Time Driven Activity Based Costing When theory and reality collide: A pilot study of

(1)

Time Driven Activity Based Costing

When theory and reality collide: A pilot study of

TDABC in a financial service company

Bachelor’s Thesis 15 hp

Department of Business Studies

Uppsala University

Fall Semester of 2019

Date of Submission: 2020-01-17

Ann Wilhelmsson

Lourdes Zemariam Ermias

(2)

Preface

By working with cost allocation in our thesis, we have gotten the privilege of working with an interesting and important part of management and control. Further, the knowledge gained concerning cost allocation has made this period incredibly fun and rewarding. Through writing this thesis, we have gotten a growing understanding of the weight and importance of effective communication and collaboration. But mostly, we have gotten the understanding of how valuable and informative an accurate cost allocation can be to organizations.

First and foremost, we would like to thank our mentor Jan Lindvall for the continuous support, guidance and positivity throughout the process. Further, we would like to thank Alfex for allowing us to collaborate with them in this study, and all the involved departments and people in Alfex who have contributed to our research through support, interviews or otherwise. As a holistic understanding of the involved departments have been necessary, access to company-wide personnel has been crucial.

_____________________________________ Lourdes Zemariam Ermias

Date:

_____________________________________ Ann Wilhelmsson

(3)

Abstract

The value of cost allocation comes from its initial purpose; decision support. In other words, cost allocation is considered a vital part of management, as it generates valuable information concerning efficiency and profitability. By applying Time Driven Activity Based Costing (TDABC) in a financial service company, this pilot study aims to learn from the consequences of the application, and discuss the lessons learned. The application resulted in a two-step allocation using Traditional Cost Allocation in the first step and TDABC in the final step, where the overhead cost of four support departments were allocated down to products. To build the model, interviews were conducted with personnel and internal documents were used. The application's most important lessons are the difficulty of identifying and measuring activities, the model’s requirement of high-quality data and the complexity of the capacity measures.

Keywords: Time Driven Activity Based Costing, Cost Allocation, Traditional Cost

(4)

Abstract

Kostnadsallokerings initiala värde grundar i att ge viktig information om lönsamhet och effektivitet, och är därav en viktig del av det beslutsunderlag som används i företag. Genom att applicera Time Driven Activity Based Costing (TDABC) i ett finansiellt serviceföretag ämnar denna pilotstudie att utforska konsekvenserna av applikationen, för att sedan diskutera lärdomarna. Applikationen resulterade i en tvåstegsallokering då Traditionell kostnadsallokering användes i det första steget, följt av TDABC i det andra steget. På så vis allokerades kostnaderna från stödfunktionerna i ett företag ner till produktnivå. För att bygga modellen hölls intervjuer med personal och interna dokument användes. Applikationens främsta lärdomar resulterade i: svårigheten i att definiera och mäta aktiviteter, modellens krav på hög-kvalitativ data och komplexiteten av att beräkna, samt analysera kapacitetsmåtten.

(5)

1. Background

Does cost allocation really matter? Looking at economic theory, allocated costs have already occurred and thus are sunk (Hong, Huang and Zhao, 2019). However, within management accounting, cost allocation is seen as an important tool, allowing companies to gain important insights concerning profitability and efficiency (Kaplan and Cooper, 1998; Ray and Goldmanis, 2012). Regardless of economic theory’s view on sunk costs, different cost allocation models have received a lot of attention in both academia and practice (Ringelstein, 2018; Kaplan and Anderson, 2003). Furthermore, as cost allocation can be linked directly to profitability, it is a great part of the basis of decisions taken in management (Kaplan and Cooper, 1998; Horngren, 2004).

Cost allocation is the process of identifying and assigning costs to cost objects, which usually is a department, product or customer. The process is practiced internally within companies and can be described as a management tool used to gain information and steer (Kaplan and Cooper, 1998). In cost allocation two main types of costs can be identified, direct costs and indirect (overhead) costs (Ax and Ask, 1995). Direct costs are directly tied to a cost object, whereas overhead costs are collected in a cost post, and thereafter allocated to cost objects. The decision of treating costs as direct or indirect is made in the process of accounting within companies (Ibid.). In order to allocate overhead costs, practitioners need methods that allocate these representatively to what cost is caused by the cost object (Horngren, 2004).

In our current economic climate, characterized by recurrent economic crises, information about company performance can be considered more relevant than ever to managers (Maryskaa and Doucek, 2015).For cost allocation to be informative, accuracy is essential as it results in more precise estimations of what costs are generated by what cost objects (Kaplan and Cooper, 1998). Simultaneously, preciseness requires a more complex and time-consuming cost allocation model, which results in higher expenses related to implementing, maintaining and updating cost allocation systems (Kaplan and Anderson, 2003). Still, due to increasing overhead costs in companies related to IT and marketing (Ax and Ask, 1995), efficient methods for allocating the costs are needed. Because of this paradox, one of the greatest challenges in cost allocation is the trade-off between accuracy and cost (Kaplan and Cooper, 1998).

Ray and Goldmanis (2012) describe efficient cost allocation as reliant on the reflection of a company's underlying costs. The reflection could be compared to what Horngren (2004) describes as a cause and effect relation in cost allocation. The past century, this issue has been central within the evolution of management accounting, and greater emphasis has been put on the cause and effect relationship (Ibid.). This can be seen in the evolution of cost allocation models such as Activity Based Costing (ABC), which compared to prior models has more refined ways of handling overhead costs. The latest refinement of ABC, Time Driven Activity

(8)

Based Costing (TDABC) was introduced in 2003 by Kaplan and Anderson. TDABC captures the accuracy and cost trade-off, as it alike ABC has refined ways of handling overhead costs. However, with time as a cost driver throughout, the model is thought to be easier to implement, maintain and update than its predecessor (Kaplan and Anderson, 2003).

TDABC has been implemented and tested in different settings including hospitality and banking (Järvinen and Väätäjä, 2018; Rahman, Ali, Hussein, 2019). However, earlier research suggests that more empirical testing is needed for the positive outcomes of TDABC to be established (Namazi, 2016). This study aims to target this issue, through applying TDABC in a financial service company. The company, referred to as Alfex in the study, is a subsidiary of a larger industry leading European company. The setting of the application in a service company seems in a larger context suitable as the force of servicification in society over recent years has enlarged the amount of service companies substantially (Jal Mystry, 2019). Moreover, due to the large amount of overhead costs composed by the support functions in Alfex, they as many other modern companies are in need of an efficient cost allocation. Lastly, as a large part of the overhead costs are composed of salaries for personnel, the variable time is vital, as it is one of the main bases for the magnitude of overhead costs. As time is argued to be an important factor explaining costs, we hope to see that TDABC may be able to explain the cause and effect relation by costs generated in Alfex efficiently.

