items in the most accurate and fastest way
The system should support warehouse bar coding elements
The system should support the exchange of messages between the PC client and terminal
client
57
The system should support different warehouse modes such as cross-docking mode and
wave mode
The system should support operations with serial and defective goods
The second step of initial analysis stage was making decision regarding developing a
WMS using its internal personnel or acquiring a WMS. The make/buy decision took 2 working
days and was accomplished by director of logistics and warehouse manager. Company decided
to implement WMS on its own, since it had highly qualified personnel among warehouse and IT
employees. As warehouse manager emphasized:
‘Our company was one of the pioneers on the Russian market who implemented WMS
from within’.
Warehouse manager
The second stage of WMS implementation included planning of WMS implementation.
In the beginning of this stage company defined project framework, such as goal, objectives,
expected results of the WMS implementation. After that company developed technical design
specification or product requirements document, where the following elements were stated:
purpose of the object, its technical characteristics, quality of project performance, technical and
economic requirements. Next, company assigned a project team for the implementation. The
project team consisted of warehouse manager, operations manager, IT manager, IT specialist and
an HR specialist. As a project manager warehouse manager was assigned. As a project
coordinator operations manager was assigned. Afterwards necessary documentation required for
WMS implementation was developed and approved. During the planning stage regular
communications among the involved project members were established. Apart from that a HR
specialist did an internal promotion of WMS to prevent misunderstanding of the new project and
provide clear expectation about the system. The planning stage required around 2 months.
The third stage of WMS implementation consisted of developing of a WMS. This stage
was the most time-consuming since it required determining WMS content, specific modules,
which are to be included in WMS, detailed description of these modules, integration of WMS
and existing systems. WMS was developed by company’s IT specialists and this development
took 3 months.
The fourth stage included practical implementation of WMS. As warehouse manager
stated this stage took 3 months. At the beginning of this stage a pilot version was launched in
order to identify possible shortcomings of the system and to correct them. IT manager elaborated
the content of the practical implementation stage:
‘Practical implementation of WMS consisted not only of the physical installation of the
software on the server, but also integrating WMS with the existing programs’.
IT manager
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The fifth and the last stage was evaluation of WMS performance. After practical
implementation of WMS warehouse manager observed that warehouse workers’ productivity has
been significantly increased and order-picking accuracy has been boosted so that company had
very few mistakes during its warehouse operations. The evaluation stage required around 2
months to identify impact of WMS implementation. The stage was carried out by Warehouse
manager, HR director and HR specialist.
As commercial manager stated company reduced its warehouse personnel by 25% after
WMS implementation. Commercial manager added:
‘We didn’t estimate return on investment of WMS since it would be very imprecise and it
was obvious for us in the beginning that WMS implementation would have much more benefits
than incurred costs’.
Commercial manager
Responsible employees during implementation of the digital solution
The project team included employees from various departments such as warehouse
manager, operations manager, an IT specialist and an HR specialist. Additionally, a project
manager was assigned who was company’s warehouse manager as well as project coordinator,
who was company’s operations manager.
Problems during the digital solution implementation in warehouse management
Regarding problems, which occurred during WMS implementation, there were some
problems connected with technical issues such errors in software and bugs. Apart from that,
commercial director noted that there was resistance from warehouse employees who did not see
benefits of the WMS at first. In addition, a predictable problem occurred during integration of
WMS with existing company’s software since they had different data formats, layout etc.
3.1.2. Within-case analysis of companies with Pick-by-voice solution
Company D
Company overview
Company D is one of the largest distributors of food products in the Russian market. The
company is part of an international holding founded in 1978 in Denmark and operating on the
markets of over 20 countries of the world. Company D in Russia was founded in 2009. The
partners of the company are almost all the major players in the HoReCa segment and retail
industry. Company's approach of organizing warehouse processes is determined by the high
requirement on the quality of goods and services. Company’s mission is defined as linking
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suppliers of high quality products, business solutions and brands to customers in the market,
ensuring the growth of the value of their business.
In order to analyze company’s digital solutions both primary and secondary data sources
were used. Secondary data sources included company’s website, internal company
documentation, articles and primary data sources consisted of interviews with company’s
employees. Interview questions are presented in Appendix 2. In total, four semi-structured
interviews were conducted with the following company’s representatives: warehouse manager,
director of logistics, IT director and marketing director. Moreover, an additional interview with
an expert of voice order picking implementation was conducted, since this expert is a consultant
from KORUS consulting, who participated in pick-by-voice implementation in Company D.
Existing digital solutions in warehouse management
Among digital solutions in warehouse management Company D has WMS (Manhattan
SCALE) and pick-by-voice/voice order picking technology. It is worth mentioning that pick-byvoice technology is connected with WMS system. Since 2010 company has installed WMS
system, implementation of pick-by-voice technology was much less complicated. Further, pickby-voice technology implementation is investigated in detail. This technology was implemented
in Company D in cooperation with KORUS consulting, a Russian system integrator, which deals
with the optimization of business processes, implementation of information systems and IToutsourcing.
Reasons of implementing the digital solution in warehouse management
Company D decided to implement pick-by-voice technology for several reasons. Firstly,
the use of voice order picking in the warehouse can significantly increase the productivity of
warehouse operations, improve screening accuracy and the ergonomics of the warehouse.
Secondly, such system makes it possible to reduce training personnel costs. Moreover, due to the
fact that voice order picking is conducted via voice portable terminals and these terminals send
employees step by step voice instructions directing an employee to a particular passage or cell
for the selection of the necessary goods, the employee does not have to learn the picking lists, he
focuses on the task. As a result, an employee achieves a significant reduction in the number of
picking errors and accelerates the processing of each order line. As it was found out from the
interview with the warehouse manager, voice technology is particularly effective in warehouses
with a wide range of goods, special temperature conditions, where a large amount of manual
selection is expected (picking). As the warehouse manager stated his opinion considering
training warehouse personnel:
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‘A new employee needs just one working day in order to learn how to work with a voice
terminal and fully perform the duties of a warehouse worker’.
Warehouse manager
Stages of implementation of the digital solution, duration of stages
Pick-by-voice implementation in Company D was carried out in cooperation with
company KORUS consulting, which is one of the leading Russian system integrators. According
to the warehouse manager implementation of pick-by-voice technology started August 2010 and
finished in January 2011. Thus, implementation took 6 months. As director of logistics and
warehouse manager pointed out logistic providers currently in majority of cases tend to
cooperate with consulting companies for the digital solutions’ implementation.
In 2010, Company D has built a new distribution center with total area of 11000 m 2 in the
Moscow region and started to use it. Later company decided to automate operations of the new
warehouse and integrate WMS with voice order picking technology.
The first stage of pick-by-voice implementation in Company D was initial analysis. Since
company already had installed WMS, logistics warehouse model was already developed before
pick-by-voice implementation. Thus, the initial analysis stage consisted of making decision
considering acquiring or developing pick-by-voice technology on its own. Due to the fact that
Company D in Russia was founded in 2009 and didn’t have vast experience in Russia, company
decided to acquire voice order picking technology. The make/buy decision stage required 2 days
and was done by director of logistics and warehouse manager.
The second stage of pick-by-voice implementation was supplier selection. After
monitoring the Russian market of warehouse pick-by-voice solutions and taking into account
experience of European subsidiaries of the Company D international holding, company's
management decided to implement a voice order picking technology ‘Vocollect Voice’. Partner
of this technology implementation was a Russian IT-integrator KORUS Consulting, which is an
exclusive partner of Manhattan Associates in Russia and CIS countries. As director of logistics
underlined:
‘We decided to work with KORUS Consulting, because this company has a great
experience in implementing large and complex projects in the field of warehouse management’.
Director of logistics
Supplier selection stage required around 1 month and was carried out by director of
logistics, warehouse manager, IT director, senior and junior consultants from KORUS
consulting.
Furthermore, director of logistics added that Company D monitors actions of their
competitors in terms of warehouses automation on a regular basis and according to the
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company’s observation Manhattan solutions, provided by KORUS Consulting at distribution
centers of other companies fully met the imposed expectations. Since company already selected
a supplier for pick-by-voice, tender arranging was no longer needed.
The third stage consisted of planning pick-by-voice implementation. During this stage
company defined project framework, such as goal, objectives, expected results of the technology
implementation. Afterwards, a project team was assigned for pick-by-voice implementation. The
project team consisted both of Company D and KORUS consulting employees. Company D
employees consisted of director of logistics, warehouse manager, IT director, warehouse
specialists, an IT specialist and an HR specialist. KORUS employees consisted of senior and
junior consultants and an IT specialist. As a project manager KORUS senior consultant was
assigned. As a project coordinator director of logistics of Company D was assigned. As a next
step of planning stage all the required documents for the project were developed and approved.
