Improving an existing Customer Information System (CIS) by examining customer decisions, development, and planning to increase the effectiveness for ISC and ISM

Table of contents

List of abbreviations

Index of appendices

List of definitions

List of definitions (VARTA)

1. Introduction
1.1 Background to the research
1.2 Research problem, research issues and contributions
1.3 Justification for the research
1.4 Delimitations of scope and key assumptions

2. Methodology
2.1 Research approach
2.2 Information model criteria
2.3 Procedure
2.4 Reliability and validity

3. CIS-model
3.1 Determination of influence factors
3.2 Analysis of influence factors

4. CIS status quo
4.1 Hierarchy
4.2 CIS information insert
4.2.1 Insert application software
4.2.2 Insert sources
4.2.3 Information preparation and output

5. Gap-analysis
5.1 Customer status quo and estimated status quo
5.1.1 Improvements concerning insert and preparation
5.1.2 Improvements concerning layout output
5.2 Potential status quo
5.3 Gap concerning pricing, deviation and benchmarking

6. Practical improvements
6.1 Pricing
6.2 Deviation analysis
6.2.1 ISC deviation methods
6.2.2 ISM deviation analysis output
6.3 Contribution benchmarking

7. Conclusion

Appendix 1 - Tables

Appendix 2 - Figures

Bibliography

List of abbreviations

illustration not visible in this excerpt

Table of appendices

Table 1: IS requirements

Table 2: Reporting models

Table 3: Overview of different approaches

Table 4: Survey on IS implementation

Table 5.1: Method areas

Table 5.2: Information side allocation

Table 5.3: Strategy allocation

Table 6: Strategy evaluation diagram

Table 7: IS categories

Table 8: Operative business characteristics

Table 9: Decision Analysis

Table 10: “6 W” method

Table 11: ISC process analysis

Table 12: Insert, time, and preparation

Table 13: Direct-cost oriented pricing

Table 14: Full cost-oriented pricing

Table 15: Subsidiary-specific full-cost oriented pricing

Table 16.1: Marginal break-even analysis - variable costs

Table 16.2: Marginal break-even analysis - fixed costs

Table 17: Fictive customer

Table 18.1: ISC deviation analysis

Table 18.2: Deviation in sales volume

Table 19: Deviation in fixed costs

Table 20: Break-even analysis - sales volume

Table 21: Break-even analysis - net sales

Table 22: Benchmarking information insert

Table 23: Benchmarking report

Index of figures

Fig. 1: Research procedure

Fig. 2: Four circle information model

Fig. 3: Three circle information model

Fig. 4: Communication flow

Fig. 5: Meaning within communication

Fig. 6: Relationship of SIR and OIR

Fig. 7: Control loop

Fig. 8: Management (MM) hierarchy

Fig. 9: Management system

Fig. 10: Database structure

Fig. 11.1: EIS screenshot

Fig. 11.2: CIS screenshot

Fig. 11.3: Customer Cost Allocation screen

Fig. 11.4: Minimum CuCo / Price screen

Fig. 12: ISM requests / three-circle model

Fig. 13: Insert, time, and preparation

Fig. 14: Pricing - influence factors

Fig. 15: Price policies

Fig. 16: Price ranges

Fig. 17: CIS layout (“from-to” guidelines)

Fig. 18: Layout for break-even analysis

Fig. 19: CIS layout (break-even analysis)

Fig. 20: CIS layout (CVP sensitivity analysis)

Fig. 21: Benchmarking results - break-even

Fig. 22: Benchmarking results - customer distance

Fig. 23: Customer value portfolio

List of definitions

illustration not visible in this excerpt

1. Introduction

1.1 Background to the research

Worldwide nations are trying to strengthen their international ties. Therefore, the former protectionist barriers are falling. This is stimulating free capital movement as well as it is paving the way for companies to establish subsidiaries abroad (Svend Hollensen, 2001). Global alliances and new information technologies are exerting pressure on the international markets. This leads to worldwide competition and more price transparency. Moreover, companies must deal with different customer preferences, habits, and laws on this world market. Hence, companies should obtain all local market and unique customer information. Thereby, they could manage to achieve long-term profit and liquidity targets. Therefore, a company must know all customer costs and revenues to secure a short and medium-term activity management (Joos-Sachse, 2001). Finally, the strategic controlling hedges this operative controlling steering task.

The relationship between a company and its environment becomes increasingly complex. This makes an Information Management (IM) with Information Systems (IS) a crucial competitive factor. A company should give IM a corresponding significance within the organization because it allows monitoring and measuring subsidiaries, customers, and products (Picot, 2001). A successful IM must consider all affected and interacting users ([Picot, 1988]; [Horváth, 1996]; [Krcmar, 1997]) and an IS should permit an effective communication between these users ([Shenk, 1997]; [Wimmer, 2001]). Consequently, concerning marketing and sales departments, appropriate methods are essential in order to guarantee a common understanding ([Zahn, 1998]; [Zerres, 1998]). Moreover, IM also requires cost accounting and cost management knowledge because qualitative interior and exterior information often derives from quantitative background information. Therefore, several authors illustrate the appropriateness of different cost accounting methods within various IM and IS conditions (Coenenberg, 1999).