2. Purpose and research question

For this pilot study, Alfex wished to gain more theoretical knowledge concerning cost allocation and obtain more specific information concerning costs on a product level. The pilot study aims to provide them with greater knowledge, but also to contribute to academia within management accounting through discussing the lessons learned through applying TDABC in practice. The application’s aim is therefore to obtain a greater understanding of the consequences the model has in practice. Thus, the research question being answered is: “What are the lessons learned from an application of TDABC in a financial service company?”

(9)

3. Literature overview

The following section will provide an overview of the cost allocation models: Traditional cost allocation, ABC and TDABC, followed by a pedagogical review of TDABC.

3.1 Traditional cost allocation

Traditional cost allocation, also referred to as conventional cost allocation, was first introduced in manufacturing companies, the predominant type of business at the time in the 1870s (Emblemsvag, 2008 in Rasiah, 2011). Traditional cost allocation uses only a few variables to allocate overhead costs, examples of such variables are volume, size and cost of direct labour. The more of the variable the product demands, the larger part of the overhead cost it bears. The model has received critique as it is a simplification and therefore lacks accuracy. An example of this is how one of the most frequently used variables is direct labour connected to the product, Christmann and Jórasz (1993, p. 571) points out that in capital intensive companies the overhead costs can be several 1000% of direct labour. The example shows a flaw in the methods ability to allocate costs when overhead costs are high, due to being too generalizing and simplistic.

3.2 Activity based costing (ABC)

In the 1980s the model ABC was developed by practitioners, and then introduced in several Harvard Business School cases and articles (Siguenza-Guzman et al, 2013; Kaplan and Anderson, 2003). ABC managed to overcome critical deficiencies that Traditional cost allocation had, e.g. causing discrepancies in the allocation (Kaplan and Andersson, 2007) when overhead costs are not proportional to production volumes. The ABC model identifies activities that are performed in the departments and the amount of effort each activity demands (measured in %), referred to as effort cost drivers. Based on the effort cost drivers’ given percentages, the share of overhead costs each activity bears is calculated. Henceforth, by knowing the cost of each activity and its frequency, the cost per time an activity is performed (cost rate) is calculated. These cost rates are then used to calculate each product’s share of the overhead cost (Kaplan and Andersson, 2003). Although, the ABC model is considered to be accurate, it has received critique. The criticism refers to the demand of time and resources required for implementation, maintenance and update, e.g. the extensive interviewing needed to identify activities and the effort cost drivers, resulting in a complex and expensive model. Moreover, the critique addresses the subjectivity of the effort estimations as they are based on the perception of the interviewed employees (Kaplan and Andersson, 2007).

(10)

4. Time Driven Activity Based Costing

Due to the challenges of implementing, maintaining and updating ABC, in 2003 Kaplan and Anderson suggested a reintroduction of ABC through Time Driven ABC. In contrast to ABC, TDABC eliminates the extensive and continuous interviewing needed to identify effort cost drivers (Kaplan and Anderson, 2003). Instead TDABC uses transactional cost drivers, meaning the allocated overhead cost is based on the number of times an activity is performed. The transactions are then used to compose time equations that calculate the total time each cost object consumes. The time consumed is lastly multiplied by the capacity cost rate, the total cost per minute of the department, and the cost is thereafter allocated to the cost objects. How the model works more precisely is presented in the pedagogical review.

As the cost allocation is driven by time, the time equations become the bottom line of TDABC. Hence, the need for quantitative information concerning transactions become essential. Through the development of information- and Enterprise Resource Planning (ERP) systems, information concerning the time required and frequency of transactions is made more accessible in a wide range of organizations today. Further, TDABC has enabled for an optimization of the usage of the data, which in combination with the time equations makes TDABC scalable (Kaplan and Anderson, 2003).

Even though TDABC is suggested to be less complicated than ABC (Kaplan and Anderson, 2003), the model has received criticism. Ringelstein (2018) states that the model does not live up to being less complicated than ABC, and Adenle and Valverde (2014) points out the issue of TDABC being developed to allocate costs on operational levels of an organization. When there is a lack of clearly defined procedures and set teams for certain tasks, the use of TDABC is limited (Ibid, p. 122). In former implementations of TDABC this issue has been targeted through allocating costs through percentage allocation (Kaplan and Anderson, 2007, p. 58). However, Kaplan and Anderson (2007) argue that a time driven allocation would have been possible in these situations as well. Finally, Namazi (2016) refers to the advantages of TDABC as baseless, as case studies of TDABC are scarce and the findings of existing studies contradictory - perhaps the statement describes the inconsistent view academia has on TDABC?

4.1 A pedagogical review of TDABC in practice

In order to show how the model works in practice, a numerical step-by-step example will be illustrated using a made-up case as well as how the model is used in multi-layered organizations. The descriptions and examples are based on Kaplan and Andersons (2007) illustration of TDABC for a customer service department.

(11)

1. Calculating the capacity cost rate:

The first estimate that is needed for TDABC is the capacity cost rate, the capacity cost rate is the cost rate for the use of resources in a unit and is calculated using the following equation:

𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦 𝑐𝑜𝑠𝑡 𝑟𝑎𝑡𝑒 = 𝐶𝑜𝑠𝑡 𝑜𝑓 𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦 𝑠𝑢𝑝𝑝𝑙𝑖𝑒𝑑

𝑃𝑟𝑎𝑐𝑡𝑖𝑐𝑎𝑙 𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦 𝑜𝑓 𝑟𝑒𝑠𝑜𝑢𝑟𝑐𝑒𝑠 𝑠𝑢𝑝𝑝𝑙𝑖𝑒𝑑

The cost of capacity supplied is the total cost that is to be distributed, which could be for a

team, a department or a company. In this example the cost capacity supplied is 5 000 000 SEK over a period of one year.

The practical capacity of resources supplied is the total quantity of resources measured in time, the resources can be personnel or equipment depending on the nature of the organization. In this scenario the resources are six full time employees. Assuming all six employees work full time (40h/week), but also taking into consideration vacation, sick leave etc. (thus, assuming they work full time 80% of the year), the total practical capacity will equal 599 040 minutes. Using the estimates for capacity supplied and practical capacity of resources supplied, the capacity cost rate can be calculated:

𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦 𝑐𝑜𝑠𝑡 𝑟𝑎𝑡𝑒 =5 000 000 𝑆𝐸𝐾

5 99 040 𝑚𝑖𝑛 = 8.35 𝑆𝐸𝐾/𝑚𝑖𝑛

2. Identifying the activities and the time requirement:

The second estimate needed is the capacity required for each activity, i.e. the time to perform each activity. In order to illustrate, the following activities and unit times are assumed:

Process customer orders: 10 minutes Handle customer inquiries: 30 minutes Perform credit checks: 45 minutes

(12)

3. Calculating the cost driver rate:

After having collected the necessary estimates in step 2, the cost driver rate can be calculated for each activity. The cost of performing each activity is calculated by multiplying the previously calculated capacity cost rate and the unit time for the activity. See illustrated in table 1 below.

