[1]
EXAMENSARBETE INOM INDUSTRIELL EKONOMI, AVANCERAD NIVÅ, 30 HP STOCKHOLM, SVERIGE 2018
Developing a product costing model using Process-Based Cost Modeling
A case study of early stage cost estimation in a multinational agricultural cooperative
ALEXANDER ERIKSSON
KTH
SKOLAN FÖR INDUSTRIELL TEKNIK OCH MANAGEMENT
[2]
[3]
Developing a product costing model using Process-Based Cost Modeling
A case study of early stage cost estimation in a multinational agricultural cooperative
by
Alexander Eriksson
Master of Science Thesis TRITA-ITM-EX 2018:630 KTH Industrial Engineering and Management
Industrial Management SE-100 44 STOCKHOLM
[4]
Developing a product costing model using Process-Based Cost Modeling
A case study of early stage cost estimation in a multinational agricultural cooperative
av
Alexander Eriksson
Examensarbete TRITA-ITM-EX 2018:630 KTH Industriell teknik och management
Industriell ekonomi och organisation SE-100 44 STOCKHOLM
[5]
Master of Science Thesis TRITA-ITM-EX 2018:630
Developing a product costing model using Process- Based Cost Modeling
A case study of early stage cost estimation in a multinational agricultural cooperative
Alexander Eriksson
Approved Examiner
Andreas Feldmann
Supervisor
Bo Karlsson
Commissioner Contact person
Abstract
Product costing can be used to estimate potential future costs and revenues associated with a product. In the development of new products early cost estimates can be used to support decision making regarding which products are worth pursuing, and which production processes that are the most profitable. For a firm to make precise early cost estimates both technical and financial expertise is needed; however, in practice there is generally a gap between technology and cost. Process-Based Cost Modeling (PBCM) is a model developed to address this gap and generate costing estimates of higher precision. The model is especially developed for process production technologies. Although promising, PBCM is under researched and its applicability in new contexts are yet to be explored.
The purpose of this study was to explore the PBCM’s applicability in new context of process production. This was done through a case study at a multinational agricultural cooperative. The problematization presented by the Case Company was to make early cost estimation of the production process of a main product and its byproducts.
Furthermore, the Case Company wanted to compare alternative production designs and use of different raw materials in the production process. To create a product costing model that fully captures the contextual depth of the problem both qualitative and quantitative data was gathered from internal documents, a series of interviews, and observation of one of the sub-processes.
The findings of the study resulted in development of a batch costing model, a hybrid between continuous
operations and order costing systems. The batch costing proved to be dynamic and allowed comparison of different production and raw material alternatives. Furthermore, the PBCM methodology that resulted in the batch costing model was evident to give a deeper contextual understanding of the relationship between cost and production technology. For the Case Company, the outcome of the study highlighted key areas needing further investigation and process design features that lower operational costs. The results also provide recommendations how to increase the precision of the product costing models when more data are available. Finally, the academic outcome of the thesis provides trajectory in the further research on PBCM and gives new perspective on the use of batch costing in continuous operations.
Key Words: Process-based cost modeling, product costing, batch costing, full costing, continuous operations, process mapping, early stage product costing.
[6]
Examensarbete TRITA-ITM-EX 2018:630
Developing a product costing model using Process- Based Cost Modeling
A case study of early stage cost estimation in a multinational agricultural cooperative
Alexander Eriksson
Godkänt Examinator
Andreas Feldmann
Handledare
Bo Karlsson
Uppdragsgivare Kontaktperson
Sammanfattning
Produktkalkylering kan användas för att uppskatta framtida kostnader och intäkter associerade med en produkt.
Vid utveckling av nya produkter och produktionsprocess kan produktkalkylering således användas vid beslutsfattande i situationer där man ska välja vilka produkter som är värda att arbeta vidare med, och vid lönsamhetsberäkningar vid olika tillverkningsprocesser. För att företaget ska kunna göra precisa
kostnadsuppskattningar behövs både teknisk och ekonomisk expertis. Detta överses dock ofta i praktiken, vilket leder till en klyfta mellan teknik och kostnad. Processbaserad kostnadsmodellering, eller Process-Based Cost Modeling (PBCM), är en metod som har tagits fram för att överkomma denna klyfta, framförallt inom processproduktion. Även om modellen är lovande så saknas forskning på området, därav behöver PBCM:s applicerbarhet prövas i nya kontexter.
Syftet med denna studie var att undersöka PBCM:s applicerbarhet i en ny kontext inom processproduktion. Detta gjordes genom att genomföra en fallstudie på ett multinationellt lantbruksföretag som har verksamhet inom livsmedelproduktion. Fallföretags problematisering byggde på att de ville göra en tidig kostnadsbedömning på tillverkningsprocess som producerar en huvudprodukt och ett antal biprodukter. Tillverkningsprocessen är ännu inte utvecklad och företaget vill således jämföra produktionskostnader vid användning av olika råmaterial och tillverkningsalternativ. För att utveckla en lämplig produktkalkyl till företaget samlades både kvalitativa och kvantitativa data in genom interna dokument, en serie av intervjuer, samt genom observation av en av de underliggande tillverkningsprocesserna.
Studien resulterade i en hybridkalkyl som använder sig av både process- och orderkalkylering. Hybridkalkylen visade sig lämplig både för företagets produktionsteknologi, men framförallt tillät jämförelse mellan olika tillverkningsalternativ. Metodiken hos PBCM visade sig även användbar för att förstå hur kostnaden påverkas av produktionsteknologin. För fallföretaget påvisade resultaten områden som behöver undersökas ytterligare. Det ges även rekommendationer hur hybridkalkylen kan finslipas när företaget har mer data tillgängligt. När det kommer till det akademiska bidraget, så ger rapporten riktning för fortsatta forskningen på PBCM och ger nya perspektiv på hur hybridkalkylering kan användas i processproduktion.
Nyckelord: Process-based cost modeling, produktkalkylering, hybridkalkyl, processproduktion, orderkalkyl, processkalkyl, processkartläggning, tidiga kostnadsbedömningar.