Further, communication process between all project members was established, for example there
was made a schedule of meetings, regular reports and calls. In order to accelerate the pick-byvoice implementation HR department of Company D made the internal promotion of the new
technology launch among all company’s employees. The planning stage took 2 months and was
conducted by director of logistics, warehouse manager, IT director, senior and junior consultants
from KORUS consulting.
The fourth stage was practical implementation of pick-by-voice. During this stage not
only physical installation of the new technology was carried out, but also all warehouse
operations were revised according to the new technology. Moreover, an integration of WMS and
voice order picking technology was accomplished. The practical implementation stage required
2 months and was accomplished by director of logistics, warehouse manager, IT director,
warehouse specialists, IT specialists, HR specialist and senior and junior consultants from
KORUS consulting.
The fifth stage was evaluation of pick-by-voice performance. After the new technology
implementation it was observed that employee order picking productivity has significantly
improved and as a result employee motivation has also increased. Evaluation stage took around 1
month and was done by warehouse manager, HR director and HR specialist and senior consultant
from KORUS consulting.
After 2 years company estimated the interim results of the implementation. According to
the company’s daily statistics staff productivity has dramatically increased, i.e. number of
processed goods per each employee in the warehouse. In the beginning of 2012 employee
productivity was approximately 300 kg per hour and at the end of 2012 productivity reached a
value of 800 kg per hour. As director of logistics noted by the example of Company D an
additional conclusion can be made.
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‘Improving technology helps employees to increase their productivity, consequently
productivity growth leads to an increase in salary, since this criterion is taken into account in
calculating the remuneration’.
Director of logistics
Hence, it can be inferred the staff has an additional incentive to increase its productivity
and the efficiency of all company increases correspondingly.
Responsible employees during implementation of the digital solution
Project team consisted both of Company D and KORUS consulting employees. Company
D team included of director of logistics, warehouse manager, IT director, warehouse specialists,
an IT specialist and an HR specialist. KORUS team included senior and junior consultants and
an IT specialist. As a project manager KORUS senior consultant was assigned. As a project
coordinator director of logistics of Company D was assigned.
Problems during the digital solution implementation in warehouse management
During the pick-by-voice implementation company faced several problems. First of all,
there were software bugs and errors in the system configuration connected to the lack of
experience. However, through interaction with the consultants of KORUS consulting, Company
D solved all system errors. One of the major problems during the implementation was connected
with the personnel, since all warehouse employees should have been trained how to work with
the new technology. Moreover, initial resistance of the new technology of some of the employees
also took place. As a potential problem HR director mentioned staff reduction due to the future
increased employee productivity. However, company’s management company chose a different
scenario. By increasing employee productivity with the help of pick-by-voice technology, the
company did not reduce staff and instead increased volumes of trade flows, shipping and
developed new areas of business. For instance, company began to develop the new area of safe
custody services. As a result, since the implementation of voice order picking the number of
clients has been significantly increased. The system allows to create multi-dimensional regular
reports to provide customers with accurate timely information on commodity stocks.
Company E
Company overview and its warehouse logistics
Company E was founded in Germany in 1980 and currently has grown into one of the
world's leading logistics providers. At present company is presented in over 100 countries.
Company has plenty of capabilities in different areas such as seafreight, airfreight, contract &
integrated logistics and overland. Company E provides logistics services in all key industry
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sectors: aerospace, automotive, FMCG, high tech, industrials, oil & gas logistics, pharma &
healthcare and retail (Official website of Company E, 2016). Company has cutting-edge IT
systems, global logistics network and provides excellent customer service. Warehouse logistics is
included in contract & integrated logistics area.
In Russia in contract & integrated logistics company provides comprehensive services to
meet the specific needs of customers in terms of 139 000 m 2 of warehouse space in the 5
logistics centers (both specialized and multi-client), which are located in Moscow and Leningrad
regions (Official website of Company E, 2016).
For the analysis of company’s digital solutions both primary and secondary data sources
were used. Secondary data sources included company’s website, internal company
documentation, articles and primary data sources consisted of interviews with company’s
employees. Interview questions are presented in Appendix 2. In total, four semi-structured
interviews were conducted with the following company’s representatives: contract logistics
manager, IT manager, head of corporate sales and warehouse manager.
Existing digital solutions in warehouse management
Company E has vast in-house experience in terms of digital solutions in warehouse
management. Company implemented on its own all digital solutions, such as WMS, Radio
frequency identification (RFID), pick-to-light and pick-by-voice technologies. Further, pick-byvoice technology is investigated in detail.
Reasons of implementing the digital solution in warehouse management
Company implemented pick-by-voice technology for several reasons. First of all,
company had problems with levels of order picking performance. Due to pick-by-voice
technology implementation, company was able to improve its key performance indicators in
terms of warehouse operations. As contract logistics manager stated:
‘Company’s management wanted to improve productivity of warehouse employees,
achieve greater order picking accuracy and improve entire warehouse management efficiency’.
Contract logistics manager
Stages of implementation of the digital solution, duration of stages
Company E carried out voice order picking implementation on its own in Russia, since it
had vast in-house experience of implementing digital solutions and company already
implemented such technology in other subsidiaries. According to the contract logistics manager
implementation of pick-by-voice technology started in the beginning of October 2014 and
finished in the end of May 2015. Thus, implementation took 8 months.
The first stage of pick-by-voice implementation in Company E was initial analysis. Since
company already had installed WMS, company didn’t need to develop a logistics warehouse
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model. Thus, the initial analysis stage included making decision considering acquiring or
developing pick-by-voice technology on its own. Since Company E had rich experience in
cutting-edge solutions in warehouse management and other company’s subsidiaries could share
their knowledge with the Russian subsidiary’s employees, company decided to implement pickby-voice technology without assistance. The make/buy decision stage took 2 days and was done
by director of logistics and warehouse manager.
The second stage was planning of pick-by-voice technology implementation. This stage
included identifying goal and objectives of implementation, expected results and project
limitations. Then, for the implementation a project team was assigned. The team consisted of
contract logistics manager, warehouse manager, IT director, warehouse specialists, an IT
specialist and an HR specialist. As a project manager contract logistics manager was assigned.
As a project coordinator warehouse manager was assigned. Further, all the necessary
documentation was developed and communication process between all project member was
established. For making the process of pick-by-voice implementation smoother an HR specialist
promoted a new technology inside the company on a regular basis. The planning stage required 2
months and was conducted by director of logistics, warehouse manager and IT director.
The third stage was developing of a pick-by-voice technology. This stage wasn’t a timeconsuming one, since employees from another company’s subsidiary shared their knowledge
with their colleagues in the Russian subsidiary. During this stage specific functions of the
technology, which should be included, were identified. The developing of pick-by-voice required
1 month and was conducted by warehouse manager, IT director and IT specialists.
The fourth stage was practical implementation of pick-by-voice. This stage consisted of
not only physical installation of the new technology, but also all warehouse operations were
revised according to the new technology. In addition, an integration of all software programs and
digital warehouse solutions with voice order picking technology was accomplished. The practical
implementation stage took 2 months and was accomplished by director of logistics, warehouse
manager, IT director, warehouse specialists, IT specialists, HR specialist.
The fifth stage was evaluation of pick-by-voice performance. Due to pick-by-voice
implementation company has spotted increased warehouse key performance indicators. As
warehouse manager pointed out:
‘Order picking productivity of warehouse workers has been improved by several times and order
picking accuracy has also increased’.
Warehouse manager
Evaluation stage took around 1 month and was done by warehouse manager, HR director
and HR specialist. During the evaluation company found out that payback period of the voice
order picking technology was 6 months.
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Responsible employees during implementation of the digital solution
As mentioned earlier a project team for voice order picking implementation was assigned.
The team consisted of contract logistics manager, warehouse manager, IT director, warehouse
specialists, an IT specialist and an HR specialist. As a project manager contract logistics manager
was assigned. As a project coordinator warehouse manager was assigned.
Problems during the digital solution implementation in warehouse management
Among problems during pick-by-voice implementation company’s management faced
several ones. First of all, during the implementation it was found out that voice order picking is
suitable only for simple order picking processes, which don’t have plenty of features. Moreover,
at first pick-by-voice technology wasn’t able to recognize some accents of warehouse workers,
since they were not Russian native speakers. Contract logistics manager described this problem
in the following way:
‘Some of our warehouse employees had difficulties at first with voice direction since they
are not native Russian speakers and consequently system was not able to recognize their
speech’.
Contract logistics manager
Further, this problem was eliminated when company updated the technology and
downloaded accents recognition tool.
