DEPARTMENT OF TECHNOLOGY MANAGEMENT AND ECONOMICS 
DIVISION OF SUPPLY AND OPERATIONS MANAGEMENT  

CHALMERS UNIVERSITY OF TECHNOLOGY 
Gothenburg, Sweden 2023 

www.chalmers.se 
Report No. E2023:120 

Investigating requirements for introduction 

of automated warehouse operations 
Master’s thesis in Supply Chain Management 

 
 
 

Daniel Thörnblad 

Erik Stigling Svantesson 

 



 

 

 
 

 

 

  

 

 

 



   

 

 

 

 
REPORT NO. E2023:120 

 
 
 
 
 
 
 

 
 

Investigating requirements for introduction of 

automated warehouse operations 

 
 
 

Daniel Thörnblad 

Erik Stigling Svantesson 
 
 
 
 
 
 

Tutor, Chalmers: Tarun Agrawal 

Company supervisor: Carl Lamberg 

 
 
 
 
 
 
 
 
 
 
 
 

 
 

 
 
 
 
 

Department of Technology Management and Economics 

Division of Supply and Operations Management 
CHALMERS UNIVERSITY OF TECHNOLOGY 

Gothenburg, Sweden 2023



   

 

 

 

Investigating requirements for introduction of automated warehouse operations  
Daniel Thörnblad  
Erik Stigling Svantesson 
 
 
© Daniel Thörnblad, 2023. 
© Erik Stigling Svantesson, 2023. 
 
 

 

 
 
Report no. E2023:120 
Department of Technology Management and Economics 
Chalmers University of Technology 
SE-412 96 Gothenburg 
Sweden 
Telephone + 46 (0)31-772 1000 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
 
 
 
 
 
Gothenburg, Sweden 2023 



   

 

i 

 

Investigating requirements for introduction of automated warehouse 
operations  
 
Daniel Thörnblad  
Erik Stigling Svantesson 
 
Department of Technology Management and Economics 
Chalmers University of Technology 
 

Abstract 
 

The introduction of automated operations is gaining pace due to introduction of 

industry 4.0’s vision to achieve increased efficiency and cost savings. Companies 

operating warehouses thus, need to adapt their current Warehouse Management 

System (WMS) setup to fulfil the new system demands and requirements. This would 

require WMS in-house or through external help. 

 

The aim of this thesis is to study how the requirements and capabilities of a WMS 

setup change as a case company transition from manual to automated warehouse 

operations. By examining these new requirements and capabilities, a decision 

concerning whether the case company’s current WMS or an alternative WMS setup is 

required to handle the new demands and requirements posed upon the WMS will be 

made. The study has been performed by analysing a case company´s use of WMS and 

its warehouse operations through interviews and site visits. Interviews have been 

performed together with the managerial levels of warehouse, IT, and business 

departments to gain a greater understanding of the current situation and their 

requirements of a new WMS when transitioning to automated warehouse operations. 

 

The study has contributed with information concerning how companies can approach 

an elicitation of new requirements as they are to automate manual operations. It 

further provides information regarding how the requirements and demands upon a 

WMS shift as processes within a warehouse become automated.  

 

Some of the important findings of the study are: (a) High quality master data is 

important for companies as they are to automate since the automated operations rely 

on correct master data for efficient operations without standstills. (b) Important to 

prepare the WMS to handle automation since the introduction of automation brings 

new requirements on capabilities of the WMS. (c) 3rd party WMS applications when 

applied to a company’s current WMS for improved functionalities could result in 

synchronization problems that could affect the company’s operations. (d) A company 

standardise their operations before they implement automation, the implementation 

process of the automated operations would become easier. The reason for this was 

due to that the company will get simplified processes that is easier to translate into 

automated operations. (e) Reduce wrongful data scanning or manage of data, since 

wrongful data cause input of wrong master data to other systems which will create 

constraints when implementing automated warehouse operations. These findings have 

provided an valuable insight into how companies need to adapt their WMS as they are 

to implement automated operations.  

 

Keywords: Warehouse Management System (WMS), Warehouse, Automation, System 

Requirements  



 

 

 
 

 

ii 

 

Abbreviations: 

 

ERP           Enterprise Resource Planning 

 

WMS         Warehouse Management System 

 

IoT             Internet of Things 

 

IIoT            Industrial Internet of things 

 

CPS           Cyber Physical Systems 

 

RF              Radio Frequency 

 

RFID          Radio Frequency Identification 

 

ROI            Return of Investment 

 

DC             Distribution Center 

 

NDC          Nordic Distribution Center 

 

EDC          European Distribution Center 

  



 

 

 
 

 

iii 

 

 

 

  



 

 

 
 

 

iv 

 

Table of Contents 

1 Introduction ....................................................................................................................................................... 1 

1.1 Background .................................................................................................................................................................. 3 

1.2 Aim .................................................................................................................................................................................. 4 

1.3 Research questions .................................................................................................................................................... 4 

1.4 Limitations .................................................................................................................................................................... 5 

1.5 Ethical and social considerations ........................................................................................................................ 5 

2.  Literature review and Frame of references ............................................................................................. 8 

2.1 Industry 4.0 .................................................................................................................................................................. 9 

2.2 Internet of Things ..................................................................................................................................................... 10 

2.3 Radio Frequency Scanners ............................................................................................................................... 11 

2.4 Enterprise Resource Planning ............................................................................................................................. 13 

2.5 Warehouse Management System ........................................................................................................................ 15 

2.6 Requirement engineering ...................................................................................................................................... 18 

2.7 Master Data ............................................................................................................................................................... 20 

3. Methodology ................................................................................................................................................... 21 

3.1 Research approach and design ........................................................................................................................... 21 

3.2 Structure and motivation of the study ............................................................................................................... 24 

3.3 Data collection .......................................................................................................................................................... 26 

3.4 Trustworthiness ......................................................................................................................................................... 28 

4. Empirical Findings ....................................................................................................................................... 30 

4.1 As-Is description ....................................................................................................................................................... 30 

4.2 Flow Charts................................................................................................................................................................ 36 

4.3 Summary tables ......................................................................................................................................................... 39 

5. Analysis and Discussion ............................................................................................................................... 43 

5.1 RQ1 ............................................................................................................................................................................... 43 

5.2 RQ2 ............................................................................................................................................................................... 48 

6. Conclusions and recommendations .......................................................................................................... 52 

7. References ....................................................................................................................................................... 55 

8. Appendix ......................................................................................................................................................... 59 

Appendix A: Search queries ......................................................................................................................................... 59 

Appendix B: Interview guide ....................................................................................................................................... 61 

Appendix C: Flow chart over NDC and EDC ....................................................................................................... 68 

Appendix D: Result of interviews .............................................................................................................................. 70 
 

 
  



 

 

 
 

 

v 

 

  



   

 

1 

 

1 Introduction 
 

In recent years, industrial development has gone through significant technological and 

system development changes, resulting in a totally new industrial environment. This 

change to a new industrial era is known as Industry 4.0, which together with i.e., 

Internet of Things (IoT) brings new technology in the shape of automation and 

intelligent robotics for both system and operational level. These technologies bring 

several benefits such as better production efficiency, resource utilization, and 

competitiveness. But the technology might be difficult to implement for companies 

since they entail high system requirements.  

 

For companies to be competitive, they needed to invest in new technology to be able 

to handle automated system and operation solutions, while still managing the 

operational processes effectively. Consequently, it put forth new demands and 

requirements on the operations and Enterprise Resource Planning (ERP) systems that 

are currently in use. This also entails that ERP systems need to be capable of handling 

i.e., intelligent manufacturing, transformation to digital solutions, cloud-based 

systems, and have the capacity to track the internal and external flow of goods (Yanti 

et al.,2022). To manage the operation and in-and-out flow within the warehouse, the 

ERP system has a submodule called Warehouse Management System (WMS). It’s a 

software system that manages logistic operations and can be used when increasing the 

level of automation in a warehouse. The WMS enables, coordination of internal 

transportation, logistics management, and planning for both internal and external 

demand. It’s also a software that enables connectivity between warehouse 

information, automation, ERP functions, and the entire supply chain (Karpova, 2022). 

Industry 4.0 has also presented challenges concerning how to implement and develop 

technologies, such as WMS functionalities, digitalization, and automation. 

Succeeding with the implementation will result in highly automated processes and an 

ERP system that create competitiveness on both operational and corporate level for 

the company (Thanh, 2022). 

 

According to Thanh (2022), implementing automation results in more efficient 

processes. Additionally, it’s a solution that decreases manual handling, improves 

inventory control, and integrates WMS with data and information from the ERP 

system. To manage and control all the systems and automated features, a Cyber-

Physical System (CPS) is required to connect all the systems. CPS is called the core 

of software systems and make the systems automated on a system level by integrating 

all the software systems and data flows between the different systems (Gong et al., 

2019). 

 

The advancement of new technology and automation for warehouses has entailed new 

criterions and requirements resulting in challenges of how to identify requirements on 

the operations and prioritize processes. However, previous studies have focused on 



 

 

 
 

 

2 

 

establishing a process for analysing and identifying requirements upon WMS and 

automation. But many of the studies are focusing upon a specific setup of operation or 

warehouse layouts (Thanh., 2022). When companies are to choose their ERP system, 

they may choose one of several available ERP providers. To easy the search for the 

most suitable ERP system for a company, Thanh (2022) developed a mathematical 

model that could rank the different ERP providers systems based on different 

criteria’s and could thereby help companies find the optimal system for them. The 

criteria presented in the study originate from both quantitative and qualitative data 

from only previously performed research and literature. 