[7]
1. INTRODUCTION... 11
1.1BACKGROUND ... 11
1.2PROBLEMATIZATION ... 12
1.3PURPOSE ... 12
1.4RESEARCH QUESTIONS ... 13
1.5CONTRIBUTION ... 13
1.6DELIMITATION ... 13
1.7DISPOSITION ... 14
2. METHOD ... 15
2.1CLASSIFICATION OF RESEARCH ... 15
2.2RESEARCH STRATEGY ... 17
2.3DATA COLLECTION METHODS ... 19
2.4ANALYSIS OF DATA ... 22
2.5QUALITY OF RESEARCH ... 23
2.6ETHICAL CONSIDERATIONS ... 25
3. THEORY ... 26
3.1PROCESS BASED COST MODELLING ... 26
3.2PROCESS MAPPING ... 29
3.3PRODUCT COSTING ... 34
4. THE CASE COMPANY ... 48
4.1RAW MATERIAL ... 48
4.2PRODUCTION ALTERNATIVES ... 49
4.3IMPORTANT TECHNICAL ASSUMPTIONS ... 50
5 RESULTS ... 51
5.1PROCESS MAPPING ... 51
5.2OPERATIONAL ... 58
5.3COSTING ... 68
6 DISCUSSION OF RESULTS ... 76
6.1PROCESS ... 76
6.2OPERATIONAL ... 78
6.3COSTING ... 80
6.4PROCESS BASED COST MODELING ... 84
6.5APPLICATION AND GENERALIZABILITY ... 85
7 CONCLUSION ... 86
7.1RESEARCH OBJECTIVE 1-PROCESS ... 86
7.2RESEARCH OBJECTIVE 2–OPERATIONAL ... 86
7.3RESEARCH OBJECTIVE 3–COSTING ... 86
7.4MAIN RESEARCH QUESTION –PBCM... 87
7.5LIMITATIONS AND FUTURE RESEARCH ... 87
REFERENCES ... 91
APPENDIX A: FOR CHAPTER 4 ... 94
[8]
List of Tables
Table 1: Classification of Research according to Collis and Hussey (2014) ... 16
Table 2: Summary of performed interviews... 20
Table 3: Summary of collected documents. ... 21
Table 4: Reasons for process mapping based on Damelio (2011), Olhager (2000) and Halseth (2008). .... 30
Table 5: Allocation and assignment of overhead cost to a product based on Ax et al, 2013; Olsson, 2012; Onoszko and Hallersbo 2017. ... 41
Table 6: Standardized absorption costing template Ax et al, 2013; Olsson, 2012. ... 41
Table 7: Examples of activities and their respective cost drivers based on Ax et al (2013), Engwall et al. (2014) and Olsson (2012). ... 43
Table 8: Central concepts of Contribution Costing based on Engwall et al., 2017; Ax et al., 2013. ... 44
Table 9: Contribution margin using step costing based on Ax et al. 2013. ... 46
Table 10: Batch costing based on Drury (1992). ... 47
Table 11: Content of Raw Material, total carbohydrate is the sum of starch and fibers, and arabinoxylan assumed at 48.6% of total carbohydrate. ... 48
Table 12: Important technical assumption ... 50
Table 13: Activities and Cost Elements in WSE. ... 53
Table 14: Activities and Cost Elements for Enzymatic Starch Extraction. ... 54
Table 15: Activities and Cost Elements in Protein Extraction. ... 55
Table 16: Activities and Cost Elements in arabinoxylan Extraction. ... 56
Table 17: Summary of resource requirements for respective sub-process and with their respective source of information. ... 60
Table 18: Resource Requirements for Water Starch Extraction. ... 61
Table 19: Resource requirements for the enzymatic starch extraction depending on the raw material used. ... 62
Table 20: Resource requirement for the protein extraction and further processing of protein depending on the input used. ... 64
Table 21: Resource requirement for the arabinoxylan extraction depending on the input used. ... 66
Table 22: Joint requirements with direct relationship to the production operations. ... 67
Table 23: Reoccurring cost elements and their factor cost. ... 69
Table 24: Cost of production for the water starch extraction. ... 70
Table 25: Contribution margin from Starch byproduct independently of raw material choice. ... 70
Table 26: Cost of Production in the enzymatic starch extraction depending on the raw material choice. 71 Table 27: Contribution margin from Starch Syrup byproduct depending on the raw material choice. ... 71
Table 28: Cost of production for the protein extraction. Above the CoP when using ESE wheat bran, and below the average CoP of the other production alternatives. ... 72
Table 29: Contribution margin from Protein byproduct in a best to worst case scenario, independently of the choice of input. ... 72
Table 30: Cost of arabinoxylan extraction depending on whether ESE Wheat bran is used, and whether ProE has been performed... 73
Table 31: Joint processing cost for production ... 74
Table 32: Total Cost of Production in a best-to-worst case scenario for all production alternatives... 74
Table 33: Unit cost of arabinoxylan in a best to worst case scenario depending on the production alternatives and unit price of byproducts. ... 75
[9]
Table 34: Yield of starch in the water extraction, depending on the raw material of choice. ... 94
Table 35: Remaining mass of the WIP after WSE and relative content of remaining components, depending on the raw material of choice. ... 94
Table 36: Yield of starch in the enzymatic extraction, depending on the raw material of choice... 94
Table 37: Remaining mass of the WIP after ESE and relative content of remaining components, depending on the raw material of choice. ... 95
Table 38: Protein yield depending on the raw material of choice and method for starch extraction. ... 95
Table 39: Remaining mass of the WIP after ProE and relative content of remaining components, depending on the raw material of choice and method for starch extraction. ... 95
Table 40: arabinoxylan yield depending on the raw material of choice, method for starch extraction, and whether the protein was extracted. Yield displayed in high molecular (HM), 1st and 2nd low molecular (LM) form, as well as the total yield. ... 96
List of figures
Figure 1: Sorting and analysis of data based on PBCM model by Field (2001; 2007) . ... 22Figure 2: Process Based Cost Modeling based on Field (2001; 2007). ... 26
Figure 3: Hierarchy of a manufacturing process based on Sandholm (2010). ... 29
Figure 4: Supplier-Customer template based on Sandholm (2001), Damelio (2011). ... 31
Figure 5: Relationship map based on Sandholm (2001), Damelio (2011). ... 32
Figure 6: Cross-Functional Process Map based on Damelio (2011). ... 32
Figure 7: Summary of flowchart symbols described by Damelio (2011), Sandholm (2001), Slack (2010), and Onoszko (2017). ... 33
Figure 8: Costing methods derived from the costing philosophy and production technology of the firm, based on Greve (2014) and Ax et al. (2013) with addition of batch costing from Drury (1992)... 35
Figure 9: Allocation of overhead costs in absorption costing based on Ax et al., 2013. ... 42
Figure 10: Allocation of costs in ABC based on Ax et al., 2013. ... 43
Figure 11: Production process alternatives in the production of arabinoxylan. ... 49
Figure 12: Flowchart Overview of the different production alternatives. ... 52
Figure 13: Flowchart visualizing WSE activities. ... 53
Figure 14: Flowchart of activities for Enzymatic Starch Extraction ... 54
Figure 15: Flowchart for Protein Extraction. ... 55
Figure 16: arabinoxylan extraction flowchart. ... 57
Figure 17: Mass of WIP after starch extraction and yields of starch byproduct and arabinoxylan products based on a yearly raw material input of 10 000 tons. ESE wheat bran highlighted. ... 59
Figure 18: Mass of WIP after starch respectively protein extraction to the left. Yields of starch and protein byproduct to the right, and yield of main product at the bottom. Based on a yearly raw material input of 10,000 tons. Path containing ESE wheat bran is highlighted. ... 59
Figure 19: Unit cost of arabinoxylan production depending on manufacturing alternatives. ... 81
Figure 20: Current and future batch costing system to produce arabinoxylan. ... 82
[10]
List of key terms
Arabinoxylan – A fiber found in plant cell walls, which is the main product of the production process.