Company F
Company overview and its warehouse logistics
Company F is a Finnish public company, which penetrated Russian market in 1997 and
started its operations originally in Saint Petersburg. The company is a third-party logistics
provider, which provides services in warehouse logistics, transportation logistics and marketing
communications. At present Company F is one of the leading companies in the logistics market
in Russia. Company offers customized solutions designed specifically for each client from
various business industries and is considered as a reliable partner among its customers, since
company complies with the legal, ethical and professional standards of doing business.
As for the warehouse logistics, company provides such warehouse services as custody
services for goods and additional services, including the handling of goods in the warehouse,
crossdocking, inventory management. Total area of all company’s warehouses in Russia is over
500 000 m² and all warehouses belong to category A, which complies with the highest standards
in warehouse management. Total area of the warehouse in Saint Petersburg is 22 000 m². Apart
from Saint Petersburg company has warehouses and offices in all major regions of the country:
Moscow, Samara, Rostov-on-Don, Yekaterinburg, Novosibirsk, Vladivostok and Novorossiysk
(Official website of Company F, 2016).
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For investigating pick-by-voice implementation in the company both primary and
secondary data sources were used. Secondary data sources included company’s website, internal
company documentation, articles and primary data sources consisted of interviews with
company’s employees. Interview questions are presented in Appendix 2. In total, three semistructured interviews were conducted with the following company’s representatives: warehouse
manager, Business Applications Development Manager and Head of Competence Center Project
Department.
Existing digital solutions in warehouse management
Among digital solutions in warehouse management Company F has WMS, pick-by-voice
and pick-to-light technologies. It is noteworthy to mention that pick-by-voice and pick-to-light
technologies are connected with WMS system. Company implemented pick-by-voice technology
in 2014. Due to the fact that in 2014 company had already installed WMS system,
implementation of pick-by-voice technology went much smoother. Further, pick-by-voice
technology implementation is investigated in detail. Company cooperated with one of the
consulting companies in Saint Petersburg for pick-by-voice implementation.
Reasons of implementing the digital solution in warehouse management
Company had several reasons for implementing pick-by-voice technology. First of all, as
Business Applications Development Manager pointed out the following reason:
‘Pick-by-voice technology was an inexpensive way for increasing order-picking accuracy
in our warehouse’.
Business Applications Development Manager
Head of Competence Center Project Department added that company was able to
accelerate warehouse operations since employee productivity was boosted. Thus, pick-by-voice
technology enabled working hands and eyes-free. In addition, from the interview with the
warehouse manager it was found out that pick-by-voice technology allowed decreasing
personnel costs, since fewer workers were needed to provide the same level of productivity.
Stages of implementation of the digital solution, duration of stages
Pick-by-voice implementation in Company F was carried out in cooperation with one of
the consulting companies in Saint Petersburg. According to the Business Applications
Development Manager implementation of pick-by-voice technology started in February 2014
and finished in July 2014. Thus, implementation took 6 months.
The first stage of pick-by-voice implementation in Company F was initial analysis.
Because company already had WMS, all warehouse processes were revised and documented
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before pick-by-voice implementation. Hence, the initial analysis stage included making decision
considering acquiring or developing pick-by-voice technology on its own. As warehouse
manager underlined in 2014 company experienced some reorganizational issues, that is why
company’s management decided to acquire voice order picking technology. The make/buy
decision stage took 2 days and was done by director of logistics and warehouse manager.
The second stage of pick-by-voice implementation was supplier selection. During this
stage company thoroughly analyzed existing pick-by-voice providers and their solutions. For the
analysis company involved the consulting with which Company F cooperation for this project.
As a result, Company F developed a list of requirements for the pick-by-voice solution with
specific evaluation criteria such as solution flexibility, price, level of customization etc. Supplier
selection stage required around 1 month and was carried out by director of logistics, warehouse
manager, IT director and consultants.
The third stage of pick-by-voice implementation consisted of tender arranging. For the
tender company used developed list of requirements and the winner of tender was the company
who received the biggest number of points among all criteria. Tender arranging stage took 1
month.
The fourth stage consisted of planning pick-by-voice implementation. This stage consisted of
defining project framework. Next, company’s management assigned a project team, which
consisted both of Company F employees and several consultants from the consulting company.
Company F’s project members included warehouse manager, IT manager, Head of Competence
Center Project Department, warehouse specialists and an IT specialist. Consulting company
project members consisted of two senior consultants. Project manager of pick-by-voice
implementation was one of the senior consultants of the consulting company and a project
coordinator was Company F’s warehouse manager. Afterwards, all the required documentation
for the project was developed and approved and system of communications among project
members was established. Communication included regular meetings from both sides, reports,
calls and e-mails. The planning stage required 2 months and was conducted by director of
logistics, warehouse manager, IT director and consultants.
The fifth stage was practical implementation of pick-by-voice. This stage included
installation of pick-by-voice technology and its integration with WMS system. In the beginning
of this stage a trial version was conducted in order to identify errors, bugs and other potential
problems. The practical implementation stage required 1 month and was accomplished by
director of logistics, warehouse manager, IT director, warehouse specialists, IT specialists, HR
specialist and consultants.
The last stage was evaluation of pick-by-voice technology. As Head of Competence
Center Project Department pointed out:
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‘We didn’t evaluate return on investment for pick-by-voice, however there were spotted
some significant positive changes in terms of warehouse key performance indicators. For
instance, order-pickers’ productivity has been increased by 26%’.
Head of Competence Center Project Department
Evaluation stage took around 1 month and was done by warehouse manager, HR director
and HR specialist and one of the consultants.
Based on interviewees’ answers it is interesting to notice that order-picking accuracy
almost has not been changed, since company already had very high order-picking accuracy rate
(around 99,7%).
Responsible employees during implementation of the digital solution
As mentioned earlier project team for the implementation of pick-by-voice consisted both
of Company F employees and several consultants from the consulting company. Company F’s
project members were warehouse manager, IT manager, Head of Competence Center Project
Department, warehouse specialists and an IT specialist. Consulting company project members
consisted of two senior consultants. Project manager of pick-by-voice implementation was one
of the senior consultants of the consulting company and a project coordinator was Company F’s
warehouse manager
Problems during the digital solution implementation in warehouse management
During the implementation there were several problems, which company faced. Firstly,
one of the major problems was connected to personnel, since some of the warehouse employees
were reluctant to use the new technology since they already got used to manual picking. Another
problem mentioned by warehouse manager is interaction problem between the company and
technology provider. Warehouse manager clarified:
‘Since sometimes our company and provider of pick-by-voice had different understanding
of the requirements and technology functions, there was an interaction problem and we had to
spend additional time to clarify all the issues with the provider before the launch of the
technology’.
Warehouse manager
Finally, one more problem was revealed during the interviews, which is connected not
specifically to the implementation, but to the technology itself. As Head of Competence Center
Project Department noted pick-by-voice technology is not suitable for all warehouse workers, for
instance he cited an example of a warehouse employee who changed her speaking manner, i.e.
stuttered and then spoke slower or faster. Hence, pick-by-voice technology cannot be a universal
solution for all employees, but for the majority of workers it was a reasonable solution for
productivity increase.
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3.2. Cross-case analysis
According to the conducted within-case study analysis and the chosen dimensions, crosscase analysis is further elaborated. For each digital solution 3 case studies were conducted. Thus,
for investigating WMS implementation such companies as Company A, Company B and
Company C were observed. For investigating pick-by-voice technology implementation such
companies as Company D, Company E and Company F were analyzed. Firstly, cross-case
analysis for WMS is conducted and then cross-case analysis for pick-by-voice is carried out.
Considering WMS implementation it was observed that in general companies
implemented this system for the same reasons, such as increasing productivity and reducing
costs. Thus, companies strived for increasing employees’ productivity during all warehouse
operations: receiving, put-away, processing customers’ orders, order-picking, checking and
packing and shipping. As for the costs, companies expected to decrease overhead and personnel
costs, since fewer warehouse personnel would be needed to provide the same level of
productivity. Moreover, two of three companies decided to implement WMS to keep track of
warehouse key performance indicators and have an ability to make forecasts based on historical
data provided by WMS. Only one of the three analyzed companies (Company A) implemented
WMS for the future commercialization. It is interesting to mention that company intends to sell
WMS only to production companies and not to logistics providers in order to keep its
competitive advantage in-house. For the Company C WMS implementation was especially
important, because it enabled to decrease number of mistakes made by warehouse employees
and with the implementation of the new system customer service level was substantially
increased.
Depending on the company duration of the solution took 9 months or 1 year. Difference
in the implementation duration can be easily explained by the fact that Company A and Company
C implemented WMS on their own, while Company B cooperated with Ant Technologies to
implement the system. Hence, it can be inferred that cooperation with the integrator/consulting
company makes implementation of WMS faster, but at the same time companies who implement
WMS on their own get valuable experience of digital solutions’ implementation.