Table 1: Activities and unit times

Activity Unit time Cost driver rate - at 8.35 SEK/min

(minutes) (SEK)

Process customer orders 10 83.5

Handle customer inquiries 30 250.5

Perform credit checks 45 375.8

4. Forming time equations:

Knowing the activities and number of transactions a time equation can be structured for the department. An equation is then constructed for each cost object to calculate their share of the customer service departments costs.

Customer service time equation (minutes) =

(10 ∗ 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑐𝑢𝑠𝑜𝑚𝑒𝑟 𝑜𝑟𝑑𝑒𝑟𝑠) + (30 ∗ 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑐𝑢𝑠𝑡𝑜𝑚𝑒𝑟 𝑖𝑛𝑞𝑢𝑖𝑟𝑖𝑒𝑠) + (45 ∗ 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑐𝑟𝑒𝑑𝑖𝑡 𝑐ℎ𝑒𝑐𝑘𝑠)

5. Identifying used and unused capacity:

Further, TDABC provides the opportunity to identify used and unused capacity. Used and unused capacity are expressed as a percentage which shows what part of the practical capacity of the resources is used and not. In table 2 below the column “total minutes” shows the total amount of the resources that are used expressed in minutes, and by dividing that amount by the total practical capacity of resources (474,000/599,040), the used capacity can be identified, and the residual represents the unused capacity. In the same way which minutes are used to calculate the capacity, the total cost can be used too (3 957 900/5 000 000 for used capacity)

(13)

Table 2: Measuring Used and Unused capacity

Activity Unit time Quantity Total minutes Total cost - 8.35sek/min

(minutes) (number of transactions) (SEK)

Process customer orders: 10 30 000 300 000 2 505 000

Handle customer inquiries 30 4 000 120 000 1 002 000

Perform credit checks: 45 1 200 54 000 450 900

Used capacity (79,1%) 474 000 3 957 900

Unused capacity (20,9%) 125 040 1 042 100

Total 599 040 5 000 000

The used capacity can be used to identify what part of the time spent working is used effectively, and thus, if unused capacity is high, it may signal to managers that there is room for expansion in terms of resources. Not to be forgotten, the unused capacity still needs to be allocated as it still has an origin. If the capacity was meant to meet certain demands, the cost of the unused capacity can be allocated to the unit which did not meet the anticipated demands.

4.2 TDABC in multi-layered organizations

Figure 1: Resource Expenses, Flow to Support and Operating Departments (Kaplan and Anderson, 2007)

In organizations, there are not only departments directly connected to the products such as the customer service department in the previous example, but also supporting departments whose costs need to be allocated as well. The graph above demonstrates a top-down structure, which show how organizations should allocate all types of costs using TDABC. As seen in figure 1, each department’s costs are allocated onto the departments that uses its resources. In other words, general resources are allocated upon all departments, the cost of support departments are allocated upon operating departments and operating departments are then allocated to products.

(14)

5. Method

In the method section, the study’s research approach and model adaptations are motivated. Further, the methods for collecting data and samples are presented outlining the rationale behind the choices. Finally, a discussion concerning the trustworthiness of the method is discussed.

5.1 Research approach: Engaged Scholarship

One of the greatest challenges of modern research is to conduct studies that contribute both to research and practitioners (Van de Ven, 2007). Within the field of management, another challenge is that practitioners tend to fail in implementing findings from research, resulting in a widening gap between theory and practice (Ibid.). In contrast to traditional research, Engaged scholarship targets this widening gap. Engagement can be described as a relationship built on negotiation and collaboration between practitioners and researchers (Ibid.) From this point of view, organizations are idea-factories, where possible solutions are implemented in order to co-produce knowledge and tackle important questions. Therefore, the importance of advising practitioners and contributing to research is equally emphasized. There are challenges that may arise when pursuing Engaged Scholarship, related to engaging with inside informants, spending time in research sites and understanding the role as researcher in the context (Ibid.). However, Van de Ven highlights the fact that consensus is not required between two parties (referring to practitioners and researchers) in order to create practical and theoretical learning, and it may also contribute to the discussion of the findings.

There are former studies that have been of a collaborative character when applying TDABC in organizations (Basuki and Riediansyaf, 2014). This pilot study have had a similar approach, and the collaboration between us and the study object Alfex was expressed through feedback and advice from managers and employees within the company. The collaboration is further important to highlight as the wish from Alfex of getting more theoretical knowledge about cost allocation on a product level have shaped the pilot study. However, we as researchers have been in control of designing and performing research activities and were detached as outsiders to the social system of Alfex. As this pilot study is an application it can be assimilated with an attempt to analyse the impact of TDABC in settings such as Alfex. As this has not been done before in Alfex, the process of applying TDABC has been littered by challenges which we had not accounted for. However, these challenges lay the ground for our contribution to the research within cost allocation and has also provided Alfex with more theoretical knowledge concerning cost allocation. Lastly, we want to highlight that all numbers are not real, however, as the proportions are, the allocation will still provide us with valuable information, and the lessons learned from the application will not be affected.

(15)

5.2 Adaptation of Time Driven Activity Based Costing

When applying TDABC in Alfex, certain modifications have been made in order to make the application more efficient and manageable.

5.2.1 Model adaptations

Two types of departments have been identified in Alfex. First there are support departments (SDs), an example of general SDs in companies is: IT or HR (Kaplan and Anderson, 2007, p. 63). Second, there are operating departments (ODs), that have contact with customers or somehow assist the day-to-day operations. The ODs were all included in the application, as they are working with different products and provide a link to the products. Finally, there are several identified product types that were divided into two product groups (used as the final

cost objects).

Figure 2: Cost allocation process of pilot

The overhead costs allocated in this pilot study were based on four different SDs, and the allocation was done in two steps as demonstrated in figure 2 above.

Step 1) First the overhead cost produced by the four SDs were allocated towards the three ODs, this first step of the allocation was not done through TDABC, but through Traditional cost allocation. The rationale behind the decision was that these departments have a lot of activities which vary heavily in time requirement and include a high variation in activities, which resulted in TDABC being time consuming if used. Further, in the analysis phase of TDABC, Kaplan and Anderson (2007, p. 62) themselves states:

“Initially, to keep the model simple, the assignment of corporate staff department costs such as HR and IT, can be excluded or allocated without the use of time-driven algorithms. These indirect and support costs will be incorporated more accurately when the team scales the model to the entire enterprise.”