Byproduct – Products that are inevitable produces when producing the main product, or products that have a substantially lower value than the main product.
Common Cost – Costs that are not affected by the choice of producing a product.
Continuous Operations – Operations where the production occurs in a continuous flow, as often in process production.
Contribution Factor – The amount of the cost element needed per product unit.
Cost Element – The cause of cost, such as an activity or a resource.
Cost Estimate – Product costing that are performed before the product has been produced.
Direct Cost – Costs that are directly attributable to a product costing object.
Factor Cost – The cost of resources.
Indirect Cost – Costs that are not directly attributable to a product costing object and must therefore be allocated to the product.
Joint Cost – Costs that occur at production level and benefit more than one product in process production.
Main Product – The product that the production process mainly seeks to produce.
Overhead Cost – All costs that are related to the product costing object but that are not direct.
Process Production – A production technology where the products are generally undistinguishable as individual units until they reach the end of the production process.
Product Costing – The calculations of earnings and/or spending related to an object, such as a product or service.
Production Technology – The type of technology used in the production process, including mass-, unit- and process production.
Resource Requirements – The amount of resource required to produce a specific amount of products.
Specific Cost – Costs that occur as a choice of producing a product.
Split-off point – The point in process production where products are split of from each other and can be distinguished as individual or be subject to further processing.
Work in progress (WIP) – The number of product units in production at a specific stage or time in a continuous operation.
[11]
1. Introduction
1.1 Background
Developing new products is an essential part in many firms to maintain profitability (Cooper, 2012). To get a realistic assessment whether these new products meets the profitability expectations the firms need to make early estimates of the costs associated with the product. An early cost estimation of the product serves as an important tool in assessing profitability and supports decision making in the future development of the product (Engwall et al., 2017).
Product costing centers around calculations of cost and/or revenues derived from a specific object, such as a product or service (Ax et al., 2013). Product costing can be used prospectively to estimate potential future costs and revenues associated with a product. These cost estimates can be used to support various decisions regarding a product. For new products a cost estimate can be used to support decisions regarding the following: which products to pursue, at which production volume, and through which production processes (Ibid, Engwall et al., 2017). However, the cost estimate needs to reach an adequate level of precision to base decision upon it (Al-Omiri and Drury, 2007).
Al-Omiri and Drury (2007) states that the precision of a cost estimate depends on the reliability of cost data and sophistication of the applied costing method. When doing early cost estimates the
opportunities to gather cost data are substantially different to when product costing is applied in retro perspective. Firstly, because cost data are non-existent for the new product. The reason for this is simple: the product has never been produced. Secondly, the characteristics of new products may change during their development process, making cost data inherently uncertain for new products (Davila 2000;
Kahn 2013; Cooper 2012). All in all, technical expertise is needed both to retrieve cost data from the production process design, but also to understand the implications of alterations in production design during the development of the product. Thus, cost data must be estimated from other sources to facilitate precise cost estimates. Field (2001; 2007) argues that cost data of a product can be estimated by looking at the product characteristics and analyzing the production process required to produce the product. However, in many industries the production process is complex and technical expertise is needed to understand the production process design and retrieve cost data from it.
At the same time the precision of cost estimates depends on the sophistication of the applied product costing model, which in turns depend on three things: firstly, how overhead costs are allocated to the product, secondly that all costs occurred by the product is included in the model, and thirdly that the costing method is understandable (Brierly, 2008). Thus, to incorporate the generated cost data and perform sophisticated costing model requires financial expertise. Different product costing methods are differently well suited depending on the firm and the technical context, and financial expertise is needed to apply the costing methods in a correct way (Greve, 2014; Ax et al., 2013). In literature the choice of costing method should depend on two contextual factors: costing philosophy of the firm and the production technology used (ibid). The costing philosophy is a conscious choice of the firm in how they choose to view and account for for example common costs, whereas the production technology used depends on the product characteristics and the circumstances needed to produce that product (ibid).
This ties back to the bilateral need of both technical and financial expertise in the performance of cost estimates.
[12]
A particular type of production technology is process production, or continuous operations production, where the products are produced through a set of tightly intervened activities, which makes the products indistinguishable as individuals until they reach the end of the production process (Drury, 1992). In general literature describes costing methods for continuous operations as simple and quite straight forward when the production process produces a single product, as all operation costs are directly attributable to the product (Fabozzi et al. 2008; Ax et al., 2013). However, when the production process produces several products, or byproducts, the costing models grows more complex and it’s harder to attribute product units with both joint and overhead costs (Bragg, 2012; Drury, 1992).