Regarding the stages of WMS implementation it can be noticed that companies who
implemented WMS on their own have fewer stages of implementation (one stage less), since
they don’t have to select supplier and arrange tender, but at the same time they have to develop
WMS content on their own. Thus, Company A and Company C had five stages of WMS
implementation and Company B had six stages of WMS implementation. Comparing stages of
Company A and Company C, who had the same number of stages, it is interesting to mention
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that during the first stage of the initial analysis Company A had 3 steps (development of logistics
warehouse model, identifying WMS requirements and making decision considering developing
WMS using internal personnel or acquiring WMS from the third party), while Company C had
just 2 steps (identifying WMS requirements and make/buy decision). This difference can be
explained by the fact that Company A had to develop a logistics model to determine the
warehouse processes and required documentation, allocate labor resources and loading
equipment, calculate performance storage for each process area, while Company C already
carried out this step, since company had reorganized its warehouse structure in 2004 and
prepared a logistics warehouse model right after the reorganization.
As for the responsible employees it can be concluded that in case of developing WMS on
its own (cases of Company A and Company C) project teams were quite the same in terms of
structure and project team members had similar responsibilities during the WMS
implementation. However, there were spotted some differences in terms of assigning major roles
of the project, notably in case of Company A as a project manager head of warehousing was
assigned and a project coordinator was warehouse manager, while in case of Company C project
manager was a warehouse manager and project coordinator was operations manager. Thus, it can
be inferred that in the first case responsibility was held by warehouse employees and in the
second case it was distributed among the warehouse and operations departments. In case of
acquiring WMS (Company B) project team was obviously much bigger and apart from
company’s employees who were involved in the project (warehouse manager, IT director,
warehouse specialists, IT specialists, HR specialist) there were also representatives from
company Ant technologies who included senior consultant, junior consultant and IT specialist. In
this case more responsibility was held by Ant technologies since project manager was their
senior consultant and project manager was warehouse manager, who represented interests of
Company B and coordinated interaction between all the involved parties.
Regarding problems during the WMS implementation it can be noted that there were
various difficulties, which companies faced during the implementation. However, in all cases
there was spotted such problem as human factor, for instance initial resistance of employees
(especially warehouse workers) towards the new digital solution since employees were used to
working with other software systems or even using paper-based approach. Also in two cases
(Company B and Company C) there were occasional technical problems with WMS
implementation, which consisted of different errors and bugs of the new system, but during and
after the implementation all these shortcomings were eliminated. Regarding individual problems
there were some problems with lack of documentation and no database structure, which
Company A had. Thus, during the planning stage of WMS implementation company didn’t
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prepare all the necessary official documents (orders, regulations etc.) required for WMS
implementation and that complicated to some extent WMS implementation. Company C had also
such individual problem among the observed cases as integration of WMS with existing software
programs. Since Company C was less tech-savvy at that time (2005) in comparison with the
other two companies, Company C experienced some difficulties from the technical perspective
of WMS integration with other software programs.
Having conducted cross-case analysis for WMS it can be concluded that in general
implementation of the system was quite similar among three observed cases. Thus, companies
pursued similar reasons of implementing the solution, however in each case there were some
individual reasons of implementing. Duration of the implementation was the same in two cases,
since these companies developed the system from within and the other company cooperated with
the system integrator, which accelerated the process of WMS implementation. Regarding
implementation stages it was identified that companies in general followed the same path,
especially those who implemented WMS using its internal personnel (Company A and Company
C). In the case of cooperating with the system integrator (Company Bs) there was one more stage
in comparison with the cases of independent implementing (Company A and Company C). As for
responsible employees during WMS implementation is was spotted that in cases of Company A
and Company C project teams were similar in structure. However, in terms of responsibilities in
case of Company A project manager and project coordinator were warehouse employees and in
case of Company C responsibilities were distributed between warehouse and operations
departments since project manager was warehouse manager and project coordinator was
operations manager. Finally, in all cases companies faced technical problems and problem
connected with the human factor, as companies’ employees initially were reluctant to apply the
new technology on a regular basis. Additionally, companies faced some individual problems
such as lack of documentation during the implementation and integration problems of WMS and
current companies’ software programs.
Further, cross-case analysis for companies with pick-by-voice implementation is
elaborated. As for the pick-by-voice implementation it was observed that in general companies
implemented this system for the same reasons, such as increasing productivity and order-picking
accuracy. Furthermore, in all cases companies expected costs to be decreased, but in a different
way. Thus, Company E and Company F were oriented to decreasing personnel costs after the
pick-by-voice implementation so that warehouse personnel would be downsized due to increased
productivity. However, Company D company was oriented to reducing training personnel costs
and didn’t conduct any lay-offs and found a different way. With the implementation of pick-byvoice technology warehouse workers’ productivity has been increased and instead of reducing
72
personnel, company increased volumes of trade flows, shipping and developed new areas of
business. Thus, there were not additional costs for firing employees and what is more important
warehouse employees’ morale has not been worsened, but only improved since they felt support
from the company’s management. It is noteworthy to mention that in comparison with the WMS
implementation more homogeneity can be observed in pick-by-voice implementation in terms of
reasons of the technology implementation.
In two of observed cases duration of the pick-by-voice implementation took 6 months and
in case of the other company (Company E) pick-by-voice was implemented during 8 months.
Difference in the implementation duration can be explained by the fact that for Company E
implemented pick-by-voice on its own and company had vast in-house experience in warehouse
management, while Company D and Company F cooperated with consulting companies to
implement the new technology. Thus, it can be concluded that involving a third party can
accelerate the process of implementing the new solution in warehouse management, but at the
same time, companies who conduct implementation independently receive experience, which
can be transferred while implementing new technologies.
Consequently, it can be noted that stages of implementation also differ to some extent,
since Company E implemented pick-by-voice without assistance and Company D and Company
F cooperated with other companies to implement the solution. Hence, Company E had five
stages of pick-by-voice implementation: initial analysis, planning, developing, practical
implementation and evaluation and didn’t have such stages as supplier selection and tender
arranging. Among companies who involved consulting companies for pick-by-voice
implementation (Company D and Company F) there were five and six stages of implementation
respectively. This can be explained by the fact that in case of company D there wasn’t such stage
as tender arranging since company already chose the supplier during this stage and didn’t
provide a tender for making a choice. Company used experience of European subsidiaries of the
Company D international holding and decided to implement a voice order picking technology
‘Vocollect Voice’. As for Company F company, it had six stages of pick-by-voice
implementation, which were the same as in the case of Company D plus one additional stage of
tender arranging, which followed supplier selection stage.
As for responsible employees it can be inferred that in cases of cooperating with
consulting companies (Company D and Company F) project teams were quite the same in terms
of structure and project team members had similar responsibilities during the pick-by-voice
implementation. Thus, in case of Company D project team was a bit bigger in terms of both
sides: company and consulting company. From the company’s side employees from various
departments were involved in pick-by-voice implementation: director of logistics, warehouse
manager (project coordinator), IT director, warehouse specialists, IT specialists and HR
73
specialist. Comparing with Company F’s project team from the company’s side it can be spotted
that in Company F’s case there wasn’t an HR specialist in the implementation. As for the project
team from the third party, in case of Company D there were three employees involved: senior
consultant, junior consultant and IT specialist, while in case of Company F there were two senior
consultants. Regarding project responsibilities it was identified that in both cases of Company D
and Company F responsibilities were divided equally since in the observed cases as a project
manager senior consultant was assigned and as a project coordinator company’s warehouse
manager was assigned.
Regarding problems during the implementation it can be noted that there were different
problems, which companies faced during the implementation, but in all cases there was such
problem as human factor, for instance initial resistance of employees (especially warehouse
workers) towards the new digital solution. Moreover, companies also faced individual problems
during the implementation such as software bugs and errors in the system configuration (case of
Company D), interaction problem between the company and the technology provider (case of
Company F) and accents recognition (case of Company E). During the interviews with Company
F’s managers it was identified that interaction problem between the company and the technology
provider was especially critical for the company since sometimes company and the technology
provider had misunderstandings in the terms of technology functions and pick-by-voice
implementations. In case of Company E accents problem was one of the biggest issues, since
majority of warehouse order-pickers in the company were not native Russian speakers and
because of the accents pick-by-voice technology was not able to recognize worker’s speech.
Company solved this problem by installing additional module in pick-by-voice, which was able
to recognize different accents.