(16)

The statement above has further given support for the choice of using a Traditional cost allocation in the pilot study, as we see our application as more of an analysis than an implementation. However, as we have not used TDABC for these allocations, we cannot state this would be less accurate. Still, doing these estimations would have required more interviews and interviewees, which at the time of the application would have been difficult to get access to and time for.

Step 2) The costs were then allocated from the operational departments upon the 16 products, i.e. the cost objects, using TDABC.

5.2.2 Allocation of unused capacity

According to Kaplan and Andersson (2007) the identified unused capacity is to be allocated as organizations can identify cost objects which have not reached expected demand or targets. In this study the unused capacity was not allocated to the final cost object (i.e the products). Instead the unused capacity was only allocated to the ODs. The rationale was that the process of allocating unused capacity is something which is only briefly discussed by Kaplan and Andersson (2007). As the pilot study’s main focus is to identify the consequences of applying TDABC in its current form, a self-constructed allocation method for allocating of unused capacity would not contribute to the study.

5.3 Sampling strategy

For the data collection, different methods were used for sampling the respondents for the interviews and the data for the cost allocation. A purposive sampling was conducted as samples needed to fulfil a purpose or/and specific information was needed. The pilot study allocated the overhead costs of four SDs, these departments were selected as they are four of the most cost intensive departments, responsible for 75% of the overhead costs in Alfex. Therefore, the result of the allocation both gives a fair indication of how TDABC would allocate costs to each product, and the resulting impact, at the same time the study became more manageable. Furthermore, interviews were held with personnel from all SDs and ODs involved in the cost allocation. The main goal of the interviews was to gain insights into how the departments functioned, their structure and the activities performed. In order to get a holistic and accurate understanding of the department, personnel with appropriate knowledge of the departments were sought. The aim was to have two interviews for each department, however in some cases there was only one person with enough insights, and thus, for some departments only one interview was held (see appendix 1). The combination of a need for personnel with broad knowledge and accessibility led to a small amount of eligible interview candidates, and thus for many departments only one interview was conducted.

(17)

product. E.g. how many minutes does “activating a contract” take and how many contracts were activated for product Y. The selection for the data was therefore dependant of the identified activities and products. Further, the collected data covered a period of one year as Alfex have a business year of 12 months.

5.4 Data collection

Earlier empirical studies of TDABC have collected data through interviews, observations, studying cost systems and collection of internal company documents (Barros and Costa Ferreira, 2017; Järvinen and Väätäjä, 2018). In this study the qualitative data were collected through interviews in person, phone-interviews and follow-up questions. The quantitative data has been collected through ERP systems, interviews, internal documentation and follow-up questions. In general, the qualitative data was related to understanding the company, the departments and the activities while the quantitative data was time estimations and data of the transactions.

In total 14 interviews were conducted with personnel across different SDs and ODs. In order to perform the TDABC application in Alfex, data as to how the departments were designed, what activities they perform and the time estimations were essential, this information was mainly accessed through the interviews. The interviews were of a semi-structured design, which assures a certain degree of homogeneity, but also leaves space for adaptations during the interview (Leavy, 2014, p. 286). Adaptations can be explanations of question formulations or follow up questions, which allows for greater knowledge production through dialogue between interviewer and interviewee. The majority of the interviews were held in person, however, due to limitations related to geographical reach seven interviews were held over the phone. When conducting interviews over the phone, information gathered through social cues such as body language is excluded (Opdenakker, 2006). In our case, the advantage of enabling extended access to the interviewee was regarded to be greater than the disadvantages of phone interviews. All interviews were held in Swedish and therefore, citations are translated to English in the text. Moreover, the interviews were recorded and transcribed with the approval from the interviewees and were 15 to 30 minutes long.

The interviews were complemented with follow-up questions which were answered in written form over email or in structured forms sent within a week after the interview. The purpose of the follow-up questions was to enable the interviewees to extend on questions they were not able to fully answer during the interviews, or to elaborate further on a topic. E.g. give an opportunity for the interviewee to find a time estimation in the ERP and get back to us afterwards, or to collect further information concerning differences between teams within a department. Both open questions and Likert scales were used in the questionnaire. In addition, relevant information was shared by personnel in non-interview formed meetings, these included

(18)

spontaneous and informal meetings and conversations with employees in the office space and internal weekly meetings.

5.5 Lack and loss of data

In order to apply TDABC, quantitative information of all the transactions related to the activities were collected, as they are a vital part of the time equations. A loss or lack of data can create inaccuracies in the allocation as the number of transactions defines how big part of a cost a product is allocated (along with the time estimation). In the received data from Alfex there were certain data losses where transactions were not categorized, and thus could not be allocated to a product. The number of transactions that could not be traced differ for the different activities, however, they only make up 1.8% of the total amount of transactions. Because it is such a small proportion of the total number of transactions, we believe the impact is not integral, and thus have decided not to take the transactions into consideration. Further, there was a lack of data for certain products, which led to an allocation only being possible for the products which there was data for, resulting in an allocation to eight products, instead of the 16 products. Another limitation concerning the data, was that the transactions could not be traced to a specific product within the ERP system. I.e. number of phone calls were a total amount of calls which could concern any product. Therefore, the percentage of contracts each product represented, was used to allocate the transactions between the products. E.g. if product 1 was 10% of all contracts, and the activity receiving phone calls had 1000 transactions, we estimated that 100 calls concerned product 1 in the allocation.

5.6 Methodological discussion

Reliability and validity are two terms associated with the trustworthiness of research. Bell and Bryman (2015) suggest that to a large part, it is up to researchers of case studies to decide whether these are appropriate to their work. In addition, they argue case studies that are influenced by quantitative research tend to pay more attention to the validity and reliability of studies. An alternative to measure trustworthiness more suitable for qualitative studies is credibility (how believable are the findings), transferability (do the findings apply to other context), dependability (are the findings likely to apply at other times) and confirmability (has the investigator allowed his or her values to intrude to a high degree) (Lincoln and Guba, 1985). In this section, the methodology for the study will be discussed using the aforementioned concepts.

In order to make the pilot study applicable to Alfex, several modifications were done to the model. First, Traditional cost allocation is used to allocate the SDs to the ODs, the pilot study will not give a precise indication of how the allocation would have been if TDABC were to have been applied throughout the allocation, thus hurting the study’s credibility. Second, as not

(19)

TDABC in the setting, and as the four SDs add up to 75% of the overhead costs we believe the impact will not be integral. Further, the fact that modifications have been made could affect the level of transferability, as certain parts have been simplified, it could be argued that the study does not incorporate certain parts. As previously mentioned, the discussed limitations were however necessary in this pilot study.