Similarly, the technical details of process production may also stretch from the very simple to the highly complex. Thus, process production technologies face a specific set of challenges both from a technical and financial perspective.
All in all, to assess future profitability of a product and support decision making in the development of the product and its production process there is a need to reach an adequate level of precision in the early cost estimates. However, to get a precise early cost estimate both technical and financial expertise is needed to extract reliable cost data from production process design and use this cost data in
sophisticated costing models. Furthermore, in the case of process production technologies the cost estimates face a specific set of technical- and financial challenges.
1.2 Problematization
In practice there is generally a gap between technical and financial understanding when making early cost estimates of a product. Field (2007) argues that this is because engineers tend to focus on the technical details of the process, and financial or business accountants tend to rely on models designed to calculate cost retrospectively. A potential solution to overcoming this gap is Process-Based Cost
Modeling (PBCM); a systematic approach that structures the technical aspects of production processes into resource requirements of operations. These resource requirements can thereafter be used as cost data in the firm’s product costing model. The principles of PBCM can be used for any production technology, but has been particularly used to accommodate for the challenges of making early cost estimates for process production technologies. It has proven promising for early cost estimation in production of electronic components (Bloch, 1992), metal components in the automotive industry (Field, 2007), bio refineries (Cheali et al, 2017; Tsagkari et al., 2016), and gasoline refining (Li et al., 2013). PBCM has also been used to estimate the cost consequences when altering the product- or production process characteristics, for example the change of raw materials in automotive part manufacturing (Field, 2007;
Johnson and Kirchain, 2009). However, as production processes and costs are highly context dependent, PBCM is yet to be tested in other fields and industries than the above presented. Although promising, PBCM’s applicability, potential advantages and disadvantages is under-researched.
1.3 Purpose
The purpose of this thesis is to investigate the applicability of Process Based Cost Modeling in a new context. The context being the early cost estimates of a process production that produces several products. This distinguishes it from previous cases of PBCM where generally the object of the cost calculation is a single product. Furthermore, the thesis seeks to reveal new insights and aspects of PBCM that are important to consider when trying to achieve adequate precision in early cost estimates.
[13]
1.4 Research Questions
The main research question (MRQ) in this thesis revolves around the difficulties in performing early cost estimates, and whether PBCM can be used to achieve higher levels of precision and thus support informed decision-making. This thesis is a single case study with no opportunities to verify the precision in retro perspective, therefore precision has to be viewed from a theoretical standpoint.
• MRQ – Does PBCM strengthen the underlying factors that affect precision of early cost estimates?
To reach a conclusion regarding the MRQ three research objectives (RO) connected to the specific context has been set up. The RO’s have been derived from PBCM and each correspond to the individual sections of the model; Process, Operational, and Financial.
• RO1 – Develop a process map for the production process
• RO2 – Determine resource requirements for the production process
• RO3 – Develop a product costing model and estimate the cost of the production process
1.5 Contribution
This thesis was performed at a multinational agricultural cooperative with operations in food production.
The thesis seeks to contribute both to the Case Company and to academia. At the company level the thesis will have methodological contribution as it presents a methodology for mapping the production process and determining resource requirements, furthermore a product costing model especially suited for the context was developed. The results of this thesis also highlight materials and activities that influence cost and to what degree. The identification of these provide basis for decision-making in the future product and process development for the Case Company.
The study may also have an academic contribution in the fields of PBCM, process mapping, and product costing. It has to be kept in mind that this is a single case study and the academical generalizability discussion is of importance. The single case design of this thesis can only provide analytical
generalizability on how the findings may be applicable in other contexts. Firstly, in the field of PBCM the findings indicate challenges in the performance of PBCM for this specific context, and especially indicates that cross-functional competencies are needed to extract reliable cost data from the production process design. Secondly, in the field of process mapping the findings indicate that different process mapping methods are differently well suited when it comes to identifying cost at different hierarchical levels of the firm. Finally, in the field of product costing the thesis contributes with a product costing model especially suited for process production with several products and alternative manufacturing choices.
Furthermore, the thesis highlights new insights and applicability of batch costing in comparison of different production process alternatives.
1.6 Delimitation
This thesis was facilitated by an opportunity given by the Case Company; thus, a delimitation is the priorities of the Case Company. The Case Company’s intention was to determine production cost factors of the production processes and estimate cost of the main product at an early stage. As no similar economic estimates has been done on other projects in the portfolio, the thesis is limited to a single case study. Thus, findings may be highly specific to the project itself. The time scope of the thesis also limits
[14]
the study from following the project until the process has been fully up-scaled. The precision of cost estimates can therefore not be supported or verified in a retro perspective. Instead the precision may be discussed from a theoretical perspective. Even though, single case study provides in depth knowledge of the PBCM’s applicable and important aspects for the specific case.
1.7 Disposition
The disposition of this thesis, and the content of each chapter, is summarized in the list below.
1. Introduction – This chapter provides background to the hardship of making early cost
estimations and highlights the academic gap in PBCM. Based on these points the purpose, main research question, and research objectives are stated. The contribution and limitations of the study are also stated.
2. Method – This chapter starts by classifying how the research question was addressed, and thereafter presents how the research was designed in practice. The chapter also presents how data were collected and analyzed, and the quality of the study is discussed.
3. Theory – The theory chapter present the theoretical field needed to answer the research question and objectives. Including the field of process mapping, product costing, and PBCM. The chapter also serves as a literature review by discussing the models’ applicability in different context.
4. Case Company – The Case Company is presented in more detail. The raw material is described, and the underlying technical assumptions in this thesis are presented.
5. Results and Analysis – This chapter presents the empirical findings divided into three sections based on the PBCM; including Process, Operational, and Costing. This chapter also includes the calculative assumptions and what this implies for the results.
6. Discussion – This chapter discusses the findings in relation to the academic field of process mapping, product costing, and PBCM. The chapter also highlights aspects important to consider in the further development of the production process and addresses the generalizability and applicability of the results in other settings.
7. Conclusion – The conclusion answers the research questions and research objectives.
Furthermore, the limitations of the thesis are stated, and areas for future research are concluded.