Having conducted cross-case analysis for pick-by-voice it can be inferred that
implementation process of the technology was heterogeneous among the observed cases and
more similarities than differences were spotted during the analysis. Considering reasons for
implementing pick-by-voice companies were oriented to increasing productivity and improving
order-picking accuracy. In two cases companies implemented pick-by-voice to reduce personnel
costs, i.e. lay-off some of the warehouse workers. As for the duration of pick-by-voice
implementation it was found out that in two cases (Company D and Company F) implementation
took 6 months and in the other case – 8 months. This difference can be explained by the fact that
in cases of Company D and Company F there were consulting companies, who were involved in
pick-by-voice implementation and that accelerated the process. While in case of Company E
implementation was conducted independently and that is why implementation was longer by two
additional months. As for the implementation stages in cases of Company D and Company F,
74
stages very similar in terms of content except that in case of Company F there was an additional
stage of supplier selection, which followed the supplier selection stage. In case of Company E
there were not such stages as supplier selection and tender arranging, but instead there was a
stage of developing pick-by-voice technology. Regarding project teams it was identified that in
cases of cooperating with consulting companies structure of the teams were very similar as well
as the distributed responsibilities. In case of independent implementing of pick-by-voice
(Company E) the project team also resembled teams of the two mentioned cases (Company D
and Company F) from company’s side. Finally, speaking about the revealed problems during
pick-by-voice implementation all companies faced problem with personnel, since warehouse
employees were not eager to apply the new technology on a daily basis. Apart from that
companies also faced individual problems such as technical issues (bugs and errors), accents
recognition and interaction problem between the company and the technology provider.
One of the last questions during the interviews was the question regarding the
peculiarities of the digital solution implementation in Russia. As interviewees underlined there
were no specifically Russian peculiarities during the implementation, therefore this aspect was
not considered during the analysis. Further results of cross-case study analysis for WMS and
pick-by-voice are presented in the tables.
75
Table 7. Results of cross-case study analysis for Warehouse Management System
Reasons of implementing the
digital solution in warehouse
management
Company A
Company B
Inseparable part of
warehouse operations
Keeping track of
warehouse KPIs, make
forecasts
Increasing productivity,
reducing costs
WMS commercializing
Increasing productivity,
reducing costs
Effective and economical
use of specialized storage
equipment and storage
space
Managing warehouse KPIs,
making forecasts
Duration of the
digital solution
implementatio
n
1 year
1 year
Stages of implementation of
the digital solution
1) Initial analysis
Development of logistics
warehouse model
Identifying WMS
requirements
Make/buy decision
2) Planning of WMS
implementation
3) Developing of WMS
4) Practical implementation
of WMS
5) Evaluation of WMS
performance
1) Initial analysis
Identifying WMS
requirements
Make/buy decision
2) Supplier selection
3) Tender arranging
4) Planning of WMS
implementation
5) Practical implementation
of WMS
6) Evaluation of WMS
performance
Responsible employees of
implementation of the
digital solution
Head of Warehousing
(project manager)
Warehouse manager
(project coordinator)
IT director
Warehouse specialists
IT specialists
HR specialist
Company B:
Warehouse manager
(project coordinator)
IT director
Warehouse
specialists
IT specialists
HR specialist
Ant technologies:
Senior consultant
(project manager)
Problems during the digital
solution implementation in
warehouse management
Lack of module-based
structure in WMS
Lack of documentation
and no database structure
Human factor
Software bugs and errors
in the system
configuration
Human factor
Company C
Reducing time for goods’
put-away and orderpicking processes
Decreasing number of
errors
Reducing overhead costs
Eliminating doublechecking of data in
different programs
1 year
1) Initial analysis
Identifying WMS
requirements
Make/buy decision
2) Planning of WMS
implementation
3) Developing of WMS
4) Practical implementation
of WMS
5) Evaluation of WMS
performance
Junior consultant
IT specialist
Warehouse manager
(project manager)
Operations manager
(project coordinator)
IT manager
IT specialists
HR specialist
Technical problems
(errors, bugs)
Human factor – initial
personnel resistance
Integration of WMS with
existing software
programs
Table 8. Results of cross-case study analysis for pick-by-voice technology
Reasons of implementing
the digital solution in
warehouse management
Duration of the digital
solution implementation
Stages of implementation
of the digital solution
Responsible employees of
implementation of the
digital solution
Problems during the
digital solution
implementation in
warehouse management
77
Company D
Company E
Increasing
productivity
Reducing training
personnel costs
Improving order
picking accuracy
Increasing
productivity
Decreasing
personnel costs
Improving order
picking accuracy
6 months
8 months
1) Initial analysis
Make/buy decision
2) Supplier selection
3) Planning of pick-byvoice implementation
4) Practical
implementation of
pick-by-voice
5) Evaluation of pick-byvoice performance
1) Initial analysis
Make/buy decision
2) Planning of pick-byvoice implementation
3) Developing of pickby-voice technology
4) Practical
implementation of
pick-by-voice
technology
5) Evaluation of pick-byvoice performance
Company D:
Director of logistics
Warehouse manager
(project coordinator)
IT director
Warehouse
specialists
IT specialists
HR specialist
KORUS consulting:
Senior consultant
(project manager)
Junior consultant
IT specialist
Contract logistics
manager (project
manager)
Warehouse manager
(project coordinator)
IT director
Warehouse
specialists
IT specialist
HR specialist
Software bugs and
errors in the system
configuration
Human factor –
initial personnel
resistance
Accents recognition
Human factor
78
Company F
Increasing orderpicking accuracy
Increasing
warehouse workers’
productivity
Decreasing
personnel costs
1)
2)
3)
4)
6 months
Initial analysis
Make/buy decision
Supplier selection
Tender arranging
Planning of pick-byvoice implementation
5) Practical
implementation of
pick-by-voice
6) Evaluation of pick-byvoice performance
Company F:
Warehouse manager
(project coordinator)
IT manager
Head of Competence
Center Project
Department
Warehouse
specialists
IT specialists
Consulting company:
Senior consultant
(project manager)
Senior consultant
Human factor –
reluctance to use the
new technology
among warehouse
employees
Interaction problem
between the
company and the
technology provider
79
3.3. Algorithm of implementing digital solutions in warehouse management for
Russian companies
Based on conducted within-case, cross-case study analyses and consultations with digital
solutions’ integrators (Ant technologies and KORUS Consulting) an algorithm of implementing
digital solutions in warehouse management for Russian companies is developed. Since WMS
and pick-by-voice have their own peculiarities, separate programs for them were developed. For
WMS an algorithm consists of 1 year or 264 working days (provided that on average there are 22
working days in a month) and an algorithm for pick-by-voice technology consists of 6 months or
132 working days. For both algorithms the following elements were defined: stages of
implementation, duration of each stage, responsible employees and stage content. Both
algorithms are developed based on the assumption that companies would implement digital
solutions using both internal and external personnel, i.e. cooperate with technology provider and
consulting company.
Considering an algorithm for WMS implementation the following stages were
determined: initial analysis, supplier selection, tender arranging, planning of WMS
implementation, practical implementation of WMS and evaluation of WMS performance. In the
table provided below each of the stages is elaborated in detail in the last column Stage content.
For the successful implementation of WMS coordinated actions of various departments
are required. Thus, it was defined that the project team for the implementation should include the
following employees:
Director of logistics
Warehouse manager
IT director
Warehouse specialists
IT specialists
HR specialist
Senior consultant (consulting company)
Junior consultant (consulting company)
It should be noted that for WMS implementation project manager and project should be
assigned to provide monitoring and resolve arising issues during the project. It is recommended
to assign a senior consultant from the consulting company as a project manager and company’s
director of logistics as a project coordinator. Project manager will be responsible for the overall
project execution efficiency, balancing interests of company, consulting company and technology
provider and managing changes. Project coordinator will have a subset of project manager’s
responsibilities, thus he will be responsible for smooth running of the project and all related
activities.
As for the algorithm for pick-by-voice technology the following stages were identified:
initial analysis, supplier selection, tender arranging, planning of pick-by-voice implementation,
practical implementation of pick-by-voice and evaluation of pick-by-voice performance. In the
table provided below each of the stages is elaborated in detail in the last column Stage content.
As in the case of WMS for successful pick-by-voice implementation coordinated actions
of various departments are required. Hence, it was defined that the project team for the
implementation should include the following employees:
Director of logistics
Warehouse manager
IT director
Warehouse specialists
IT specialists
HR specialist
Senior consultant (consulting company)
Junior consultant (consulting company)
For pick-by-voice implementation project manager and project should be assigned to
provide project execution. It is recommended to assign a senior consultant from the consulting
company as a project manager and company’s director of logistics as a project coordinator.
Similarly with the WMS implementation, project manager will be responsible for project
efficiency, managing interests of company, consulting company and technology provider. Project
coordinator will have some of the project manager’s responsibilities, thus he will be responsible
for monitoring of the project and establishing communications among all the project members.
As for the compensation and benefits policy regarding implementation of both WMS and
pick-by-voice solutions, it can be noted that non-financial compensation, which doesn’t require
investment is recommended. Examples of non-financial compensation might include gratitude,
honor boards, providing workplace flexibility etc.