When collecting data through interviews, in the case of certain departments, one interview was conducted, rather than having multiple. As basing an overview of a whole department based on one person's testimony leaves room for inaccuracy, loss of information and subjectivity the credibility and dependability of the study can be considered to be affected by this. As previously mentioned however, the circumstances did not always allow for more than one fitting employee to be interviewed and could even have hurt the credibility as in some cases, there was none with the appropriate information to interview. Data was also collected through “follow-up” questions which were answered in written format, one set of data that was collected in the follow-up was the time estimations for the different set of activities. As these were not directly observed, but asked for, there is no way to validate the time estimation - thus, leaving room for a loss of credibility and dependability.

Finally, some general measures were taken to maintain overall quality and trustworthiness. As we find reliability and transparency important, we have in the theory section, written a step by step guide demonstrated how costs are allocated using TDABC and attached the interview questions. Further, in the empirics, the decisions that were taken in the allocation process are clearly outlined.

(20)

6. Application of TDABC

In this section information about Alfex’s current cost allocation will be introduced, followed by a step by step description outlining the application of TDABC. Further, decisions will be explained in detail and adaptations of the model will be presented.

6.1 Alfex

Alfex, is a financial service company and a subsidiary to a larger international company which is considered one of the leading companies in its industry. In Alfex there are departments operating as supporting functions (SDs) and operational departments that operate towards customers both directly and indirectly. As a financial service company, Alfex offers a range of products which are both asset-based and non-asset based. The product mix can be described as a mixture of rental and asset-based finance products, as Alfex offers a set of core products, but also complementary products related to the financing of the core products. The products offered by Alfex are sold both to companies and to private customers. In our allocation we have divided the products offered into two groups, Product group 1, consisting of products towards smaller companies and private customers and Product Group 2, which are the products directed towards larger companies. OD 1 and OD 3 work towards Product group 1, and OD 2 work independently towards Product group 2.

The current cost allocation of Alfex is based on a percentage estimation from each of the managers of the operational departments, used to allocates direct costs down to products. The allocation of cost from the supporting departments is based on “ability to bear”, meaning, the allocation depends on a product’s profit contribution. The larger the profit, the larger the cost burden. All overhead costs are aggregated and then divided between the products based on the percentage share of the profit they provide. If product Y is responsible for 20% of the total profit, product Y will be allocated 20% of the total overhead costs. However, as the ability to bear does not have to reflect the underlying causes of what drive costs, therefore through collaborating with us in this pilot study, Alfex wish to gain more theoretical knowledge of how to allocate overhead costs down to products.

6.2 Allocating the overhead cost of the SDs onto the Ods

In this section the following is explained:

(1) What allocation keys have been used when using Traditional Cost Allocation and why (2) The redefinition of the OD’s as two were consolidated into one cost pool

(21)

6.2.1 Traditional Cost Allocation of SD 1

In conversation with one of the accounting employees, it was explained that as SD 1 handle the whole company’s pension costs, the whole company’s total pension costs were allocated onto them and equals to 79.3% of SD 1’s costs. As the pension costs can be directly traced to the number of employees, number of employees has been chosen as cost driver. The remaining

20.7% are efforts that are directed to the entire organization, but one of the two interviewees said that “So we have a lot of contact with our bosses, and some who have larger departments,

a bit more often”, suggesting that larger departments (in terms of employees) demand more

time. Therefore, the remaining 20.7% of the cost, can also be tied to the size of the ODs, which further gives support for the choice of cost driver. Because the majority of the cost of SD 1 is a cost that can be allocated directly towards the ODs, TDABC would not be able to trace the underlying cause of the costs, hence, Traditional cost allocation is used. The choice of using

number of employees as cost driver, results in a higher amount of cost allocated to ODs with

a larger number of employees.

6.2.2 Traditional Cost Allocation of SD 2

SD 2 work toward both other operational and supporting departments in Alfex. In the interviews and the follow up survey, the two interviewed employees described the work towards the frontend departments as: “spontaneous”, and that examples of the work they perform for the departments are “one time analyses”, “specific questions about products” and “support” - but explained that there is a large variety in the type of work towards the ODs. Further, they explained how the tasks toward the ODs are conducted irregularly. Because the type of work that is performed in SD 2 is based on demand, and the types of activities often differ, Traditional cost allocation have been used. TDABC is not used, as the spontaneous activities were found difficult to translate into time equations, due to no set procedures and high variety in activities. When looking closer at the work conducted towards ODs, the amount of work differs by little. When asked about the amount of work they perform to support the three ODs, their answers differ. One employee state that there is no difference, while the other states that there is a difference. However, the difference is described to be only a few percentage points. Due to only small variation in work directed towards different departments, the overhead cost is divided

evenly.

6.2.3 Traditional Cost Allocation of SD 3

The third support department, SD 3, works with conducting larger projects that have to be approved by the management board. The head of the department described the nature of the project by saying that “The projects that pass through us are often those who affect multiple

departments at a higher cost. We just finished a GDPR project, and that no one [department] can get away from” and “I see us as a very independent part that helps and supports everyone”.

From the interview it was understood that the department supported the entire company. Further, the tasks performed were described as: “following up projects”, “reporting to the

(22)

managers”, “assign project leaders and onboarding project leaders”. The time required for

different projects vary to a large degree, and the team members in project teams are different for each project (existing of both consultants and employees). The results of variation of team members and the size of projects makes it challenging to define transactions and estimate time consumption. Therefore, the overhead cost produced by SD 3 is (alike the allocation of SD 2’s costs) allocated evenly. The allocation is explained by that the activities performed in the department mainly focus on company-wide improvements, and that the transactions are difficult to estimate, and the members of the project team differ from project to project. As there is no way of efficiently measuring the benefit from SD 3 to the ODs, and the interview shows no reason to assume it would differ greatly, the cost was allocated evenly.

6.2.4 Traditional Cost Allocation of SD 4

SD 4 consists of five teams working with IT related tasks. Two of the teams’ work is specifically directed towards two of the ODs, the remaining three teams work with areas affecting several departments. According to the two interviewed employees, there are four frequently performed activities within the department: development, adaptations of systems, testing and fixing bugs. When asked if it is possible to estimate the time required for these activities, an employee who performs these tasks answered: “How long is a piece of string?” referring to the difficulty of estimating time due to variation. Alike the other SDs, it is difficult to estimate time and transactions, thus Traditional cost allocation is used instead of TDABC. Further, as two of the aforementioned teams are assigned to specific OD’s, these allocated directly from SD 4 to specific ODs. However, the three remaining teams require a cost driver. As the three teams work alike SD 2 and 3 work towards the entire organization, their costs are allocated evenly between the ODs.