[15]
2. Method
In this chapter the research is classified, and the applied research design is depicted. Furthermore, the collection and analysis of data are described. In the last section of the chapter the quality of the research is discussed.
2.1 Classification of Research
This research is classified according to Collis and Hussey’s (2014) four key characteristics: purpose, process, logic, and outcome. These characteristics give the reader an overview to how the research question was addressed. Each characteristic is discussed in the paragraphs below, and a summary of the section is presented in Table 1.
2.1.1 Purpose
The purpose describes why the study was performed (Collis and Hussey, 2014). The overall purpose of this study is of both exploratory and explanatory character. It is exploratory in the sense that it investigates the PBCM in new contexts, and the implication that context has on the model. This was deemed appropriate as there is little research of the problem in this context, and it is performed to detect patterns and important dimensions (Collis and Hussy 2014; Blomkvist and Hallin, 2015).
Furthermore, Collis and Hussey (2014) argue that the scope of a master thesis is often limited to an exploratory purpose. Still, the research also strives to be explanatory to some degree, in the sense that the paper investigates a real-life problem. Thus, the cause for applying certain models and methods, and the implications of the result, give insight to certain variables that influence the models (Blomkvist and Hallin, 2015).
2.1.2 Process
The process describes in what way the results of the study were collected and analyzed (Collis and Hussey, 2014). When looking at the main research question in this report a qualitative approach is suitable; however, some of the underlying research objectives require quantitative answers. Therefore, both a qualitative and quantitative approach is adopted to understand the problem in its contextual depth. The study is not defined as either qualitative or quantitative but moves between the positivistic and interpretivist continuum depending on the data points that are to be collected or analyzed (ibid).
Combining these two is not just normal, but also advantageous as the approaches complements each other, and the combination is a powerful tool in building and refining theory (Collis and Hussey, 2015;
Shah and Corley, 2006).
2.1.3 Logic
The logic of the research describes whether the study originated from theory and then tested by
empirical evidence, known as deductive research. Or if the empirical evidence influenced and developed the theory, known as inductive research (Collis and Hussey, 2014). For this study a third method
combining these two was chosen, also referred to as the abductive approach. This approach is deemed suitable as it allows to shift between theory and empirics depending on the progress of the project. As it's likely that the case empirics changes the perspective on applicable theory for the problem when working with it, and vice versa (Blomkvist & Hallin, 2015). In the case of this study both technical and financial understanding of a highly specific context ware needed. Therefore, more of an inductive approach was adopted to collect data regarding the Case Company’s specific problem. Thereafter, more
[16]
of a deductive approach could be adopted to structurally collect the variables of importance to answer the research questions.
2.1.4 Outcome
The outcome of the research describes whether the study solves an applied problem or gives basic understanding for the solving of general problems (Collis and Hussey, 2014). This study is characterized by both applied and basic research aspects. As the whole, the purpose of the study is to explore and give new dimensions and insight into the systematics of performing cost estimates on early phase
manufacturing process developments. These insights can build and refine existing theory and are thus viewed as basic research (ibid). Still, the context in which the methods are investigated, and the findings of the study result in applied research for the Case Company. Therefore, the basic research foundation simultaneously solves the presented problem, and act as applied research for the Case Company. This bilateral outcome is ordinary for research in practice (ibid).
Table 1: Classification of Research according to Collis and Hussey (2014)
Key Charachteristics Description of Charachteristics
Charachtertistics of this research
Purpose
The purpose describes why the study was perfomedExploratory with explanatory influences
Process
The way the results of the study werecollected an analyzed Qualitative and Quantitative
Logic
Whether the study originates from theoryor empirical evidence. Abductive
Outcome
Whether the outcome of the studyresults in basic or applied knowledge Basic research with applied effect
Classification of Research
[17]
2.2 Research Strategy
This section motivates the research strategy applied in terms of paradigm and research design, whilst the upcoming sections describe how the data were collected and analyzed.
2.2.1 Paradigm
The main paradigm in social science is interpretivism, similarly this paper leans towards the interpretivist end of the paradigm continuum (Collis and Hussey, 2014). The overall purpose of the paper makes this a natural approach, as it aims to explore theory in new contexts and through that contributes to the further development of theory in the field. Still, parts of the results need to be viewed from a positivistic perspective.
Collis and Hussey (2014) list five philosophical assumptions that underpin the two main paradigms;
ontological, the nature of reality; epistemological, what is valid knowledge; axiological, the role of values;
rhetorical, the language of research; and methodological, the process of research.
In the ontological assumption the qualitative data needs to be viewed subjectively to answer the main research question and address the purpose. However, some of the qualitative results to answer research objectives must be more objectively. Thus, resulting in mainly interpretivist ontological assumption, with positivistic influences. Similarly, the same assumption is made in the epistemological assumption of what constitutes valid knowledge (Collis and Hussey, 2014).
In the axiological assumption it’s highly interpretivist, as the phenomena under study is dependent of the researcher studying it and the findings will have value laden and partially biased influences. As this paper was conducted as an opportunity by the Case Company, there is a risk of partial bias (Blomkvist and Hallin, 2015).
In the rhetorical assumption more of a positivism perspective is assumed for the quantitative results.
This is needed to analyze them from a common set of definitions and create understanding to other practitioners (Collis and Hussey, 2014). Whilst in the qualitative results and discussion the rhetoric’s are more personally influenced and thus lean toward the interpretivist end of the spectra (ibid).
In the methodological assumption the interpretivist paradigm is predominant as it partially adopts an inductive approach, uses emerging design throughout the process, new patterns and theories are developed during the proceeding of the project, and the accuracy and reliability are tested through verification (Collis and Hussey, 2014).
All in all, making the general paradigm being interpretivism with influences of positivism to address quantitative results and make these understandable for practitioners.
2.2.2 Research Design
This thesis was performed as an in-depth exploratory single case study. Collis and Hussey (2014) states that the research should be designed to support the purpose allow answering of the research question.
The purpose of this thesis is exploratory, with explanatory influences. The in-depth single case study is suitable for the exploratory purpose as it utilizes existing theory to explain what is happening (Vonn et al, 2002; Collis and Hussey, 2014). Furthermore, the research design allows for exploring of the phenomena of interest in its real-life context, Collis and Hussey (2014) argue that this is suitable when the research problem is not clearly defined and that it supports an exploratory purpose.