 

For the operational level, Lee et al. (2018) studied the requirements for an IoT-based 

WMS with a focus on the performance of a picking process by prioritizing different 

rules with a focus on system capacity for order handling, the number of SKUs, and 

staff requirements. Afterward, the rules were analysed to determine how the rules 

integrate with each other and then prioritized from high too low to identify the most 

critical combination for the system.  

 

In another research study by Aires and Abrantes (2022), the possibility for a 

consultant company to implement a new ERP system were investigated. They 

identified requirements of new system level features by collecting qualitative data and 

requirements by performing interviews and observations of the current system, to 

clarify the requirements. They identified requirements and the traceability of the ERP, 

thereby getting an overview of what features are required and what should be further 

customized. However, the authors noted that a new method or process must be 

developed for each case to identify unique criteria and requirements.  

 

To summarize, a common issue of previous research studies is that the models and 

frameworks being used are designed according to a case company or a specific 

situation. It is therefore difficult to identify studies that approach specifically the 

operational level, and who also design a framework that may be replicated and 

adapted by the industry.   

 

Previous studies have established a foundation of how models can be designed for 

specific processes and companies. But implementing these models for companies with 

different operations and requirements can be challenging. As a result, there is a 

research gap concerning how companies with specialised WMS setups can operate 

warehouses with differing requirements and prerequisites for automated solutions. 

This means that a new WMS setup must be able to handle the diverse levels and kinds 

of automation that will be introduced to the different warehouses. Therefore, this 

study will investigate the most important criteria’s when planning for new automation 

solutions and what new WMS features that will be required. The study will analyse a 

case company, who’s warehouse operations currently include a high degree of manual 

handling in the picking process, as they are about to introduce automated operations 

in their warehouses.  



 

 

 
 

 

3 

 

This study will establish and interpret the common criterions and requirements for 

integrating automated solutions into a company’s WMS. This will be carried out by 

analysing the requirements for implementing new automation in a warehouse, and by 

clarifying if the current WMS can handle the new requirements that an automation 

entails. 

 

1.1 Background 

 

The background of this report is that the case company has decided to automate their 

present warehouse operations to make it even more aligned to the standards of 

industry 4.0. Due to the confidentiality of the focal company in this study, they will 

hereon be labelled the case company. The case company of the study is a medical 

equipment manufacturer which has seen a strong growth during the last decade, 

resulting in yearly revenues surpassing 1 billion dollars. The company has several 

thousand employees all over the globe, but with a strong foothold in Europe. Their 

manufacturing operations are based in Europe, Asia, Costa Rica, and US with a 

distribution network covering the globe. They currently run a 20+ years old ERP 

system on physical servers on premise called JD Edwards EnterpriseOne from Oracle, 

which they have customized extensively to match their changing demands upon it. To 

operate their ERP system, they have a favourable licensing model. The ERP system 

used includes modules that provide i.e., the functionalities of a WMS.  

 

Recently, during the case company’s biannual meeting, they presented that the 

company would have a focus on implementing automation to their current operations. 

For their warehouses, this means a focus upon increasing their current levels of 

automation. Their present warehouse operations on most sites are performed manually 

by employees equipped with RF scanners, in which they scan barcodes to receive 

picking instructions and picking route suggestions. With the introduction of 

automatization in their warehouse operations, new demands will be set on their 

Warehouse Management System (WMS). The case company has discussed the topic 

with their current ERP provider Oracle, who tried to sell them a new cloud-based 

WMS stating that the current setup would be unable to cope with an automation of 

warehouse operations. Thus, the focal company desired an independent neutral third 

party that will investigate whether the current WMS module would be able to handle 

an implementation of automated warehouse operations. Alternatively, if the current 

WMS would need to operate other systems in parallel or even change to a new WMS 

to manage the introduction of automation in their warehouses.  

  

  



 

 

 
 

 

4 

 

1.2 Aim  

 

This project’s aim is to investigate how the requirements and capabilities of an WMS 

setup change as automated operations are introduced within warehouses that currently 

perform manual operations. By examining the new requirements and demands that the 

introduction of automation bring upon a WMS, a decision concerning whether the 

current WMS is capable of handling the new requirements and demands, or if an 

alternative new WMS setup is necessary will be presented to the case company. 

 

 

1.3 Research questions 

 

The research questions of the study are formulated together with the case company 

based on their presented problems concerning how their WMS would be able to 

handle warehouse automation. The research questions will cover the previous 

research gap of vague approaches on how to address requirements on an operational 

level and the WMS. It will entail analysis of capabilities and functionalities that are 

required for implementing technology within Industry 4.0. The report will therefore 

answer the following questions in order to establish how automated solutions in the 

warehouse will affect the current WMS setup. 

 

Research questions: 

 

RQ1: How do operational requirements upon a company’s WMS shift as they 

transition from manual to automated warehouse operations? 

 

RQ2: What should a company modify in their current WMS to accommodate the 

transition to automated warehouse operations? 

 

The reason behind RQ1 is due to that the operational requirements is the driving force 

behind the development of system requirements of an WMS. 

 

The reason behind RQ2 is due to that automation requires a company to implement 

new features and functionalities into their WMS. The question is used to analyse a 

company’s ability to handle the new requirements within their current WMS setup or 

not.  

 

  



 

 

 
 

 

5 

 

1.4 Limitations 

 

This report will firstly focus at a process level on how demands and requirements 

upon the WMS module of the case company’s ERP system will change as they 

transition from manual warehouse operations into automated operations. Secondly it 

will investigate the compatibility between the new demands and requirements on the 

current WMS to inspect if they are compatible, or if a new WMS solution is necessary 

to meet these new demands and requirements. The focal company have over 19 

warehouses worldwide, but for this study only the two warehouses in Sweden and 

Germany will be studied. 

 

The report will neither cover how any potential system level automations such as 

Robotic Process Automation (RPA) will affect the WMS’s demands and 

requirements. Neither will the report develop an implementation strategy regarding 

any potential new WMS solutions or implementations. 

 

Due to the time limitation and scope of the thesis project, only the three departments 

of warehouse, IT, and business will be of interest to interview. 

 

1.5 Ethical and social considerations 

 

For this study to fulfil its ethical obligations, the following three conditions will be 

meet: 

• The study will cover important research questions. 

• The study will display proper scientific quality. 

• The study will be performed ethically. 

(Sandman & Kjellström, 2018). 

 

In order to cover both engineering and research ethics throughout the study, a 

framework from Sandman & Kjellström (2018), as seen in figure 1, will be used to 

reassure that ethical consideration will be taken throughout the project as visualized in 

figure 1.  



 

 

 
 

 

6 

 

 
Figure 1. Different ethical aspects taken into consideration during different phases of 

the study. Note. Figure based on Sandman & Kjellström (2018). 

 

To ensure that ethical manner and social considerations presented in the framework 

are realised, there are ethical principles to ensure considerations of appropriateness 

and responsibility in the three phases of planning, data collection, and reporting. One 

of the principles that are presented by Bell et al., (2022) are made to minimize the risk 

of harming participants, this means the project should have strong realism with 

correct data, and not exceed any limits of statements that can harm the participants 

employment or careers. It should also ensure that appropriate participants are 

involved and that they are aware of the aim (Bell et al., 2022). The participants should 

also be informed about their role of participation and ensure that they are proficient 

within the field (Bell et al., 2022).  

 

To follow these principles, in the steps of data collection, this case study has provided 

interviewees information about the study in advance to ensure that they have 

understood the scope of the study. Interview questions have been sent before 

performing interviews to ensure good awareness and results from the interviewees. 

For the part of reporting, Bell et al., (2022) have addressed principles of privacy for 

participants and how information is shared. To ensure that, participants should be well 

informed about the content of the study and that the study will be published. They 

should also be involved in the process of reviewing the information that was 

collected.   

 

To ensure good ethical consideration and awareness in this case study, the participants 

had the possibility to prepare for the interviews by reading the interview questions in 

advance as well as the purpose and scope of the study. 

  
 
  
  
  
 
  
  
 
  
 
  
 
 
  
  

 
  
  
 
  
 
  
 

                              

                     
     

             

                       

                
       

                 
                

             

                     
      

                    
           

      
       



 

 

 
 

 

7 

 

 

Publishing is also a part of the framework and it’s therefore important to prevent 

deception or deviation of the study. The publication of study must therefore be 

accepted by the participants and the case company, and the authors are those who is 

responsible for the material that are published (Bell et al., 2022). To prevent 

uncertainty among participants the purpose, scope and method for the study have been 

clarified and presented to the stakeholders.  

 

Social consideration is also a part of the ethical framework and has a more dynamic 

approach compared to the previously mentioned parts. It focuses on the social and 

ecological aspects of a study and how participants, the case company, stakeholders, 

and cultural considerations are integrated with the study. Therefore, a study should 

have a clear scope and research methodology. The study’s impact on individuals and 

organizations should also be considered and provide the participants and stakeholders 

with necessary information about the study (Ban et al., 2013). To ensure social 

consideration in this case study, the selected interviewees have varying backgrounds 

and positions in different departments within the case company. The study will not 

have a cultural or ecological impact. To minimize the conflict concerning cultural or 

ecological aspects and uncertainty among warehouse operators to be replaced by 

automation, the study will focus on the new requirements upon WMS for 

implementing automation and not on the performance of the workforce. 