6.3 Redefining the ODs

The following section will show the allocation of the support costs from the SDs onto the cost pools, consisting of the ODs. During the phase of interviewing employees at the operational level of the organization (OD 1, 2, and 3), insights were gained concerning the nature of their work tasks. One insight gained was that OD 3’s work tasks, alike the work tasks within the SDs, were described as being of a “high degree of variation”. The main function of OD 3 is handling and being responsible for the volume of sold products that pass through the dealers. Even though the department works on an operational level of Alfex, challenges arose when the activities performed within the department were to be translated into time equations. In contrast to the other ODs, the activities within OD 3 were described as being of a more strategic nature, such as: “cooperation with the dealers”, “visits”, “planning”, “education directed towards

the dealer’s employees” and “implementation of plans with respective dealers”. Further, when

speaking about the employees responsible for the sold volume, the manager of the department stated that their work was long term orientated. A few employees within the department were

(23)

In this sense, within OD 3 employees working close with the dealers either have work tasks that were of a more strategic and long-term kind, or ad hoc tasks with a high degree of variation. When activities appear to be more long term and strategic or ad hoc and of a high degree of variation, we found it difficult to estimate time and transactions. Due to the difficulty of translating activities within OD 3 into time equations, OD 3 was decided to not be used as a

cost pool.

To a large degree, the activities performed within OD 3 are strategic (building and maintaining relations with customers) and directed towards Product group 1. Further, on an operational level these products are handled by OD 1, through the customer support activities. In this sense, OD 3 is considered as a supporting function to OD 1, as both departments work towards Product group 1, whereas OD 2 independently works toward Product group 2. In other words, OD 2 have teams that work both with the customer service-related activities in OD 1, and a selling team which activity corresponds with the activities in OD 3. The description of the departments is displayed in figure 3. Therefore, a decision was made to allocate the costs of OD 3, as supporting costs to OD 1, and allocate the supporting cost on two cost pools instead of three, OD 1 (as a merger of OD 1 and OD 3) and OD 2. Further, when costs are allocated evenly between the ODs, OD 1 will carry ⅔, whereas OD 2 is allocated ⅓.

Figure 3: Illustration of the merger of OD 1 and OD 3 as cost pool

6.4 Results of the allocation

In this section the results of the allocation towards the chosen cost pools OD 1 and OD 2 will be presented. The currency of the cost is Swedish Crowns (SEK) as that is the main reported currency in Alfex.

(24)

6.4.1 Allocation of Support Department 1

Table 3: Allocation of the overhead cost of SD 1 towards the two ODs

Department Full time employees Cost allocation (%) Cost allocation (SEK)

OD 1 47 55 31 536 099

OD 2 38 45 25 497 271

Total 85 100 57 033 370

In table 3, the allocation of the overhead costs of SD 2 onto the ODs is presented. As the overhead costs are allocated using number of employees as cost driver, OD 1 with a higher number of full time employees carries a larger part of the cost than OD2. As can be read from the table, OD 1 is allocated 55% of the cost while OD 2 is allocated 45%.

6.4.2 Allocation of Support Department 2

Table 4: Allocation of the overhead cost of SD 2 towards the ODs

Department Cost share Cost allocation (%) Cost allocation (SEK)

OD 1 2/3 67 25 967 021

OD 2 1/3 33 12 983 511

Total 1 100 38 950 532

In table 4, the allocation of the overhead costs of SD 2 onto the ODs is presented. As the overhead costs are allocated evenly between the three operational department, but the cost object OD 1 consists of two departments it is allocated 2/3 of the cost. OD 2 is allocated 1/3 of the overhead costs from SD 2.

6.4.3 Allocation of Support Department 3

Department Cost share Cost allocation (%) Cost allocation (SEK)

OD 1 2/3 67 51 093 269

OD 2 1/3 33 25 546 635

Total 1 100 76 639 904

In table 5, the allocation of the overhead costs of SD 3 onto the ODs is shown. As the allocation variable is the same as in the allocation of SD 2, costs are allocated evenly between the three ODs, resulting in 2/3 being allocated to OD 1 and 1/3 to OD 2.

(25)

6.4.4 Allocation of Support Department 4

Department 2 teams allocated directly (%) 3 teams allocated evenly (%) Total (%) Total (SEK)

OD 1 16 41 57 15 574 651

OD 2 22 21 43 11 789 902

Total 38 62 100 27 364 553

In table 6 the allocation of the overhead cost produced by SD 4 towards the ODs is presented. OD 2 and 3 are both allocated the cost produced by the team that they have working directly towards them. However, each of the five teams differ in size, and thus the allocation is not equal. The team working directly towards OD 1 generates 16% of SD 4’s cost and the team working towards OD 2 generates 22%. The remaining cost (produced by the other 3 teams) has been aggregated and shared evenly between the three departments (OD 1, OD 2 and OD 3). In other words, in SD 2 and SD 3, OD 1 is allocated ⅔ of the cost and OD 2 ⅓. In table 7, the total is presented where OD 1 is allocated 57% of SD 4’s cost and OD 2 is allocated 43%.

6.4.5 Total allocation from the SDs to the ODs

Table 7: Total Step 1 allocation (from the SDs to the ODs)

Departments Cost allocation (%) Cost allocation (SEK)

OD 1 61 139 745 691

OD 2 39 87 607 221

Total 100 227 352 912

After all supporting costs have been allocated to the ODs, OD 1 carries 61% of the cost and 39% is carried by OD 2, demonstrated in table 7. In SEK this result in a total cost of 139 745 691 for OD 1, and 87 607 221 SEK for OD 2.

6.5 Allocating costs onto the products through TDABC

The final allocation is presented from the ODs onto the cost objects being the products using a similar layout as in the pedagogical review.

1. Calculating the capacity cost rate:

In the first step of TDABC the capacity cost rate is calculated for which the cost of capacity supplied, and practical capacity of resources supplied is needed.

The cost of capacity supplied has been extracted from the final allocation from the SDs to the ODs. Meaning the cost for OD 1 is 139 745 691 SEK of the total cost, and the cost for OD 2 is 87 607 221 SEK which is presented in table 7 in the previous section.