[18]
The purpose also strives to be explanatory. Generally multiple case studies are preferred over single case studies when having an explanatory purpose (Ibid; Vonn et al, 2002). However, Vonn et al (2002) argue that a best in class case does support an explanatory purpose. The Case Company is a well-established agricultural cooperative, with operations in food production, in several European countries and can thus be deemed a representable case for the industry. Therefore, although the study cannot give statistical generalizability through multiple cases, the explanatory purpose is supported by a best in class single case.
The research questions include a main question of qualitative character, and research objectives of both qualitative and quantitative characters. The in-depth case study is therefore suitable as the main
research question is not strictly yes or no, but rather based on soft- and hard data that give a contextual understanding of empirical data (Blomkvist & Hallin, 2015).
Potential Drawbacks of the Research Design
The study arose from the opportunity provided by the Case Company and is thus an opportunistic case study (Collis and Hussey, 2015). When performing opportunistic studies, it’s important to be open minded, yet critical, in the choice of purpose and research questions (Blomkvist and Hallin, 2014). Still, the results of a systematically and well performed opportunistic study may generate both theoretically interesting findings, and relevant applicable results for the Case Company (ibid). Further on, when working with a client in an opportunistic case there is a risk of biased thinking. To avoid partial bias that may arise from dealing with clients a divergent thinking is adopted, this helps keep a sober approach without converging too soon to the first solution that comes into mind (Blomkvist & Hallin, 2015).
A common limitation of a single case study is that the results may be hard to apply in a wider
perspective, therefore the generalizability discussion is of importance (Blomkvist and Hallin, 2015). This study does not strive to draw any statistical generalizability, which is impossible from a single case (ibid).
Instead, the research may lead to analytic generalizability through the representability of the case and the quality of the research performed (ibid). The case is deemed representable in an organizational and industrial perspective, as the Case Company is well-established in the Food and Agricultural business. To create analytical generalizability Blomkvist and Hallin (2015) argue that the researcher needs to discuss its applicability in other contexts and give the reader enough context for the reader to self be able to assess the reasoning.
There are alternative approaches to address the research question that may help overcome some of the disadvantages of single case studies. Still, these come with their own limits as well. The use of a multiple case studies could guard against biases, augment external validity, and support theory building and analysis of important variables (Vonn et al, 2002). However, this would require extra time and resource consumption and would provide less in-depth knowledge of the specific context. Longitudinal studies, following the cost estimations over time, could also provide verifications of the appropriateness and accuracy of estimations after operational implementation (ibid). However, this would also require more time than available for this project.
[19]
2.3 Data Collection Methods
In the early stages of the report there was a great need for contextualization by collecting both qualitative data from primary sources, and quantitative data from secondary sources. As the research problem originated from a practical problematization, rather than from literature, this contextualization could provide aim for valid data collection throughout the rest of the study (Collis and Hussey, 2014). The contextualization indicated that there were few persons with knowledge of the phenomena. This
resulted in snow ball sampling to collect qualitative data from employees with knowledge of the subject, and natural sampling in collection of quantitative data regarding the processes.
Blomkvist and Hallin (2015) state that the five most common methods for collecting data to a master thesis are: collection of documents, interviewees, focus groups, observations, and surveys. Due to the complexity of the technical problem, and the limited amount of people knowledgeable, surveys were not seen as an option. Instead mainly collection of documents, interviews and observations where
performed. Secondary data from documents were deemed of high validity to the research questions, and they formed the foundation of the research. To verify, complement, and explicate data found in
documents interviewees were shown to be a powerful tool.
2.3.1 Interviews
Interviews were mainly used during two stages of the report, the early stage to contextualize and clarify the research problem and to understand the manufacturing process. Whilst in the later stages interviews were mainly used to verify, complement and explicate data.
At the early stage mainly unstructured and semi-structured interviews were used, as these are suitable in exploring the subject (Blomkvist and Hallin, 2015). In these interviews open ended questions were used to gather broad information about the context, hypothetical questions were used to encourage broad thinking of the processes and costing evaluations, and summary questions were used to validate answers and avoid ambiguity (Collis and Hussey, 2014). Further on, probes were shown suitable to get clarity and new dimensions of the problems (ibid). During these early stage interviews there was a natural restrain to the sample, as there were very few people knowledgeable of the new product project. Only
employees at the central Research and Development (R&D) department were interviewed, as they were the only employees that could give valid primary data on the technical aspects of the research
objectives.
Whilst in the later stages of the writing of this paper more structured interviews were used. At this stage a deeper understanding of the context and familiarity to processes and costing evaluations had been achieved, and the main goal was thus to confirm, validate, complement and explicate early findings.
Therefore, mainly closed questions were used to gain factual information, and summary questions to further validate findings (Collis and Hussey, 2014). As the interviews were used to give factual information regarding different resource requirements of the production process, questions were individualized for each interviewee. Similarly as in the early stage interviews, there was a natural restrain to the interview samples regarding the technical aspects. To collect data for the operational and financial aspects of the study a snowballing approach had to be adopted to find valid interviewees. This snow balling approach proved time consumed and unfortunately resulted in insufficient data regarding overhead, packaging, storage and transport.
[20]
The interviews performed is numbered and explicated regarding their relevance to research questions, position of the interviewee, and type of interview in Table 2.
Table 2: Summary of performed interviews.
2.3.2 Documents
Document review were a major part in the collection of data in this study. There were three main type of documents collected concerning the following topics: the manufacturing processes, the context and business strategy, and operational and cost information. To protect the integrity of the Case Company the documents have been anonymized. Still, the data are deemed to be of high reliability as they originate from well-established universities and consultancy firms. Most of the documents contain secondary quantitative data, therefore interviews were used to confirm their validity and applicability with primary qualitative data. The documents are numbered and explicated regarding their connection to the research question and topic in Table 3. The documents 8 and 9 includes a bundle of multiple data sheet of different processing equipment and material resources.