 

Within the ethical framework, social consideration is included as a dynamic approach. 

This refers to the social and ecological aspects of a study, and how the study interacts 

with participants, organizations, stakeholders, and cultural considerations. A study 

should then have reasonable trade-offs within the field of study and the impact on 

individuals and the case company (Ban et al., 2013).  



 

 

 
 

 

8 

 

2.  Literature review and Frame of references 
 

The purpose of a literature review is to present the theory from literature utilised in 

the study. The review will also give the authors and readers an understanding of the 

concept and theories from previous research findings (Bell et al., 2022). The literature 

review and methodological findings will then be used to establish knowledge about 

the research scope and support the analysis of the study. A literature review can be 

done by performing a systematic review which will result in a structured review with 

transparent processes and an audit trail that makes the database search replicable (Bell 

et al., 2022). 

 

To find appropriate literature and make empirical findings for the study, a literature 

review was performed by searching on the thesis's topic on Scopus database, Google 

scholar, and Chalmers library database. This resulted in relevant keywords from 

literature, the next step in the literature review was to establish an approach for a 

systematic review by searching for queries and keywords only in the Scopus database. 

With search queries, the review was narrowed and filtered to the desired topics and 

peer reviewed articles. Keywords used in the search were i.e., WMS, IoT, 

Requirement engineering, Business, Warehouse, CPS, and Robotics. When searching 

for WMS and CPS the combined search result was approximately 60 000 articles. By 

advancing the search queries with more keywords, Boolean operators, and wildcards 

in the form of *, for both initial two topics, the database search resulted in a total of 

50 articles. Each article was then reviewed to elicit empirical findings, research 

methods, and research gaps. The literature theory and empirical findings from the 

database search are presented under the frame of reference and literature review 

chapter. A more detailed presentation of how the keywords and search queries have 

been combined can be viewed in Appendix A. 

 

Reviewing literature and previous research is a crucial part of a study to provide a 

literary framework for the reader containing representable literature covering relevant 

topics. The references may be sampled from either common theoretical concepts and 

methodologies, or case studies. The frame of references intends to address previous 

research findings and methods which will contribute to the analysis chapter and when 

answering the research questions of the study (Bell et al., 2022). The following 

sections will therefore cover theoretical concepts that are important for the study. 

Each of these sections is a fundamental part of Industry 4.0 that is integrated into a 

joint system. How each section of the frame of references is organized can be seen in 

figure 2. The lower dark grey area in the figure shows the main research area and the 

technological part of WMS that the study focuses on.  

 



 

 

 
 

 

9 

 

 
Figure 2. Illustration of the frame of references and how each section interacts within 

industry 4.0.  

 

2.1 Industry 4.0 

 

The industrial development has in recent years gone through a new era called Industry 

4.0 with the fast-paced development of technology and implementation of intelligent 

manufacturing, digitalization of operations, cloud-based solutions, and tracking 

internal and external flows (Yanti et al., 2022). Industry 4.0 is built upon the 

challenges to meet requirements of production and transaction efficiency, handling 

supply constraints and customers’ needs, and connecting machinery. To manage such 

challenges, the strategy of Industry 4.0 contains an implementation of robotics and 

automated solutions to integrate functions into a system and enterprise network (Gong 

et al., 2019). This requires that data can be transferred over and between systems, or 

to 3rd party systems, which requires structured, accessible, and visible data (Gong et 

al., 2019). According to Cambridge Dictionary (2023) a 3rd party software is a 

computer program developed for a particular purpose by a company different from 

the one who developed the existing programs of a certain system. The data 

transferring is according to Gong et al., (2019) a systematic approach for internal and 

external network integration. This can be achieved with a Cyber Physical System 

(CPS) that connect all the modules and systems. CPS connects all software systems of 



 

 

 
 

 

10 

 

a company into an interconnected system by including the ERP system, WMS 

module, automation, and robotics.  

 

The broad scope of Industry 4.0 makes it usable as a guideline to improve operations 

and increase the level of automation and technological solutions. To simplify the 

concept of Industry 4.0, Fatima et al., (2022) presented five areas of importance to 

consider:  

• Intelligent Manufacturing: The level of automation in production and 

warehouses, what features are required and what fits the current system. 

• Intelligent Product: Products' technical complexity and the requirements for 

research and development. The level of intelligence increases the requirements 

of the system. 

• Customization: A system’s capacity to manage variation of specification and 

volume. 

• Staff’s work: Concerns the balance between system automation and employee 

integration.   

• Network Foundation: The possibility to create a network of technology and 

systems. 

For warehouse management, Industry 4.0 will make processes more reliable and 

efficient by reducing manual handling and minimizing errors due to human factors. 

This can be accomplished by implementing robotics, automating time-consuming 

processes, and connecting machines to send and receive data (Fatima et al., 2022). 

Such features will make the operational processes more profitable, competitive, and 

improve their delivery rates. Besides managing the warehouse, Industry 4.0 can also 

create opportunities for increased visibility throughout the supply chain, resulting in 

improved response for ERP systems and when managing disruptions (Abbasian et al., 

2022). 

 

2.2 Internet of Things  

 

Many academic writers’ states that IoT is an integral part of realising the prospects of 

industry 4.0, but there is currently no consensus concerning a mutual definition of IoT 

(Ud Din et. al, 2022 & 2023, Khan et. al, 2022, van Kranenburg et. al, 2012). 

According to Mohanraj et al. (2019) IoT can be described as a network of connected 

items i.e., vehicles and machines, which connects data from the physical world 

through i.e., sensors and actuators, to computer operating systems by transferring data 

from physical sensors by utilizing network connectivity. This network of connected 

items therefore helps to connect the physical world to computer systems. 

 

The usage of IoT in an industrial context have created what is known as Industrial-

Internet-of-Things (IIoT), which is one of the key areas for industries that wish to 

implement Industry 4.0 and automate their processes to improve their performance 

and efficiency (Khan et al., 2022). The usage of IIoT is slowly turning the current 



 

 

 
 

 

11 

 

traditional industrial processes into what is known as a Cyber-Physical System (CPS) 

(Khan et al., 2022). The introduction of IIoT has meant that the industry as we know 

it today is slowly getting increasingly connected, data-driven and automated in order 

to stay competitive. For warehouse management the introduction of IIoT is i.e., 

reflected in how sensors are implemented to feed data of the physical world into the 

computer system, to facilitate the transition into smart warehouses to help with the 

challenges concerning human and robot activity, data collection and robust 

localization (Khan et al., 2022). For the smart warehouses to function properly, they 

are driven by a large set of algorithms which rely on a continuous input of data 

regarding position, volume and space of warehouse Stock Keeping Units (SKUs). 

This exchange of information is arranged by the IIoT and is thus essential for proper 

functionality of modern smart warehouses (Khan et al., 2022). 

 

2.3 Radio Frequency Scanners 

 

A traditional method to identify and collect information on items is to manually scan 

barcodes or QR codes in a warehouse with a barcode scanner. A more technical 

method is Radio Frequency (RF) scanners that can collect information by scanning 

for frequency from i.e. tag on the items. It’s a good tool to navigate through a 

complex warehouse with different products, processes, and storage areas. RF scanners 

are used to send and receive information and confirmation of tasks to the WMS with 

real-time updates to WMS (Liu et al., 2017). Real-time updates between WMS and 

RF scanners will result in efficient responses and improved accuracy of inventory 

control with standardized procedures to communicate to the system. With RF 

scanners items, orders, and executed operations are scanned to send information and 

warehouse stock to the WMS. The WMS can then send back information or tasks to 

the handheld scanner, providing the operators with information of what items to pick 

and pack, or the tasks in the next process (Yao & Carlson, 1999).  

 

Another method for managing warehouse operations is Radio Frequency 

Identification (RFID) (Lu et al., 2018). The RFID can identify a unique radio 

frequency from tags that are placed in the warehouse or attached to items and 

translate a tag’s code into readable information. The RFID tag for RFID scanners 

corresponds to barcodes for RF scanners, but the RFID tags can include more 

information about the item, where it will be stored, and what operations it will go 

through. This means that a large amount of data can be collected and transferred at a 

fast pace and with high accuracy, with no interaction with the goods or physical flow 

that can cause delays (Zhou, 2022). The main benefit of RFID is that an item’s 

position in the supply chain can be monitored and tracked, which can be used to 

improve the routes (Hamdy et al., 2018). To realize this verification of information, a 

system must have access to a good database and enough capacity to process the data 

(Zhou, 2022). The execution process for RFID is similar to RF scanners, with 

scanning and confirmation of every operation. However, for the inventory flow, RFID 



 

 

 
 

 

12 

 

can be used to track where goods, semi-finished products, and finished products are 

placed (Sujing et al., 2010). 

 

 



 

 

 
 

 

13 

 

2.4 Enterprise Resource Planning 

 

Managing a firm’s business and strategies requires a software system that can control 

and manage operations with a good overview of the business. A system that can 

handle such requirements is Enterprise Resource Planning (ERP), which is a system 

with different sets of features that can manage operations and processes of a 

company. The system is made to perform daily tasks ranging from financial and sales 

processes, to production and warehousing. The system contributes to improved 

overview of operations, improved decision making, headcount reduction, improved 

data integration, and better management of production and logistics (Thanh, 2022). 