Further the tables with algorithms for WMS and pick-by-voice implementation are
presented, where stages, their duration, responsible employees and stages content are elaborated.
To identify duration of each stage additional consultations with two digital solutions’ integrators
were carried out to ensure the accuracy of the stage duration.
81
Table 9. Algorithm of implementing WMS in warehouse management for Russian companies
Stages
Duration
Responsible employees
Stage content
Initial analysis
1. Development of logistics
warehouse model
8 days
Director of logistics
Warehouse manager
2. Identifying WMS
requirements
5 days
Director of logistics
Warehouse manager
Warehouse specialists
D e t e r m i ni ng t he w a r e hous e
processes and required
documentation
Allocating labor resources and
loading equipment
Calculating performance storage
for each process area
Forecasting volumes in the
warehouse
Theoretical description of the
warehouse interaction with
external storage services
Determining how WMS would
describe the goods and packaging
How WMS would distribute the
processing warehouse zones, how
it would work with documents and
reports, as well as what would be
the interface of the system and the
ability to integrate it with other
software programs
The outcome of this step is
Systems Requirement Document
(SRD), a document with a detailed
description of the required
parameters of the management
system for a particular warehouse
3. Make/buy decision
2 days
4. Supplier selection
68 days
Director of logistics
Warehouse manager
Director of logistics
Warehouse manager
IT director
Senior consultant (consulting
company)
Junior consultant (consulting
company)
Determining of resources:
experienced warehouse and IT
specialists, software programs
Identifying criteria of choosing
WMS suppliers
Selecting supplier
Director of logistics
Warehouse manager
Senior consultant (consulting
company)
Director of logistics
Warehouse manager
IT director
IT specialists
HR specialist
Senior consultant (consulting
company)
Junior consultant (consulting
company)
Arranging tender
Defining WMS implementation
framework – goal, objectives,
potential limitations, basic
requirements for the system and
the expected results of the project
Assigning project team: project
manager, project coordinator, other
members
Adjusting budget taking into
account WMS implementation
expenses
Developing and approving all
necessary documentation
5. Tender arranging
68 days
44 days
Planning of WMS implementation
6. Planning of WMS
implementation
83
7. Interaction with WMS
provider
59 days
8. E v a l u a t i o n o f e x i s t i n g
hardware and software
programs in all company’s
departments
9. Establishing communications
among project team members
2 days
Director of logistics
IT director
Senior consultant (consulting
company)
Warehouse manager
IT director
IT specialists
Director of logistics
HR specialist
10. Internal promotion of WMS
system in the company
59 days
Director of logistics
HR specialist
Director of logistics
Warehouse manager
IT director
Warehouse specialists
IT specialists
HR specialist
Senior consultant (consulting
company)
Junior consultant (consulting
company)
2 days
Practical implementation of WMS
11. Informational and technical
support
113 days
12. Launching a pilot version
5 days
Warehouse manager
IT director
IT specialists
Providing regular communications
with WMS provider
Evaluating existing software and
hardware in order to understand
which programs and hardware are
needed to be aligned with the new
system
Establishing communications
system in order to provide precise
division of responsibilities
Promoting WMS in the company
to make implementation process
smoother and provide clear
expectations among the employees
about the new system
Providing informational and
technical support through the
whole stage of WMS practical
implementation
Launching a pilot version of WMS
84
13. Receiving feedback of pilot
version functioning
5 days
14. Correcting mistakes based on
the feedback
5 days
15.
Launching WMS
5 days
16. Conducting trainings for
warehouse and IT specialists
10 days
Evaluation of WMS performance
17. E v a l u a t i o n o f K P I s o f
warehousing department
44 days
Senior consultant (consulting
company)
Director of logistics
Warehouse manager
IT director
IT specialists
Warehouse manager
IT director
IT specialists
Senior consultant (consulting
company)
Warehouse manager
IT director
IT specialists
Senior consultant (consulting
company)
Junior consultant (consulting
company)
Warehouse manager
IT director
HR specialist
Senior consultant (consulting
company)
Warehouse manager
HR director
HR specialist
Senior consultant (consulting
company)
Receiving feedback from the pilot
version of WMS
Correcting mistakes which were
identified from the received
feedback from the pilot version
Launch of WMS
Conducting trainings for
warehouse and IT specialists
which will be involved in working
with WMS
Evaluation of KPIs of warehousing
department
85
Table 10. Algorithm of implementing pick-by-voice technology in warehouse management for Russian companies
Stages
Initial analysis
1. Make/buy decision
Duration
2. Supplier selection
22 days
2 days
3. Tender arranging
Planning of pick-by-voice
implementation
4. Planning of pick-by-voice
implementation
22 days
44 days
Responsible employees
Director of logistics
Warehouse manager
Stage content
Determining of resources:
experienced warehouse and IT
specialists, software programs
Identifying criteria of choosing
pick-by-voice suppliers
Selecting supplier
Arranging tender
Defining pick-by-voice
implementation framework – goal,
objectives, potential limitations,
basic requirements for the system
and the expected results of the
project
Assigning project team: project
manager, project coordinator, other
members
Adjusting budget taking into
account pick-by-voice
implementation expenses
86
Director of logistics
Warehouse manager
IT director
Senior consultant (consulting
company)
Junior consultant (consulting
company)
Director of logistics
Warehouse manager
Senior consultant (consulting
company)
Director of logistics
Warehouse manager
IT director
IT specialists
HR specialist
Senior consultant (consulting
company)
Junior consultant (consulting
company)
Director of logistics
IT director
Senior consultant (consulting
company)
Warehouse manager
IT director
IT specialists
Director of logistics
HR specialist
Director of logistics
HR specialist
Director of logistics
Warehouse manager
IT director
Warehouse specialists
IT specialists
HR specialist
Senior consultant (consulting
company)
Junior consultant (consulting
company)
Warehouse manager
5. Interaction with pick-by-voice
provider
59 days
6. Evaluation of existing hardware
and software programs
2 days
7. Establishing communications
among project team members
2 days
8. Internal promotion of pick-byvoice in the company
59 days
Practical implementation of pick-byvoice
9. Informational and technical
support
92 days
Developing and approving all
necessary documentation
Providing regular communications
with WMS provider
Evaluating existing software and
hardware in order to understand
which programs and hardware are
needed to be aligned with the new
system
Establishing communications
system in order to provide precise
division of responsibilities
Promoting WMS in the company
to make implementation process
smoother and provide clear
expectations among the employees
about the new system
Providing informational and
technical support through the
whole stage of WMS practical
implementation
Launching a pilot version of WMS
87
10. Launching a pilot version
3 days
11. Receiving feedback of pilot
version functioning
3 days
12. Correcting mistakes based on
the feedback
3 days
13. Launching pick-by-voice
3 days
14. Conducting trainings for
warehouse and IT specialists
Evaluation of pick-by-voice
performance
15. Evaluation of KPIs of
warehousing department
5 days
22 days
IT director
IT specialists
Senior consultant (consulting
company)
Director of logistics
Warehouse manager
IT director
IT specialists
Warehouse manager
IT director
IT specialists
Senior consultant (consulting
company)
Warehouse manager
IT director
IT specialists
Senior consultant (consulting
company)
Junior consultant (consulting
company)
Warehouse manager
IT director
HR specialist
Senior consultant (consulting
company)
Warehouse manager
HR director
HR specialist
Senior consultant (consulting
company)
Receiving feedback from the pilot
version of WMS
Correcting mistakes which were
identified from the received
feedback from the pilot version
Launch of WMS
Conducting trainings for
warehouse and IT specialists
which will be involved in working
with WMS
Evaluation of KPIs of warehousing
department
88
In order to visualize algorithms for WMS and pick-by-voice, Gantt charts were developed.