(26)

The practical capacity of resources supplied has been calculated by first estimating a general estimation of the capacity for one person. A full-time employee is expected to work 40 hours a week in Alfex. Further, employees in accordance to Kaplan and Anderson (2007) are expected to work 80% of the time during a year; thus, taking vacation, holidays and sickness into consideration. Finally, the practical capacity is measured in minutes. With the mentioned information the estimation equals 99,840 minutes per full time employee per year, calculated as follows:

1. 40 hours * 52 weeks = 2080 hours 2. 2080 * 0.80 = 1664 hours

3. 1664 hours * 60 = 99,840 minutes

As OD 1 had 15 employees which work with the activities, the practical capacity for OD 1 results in a total of 1 497 600 minutes. OD 2 with 27 employees result in a practical capacity of 2 695 680 minutes. Although there are more employees in both departments, as some work with activities which could not be time estimated (due to a strategic nature) or/and there were not data for, these sections of the departments were excluded and thus the practical capacity is based on fewer people than exists in total.

When the cost of capacity and the practical capacity have been calculated, the capacity cost rate can be calculated for OD 1 and 2 resulting in the following:

𝑪𝒂𝒑𝒂𝒄𝒊𝒕𝒚 𝒄𝒐𝒔𝒕 𝒓𝒂𝒕𝒆 𝑶𝑫 𝟏 =139 745 691 𝑆𝐸𝐾

1 497 600 𝑚𝑖𝑛 = 93.31 𝑆𝐸𝐾/𝑚𝑖𝑛

𝑪𝒂𝒑𝒂𝒄𝒊𝒕𝒚 𝒄𝒐𝒔𝒕 𝒓𝒂𝒕𝒆 𝑶𝑫 𝟐 =87 607 221 𝑆𝐸𝐾

2 695 680 𝑚𝑖𝑛 = 32.50 𝑆𝐸𝐾/𝑚𝑖𝑛

The second step in TDABC all the activities and their time requirements (unit time) have been identified. In table 8 and 9 the identified activities along with the time requirement for each activity is demonstrated. As the tables show, there are activities with time requirements that vary to a large degree (marked *), due to the difficulty of using the estimates these are henceforth excluded from the allocation.

(27)

Table 8: Activities and unit times for OD 1

Activity Unit time (minutes)

Attest contract 1

Activate contract 4 Act on incoming email 5 Act on incoming phone call 5 Terminate contract 4 *Act on reported inaccuracies n/a

Table 9: Activities and unit times for OD 2

Activity Unit time (minutes)

Call off 10

Activate contract 10 Act on incoming phone call 3.50 Act on incoming email 3 Terminate contract 5 *Act on reported inaccuracies n/a *Coding of articles 0.5 – 480

*Billing Multiple days

3. Calculating the cost driver rates:

In the third step, the cost driver rate for each activity is calculated, which is done by taking the previously calculated capacity cost rate (in step 1) and multiplying it with the identified unit time presented in step 2. In table 10 and 11, for each activity, the unit time along with the calculated cost driver rate per activity is demonstrated for the two ODs. The table shows that the longer the activity takes to perform, the higher the cost driver rate is, as time is what drives the cost.

Table 10: Activities, unit times and cost driver rates for OD 1

Activity Unit time (minutes) Cost driver rate - at 93.31 SEK/min

(SEK)

Attest contract 1 93.1

Activate contract 5 466.6

Act on incoming email 5 466.6

Act on incoming phone call 4 373.2

(28)

Table 11: Activities, unit times and cost driver rates for OD 2

Activity Unit time (minutes) Cost driver rate - at 32.50 SEK/min

(SEK)

Call off 10 325

Activate contract 10 325

Act on incoming phone call 3.5 113.75

Act on incoming email 3.5 113.75

Terminate contract 5 162.50

4. Forming time equations:

In the next step of the allocation, time equations are formed in order to calculate the cost carried by each product. In this stage, however, we had issues finding data concerning a number of products in the ERP system and internal documents. Hence, we were left with a total of 8 products, which in this application will be the final cost objects. In order to allocate the cost 8 time equations are needed, one is established for each cost object. By multiplying the number of minutes each activity takes with the frequency it has been performed, the time equation calculates the total minutes spent on the product. Below is an example demonstrating the time equation for Product 10 which reveals that 512 935 minutes are spent on Product 5.

Time equation for product 10:

Product 10 = (10 * 15 517) + (10 * 15 517) + (3.5 * 7 445) + (3 * 46 054) + (5 * 7 676) = 512 935 minutes

The total number of minutes for each product is shown below in Table 10 and 11, i.e. the result of each products time equation. Time equations for all products can be found in the appendix (see appendix 2).

5. Final allocation towards products

Having formed all time equations, the final allocation towards the products can be done. By multiplying the number of total minutes spent on each product and the capacity cost rate, the total cost for each product is calculated, as displayed in table 12 for OD 1, and table 13 for OD 2. In the tables the final result of the allocation for all 16 products is presented. In both tables there is missing information denoted as “n/a” representing missing data and therefore, these are not used as cost objects.

(29)

Table 12: Activities, final allocation for Product group 1

Product Total minutes Cost per unit Total cost Percentage

1 690 301 1 029 64 414 142 39

2 508 998 1 102 47 496 180 29

3 327 577 1 029 30 567 200 18

4 247 641 1 029 23 108 128 14

5 n/a n/a n/a n/a

6 n/a n/a n/a n/a

7 n/a n/a n/a n/a

8 n/a n/a n/a n/a

9 n/a n/a n/a n/a

Total 1 774 517 165 585 650 100

Table 13: Activities, final allocation for Product group 2

Product Total minutes Cost per unit Total cost Percentage

10 512 935 1 074 16 669 946 64

11 152 917 1 074 4 969 679 19

12 21 673 1 074 704 364 3

13 114 387 1 074 3 717 476 14

14 n/a n/a n/a n/a

15 n/a n/a n/a n/a

16 n/a n/a n/a n/a

Total 801 913 26 061 465 100

In all cases but one, the cost per unit is identical for all products in each department. The reason for the indifference, is that there was a lack of product specific data, e.g. how many emails or phone calls concerning each product there were. In order to still be able to incorporate the activities, the proportion of contracts for each product instead was used to weight the number of phone calls and emails (etc.) that were to be allocated to each product. As the same weights were applied for allocating the transactions for the activities, on average the cost is the same, only the quantity it’s been performed differ. In one case, product 2, the cost per unit differs slightly which is explained by that one of the activities was only

performed for one product, and thus the entire cost for the activity was allocated directly to product 2.