 

With an integrated system such as ERP, communication and resource planning will be 

improved resulting in increased visibility over the organization, which benefits the 

analysis of operations and when developing business strategies. The reason for why 

companies use an ERP system, is due to how information and resources can be 

gathered in one single system instead of several independent systems (Yanti et al., 

2022). With an ERP system, all information and data can be managed and viewed in 

one system to secure a stable integration, analysis of Key Performance Indicators 

(KPI), planning processes, and forecasting demand (Thanh, 2022). The benefits of a 

ERP system are many since it can be designed according to a firm’s specific 

operations and unique requirements. Therefore, when implementing an ERP system, 

it’s crucial to identify criteria from both qualitative and quantitative data, but also the 

constraints of the current state. It is important to have knowledge about the business 

criteria and requirements on the ERP to better understand which functions that are 

necessary to operate the business, and what should be done to improve the system 

(Thanh, 2022). 

 

If the criteria and requirements can be identified and interpreted, the company will 

gain knowledge of how subsystems and features can be modified and improved. For 

improved performance of supply chain operations and warehouse management, ERP 

system can create efficient scheduling, resource planning, and controlling the 

inventory level and managing processes in real-time (Thanh, 2022). The sub-system 

within the ERP managing the warehouses is called Warehouse Management System 

(WMS), which can be integrated with technological solutions and automation to track 

and handle material and products, e.g., by using RFID or robotics (Thanh, 2022). By 

using an ERP system and its features together with automated warehouse solutions, 

the processes happening within the warehouse will be easy to manage and analyse. 

The implementation of an ERP system will also improve the utilization of human 

resources and control of the processes since it entails tracking progress, 

documentation, and communication on system and operation level. Lastly, ERP 

systems are designed to interact with other firms in a supply chain, meaning it can be 

used to communicate and share information within a supply chain (Mariano-Melo & 

Ramírez-Correa, 2021). 

 



 

 

 
 

 

14 

 

• 3rd Party Applications: 

When companies implement an ERP system, the system may not include all the 

functionalities the company requires for efficient operations and data flows. To solve 

this problem companies may utilize 3rd party ERP applications to gain the necessary 

functionalities within their ERP system. But the usage of 3rd party applications also 

brings certain risks for companies such as server or internet connection problems, 

resulting in system synchronization problems that lead to disturbances of business 

operations and ultimately even production (Mao et al., 2018). These problems may 

arise at either the servers of the 3rd party application provider, the company or internet 

provider resulting in synchronization problems with the ERP since the servers of the 

focal company and the 3rd party application provider are separated (Mao et. al., 2018).  

 

• Integration Infrastructure: 

The infrastructure of an ERP system and applications relies on a good integration 

infrastructure to maintain good communication with Information Technology (IT) and 

automated applications that are used in a company's processes. Along with the ERP 

system and increased data, companies can face challenges with the integration of 

systems, technology, and increased complexity due to the implementation of 

functionalities or customization (Themistocleous et al., 2001). According to 

Themistocleous et al. (2001), a weakly integrated infrastructure will end in bad 

communication to IT and applications. It could also affect the ROI of a project since it 

will require extra operations and resources if the infrastructure not is sufficient 

enough.  

 

According to Kovács & Paganelli (2003), for a company to establish an effective 

integration infrastructure, as they should avoid having replications of functionalities 

or unstructured processes. To establish a good system integration infrastructure, the 

authors conducted that commercial tools could improve data interchange, and 

standardization of communication could contribute to improved accessibility in the 

system and functionalities. These suggestions of functionalities for integration are not 

offered in an ERP system, and if a company tries to incorporate ERP systems with 

other systems or applications without a solution for integration it can result in 

integration and IT problems. A solution to establish a good system integration 

infrastructure is to have an efficient integration of applications by using EDI 

(Electronic Data Interchange) technology. This is managed by creating a more 

dynamic infrastructure and placing a company’s setup in an application network 

(Themistocleous et. al., 2001).  

 

• Standardization to reduce complexity: 

To manage a dynamic market and meet customer demand, system integration and 

communication are important within a company and its supply chain. Hence, 

standardization of the ERP system and Warehouse Management System (WMS) is 



 

 

 
 

 

15 

 

necessary to create efficient communication and collaboration within a company’s 

departments (Andiyappillai, 2019). In an ERP system, standardization of processes 

and modularity can achieve better resource utilization, effective data sharing, and 

shared knowledge within a company, with the use of common tools and standards for 

how information is shared (Chtioui, 2009). In operational processes, standardization 

will have an extensive result on the efficiency and quality of an operation. There are 

several ways to standardize a warehouse, but common standards are customer centric 

which refers to standardizing the order flows, standards for communication between 

operations and teams, or standards to manage flexibility and material flow (Raghuram 

& Arjunan, 2022).  

 

 

2.5 Warehouse Management System 

 

Warehouse Management System (WMS) is a subsystem within an ERP system that 

makes it possible to operate the warehouse and have a functional flow with full 

visibility over the supply chain. It also enables good delivery accuracy and 

management control of the warehouses when storing and tracking material (Khan, 

2022). WMS is explained by Khan (2022) as a management software system that 

arrange the warehouse operations, thus making it possible to introduce automation. 

With today’s increased complexity in the supply chain and automations in 

warehouses, a WMS can monitor and integrate automated solutions from several 

processes with ID tracking, robotics, and other ERP functionalities. A system like this 

is a crucial part when controlling both inbound and outbound material flows, where 

materials are located, and inventory levels information. It will then coordinate the 

information within the ERP system, e.g., with purchasing, manufacturing, or sales to 

have better control over stock levels and forecasting (Khan, 2022). 

 

WMS can be used together with technical solutions to track material and finished 

products, e.g., with scanners reading barcodes or RFID tags. Barcodes are a common 

method for collecting information from the warehouse and send information to the 

users i.e., where the material is located, the upcoming tasks, and general information. 

When reading barcodes or RFID tags, information is sent to the WMS and the system 

can then be updated with new information. This method is mainly utilised in a setting 

with manual handling and low degree of automation (Khan, 2022).  

 

WMS is a system that can receive and send out data along with information, thus 

acting as a facilitator of information distribution. The system will improve 

administration and increase the system level automation, resulting in efficient 

coordination and a system that can operate without manual integration. Figure 3 show 

how WMS is an important tool when integrating departments within an organization 

by receiving and sending information, the information flow can either be one way or 

two ways (Khan, 2022). 



 

 

 
 

 

16 

 

 

If a company decide to implement a new WMS, the financial burden associated with 

doing so is seen as high according to Min (2006), independently of the size of the 

company that are about to implement it. The costs associated with an implementation 

of a WMS depends upon the WMS chosen, license fees, maintenance fees and the 

number of sites utilizing the system, where the cost for each sites license fee can 

range from US$50,000 to US$250,000 (Min, 2006). When a company has decided 

that they will implement a new WMS they prioritize system integration, ease to use 

and a wide range of system functionalities above the price of the WMS (Min, 2006). 

According to Min (2006), large companies often consist of a network of complex 

operations often consider an WMS modification or upgrade as a difficult task. The 

reason for this is due to that their operations are more complex compared to that of a 

smaller company consisting of fewer individuals (Min, 2006).  

 

 

 

Figure 3. Information flow to and from the WMS as it interacts with other 

departments and systems. Note. Figure based on work by Khan (2022). 

 

With an integration to other system WMS can be used as a tool to support and 

automate warehouse performance with additional technologies for visualization of the 

operations. Since WMS is a software system that is designed and connected around 

the operations in a company, several different modern technologies can be integrated 

to produce the support functions required to run these operations. With the use of an 

WMS, the warehouse will be more efficient when it comes to accounting, operation 

analysis, and warehouse routing optimization (Karpova, 2022).  



 

 

 
 

 

17 

 

 

• WMS Complexity Level: 

 

In order for a company to be able to label their company’s current WMS level of 

complexity, they may utilize the model presented by Gartner, as seen in figure 4, to 

establish where the company is situated, and what they need to implement into their 

WMS to achieve a desired WMS complexity level (Tunstall et al., 2022).  

 

 
Figure 4, Warehouse Complexity Range framework/model and the five different levels 

of complexity. Note. Figure based on work by Tunstall et al. (2022). 

 

Level 1 WMS – Used in warehouses where the majority of operations are performed 

manually and were only a requirement for warehouse management functions for the 

warehouse processes from inbound to outbound are required i.e., receiving, storage 

and picking which are functionalities all ERP systems offer (Tunstall et al., 2022). 

This level also offers rudimentary bin tracking and often utilize a single storage 

location system (Tunstall et al., 2022). 

 

Level 2 WMS – Used in warehouse facilities that require basal WMS capabilities in 

their operations (Tunstall, 2022). Warehouses on this level are using multilocation 

inventory storage and also have low level stock locator capabilities (Tunstall et al., 

2022). The operations within the warehouse are paper based but aim to introduce 

work verification through mobile devices (Tunstall et al., 2022). 

 

Level 3 WMS – Is a more complex version of the previous level which offers 

advanced system-directed work but also offers more advanced control over processes 

i.e., with a higher degree of sophistication and more options to choose from (Tunstall 

et al., 2022). 