Mar-16 Mar-16 Apr-16 May-16 Jun-16 Jul-16 Aug-16 Sep-16 Oct-16 Nov-16 Dec-16 Jan-17 Feb-17 Mar-17
Development of logistics warehouse model
Identifying WMS requirements
Make/buy decision
Supplier selection
Tender arranging
Planning of WMS implementation
Interaction with WMS provider
Evaluation of existing hardware and software programs
Establishing communications among project members
Internal promotion of WMS system in the company
Informational and technical support
Lauching a pilot version
Receiving feedback of pilot version functioning
Correcting mistakes based on the feedback
Launching WMS
Conducting trainings for warehouse and IT specialists
Evaluation of KPIs of warehousing department
Figure 6. Gantt chart ‘WMS implementation in warehouse management for Russian companies’
89
Mar-16
Mar-16
Apr-16
May-16
Jun-16
Jul-16
Aug-16
Sep-16
Make/buy decision
Supplier selection
Tender arranging
Planning of pick-by-voice implementation
Interaction with pick-by-voice provider
Evaluation of existing hardware and software programs
Establishing communications among project members
Internal promotion of pick-by-voice in the company
Informational and technical support
Lauching a pilot version
Receiving feedback of pilot version functioning
Correcting mistakes based on the feedback
Launching pick-by-voice
Conducting trainings for warehouse and IT specialists
Evaluation of KPIs of warehousing department
Figure 7. Gantt chart ‘Pick-by-voice implementation in warehouse management for Russian companies’
90
3.4. Summary of Chapter 3
The third chapter of the thesis consists of the analysis of best practices of implementing
digital solutions in warehouse management. It was revealed in the first chapter currently the most
relevant digital solutions in warehouse management are WMS and pick-by-voice. Hence, for
these two solutions case study analysis was conducted. For the research of digital solutions in
warehouse management six Russian and international companies were chosen. These companies
were chosen based on specific criteria, i.e. companies should be logistics providers or
distribution companies, they should be Russian companies or Russian branches of international
companies and they should have experience in implementing digital solutions in warehouse
management. In the beginning for each case study within-case analysis was accomplished, which
was structured as follows. Firstly, overview of the company and its warehouse logistics are
given. Then existing digital solutions in warehouse management in the company are identified.
Further, each of defined by researcher dimensions is analyzed regarding particular company’s
digital solution in warehouse management. Within-case analysis was followed by cross-case
analysis, during which similarities and differences among the cases were revealed. It was
established that in both cases of WMS and pick-by-voice among cases more similarities than
differences were spotted. As a final step an algorithm of implementing WMS and pick-by-voice
in warehouse management for Russian companies was developed.
3.5. Discussion and conclusions
3.5.1.
Discussion of the findings
The master thesis was devoted to digital solutions in warehouse management and their
implementation in Russian and international companies. The goal of the research was to develop
an algorithm of implementing digital solutions in warehouse management for Russian companies
based on best practices of international and Russian companies. For achieving this goal the
research has been divided into three stages: conducting literature review of digitalization and
warehouse management, defining research methodology and analysis of the best practices of
implementation of digital solutions in warehouse management.
Comprehensive research of digitalization in warehouse management has shown that this
topic is one of the most crucial trends which influences supply chain management and
warehouse management in particular. Regarding digitalization implications for warehouse
management it was found out that main areas for the improvement are referred to the operational
effectiveness of the warehouse, specifically to labor and quality. As an element of fourth
industrial revolution digitalization contributes to increasing efficiency of warehouse operations
through the digital solutions.
During the analysis digital solutions in warehouse management were revealed and further
reviewed. It was established that among extant studies there is no algorithm of implementing
digital solutions in warehouse management. For developing such algorithm particular digital
solutions should have been chosen since it was not possible to develop algorithm for all the
solutions due to time and volume of research constraints. Thus, identified digital solutions were
compared in terms of their relevance, costs and ease of implementation (DHL Logistics Trend
Radar, 2014; Pfohl et al., 2015; Capgemini Consulting View, 2015; BCG report ‘Three Paths to
Advantage with Digital Supply Chain’, 2016) and it was found out that Warehouse Management
System (WMS) and pick-by-voice technology are the most widely spread and relevant solutions
in warehouse management in Russian companies. Consequently, algorithms for WMS and pickby-voice were developed for Russian companies.
Empirical research of the thesis which consisted of a series of semi-structured interviews
and consultations with digital solutions’ integrators (Ant technologies and KORUS Consulting)
allowed to achieve the research goal, i.e. to develop an algorithm of implementing digital
solutions in warehouse management for Russian companies based on best practices of
international and Russian companies.
Having conducted within-case and cross-case analyses of six Russian and international
(their Russian branches) companies it was revealed that considering implementation of WMS
and pick-by-voice in warehouse management companies in general follow the same approach of
implementation and differences in cases can be attributed to specific factors such as independent
implementation or cooperation with the IT integrator/consulting company, project team structure.
As for reasons of digital solutions’ implementation companies pursue similar goals such as
increasing order-picking accuracy and decreasing personnel costs. Considering problems of
implementation in all case there were spotted such difficulties as technical issue and personnel
problems (initial resistance of the technology), however there were also individual problems
such as lack of documentation during the implementation and integration problems with the
existing company’s software programs.
It is noteworthy to mention that implementation of WMS and pick-by-voice had its own
peculiarities, but overall there can be observed similar approach of these solutions’
implementation. Due to the fact that pick-by-voice technology is connected to WMS and pickby-voice cannot be set up without having WMS in the company, consequently implementation
process of pick-by-voice is less time-consuming.
Based on the conducted empirical research and analyzed cases the research goal could be
reached. Thus, an algorithm of implementing WMS and pick-by-voice in warehouse
management for Russian companies was developed. For WMS an algorithm consists of 1 year or
264 working days and an algorithm for pick-by-voice technology consists of 6 months or 132
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working days. The following elements were determined for both algorithms: stages of
implementation, duration of each stage, responsible employees and stage content. Both
algorithms were developed assuming that companies would attract external provider of the
technology and consulting company, since as it was found out from the interviews, currently
logistics providers prefer to cooperate with consulting companies to make the implementation
process faster and smoother. Thus, the developed algorithms for WMS and pick-by-voice were
developed, which were presented earlier in Tables 9 and 10. For visualizing these algorithms
Gantt charts were built. It should be noted that for both solutions estimation of stages duration
was made based on working days as it was found out during the interviews, but for the
convenience for managers, who might use these algorithms, stages duration was converted into
calendar days. Observing Gantt charts for both digital solutions it can be inferred that some of
the stages are carried out concurrently, such as planning of digital solution implementation,
interaction with the provider, internal promotion of the technology in the company and
informational and technical support. This overlap can be explained by the fact that these
processes are needed to be accomplished sometimes simultaneously due to benefits of saving
time and costs and increasing performance of the whole implementation project.
Thus, it can be concluded that both research questions of the thesis were answered, i.e.
digital solutions in warehouse management were identified and reviewed and implementation
algorithm for digital solutions for Russian companies was developed. As a result, the research
goal was achieved.
3.5.2.
Theoretical contribution and practical implications
This master thesis can contribute to theoretical perspective in several ways. From the
theoretical perspective this thesis contributes to the sphere of digital solutions in warehouse
management, which is quite uninvestigated. Thus, based on the analyzed articles digitalization
concept was introduced and difference between digitalization and digitization terms was
determined. Although, it was spotted that frequently scholars used these terms interchangeably.
From the analysis of articles digitalization implications for warehouse management were
defined, notably that that main improvement areas in warehouse management are attributed to
the operational effectiveness of the warehouse, specifically to labor and quality (McKinsey
Digital, 2014) and digitalization as an element of fourth industrial revolution facilitates
increasing efficiency of warehouse operations through the digital solutions.
During the analysis of articles referred to both international and Russian companies,
digital solutions in warehouse management were revealed and further reviewed. Thus, such
digital solutions were identified: Warehouse Management System, pick-by-voice, pick-to-light,
93
radio frequency identification, 3D printing, augmented reality and robotics. The solutions were
identified based on papers of the researchers (Sowinski, 2005; Gu et al., 2007; Wang et al., 2010;
Napolitano, 2012; Bond, 2013; Xiao-dong and Fan, 2016) and industry reports (McKinsey, 2013;
DHL, 2014; Capgemini, 2015; BCG, 2016). As it was analyzed in first part of Chapter 1, most of
these digital solutions refer to order-picking process. Moreover, the study offers insights
regarding impact of digital solutions in warehouse management, notably it was identified that
currently the most widely spread and relevant technologies in warehouse management for
Russian companies are Warehouse Management System and pick-by-voice. Thus, the study is
valuable to the theoretical development.
As for practical implications it can be inferred that the master thesis is rather impactful.
An algorithm of implementing digital solutions (WMS and pick-by-voice) in warehouse
management was developed, which can be used by Russian and international companies, which
intend to introduce digital solutions in warehouse management. This algorithm includes stages of
implementation, their duration and content and responsible employees. Additionally, during the
cases analysis certain problems which might occur during the implementation process were
identified. Thus, companies who might use the proposed algorithm will be prepared for the
potential difficulties. For users of this algorithm the implementation process of WMS and pickby-voice appears precise and transparent, as they will have a strong basis for the digital
solutions’ implementation. The study holds value for warehouse managers, IT managers and
other employees, who are involved in implementation of digital solutions in warehouse
management.
Another practical implication of the research is that developed algorithm might be useful
also for other digital solutions, for instance pick-to-light, radio frequency identification. Despite
the fact that each of digital solution has its own peculiarities in terms of implementation process,
as it was shown during the algorithms development for WMS and pick-by-voice, in general the
implementation processes follow the same path. Thus, the developed algorithm may be taken as
a basis and adjusted for other digital solutions.