(30)

6. Identifying used and unused capacity: Table 14: Used and Unused capacity for OD 1

Activity Unit time Quantity Total minutes Total cost

(minutes) (number of transactions) (93.31 SEK/min)

Attest contract 1 157 863 157 863 14 730 718

Activate contract 4 157 864 631 456 58 923 114

Act on incoming phone call 5 121 200 606 000 56 547 736

Act on incoming email 4 86 400 345 600 32 249 006

Terminate contract 4 8 400 33 600 3 135 320

Used capacity (118%) 1 774 519 165 585 893

Unused capacity (-18%) -276 919 -25 840 202

Total 1 497 600 139 745 691

Table 15: Used and Unused capacity for OD 2

After the final allocation has been performed, the used and unused capacity can be identified, although it’s not a part of the allocation, it’s a valuable measure as it provides insights to the productivity in the departments. In Table 15 and 16 all activities, the total time consumption and total cost can be identified for OD 1 and 2. By knowing the total practical capacity of each department and the total amount of minutes used, the used and unused capacity can be identified. For OD 1 the used capacity is 118% and unused capacity is -18% while for OD 2 the used capacity is 30% and unused capacity is 70%. As the unused capacity is not allocated to products in this study the final cost object for the amount is the two ODs. The capacity of OD 2, being over 100% shows that the total amount of minutes spent on working with the activities exceeds the number of minutes the employees in the department have worked (the practical capacity supplied). While the lower capacity of OD 2 shows the opposite relation, where there is a large gap between the number of minutes spent on working with the activities and the number of minutes the department have been working.

Activity Unit time Quantity Total minutes Total cost

(minutes) (number of transaction) (93.31 SEK/min)

Call off 10 24 259 242 587 7 884 061

Activate contract 10 24 259 242 587 7 884 061

Act on incoming phone call 4 11 640 40 740 1 324 050

Act on incoming email 3 72 000 216 000 7 020 000

Terminate contract 5 12 000 60 000 1 950 000

Used capacity (30%) 801 913 26 062 173

Unused capacity (70%) 1 893 767 61 545 048

(31)

7. Discussion

Looking at theory only, TDABC does solve the challenge of the accuracy and cost trade-off in cost allocation. As the time equations in TDABC allows for scaling of the model, the maintenance, updating and implementation of the model is suggested to be simplified, without conflicting with the aspect of preciseness too much. However, as earlier discussed, whether these advantages are applicable in practice divides researchers within the management accounting field. Our application of TDABC in Alfex does not counteract the suggested advantages of the model. Nevertheless, the consequences of our applications have taught us that there are still challenges that remain in the process of applying TDABC. These lessons will be discussed in the following section.

Firstly, activities need to have certain characteristics in order for the allocation to be efficient. The activity definition stage is not something Kaplan and Andersson particularly emphasize in their work. In our study however, the activity-definition has been one of the most challenging parts of applying TDABC. As presented in the results, in Alfex many of the departments perform activities that 1) are not homogenous 2) vary heavily in time requirement. The challenge of defining activities, was especially apparent in the SDs and OD 3, as a lot of work was described as spontaneous. If TDABC were to be implemented in Alfex, a large number of activities would have to have been identified as most departments tasks vary. But even then, as new ad-hoc activities appear often, the model would require constant updating – thus not avoiding the critique ABC received. Other times, when activities were identifiable in the SDs, they were of a strategic nature, which made it challenging to translate the activities into time equations (due to the difficulty of measuring activities in minutes). The characteristics of activities being non-homogenous or having a high degree of variation in time was an overall trend within the SDs. Furthermore, the challenges align with Adenle and Valverde’s idea of TDABC being developed for an operational level of organizations. If a time estimation were to have been given for the activities in these departments, there would have been a risk of a large discrepancy in the allocation.

Secondly, the application of TDABC presented highlighted the importance of high-quality data, and the challenges that arise when there is a lack or loss of data. The need of high-quality data became apparent in the scenarios where activities were homogenous. In these instances, the activity defining stage became profoundly easier, and thus required less time. Consequently, TDABC proved to be an efficient cost allocation model given that quantitative information

could be obtained from ERP systems or other internal documentation. In other words, an

efficient use of TDABC requires quantitative documentation of transactions, which can be traced to specific products to enable the development of time equations for each product (when products are used as cost objects as in the pilot study). The documentation, whether done through ERP systems or manually, must be updated in order to reassure an accurate cost allocation, which in a larger context can be related to the cause and effect relation emphasized

(32)

in cost allocation. The lack of detailed data in Alfex was one of the barriers which complicated the application of TDABC. It could be argued that the quantitative data could have been accessed through interviews, however, as earlier discussed, one of the advantages that TDABC is supposed to enable for, is the ability to collect data cost-efficiently (through the use of ERP systems etc.). In a setting where detailed and updated ERP systems exist, TDABC could potentially be both implemented and maintained at a much lower cost. Regardless, as this was not possible in Alfex, the simplification of using contracts in order to trace number of transactions to products was done. The simplification illustrates the need for organizations to have high-quality data at hand before implementing TDABC, as the simplification resulted in a weaker cause and effect relation in the cost allocation.

Thirdly, the application of TDABC highlighted the complexity of the unique feature of measuring used and unused capacity. When the underlying information (times estimates or quantitative transaction information) the capacity measures are based on is accurate, meaningful information concerning productivity and capacity may be provided. On the other hand, when the underlying information is not accurate, there is a risk of the capacity-measures providing inaccurate information. In the pilot study, the complexity of the capacity measures became apparent as both OD 1 and OD 2 were left with quite extreme values of used and unused capacity. The high value of used capacity in OD 1, could be a result of too positive time estimates, which creates a picture of a department working more efficiently than they actually do. Contrary, the low used capacity in OD 2, is likely to be explained by the fact that activities had to be eliminated due to lack of data concerning transactions or time estimates. However, even if a reasonable used capacity is calculated, there is a difficulty in analysing the value as it could be sign of breaks, informal meetings, ad hoc activities or other unexpected situations, not been accounted for when building the TDABC model. To summarize, the essential problem is related to the stage where activities are defined and times are estimated, as all activities cannot be identified and variations in time demand for activities can be present, there will be unused capacity.

After the used and unused capacity measures have been calculated, given that there is unused capacity, it has to be allocated. The allocation of unused capacity is something which Kaplan and Andersson have not given attention to, although they specify that the capacity should be allocated. Depending on how large the unused capacity is, it can potentially be a quite large cost which no cost object has been allocated. Thus, the lack of methods for allocating unused capacity in TDABC leaves a flaw in the model with large potential impact to the allocation and the performance of cost objects. Further, as the issue of how the allocation of unused capacity should appear is not given a lot of attention in academia, the unused capacity was not allocated towards the products in the application.

(33)

To conclude, the application of TDABC in Alfex has been proved to be a process littered with simplifications and adaptations. Apart from the three main lessons reflected on, the application has shown the importance of having extensive company knowledge when applying (or implementing) TDABC. In other words, we believe there is a possibility that we would not have struggled as much with the challenges, if we would have had more time for the pilot study and gotten a deeper understanding of Alfex as an organization.

Time Driven Activity Based Costing When theory and reality collide: A pilot study of