 
  
 
 
 
 
  

 
 
 
 
  
  
  

                            

                        

          

          

          

          

          

         

                 
            

              
            

           

         



 

 

 
 

 

18 

 

 

Level 4 WMS – Here focus is to introduce automation to improve processes by 

introducing decision support capabilities to aid the ongoing high volume and complex 

operations within the warehouse (Tunstall et al., 2022). The goal on this level is to 

improve performance and throughput besides the introduction of decision support 

capabilities (Tunstall et al., 2022). Due to the higher degree of sophistication on this 

level, operations require improved support for managers through i.e., business 

intelligence and dashboarding (Tunstall et al., 2022). 

 

Level 5 WMS – On this highest and final level the focus of operations is automation 

(Tunstall et al., 2022). This entail that the previous people-driven processes have been 

swapped by warehouse automation focused processes (Tunstall et al., 2022). On this 

level it is the decision to implement automation that drives the needs upon the WMS 

(Tunstall et al., 2022). 

 

 

2.6 Requirement engineering 

 

Within software engineering it is important to accurately translate and map the 

customers' requirements and desires before beginning to develop software (Nuseibhe 

& Easterbrook, 2000). To aid with this task, requirements engineering (RE) may be 

utilized (Nuseibhe & Easterbrook, 2000). The definition of RE according to Zave 

(1997) is stated as “Requirements engineering is the branch of software engineering 

concerned with the real-world goals for functions of and constraints on software 

systems. It is also concerned with the relationship of these factors to precise 

specifications of software behaviour, and to their evolution over time and across 

software families”. According to Nuseibhe & Easterbrook (2000), the five core 

activities of RE is as follows; 

 

• Eliciting requirements 

• Modelling and analysing requirements 

• Communicating requirements 

• Agreeing requirements 

• Evolving requirements 

 

For first core activity eliciting requirements, the aim is to understand the problem at 

hand that needs to be solved, but also to identify system boundaries that define where 

the new system will fit into the current operational environment (Nuseibhe & 

Easterbrook, 2000). In this stage of RE there is also a focus upon identifying the 

stakeholders of the project at hand to establish which key stakeholders that are 

important when eliciting the requirements (Nuseibhe & Easterbrook, 2000). This is a 

vital step when establish goals for what the project aims to achieve (Nuseibhe & 

Easterbrook, 2000). There exist several different elicitation techniques ranging from 



 

 

 
 

 

19 

 

traditional techniques such as questionnaires, surveys, and interviews, to cognitive- 

and contextual techniques (Nuseibhe & Easterbrook, 2000). 

 

The second core activity Modelling and analysing requirements contain several 

different methods that are suitable for different situations. When performing 

investigations in an organisational setting, an enterprise modelling and analysis 

approach is most suitable (Nuseibhe & Easterbrook, 2000). Enterprise modelling and 

analysis aim to understand i.e., an organisation's structure, business rules that affect 

operations and their goals, to better understand the organisation and capture the new 

systems purpose (Nuseibhe & Easterbrook, 2000). 

 

The third core activity Communicating requirements concerns the fact that RE require 

effective communication among different stakeholders regarding requirements 

(Nuseibhe & Easterbrook, 2000). To perform effective communication, requirements 

communication and requirements traceability (RT) has become increasingly 

important. The reason is due to that communication needs to be both readable and 

traceable by several stakeholders, but also easy to read, navigate, query, and change in 

the requirements documentation (Nuseibhe & Easterbrook, 2000).  

 

The fourth core activity Agreeing requirements continue were the previous step left of 

by examining if the requirements elicited are agreed upon by all stakeholders. When 

performing this task, techniques such as inspection and formal analysis may be used 

to verify the requirements description (Nuseibhe & Easterbrook, 2000). But 

techniques such as prototyping, specification animation and scenarios may be utilized 

if one wants a more open-ended approach to examine if a stakeholders view upon 

what is important is covered (Nuseibhe & Easterbrook, 2000). When performing this 

step there will also be concerns regarding both what is true and knowable, but also 

that it is hard to reach an agreement amongst stakeholders with incompatible goals 

(Nuseibhe & Easterbrook, 2000). 

 

The fifth core activity Evolving requirements concerns how stakeholder requirements 

are continuously changing, and thus creating new environments in which the system 

must operate (Nuseibhe & Easterbrook, 2000). It is due to this, that management of 

changes are an integral activity of RE (Nuseibhe & Easterbrook, 2000). Managing 

changes concerning requirements upon a system may be as simple as adding or 

deleting requirements, and fixing errors such as conflicting requirements, or due to 

mistakes made previously (Nuseibhe & Easterbrook, 2000). Evolving requirements 

besides managing the documentations also require a continued elicitation of 

requirement, risk- and system evaluation, in order to recognize how they change over 

time in their operational environment (Nuseibhe & Easterbrook, 2000) 

 

  



 

 

 
 

 

20 

 

2.7 Master Data  

 

Master data is a company's basic data about i.e., its products, employees, customers, 

and suppliers, and is used in the daily operations of a business (Haug & Stentoft 

Arlbjørn, 2010). Hence, it is important to have good quality master accessible for all 

departments within a company, this is a vital part of a well-functioning ERP system 

and good data flow between departments. In an ERP system, it’s required to 

constantly manage master data since all modules in an ERP system are relying on the 

same source of data. Maintaining good master data will create challenges in the 

correct acquisition and merger of data, primarily these challenges will affect the 

departments of IT, sales, and finance, but also a company's supply chain (Sarferaz, 

2022). For instance, master data of products are used simultaneously in multiple areas 

of a company and can be divided into master records to fit with a process, e.g., in 

engineering and material planning (Sarferaz, 2022). 

 

Hence, master data is utilized in every operation that requires information and 

transaction of data (Haug & Stentoft Arlbjørn, 2010). Further, Haug & Stentoft 

Arlbjørn (2010) express that incorrect master data will have an impact on all 

operations by increasing errors, resulting in inefficient processes for decision-making, 

low performance in manufacturing and warehousing, and affecting revenue with 

increased operational costs. The author’s research shows that many companies are 

struggling with bad master data found in the increased development of information 

technology. Although the new technology has enabled companies to access databases 

and organize the data, the challenge is the increased data volumes and complexity of 

data flow (Haug & Stentoft Arlbjørn, 2010). Barriers to good master data that Haug & 

Stentoft Arlbjørn (2010) have identified is that a company has a lack of ownership 

and responsibilities for data, lack of organizational procedures, or lack of training and 

education for data-cleansing. To ensure good master data, the data needs to have good 

validity and accurate input data, but also be collected and maintained in the system a 

few times during the time period (Haug & Stentoft Arlbjørn, 2010). The meaning of 

good master data is that it is of high quality and continuously updated, to be viewed as 

good. 

 

 

 

 

 

 

 

  



 

 

 
 

 

21 

 

3. Methodology 
This chapter will cover the methodology that will be used during the study to answer 

the research questions. 

 

3.1 Research approach and design 

 

This study’s purpose is to provide the case company with unbiased recommendations 

concerning if they have the internal capabilities necessary or not to handle an 

increased level of automation in two of their warehouses. The situation of automating 

warehouse operations is a generic procedure that has been performed or is about to be 

performed by several companies worldwide, and is thus not a company unique 

activity per se. What makes this transition unique are the prerequisites of the focal 

company’s situation, given their current highly customized WMS, which creates a 

complex and unique setting for the execution of the project. It was therefore important 

to adapt the study after the specific contextual situation. The research design chosen 

for this study therefore resulted in an intrinsic case study, the reason for which is due 

to that it aligned with the criteria’s given by both Bryman & Bell (2015) and Yin 

(2003), concerning under which circumstances case studies are the most appropriate 

research design. The motivation behind choosing a case study was based around the 

notion of how case studies are suitable when studying real life events and their 

characteristics, i.e., organizational- and managerial processes, and maturation of 

industries, which are contemporary events where little or no control is gained by the 

investigator (Bryman & Bell, 2015; Yin, 2003). 

 

According to Bryman & Bell (2015) a case study tends to utilize qualitative research 

to examine the given contextual settings in detail. The reason for why case studies are 

most suitable for qualitative studies is due to their ability to produce detailed 

information concerning the focal company (Bryman & Bell, 2015). The qualitative 

data collection methods that were utilized to map the case company in the study was 

site visits, semi-structured interviews and company information gathered from the 

intranet of the focal company. Since the case study’s aim is to investigate the unique 

features of the situation, what is known as an idiographic approach was utilized in the 

study to examine the focal company and will hence be the approach used in the case 

study (Bryman & Bell, 2015). With the idiographic approach being utilized in the 

study, it would result in recommendations that will be especially adapted for the 

context of the case company and the future recommendations concerning their new 

WMS solution. 

 

The usage of a case study with a qualitative approach is often associated with 

applying an inductive approach, meaning that the study’s observations and findings 

drive the theory, and not the other way around as in a deductive approach (Bryman & 

Bell, 2015). Since this study was to necessitate some investigation within the case 

company, the inductive approach is preferred over the deductive approach, the reason 



 

 

 
 

 

22 

 

for which is due to it allows for a more explorative and unrestrained approach 

(Bryman & Bell, 2015).  

 

To analyse and process the data from the data collection phase, there are several 

different approaches of processing and analysing qualitative data. Since this case 

study hade an inductive approach, methods such as inductive thematic analysis or 

conventional content analysis were used in this stage. To enable the data analysis, 

there was transcribing work required to facilitate further content analysis (Säfsten & 

Gustavsson, 2020). When all data were in a state where it could begin to be 

processed, a thematic analysis allowed for sorting of data based on different themes, 

whilst a content analysis made it possible to code and categorise the qualitative data 

(Säfsten & Gustavsson, 2020). 