Since multiple case study analysis was conducted based on Russian branches of
international companies and Russian companies, the developed algorithm is valid for Russian
companies. However, international companies might take the implementation stages as the basis
for the developing their own algorithm.
3.5.3.
Limitations and prospects for future research
The research has several limitations that should be taken into consideration. One of the
limitations is referred to the chosen research strategy. Since in the thesis case study strategy is
94
applied, there are limitations connected to generalizations of the findings (Yin, 2003) as the was
limited number of analyzed case studies per each digital solution (three case studies for each
solution). This can raise some biases in terms of development of algorithms of implementing
digital solutions in warehouse management. Therefore, further research can expand number of
case studies in order to obtain more relevant and objective results.
Moreover, limitations are connected to the research sample. The data was collected in
Russia, in Saint Petersburg and Moscow and this limits the opportunity to generalize the findings
to other Russian cities. It can be recommended to conduct further research based on data from
other Russian cities, thus expanding the research sample and getting more comprehensive view
on digital solutions’ implementation in warehouse management. Additionally, there was a
limitation referred to confidentiality issues. Since the implementation process of digital solutions
is considered as a confidential one, some of the details cannot be revealed during the interviews.
Finally, there were certain limitations with regard to the analyzed companies, since there
were four international companies and two Russian companies. However, it should be noted that
analyzed international companies were Russian branches, so that to some extent they can be
regarded as Russian ones. Nevertheless, it can be recommended to analyze more Russian
companies, in addition to Russian branches of international companies.
Despite all the mentioned limitations the master thesis holds both theoretical and practical
value and it was possible to reveal similar patterns of implementing digital solutions in
warehouse management for Russian companies.
Conclusion
The goal of the master thesis was to develop an algorithm of implementing digital
solutions in warehouse management for Russian companies based on best practices of
international and Russian companies. An algorithm of implementing digital solutions in
warehouse management was developed and therefore a research gap was closed, since among the
extant studies there wasn’t such algorithm of implementing digital solutions in warehouse
management. In order to achieve the research goal multiple case study analysis was carried out.
During the research both within-case study and cross-case study analyses were conducted. As
for the data collection semi-structured interviews and analysis of secondary data were carried
out. Six international and Russian companies were investigated.
To achieve the research goal the following research objectives were stated:
1)
2)
3)
4)
To review digitalization phenomenon and its implications for warehouse management
To identify digital solutions in warehouse management
To analyze best practices of implementing digital solutions in warehouse management
To develop an algorithm of implementing digital solutions in warehouse management
for Russian companies.
95
For the first objective the analysis of digitalization in warehouse management was
conducted. It was found out that digital solutions have a significant impact on warehouse
performance. Furthermore, it was revealed that there are some studies on such software tools as
Warehouse Management System (WMS), Enterprise Resource Planning System (ERP),
Warehouse Control System (WCS) etc., but there are few studies on digital solutions in
warehouse management. In addition, it was identified that in the extant literature software tools
can be sometimes attributed to digital solutions. Moreover, there are no studies on developing an
algorithm of implementing digital solutions in warehouse management.
The second objective, identifying digital solutions in warehouse management, was
achieved based on analyzed articles. Thus, it was found out that currently in warehouse the
following digital solutions are applied: Warehouse Management System (WMS), pick-by-voice,
pick-to-light, radio frequency identification (RFID), 3D printing, augmented reality and robotics.
Additionally, each of the digital solution was reviewed and it was established that WMS and
pick-by-voice are the most relevant and most widely used technologies in Russian companies,
therefore they were further used for developing an algorithm in warehouse management.
The third objective included analysis of the best practices in warehouse digitalization. Six
international and Russian companies were investigated in terms of their digital solutions in
warehouse management. The following criteria were chosen for the companies:
• Logistics providers (3PL) and distribution companies
• Experience in implementing digital solutions in warehouse management
• Russian companies or Russian branches of international companies
For the research within-case and multiple case study analyses were conducted. During
the interviews and secondary data analysis in each company existing digital solutions in
warehouse management were identified. In order to conduct within-case and cross-case study
analyses certain dimensions were chosen by the researcher and approved during the interviews
with digital solutions’ integrators. These dimensions include reasons of implementing the digital
solution in warehouse management, stages of implementation of the digital solution, duration of
stages, responsible employees during implementation of the digital solution, problems during the
digital solution implementation in warehouse management. Three companies company A,
company B and company C were studied in terms of their WMS implementation and three
companies company D, company E and company F were studied in terms of their pick-by-voice
technology implementation. Based on the conducted case study analysis it was revealed that
there can be found more similarities than differences among the observed companies. For
instance, considering WMS implementation it was revealed that reasons of implementing WMS
in warehouse management among companies are very similar as well as responsible employees
of WMS implementation. Different problems, which companies had during the WMS
96
implementation, were identified, but in general it can be concluded that most problems are
attributed to software errors and human factor, such as initial resistance of the new technology
implementation. Differences were also identified among stages of implementation of WMS,
which can be explained by several factors. Firstly, some of the analyzed companies implemented
WMS without assistance such as company A and some companies cooperated with WMS
providers such as company B and company C. Consequently, duration of the WMS
implementation among observed companies also differed from 9 months to 1 year.
The last objective consisted of developing an algorithm of implementing digital solutions
in warehouse management for Russian companies. Based on conducted case study analysis two
algorithms for two digital solutions such as WMS and pick-by-voice were developed. For each
algorithm specific stages and their duration were identified. In addition, for each stage
responsible employees were specified and detailed stage content was presented.
During the research several limitations were identified, which refer mostly to the research
sample. Moreover, some limitations were revealed, which were connected with the opportunity
to provide generalization of the findings since as the limited number of analyzed case studies per
each digital solution (three case studies for each solution) was investigated. Nevertheless, the
current thesis holds value for the sphere of digitalization in warehouse management as it was
possible to reveal similar patterns of implementing digital solutions in warehouse management
for Russian companies.
Thus, the master thesis holds theoretical and practical value since it reveals digital
solutions in warehouse management and provides an algorithm of implementing digital solutions
(WMS and pick-by-voice) in warehouse management for Russian companies. The results of the
master thesis can be useful for warehouse and IT managers and also for employees, who are
involved in the implementation process of digital solutions. Moreover, the research provides the
basis for future research on digital solutions in warehouse management. Further research can be
conducted using quantitative approach regarding impact of digital solutions on warehouse
management, for instance which digital solutions have the highest return on investment, which
solutions are the most effective in order-picking process.
97
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Appendices
Appendix 1. Interview questions for Company A, Company B and Company C
1) Please describe company’s warehouse logistics
105
2) Which digital solutions does company have in warehouse management?
3) What are the reasons of digital solutions implementation in warehouse management?
4) What is the typical implementation approach of digital solutions among the logistics
providers: independent implementation or cooperating with consulting company/IT
integrator?
5) Warehouse Management System:
a. When Warehouse Management System was implemented?
b. What are the elements of Warehouse Management System, its functions?
c. How many employees have to manage Warehouse Management System?
d. Which stages did the implementation of Warehouse Management System have?
e. Which activities were included in each stage?
f. Duration of each implementation stage?
g. How many employees did participate in Warehouse Management System
implementation?
h. Which specialists did participate in Warehouse Management System
i.
j.
k.
l.
implementation?
Was there a trial of Warehouse Management System before its final implementation?
Problems during Warehouse Management System implementation
Economic effect of Warehouse Management System implementation?
Did Warehouse Management System influence company’s key performance
indicators, warehouse operations? Was these decrease of time and personnel costs?
m. Peculiarities of implementation of Warehouse Management System in Russia
Appendix 2. Interview questions for Company D, Company E and Company F
1)
2)
3)
4)
Please describe company’s warehouse logistics
Which digital solutions does company have in warehouse management?
What are the reasons of digital solutions implementation in warehouse management?
What is the typical implementation approach of digital solutions among the logistics
providers: independent implementation or cooperating with consulting company/IT
integrator?
5) Pick-by-voice technology:
a. When pick-by-voice was implemented
b. What are the elements of pick-by-voice, its functions?
c. How many employees have to manage pick-by-voice?
d. Which stages did the implementation of pick-by-voice have?
e. Which activities were included in each stage?
f. Duration of each implementation stage?
g. How many employees did participate in pick-by-voice implementation?
106
h.
i.
j.
k.
l.
Which specialists did participate in pick-by-voice implementation?
Was there a trial of pick-by-voice before its final implementation?
Problems during pick-by-voice implementation
Economic effect of pick-by-voice implementation?
Did pick-by-voice technology influence company’s key performance indicators,
warehouse operations? Was these decrease of time and personnel costs?
m. Peculiarities of implementation of pick-by-voice in Russia
107
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