Interview Interviewee(s) Topic Type Connection to
Research Question
1 R&D Project Leader Introduction to the problem Semi-structured RO1
2 Scientific Project manager and
R&D Project Leader Project kick off Semi-structured General
3 R&D Project Leader Introduction to processes Semi-structured RO1
4 R&D Innovation and Business
Developer Context of problem Semi-structured MRQ, RO3
5 R&D Project leader and Product
Developer in affiliated company Business opportunities Unstructured,
ethnographic interviews All
6 R&D Project Leader Project outlook and upscaling Semi-structured RO2
7 R&D Group Director Process, operational, and costing
methodics, product price etc. Semi-structured RO1,2,3
8 Project Leader, production Cost of equipment Structured, by mail RO3
9 Process Engineer Costs of materials Structured, by mail RO3
10 R&D Group Director Costs of materials Structured, by mail RO3
11 R&D Project Leader Verification of findings Structured All
Ea rl y St ag e La te S ta ge
Interviews
[21]
Table 3: Summary of collected documents.
2.3.3 Observations
Blomkvist and Hallin (2015) argue that observations are good for an exploratory purpose; however, this thesis seeks to estimate costs in prospect. Therefore, typical observation methods used in management research were not possible, simply because there are no operations to observe. Instead, in the process of writing this paper there was the opportunity to test of on the production steps, the starch extraction, at a smaller scale during a 3-day visit to one of the Case Company’s manufacturing plants. In essence, this is classified as an observer as participant study. The observations were performed by performing the starch extraction according to Document 1, but at larger scale. Although not fully representative to the
industrial scale process, the observations allowed insight in design features of the processes (Collis and Hussey, 2014). The observations also led to several spontaneous ethnographic interviews with the R&D project leader as well as a product developer at an affiliated company (Interview 5, Table 2). The affiliated company is a stakeholder in the project. Field notes were taken throughout the observation phase concerning the process design, and business opportunities for the Case Company and the affiliated company. When noting the process characteristics, first order constructs were used. Whilst for business opportunities, first- and second order constructs were used.
Document(s) Documents Topic Connection to Research
Question
1 Research report 1 Lab scale process WSE and ESE RP1
2 Research report 2 Lab scale process ProE RP1
3 Research report 3 Lab scale process AxE RP1
4 Annual report Strategy and vision Context
5 Internal documents 1 Business opportunities Context and RP3
6 Internal documents 2 Market overview Context and RP3
7 Internal documents 3 Benchmarking Context
8 Data sheets, equipment Equipment running resources RP2, 3
9 Data sheets, enzymes and
microbes Material resource consumption RP2, 3
Manufacturing ProcessOperational and Cost informationContext and Business Strategy
Documents
[22]
2.4 Analysis of Data
The analysis of data consists of two parts. Firstly, a thematic approach in answering the research
objectives separately. Secondly, the findings from the individual research objectives form the discussion and answer to the main research question.
Due to the diverse nature of the research objectives, the collected data were reduced by sorting
empirical material into categories. This allows for a more comprehensive amount of data to be analyzed (Blomkvist and Hallin (2015). In accordance to recommendations by Collis and Hussey (2015), the sorting is done based on the theoretical framework. This results in the sorting into three categories: Process Mapping, Operational, and Costing. This approach attributes for the major data reduction in the analysis.
As this study was done in an abductive matter, collection of qualitative data cannot be separated from the analysis (Collis and Hussey, 2015). Therefore, in each of these the analysis has been performed by moving back and forth between theory and empirics to result in the final analysis. The approach is visualized in Figure 1:
Figure 1: Sorting and analysis of data based on PBCM model by Field (2001; 2007) .
The answer to the main research question is a natural result of the analysis of the research objectives.
Therefore, the results are structured in the linear manner of the PBCM. This allows the reader to follow the chronological thought process of the author and give a comprehensive understanding in the answering of the main research question.
[23]
2.5 Quality of Research
In this section the quality of this study is discussed based on its validity and reliability. The validity is divided into construct, internal, and external validity in accordance to Gibbert (2008) and Gibbert and Ruigrok (2010). These are the main sources in the discussion of quality. In addition to that Voss et al (2002), Collis and Hussey (2014), and Blomkvist and Hallin (2015) are used as influence giving new perspective and practical insights for the quality concepts implications in the field of operations management.
2.5.1 Construct Validity
The construct validity is to what extent the study investigates what it claims to investigate (Gibbert, 2008). Collis and Hussey (2014) argue that construct validity is of high importance for business research as there may be several variables contributing to the results. Thus, the researchers must be aware of what is being investigated during the data collection phase (Voss et al, 2002). The concepts used to enhance construct validity during data collection are: establishing a clear chain of evidence, and data triangulation.
Clear chain of evidence is the establishment of a comprehensible chain of activities that took the
researcher from the research question to the conclusion (Gibbert and Ruigrok, 2010). For this report the chain of evidence is established by a consistent outlining of the report in line with the data collection procedures. The linear approach of the PBCM supports the structure of the theory, results, discussion and conclusion section.
Data triangulation could be achieved as data were collected from multiple sources, in multiple forms.
Firstly, eleven unstructured to structured interviews were performed with six different employees connected to the organizational problem. Through this approach many perspectives on the same research problem could be found. Secondly, during the case study there was access to a number of internal documents regarding the context of the phenomena. Therefore, a deep understanding of the case settings could be achieved. Thirdly, during the data collection it was possible to perform direct observations of a separate process step. These gave insight to the nature of the raw material and the technical requirements needed to process it. However, as the Case Company where in the early stages of developing the process only employees at research and development were knowledgeable of the
subject. Thus, the validity of data could have been enhanced if there were contacts available to employees working specifically with process engineering and costing aspects of the project.
2.5.2 Internal Validity
The second level of validity is the internal validity and refers to what degree causal relationship between variable and results can be established (Gibbert, 2008). In contrast to construct validity, the internal validity is conceptualized in the data analysis phase (Voss et al, 2002). The strategies to ensure internal validity are formulating clear research frameworks, pattern matching, and theory triangulation.
The abductive approach in this study allowed for clear formulating of the research framework. Firstly, in the early phases of the project the purpose and research questions were continuously adapted to the empirical context, thus strengthening the validity of the research (Blomkvist & Hallin, 2015). Secondly, with a defined purpose, and variables that are to be measured, a clear research framework could be developed with the basis in theory. This allowed for the demonstration of relevant variables that contributed to the conclusion (Gibbert, 2008).