 

For this study the SOGI model (Societies, Organizations, Groups, and Individuals) 

have been utilized to decide the adequate unit of analysis (Bryman & Bell, 2015). 

Since this specific study has investigate the automation of two different warehouses 

belonging to the same case company, the chosen unit of analysis according to the 

SOGI model became group level (Bryman & Bell, 2015). The rationale behind this 

choice is due to that the two warehouses can be seen as different groups within the 

organization and hence the unit of analysis resulted in a group level focus. 

 

For the design of this case study, an embedded case study design was used since the 

study would not study the global nature of the focal company, as a holistic single case 

analysis would have done (Yin, 2003). Rather, since the focus of the study was upon 

how the two different warehouses of the focal company may be automated, an 

embedded case study design was utilized since it allowed for each of the two 

warehouses to be studied and assessed individually (Yin, 2003). This design therefore 

allows for each of the different warehouse's prerequisites and demands to be taken 

into consideration individually, even though they all were positioned in the same 

context as seen in figure 5. 

 



 

 

 
 

 

23 

 

 

Figure 5. A visualization of how the two embedded units of analysis fit into the setting 

of the case and the context. Note. Figure based on work by Yin (2003). 

 

 

 

According to Bryman & Bell (2015) the process of performing qualitative research 

consists of several different successive steps, these steps are shown in figure 6, below. 

These different steps can be organized into three different subgroups namely Current 

situation, Investigation & Recommendations. The first step Current situation is 

intended at specifying the research and its questions, but also at deciding upon where 

and how the necessary data will be collected for the qualitative research and the actual 

process of collecting it. The second step Investigation aim’s at analysing the retrieved 

data and see how it aligns with theory, but also whether there is a need for further data 

collection to understand the full picture of the case study, to answer the research 

questions. For the final step Recommendations, findings of the research were 

presented by answering the research questions of the case study. 

 



 

 

 
 

 

24 

 

 
Figure 6. Roadmap over a qualitative research study by Bryman & Bell (2015) Note. 

Figure based on work by Bryman & Bell (2015) 

 

 

 

3.2 Structure and motivation of the study 

 

The study began with a systematic literature review to get a greater understanding of 

previous research within the area of warehouse automation and WMS. After 

performing the literature review, the aim and research questions of the study were 

developed together with the case company. This was to ensure that the case study 

focused on the issues addressed by the company. Later, a more in-depth literature 

review was performed with the purpose of collecting information from research and 

previous cases where warehouse automation and WMS had been studied. By 

reviewing previous studies within the field, the study would be based on the latest 

research findings and will therefore also identify gaps in the previous research that 

this study can fulfil. Findings in the literature was put in context and compared with 

empirical data. The empirical data was collected at and in collaboration with the case 

company by performing interviews to get an overview of the company’s current 



 

 

 
 

 

25 

 

situation, but also to identify the requirements upon the warehouse operations and 

WMS that an introduction of automation posed. The empirical data from the 

warehouses were collected through interviews with staff from the case company and 

through observations at the warehouse in Sweden and Germany. Observation of the 

sites were to reflect the common requirements and capabilities of warehouses in the 

company.  

 

The As-Is company description and collection of empirical data did also include 

interviews with warehouse managers, operators, business departments, and IT. The 

interviews would result in a better understanding of the warehouse operations, 

features that are currently used in the WMS, and the requirements of the business 

department and operators. The hierarchical structure between these departments and 

how the requirements influence decisions in the downstream organization are 

illustrated in figure 7. The figure also shows the strategic level, tactical level, and 

operational level and the hierarchical position of the interviewed staff.  

 

After collecting system requirements and information concerning what an 

introduction of automated warehouse operations would pose upon the case company, 

the study made proposals regarding if the current WMS could handle these new 

requirements or if an alternative setup was required. The industrial relevance of the 

study was to facilitate for companies' that operate warehouse with dispersed 

requirements and capabilities to implement automated warehouse operations, by 

providing information concerning if their current WMS or an alternative setup is 

required to implement automated warehouse operations. 

 



 

 

 
 

 

26 

 

 
Figure 7. Hierarchical structure of departments in the interview process. The grey 

and red marked departments are those that were interviewed.  

   

3.3 Data collection 

 

The data collection of the study began with a literature review which consisted of two 

parts, one systematic literature review, and one in-depth literature review. The aim of 

the systematic literature review was to screen previous research and findings within 

the field of warehouse automation and WMS to gain a greater understanding of the 

two topics. This systematic literature review consisted of searching the database 

Scopus to better understand the research field and map out topics that could be 

relevant for the study. After this initial systematic literature review followed an in-

depth literature review, that was based on the findings from the aforementioned 

review. This in-depth literature review had a more structured approach to make the 

literature review replicable in the future by saving the utilized search queries. This in-

depth literature review is the theoretical foundation on which the thesis was 

performed, thus consisting of all relevant theoretical areas of the thesis. 

 

The second data collection phase following the closure of the first one was the 

interviews with relevant stakeholders within the case company. The sampling method 

was a purposive sampling, since it in a strategical way allows for a selection of 

stakeholders whose input is relevant for answering the research questions (Bryman & 

Bell, 2015). The chosen departments for this were warehouse, IT, and business since 



 

 

 
 

 

27 

 

they were seen as integral stakeholders in order to answer the research questions of 

the study. They were chosen in consultation with the industry supervisor since the 

supervisor has good knowledge concerning which stakeholders that would be affected 

by the scope of the project. When performing the interviews, a semi-structured 

approach was used since it allowed the respondent more margin when they express 

themselves (Bryman & Bell, 2015). 

 

According to Bryman & Bell (2015) it is hard to know the necessary sample size to 

reach theoretical saturation, but also keeping the sample size on a level that makes it 

feasible to analyse the gathered data deeply. For this study the chosen sample size was 

six individuals distributed evenly among the three chosen departments, where each 

individual held a position within the company that was relevant when answering the 

posed research questions. 

 

In these interviews, stakeholders from the case company’s warehouse, IT, and 

business department were of interest. Starting off with the business department, they 

were a stakeholder of interest since the industrial supervisor had pointed to them 

being involved in the implementation of warehouse automation. These were 

interviewed to find out their involvement and degree of governance over the 

implementation, but also how their decision processes concerning automation looked 

like and to what extent they utilized in-house expertise from warehouse and IT 

department concerning what to automate. 

 

Following the interviews with business came the interviews with IT department. 

These interviews were meant to probe the internal capabilities of the company to cater 

to the new system requirements developed by business departments. 

 

Lastly, interviews with the warehouse department were conducted to investigate how 

they currently work, but also to investigate what they think about the future 

warehouse automation. The warehouse department was interviewed due to the fact 

that they are the stakeholder that daily work with the current warehouse processes and 

are the ones ultimately affected by a future automation of warehouse operations. 

 

Besides the literature reviews and interviews, site visits to the warehouses in Sweden 

and Germany were performed. According to Lawrenz et al. (2003) it is important to 

identify the reason behind why a site visit is necessary. For this occasion, the reason 

behind the site visits was that they would be a part of the As-Is company description 

by providing insight into how they operated these two warehouses. 

 

Finally, internal company data in the form of reports and presentations was used to 

gain a greater understanding of thoughts and progression within the case company. 

Areas that could be of interest to this study were i.e., previous automation endeavours 

or strategic plans concerning automation. 

 



 

 

 
 

 

28 

 

 

3.4 Trustworthiness 

 

The scientific quality is based on validity and reliability of a study. To strengthen the 

quality, Säfsten and Gustavsson (2020) present trustworthiness as a method with 

extended criterions to measure the quality. These criterions are credibility, 

transferability, dependability, and confirmability and measures and clarifies the 

validity and reliability of a study. The validity shows that the performed research 

fulfils the aim and has a qualitative result. The reliability corresponds to be 

repeatability of the measurement and that the same results can be accomplished by 

repeating the research (Säfsten & Gustavsson, 2020).  

 

• Credibility: 

Validity can be divided into internal and external, where credibility defines the reports 

internal validity. This refers to the performed study, material to answer the research 

questions, and that no other factors are influencing the answer and result (Säfsten & 

Gustavsson, 2020). To full fill credibility in this case study, the research area was 

chosen together with the case company that suggested the research topic. For 

qualitative data, the authors visited two sites for observations and got a perception of 

the current state. Interviews have been performed with respondents from several 

departments and different positions within the company to secure valid knowledge 

and a wide collection of requirements. 

 

• Transferability: 

Transferability is the external validity of a study, which means a study's result should 

be valid for other stakeholders and companies on the market. To accomplish a high 

external validity, the study should be relevant for the scope of the topic and industry 

(Säfsten & Gustavsson, 2020). To accomplish transferability, the approach in this 

study has been a case study of a common process and with a literature review of 

previous research studies. This has ensured a good approach of the study and 

conclusions with strong reasonings from both the industry, case company, and 

fundamental literature of WMS and warehouse automation. The aim and research 

questions in the study are designed to have a relevant topic for the industry as a 

whole. By doing a case study of the warehouses, the real scenario approach has 

contributed to higher recognition and understanding of the study.  

 

• Dependability: 

Dependability represents the reports' reliability and that the research has a structured 

method that provides necessary information that ensures good ability for repeatability. 

This requires a careful review of literature, method, and participants. A study should 

also present the process of data collection and what has been made to minimize 

distorted information (Säfsten & Gustavsson, 2020). To ensure dependability in this 



 

 

 
 

 

29 

 

study the authors had an objective role of analysing the case company and ensure that 

participants had the required knowledge about the WMS and the current situation in 

the warehouse. The interviews and literature review have been clearly audited, 

reviewed, and structured through documentation.  

 

•  Confirmability: 

Confirmability ensures objective research and no dependability on perception or 

special occasion. Research and findings must follow a structural approach and be 

based on experience and collected information without interference of distorted or 

refined information. The information needs to be audited and reflected against the 

theoretical framework to determine confirmability (Säfsten & Gustavsson, 2020). To 

ensure confirmability in this study, the research is based on a structural framework 

with analysis of the empirical findings. Analysis of the case company and empirical 

findings have been structured and addressed in the study to ensure high 

confirmability. 

 

 

  



 

 

 
 

 

30 

 

4. Empirical Findings 
 

The empirical findings are structured under the titles “Automation” and “System 

requirements”. The rationale behind the partitioning were due to that a greater 

understanding of what the case company desired to automate were required to better 

understand their new system requirements. Their system requirements were then 

required to be able to understand the demands they would pose on their WMS as they 

introduce automated operations. Therefore, the empirical findings will be presented 

under these two titles for each interview henceforth. A deep review of the empirical 

findings from each of the interviewees can be viewed in Appendix D.  

 

4.1 As-Is description 

  
This is a summary of the empirical findings based on interviews and warehouse 

observation at the case company. The findings have been divided into automation and 

system requirements from interviews with the departments of warehouse, IT, and 

business. The observations have resulted in a good overview and knowledge of 

current operations and warehouse setup. 

 

Warehouse: 

 

• Automation: 

The two warehouses, NDC and EDC, of the case company differ in size and layout. 

The operations at NDC have only manual operations, whilst operations at the EDC 

are becoming automated. According to interviewee A, it is the fact that the EDC is 

building upon the push principle and larger throughput volumes that makes it viable 

to implement automated solutions in EDC. For the implementation of automation in 

EDC, interviewee B states that this is a part of their continuous improvement process 

by EDC since there is currently no tangible vision for automation efforts present 

within the company. The current automation in EDC is a conveyor system with 

several automated built-in functionalities such as weight control, closing process, and 

sorting to the designated carrier after placing the shipping label. Interview B state that 

EDCs vision for future automation is to automate operations upstream and 

downstream of the currently semi-automated conveyor system. For instance, this 

could be automated pallet building at the end of the conveyor belt or customer 

product customization before the conveyor begins. The future desired automation for 

NDC is to implement the conveyor system present at EDC, but according to 

interviewee A they currently lack the volumes to produce a ROI that motivates the 

implementation of such a system. Interviewee A also expresses how important it is for 

NDC to have a WMS with good uptime, reliability, and system response if they are to 

automate to not disrupt their operations.  

 



 

 

 
 

 

31 

 

• System Requirements: 

 

The two warehouses NDC and EDC are facing the same issues in the current system 

setup and they both have similar system requirements on a new WMS. Both NDC and 

EDC are using RF scanners in the picking process to receive information about orders 

from the WMS. The case company describes it as RF scanner, but the technology is a 

traditional scanning of barcodes or QR codes, henceforth the barcode and QR code 

scanning will be called RF scanning.  

 

Currently the RF scanner is a bottleneck because of delays when scanning items, 

which creates unnecessary waiting time for confirmation from the WMS. This causes 

frustration among operators and increases the risk of scanning and picking the wrong 

number of items. Therefore, both NDC and EDC have requirements for a system with 

improved up-time, response, and reliability. This would result in better response for 

RF scanners with decreased delays and better master data, which is important when 

implementing automation.  An example of good master data was when EDC 

implemented an automated process for operating the weight control, closing of boxes, 

and sorting before shipping. When they started the new process, they had issues with 

bad master data of the products, which affected the weight control. Therefore, master 

data is an important system requirement when implementing automation to have full 

control of the orders they ship and to ensure quality of the picking process.  

 

Compared to NDC, the EDC warehouse has higher capacity and handled volumes. 

Therefore, they are more involved in projects and in collaboration with other 

departments, and they will be one of the first distribution center’s (DC) that 

implement new changes. Hence, interviewee B states that when EDC is participating 

in projects, they have faced a problematic relationship to standardize processes in the 

company, and the interviewee states that they are especially in need of standardizing 

the sales process because this would minimize the complexity and errors of orders. 

Because complex orders result in a high variation of sales order layouts and risk 

incorrect orders to both NDC and EDC. This requires that the warehouses constantly 

need to adapt according to the sales department. The sensitivity to variation of orders 

in the warehouses is due to highly customer-oriented orders and the unique sales 

combinations. To cope with this, they need to handle a flexible logistic system or 

establish standardized processes for sales processes and other processes within the 

case company.  

 

 

  



 

 

 
 

 

32 

 

Business department: 

 

• Automation: 

 

During interview C, the interviewee told of their previous endeavour of implementing 

voice picking which failed due to lacking blueprints and documentation of 

distribution processes. From interview D, they expressed that before they automate 

anything it is important with good preparation and standardized processes in place. 

According to interviewee C, there are several obstacles that make the implementation 

of automation complex for the company. This is i.e., “freestyle” selling driving 

complexity of sales order layouts, too small volumes to have B2B and B2C in 

separate warehouses for optimal warehouse design, need for on-site automation 

expertise and that automating processes creates a bottleneck since they can’t just add 

more staff to increase the throughput of the warehouse during peak demands. Both 

interviewee C and D express that the way the case company's sales and marketing 

team currently operates drives complexity in the sales order layout ultimately 

affecting the warehouse design and layout. The reason for this is due to that they are 

customer centred and depend on their customer for further success. They hence 

express that implementing standardized processes for sales and marketing could be of 

interest since it would enable easier design criterions for the warehouse design and 

future automation. But on the other hand, this would result in less flexibility for sales 

and marketing to create customer specific solutions tailored after the consumers’ 

needs and preferences, thus reducing their current level of customer care. 

 

Interviewee D is responsible for creating a vision for automation within the case 

company but are then also responsible for seeing the projects through to see that they 

are standardized and scalable within the company. They express that it currently 

exists a vision, but the vision does yet not consist of warehouse specific details 

concerning how it’s to be realized. They further express that the larger DCs may be 

more self-governing in their automation since they have the necessary knowledge and 

skills in-house to perform such projects. 

 

• System Requirements: 

 

According to interviewee C, the sales organization’s flexibility mentioned above is an 

issue for the case company and especially for the warehouse operations. The 

interviewee requirements upon the system are that it should include a more stable 

sales process as well as efficient processes for managing the orders when transitioning 

to a potential future standardized and structured sales order placement process. 

 

A change such as the one stated above would improve the logistics operations, but 

also the complete value chain by offering an improved data flow, efficiency, and 



 

 

 
 

 

33 

 

reduced system complexity. Standardization was also seen as a necessity for the 

process of decision-making and projects since it reduced the level of complexity since 

fewer variation of inputs must be considered. In the current system setup, every large 

decision concerning the warehouses needs to be confirmed by headquarters according 

to interviewee C, which is a time consuming and unnecessary step according to the 

interviewee. Instead, the interviewee suggested that the company should have a global 

standardized framework for decision-making and improvement implementation so 

that decisions can be made locally to achieve a more rapid response.  

 

If a new WMS were to be implemented, interviewee C has a requirement for a single 

system that includes all modules, features, and system requirements that are required 

to operate the processes within the company. A system like this could according to the 

interviewee minimize the risk of creating silos in the system or between departments, 

since communication and data flow would be performed through one single 

companywide system. Interviewee D expressed that their system requirements upon a 

new “next level” WMS is that it can be used to support projects globally within the 

company. They also require that the system should be able to fulfil potentially new 

requirements and criteria’s that an implementation of automation in the processes for 

picking and outbound goods may produce.  

 

According to interviewee D, the vision and main requirements are aimed at increasing 

the level of automation in the warehouses. The establishment of new requirements are 

done by involving big Distribution Centers (DC), e.g., EDC. They involve the big 

DCs in the process since they have high volumes and data flows in their operations, 

hence creating the required ROI on potentially new investments. The new system 

requirements from Global Distribution (which interviewee D belong to) have focused 

on the integration of automation and the ERP system but have not yet included any 

technical requirements. The interviewee further expressed that there is currently no 

integration between the automated conveyor setup in EDC and their ERP system 

EnterpriseOne (E1), the setup is hence basically operating as a black box with just 

data being transferred back and forth. The interviewees also mentioned that they 

eventually plan to implement a Multi Carrier Parcel Management System (MCPMS). 

They currently consider they have the necessary information and requirements for 

MCPMS but need to select a time window for the implementation and connect it to 

the system. A system like MCPMS can, when implemented, improve the data flow 

within all departments and operations.  