[24]
Pattern matching is achieved by matching the Case Company’s problematization with that of literature (Gibbert, 2008). More precisely the hardship in evaluating production cost at an early stage was matched with the studies of Bloch (1992), Field (2007), Cheali et al (2015), Tsagkari et al (2016), Li et al (2013) and Johnson and Kirchain (2009). Expected pattern matching could not be achieved to the same extent, as this would require either a longitudinal or multiple case study to confirm findings (Gibbert, 2008; Vonn et al 2002).
Theory triangulation, as opposed to data triangulation referred to in construct validity, is the use of multiple literature sources. This has been achieved by conducting an extensive literature review and adopting a critical perspective towards theory. The theory chapter of this report includes a fluent
discussion of the theories applicability and practical implications with perspective from multiple sources.
2.5.3 External Validity
The final level of validity is the external validity, also known as generalizability. In interpretivist studies this means to what extent the theories used to study the phenomena can be generalized from its single setting to other settings (Collis and Hussey, 2014; Gibbert, 2008). This is known as analytical
generalizability. Gibbert (2008) states three ways to generate analytical generalizability: cross case analysis, rationale for case selection, and context details of the case.
In this paper a single case study was performed. Therefore, the opportunity of generalization through cross case studies could not be achieved. Gibbert (2008) argues that cross case analysis of 4-10 cases can be a good starting point for theory building purpose. Although this report strives to support theory building, it mainly addresses an exploratory purpose. Thus, this report can be a contributor to continued theory building rather than the driver of theory building. Further on, the time and resources required to do a multiple or nested case study exceed what is possible in the extent of this study. Still the rationale of this study supports generalizability as the Case Company is a well-established agricultural cooperative, with real-life problems in their food production operations. All in all, the research objectives and
research questions stem from a representable case setting, that may be like other firm settings within the industry.
The context details of the case settings have been depicted as carefully as possible to give the reader a comprehensive understanding of the case settings. According to Collis and Hussey (2014) this is required to be able to generalize the conclusion of the study; however, upon request of the Case Company the report is anonymized and sharing of certain data confidential. Hindering this paper from reporting the full extent of the case settings. Still this does not discharge the possibility of generalization, as this is a common scenario for case studies (Collis and Hussey, 2014).
2.5.4 Reliability
Reliability is the absence of random errors, which in turns makes it the possibility for other researchers to reach the same results when performing the study with the same methods (Gibbert, 2008). When reliability is high the incidence of random errors is low, and vice versa (ibid). For positivistic research the repeatability of a study is of high importance; however, in interpretivist research it is at many times impossible to provide full repeatability. This study is thus more concerned with strengthening the authenticity of the findings (Collis and Hussey, 2014). This is done by establishment of a case study protocols to enhance reliability. These documents support the transparency of the research and give rise to repeatability (Gibbert, 2008). Table 2 and 3 does not only include the performed interviews and
[25]
collected documents, but also indicate the chronological order in which they were collected and analyzed. Thus, serving as a study protocol.
A case study database could further enhance reliability. Such a database should include all the
documents, notes, and narratives collected during the study (Gibbert, 2008). For this study many of the collected documents are classified and are not possible to share. Several of the unstructured, and semi- structured interviews were not recorded. Still, notes have been taken and included throughout the collection process. Still, all these documents and notes are saved and attainable at request of the Case Company.
Further on, the reliability of the findings was enhanced by as objectively as possible constructing and describing the context, research design and methods of collecting data (Gibbert, 2008).
2.6 Ethical Considerations
In accordance to the Swedish Research Society there are four essential ethical requirements for academic research: information, consent, confidentiality, and good use requirements. (Blomkvist &
Hallin, 2015) Upon agreement with the client both the information and consent requirements are filled;
however, the client requested confidentiality of the report through anonymization of sensitive
information. Therefore, the Case Company and interviewees are not mentioned by their real-life name, documents are not cited regarding their author(s) or title, and some information regarding materials in the production are not disclosed. Thus, good use requirements are restricted to only using the collected data for publishing an anonymized report as a master thesis, and an open report for the Case Company.
[26]
3. Theory
The theory chapter include the theoretical field that have been used to address the problem, and fields that have generated new perspectives and insights of the problem. The chapter is structured in sections according to the research areas of: Process Based Cost Modeling, Process Mapping and Product Costing.
The theories are discussed in terms of applicability and their advantages in different settings.
3.1 Process Based Cost Modelling
As the name implies Process-Based Cost Modelling (PBCM) is a fusion of cost and process models (Bloch, 1992). The model was developed as a response to the gap between technical- and financial
understanding in practice. Practitioners have noted that this gap has resulted in difficulties when doing early cost estimates, and when estimating the cost consequences of production process alterations (Field, 2007). Field (2001) states that “[…] cost of a product is a function of the process used to make it, at the same time, the cost of operating a process is a function of the design of the product being made”.
Moreover, Field (2001) argues that process engineers are generally concerned with the fine tuning and optimization of physical parameters to enhance both product and process performance; however, these adjustments also affect production cost. Similarly, product costing methods are generally focused on calculating and enhancing cost performance of existing processes, where cost data can be attained from analyzing the production process in retrospective. On the other hand, when doing early cost estimates the cost data have to be derived directly from the production process design. Therefore, financial and/or business accountants are forced to work directly with the physical analog of the cost, rather than cost data from operations which they are more familiar with (ibid). Thus, resulting in a gap between technical- and financial understanding despite them having a symbiotic relation.
PBCM is a sequential approach to address and bridge the gap between the technology and cost in a production process (Field, 2007). The foundation model was first described in 1987 and 1988 by Busch, respectively Busch and Field, and includes three steps covering a technical process model, a production operations model, and a financial accounting model (Field, 2001). Although the authors refer to the last step as a financial model, the goal of the model is to determine production cost, which is essentially the same as a product costing model. Therefore, when referring to the financial step of the PBCM this thesis refers to the application of product costing on the findings from the process and operational step. The PBCM sequential approach is depicted in Figure 2.
Figure 2: Process Based Cost Modeling based on Field (2001; 2007).