 

 

IT department: 

 

• Automation: 

 



 

 

 
 

 

34 

 

In the interview with interviewee E, it was expressed how they are currently 

automating simple iterative operations in their ERP system by utilizing a built-in 

program called “Orchestrator Studios”. Further, interviewee E explained how Global 

Distribution (GD) is driving the automation of operations and not the other way 

around, and the issue with this is that the IT team is lacking knowledge about how the 

processes they program should be performed. Therefore, interviewee E thinks it’s 

important that when GD come with a new desire to automate an operation, they need 

to provide the IT team with detailed information concerning what they should 

produce in order to simplify the coding and testing process. Both interviewee E and F 

express that it is possible and easy to make changes to their current ERP setup since 

they have the required capabilities and knowledge in-house. If a new WMS setup 

were to be implemented, interviewee F expresses that a new WMS setup would not 

suit the company “straight out of the box” since they would need to perform extensive 

changes to tailor it after their requirements of a WMS setup.  

 

• System Requirements: 

 

When implementing automation, IT department’s system requirement is that the 

system should be able to handle the increased amount of data in a smooth and 

controlled manner. Interviewee E suggests having an ERP setup with a low amount of 

system integration infrastructure. To prioritize, the case company should, according to 

interviewee E, focus on system integration and automation of existing operations 

because the case company already has a good infrastructure, dataflow, and master 

data for these operations. If the case company would run a 3rd party system in parallel 

to their current ERP or WMS, the systems need to be continuously synced. If not 

synced, the systems will be unable to run in parallel and the data flow will be 

interrupted by delays.  

 

From the interview with interviewee F, the interviewee explains that the system is 

required to meet the requirements that Business and GD have identified and 

announced. However, since the requirements for the case company when developing a 

system is to have full ownership and good software safety, it can be difficult to have a 

3rd party system or implement other external supports. Instead, the case company and 

their IT team must develop their own systems and have control over all modifications 

to retain the knowledge in-house.  

 

Interviewee F adds that the system requirements are also dependent on the possibility 

to implement a new WMS and where they want to make a cut in the system when 

implementing automation. If they choose to make an early cut in the system, they will 

implement a new WMS that integrates early in the current system setup. With an early 

cut, the focus will be more on system development, which will require more in-house 

competence. Doing a late cut means that data will remain in the current system setup, 

but necessary data to manage automated processes is transferred to the external WMS 



 

 

 
 

 

35 

 

or automation. According to interviewee F, common system requirements for all 

departments, regardless of where they do a system cut, are the process for reporting 

within the systems, a good integration of systems, and communication.  

 

 

  



 

 

 
 

 

36 

 

4.2 Flow Charts 

 

During the site visits at NDC and EDC, the warehouse operations and their 

interactions with the ERP system were tracked to provide a flow chart of current 

operations. The reason behind the creation of the flow charts were to provide a good 

overview of the current warehouse operations, but also to be able to see the 

differences in operations between the two DCs. One important notation according to 

the case company is that they utilize a push principle to their different markets such as 

Germany and Sweden. This means that the case company do not use a push principle 

in their warehouses, it is rather that the warehouses such as NDC and EDC happens to 

be the locations of the regional markets the push items arrive at. 

 

 
Figure 8: Flow chart over NDC. 
 

The flow in the NDC as seen in figure 8 and appendix C contains several steps that 

are manually operated with help of RF scanners. The flow starts with receiving the 

inbound goods from EDC and then reallocation and sorting in the inbound area. In 

this step the inbound goods are scanned for a delivery verification to the WMS and 

are thereafter temporarily placed in the inbound area. The next process is putaway of 

items directly to pick-area or the bulk area. The bulk area is where pallets are stored 

before the items are send for replenishment to the pick-area. The pallets are sorted 

according to lot number and location, the pallet and the location are then scanned to 

send the new locations into the WMS. After the inbound goods and putaway starts the 

processes of handling orders, and the first process is the orders release. In the order 

release each order are manually checked before sending orders to warehouse 

operators that scans the orders pick slip that sends a signal to WMS that the order will 

be picked, and the operator then receive information in the RF scanner about what to 

pick. The next step is the pick and pack operation. In this operation every item is 

scanned to send confirmation to the WMS that the correct number of items are picked. 

In the same operation the boxes are filled with filling material, and the last step in this 

process is closing and placement of shipping label. The shipping label is scanned to 

send information to the WMS that the order is packed and ready to be shipped. The 



 

 

 
 

 

37 

 

last step is to build a pallet with boxes and then sending the pallets to outbound goods 

for further transportation.  

 

Replenishment of items to the pick area is performed during the not so busy hours or 

when all orders are packed and ready to be shipped. This process is performed by 

sending items from bulk area to the picking area for replenishment. The items that are 

picked for replenishment are scanned to update the WMS with the bulk’s location and 

then confirm the replenishment by scanning the new location in the pick area. 

 



 

 

 
 

 

38 

 

 
 

Figure 9: Flow chart over EDC 



 

 

 
 

 

39 

 

 

The flow chart over EDC as seen in figure 9 and appendix C illustrates the layout of 

the warehouse and the setup of current operations. The figure does not include any 

information concerning the operations interaction with the WMS through the RF 

scanners since these interactions are nearly the same as for NDC and have hence been 

avoided to reduce the complexity of the figure. 

 

As in the flow chart over NDC, each operation interacts with the WMS by RF 

scanners. Compared to NDC, EDC handles larger volumes and distributes to several 

markets and performs bulk resupply shipments to NDC and other EU DCs. Because 

of the big volumes and different flows, the layout of the warehouse is divided into 

several different parallelly operated flows. The flows of interest here were the flow 

for the German market, as well as the flow serving other European markets. Thus, 

leaving the sample warehouse out of the scope. What can be noted in figure 9 over the 

EDC, the warehouse flow to the German market is semi-automated whilst the other 

flows are completely manual. The reason behind this is that the warehouse is 

evaluating the automated conveyor belt through a pilot project for the warehouse 

operations of the German market. 

 

 

4.3 Summary tables 

The following two tables summarize the empirical findings from the interviews under 

the two areas of automation and system requirements. 

 

Table 1. Summary table for interview questions concerning automation. 

Findings from 

interviews: 

When does it occur?: Cause of 

occurrence: 

Effect of 

occurrence: 

Lack of 

standardization in 

sales and 

marketing 

operations 

When registering sales 

orders 

Highly 

individualised 

sales 

combinations & 

sales order layout 

Creating a 

complex setting 

with many 

different requests 

which automation 

are supposed to 

fulfil. 

Poor application 

feature information 

from business 

department to IT 

department 

When business submits 

information about desired 

functionalities in their 

ERP system for IT to 

code/build 

The information 

received are not 

as nuanced as IT 

would need to 

build business 

departments 

desired 

application 

IT department 

being unable to 

fulfil the request 

without further 

information from 

business 



 

 

 
 

 

40 

 

Suboptimal 

warehouse layout 

configuration 

When they provide B2B 

and B2C out of the same 

warehouses 

Too low volumes 

to run dedicated 

warehouses for 

B2B and B2C 

separately 

Suboptimal 

warehouse layout 

and future 

automation needs 

to fulfil both B2B 

and B2C 

warehouse tasks 

High peak loads in 

order handling 

If potential automation 

fails during peak loads 

Mechanical or 

system 

breakdown 

Unable to fulfil 

24H delivery to 

customers and 

creation of 

backlog 

Low ERP system 

setup knowledge 

amongst 

warehouse 

managers 

When warehouse 

managers look for 

compatibility between 

ERP system and their 

proposed 

improvements/automation  

Warehouse 

managers lacking 

ERP system setup 

knowledge 

Depending upon 

IT for help in 

creating their 

proposed solution 

and also having to 

wait in a que for 

help 

No shared tangible 

vision concerning 

automation for 

warehouses 

When warehouses plan for 

future improvements  

Business 

department has a 

vision for 

automation but 

not a tangible one 

for warehouses to 

use  

Warehouses has 

no common 

automation vision 

to guide them in 

their warehouse 

operation 

improvements i.e., 

automation  

Not financially 

viable to 

implement 

automation for all 

warehouses 

When the warehouse that 

want to implement 

automation as a warehouse 

improvement, handle to 

low volumes to create 

good ROI 

Not all 

warehouses are 

able to implement 

automated 

solutions due to 

the ROI of such 

an investment is 

to low due to low 

volumes in the 

warehouse 

Each warehouse 

handle varying 

volumes makes it 

impossible to roll 

out a generic 

automation vision 

to be followed by 

all warehouses, 

instead it has to be 

tailored after each 

warehouse 

 

 

  



 

 

 
 

 

41 

 

Table 2. Summary table for interview questions concerning system requirements. 

Findings from 

interview:   

When does it occur?: 

 

Cause of 

occurrence: 

Effect of 

occurrence: 

Important with good 

and correct master 

data for efficient 

automated 

operations 

When master data of a 

product does not 

correspond to the 

product’s actual 

attributes 

Wrong or old 

master data in the 

system 

Automated 

operations 

registering products 

as wrong or 

wrongfully packed, 

or automated 

operations coming 

to a standstill. 

Many different sales 

layouts and order 

registrations 

When sales register 

their orders into the 

system 

Not standardised 

sales processes 

Creates many 

different 

requirements upon 

the ERP and WMS 

to fulfil the logistic 

operations 

necessary to fulfil 

sales way of placing 

orders 

Decisions has to be 

approved by HQ 

When warehouses 

desire a quick change  

HQ having to 

approve their 

request for change 

Warehouses does 

not have access to a 

decentralized 

decision-making 

framework, making 

them unable to 

make quick changes 

themselves 

Lagging RF