This thesis focuses on the Customer Information System (CIS) improvement of VARTA Gerätebatterie GmbH (VARTA). According to the IS lifetime model (Watson, 1993), this CIS has passed the initial phase and is at an evolutionary stage . Nevertheless, Wattson’s survey (1991) demonstrates an average IS failing rate of 42 percent during both phases. Hence, an IS condition adjustment process and an observation of current weaknesses is essential. Thereby, companies learn from their failures. Finally, a company should adjust the coordination of insert, preparation, and output in predetermined intervals in order to match new exterior and interior conditions.

1.2 Research problem, research issues and contributions

The thesis examines customer decisions, customer development, and customer planning in order to improve the existing CIS by increasing the effectiveness of International Sales Controlling (ISC) and International Sales & Marketing (ISM).

Firstly, the thesis deduces the importance of identifying all IS influence factors for generating an optimal CIS frame. Thereby, the thesis considers all interacting users and their needs.

Secondly, the thesis infers the necessity of involving all users into the CIS content determination process. Thereby, users could express their understanding of a satisfying CIS. Thus, they can realize the integration of their needs. Thirdly, the thesis determines the CIS status quo. Thereby, the thesis can examine all differences between the current and the optimal CIS frame and content. In addition, this comparison permits evaluating current preparation and integration methods, such as calculation, allocation, and tracing. The same applies for all user- specific adapted information output characteristics, such as time, layout, and preciseness.

Fourthly, the thesis displays the importance of having a risk and feasibility rating. Thereby, VARTA could cancel further investment consuming implementation actions in time. Moreover, these infeasibility-causing issues redirect a company’s focus to other necessary pre-research areas. Fig. 1 in the appendix shows a graphical research overview.

This thesis explains and uses several theoretical approaches. This overview is merely a brief summary at this point:

The research process describes the appropriateness of information models within section 2.2 and uses various analysis methods within section 3.1 and section 3.2. Moreover, concerning operational business departments, it employs theoretical definitions within section 3.2. Afterwards, it applies this theoretical background knowledge to the analysis within section 3.4. Additionally, the thesis mentions several accounting, allocation, and tracing methods within section 5 and 6. In section 6, it uses further theoretical approaches for pricing, deviation analysis, and contribution benchmarking methods.

1.3 Justification for the research

In general, user problem statements emphasize weaknesses and initiate researches. Thereby, the CIS ISM users argue about missing, undetectable, and imprecise information. This leads to user aversion due to inefficient search processes through a large amount of irrelevant data.

A further research justification is user questions about qualitative meanings deriving from quantitative values. This leads to enormous clarification efforts and it reduces ISC’s efficiency in steering and guiding operational business processes. Moreover, unreliable CIS maintenance and allocation based on historic assumptions vindicate this research because unsupported and inaccurate information could lead to wrong decisions.

Additionally, users merely utilize the CIS as a query system in order to receive customer status quo information. The ISM and ISC decision support concerning customer development and planning is missing, i.e. time-oriented measurement and benchmarking are unavailable.

Finally, all these reasons lead to the last justification. ISC has less time for generating additional reports about crucial processes, weaknesses, and problem sources. This degrades their unique observing, steering, and guiding task.

1.4 Delimitations of scope and key assumptions

The thesis concentrates on the CIS concerning customer decisions as a supporting information tool on a programmed application-level. Therefore, it does not examine any non-database related disturbances regarding this information flow, e.g. cultural differences between users and different meanings of terms. Moreover, it does not consider irrelevant customer decision information as well as all exterior company information, such as market researches. Additionally, the thesis focuses on quantative customer information as basis for qualitative decision support due to the existing cost and revenue-oriented CIS structure. It examines the CIS as a stand- alone tool without any references to management or other departments. The thesis highlights ISM decision support to the extent this information is matching the regular ISC reporting task. The major body of research is to improve the CIS as an ISC analysis tool with regard to a few additional reporting improvements concerning ISM. The thesis must consider the second issue due to the research aim of providing ISC with more time in steering business processes with additional irregular analyses.

2. Methodology

2.1 Research approach

There are two different research approaches for an improvement process: an inductive and a deductive approach (Enström, 2002). An inductive approach observes an actual situation based on a theoretical model (section 2.2). A deductive approach begins with a status quo analysis, from which it derives conclusions. This thesis uses both within different sections. Adaptations and changes focus on the comparison of an actual CIS (section 4) with an optimal CIS (section 3). Thereby, from a main perspective, the whole improvement process is a deductive approach. On the other hand, theoretical models are the main source for generating an optimal CIS. They are the only possibility for eliminating weaknesses existing in an actual situation because they replace practice by theory.

2.2 Information model criteria

IS users have different responsibilities and they focus on different tasks. Therefore, an application-level IS must provide user-related information meeting specific requests. This also comprises communication volume and quality ([Horváth, 1996]; [Kuhlmann, 2001]; [table 1]). A CIS query system is only convenient if the users recognize a benefit of the provided information (table 2) because a user must discharge this dept at the domicile of the debtor. Otherwise, it is unsuitable and users reject this information completely due to a current “information and stimulus overload” as well as a “data addiction” (Shenk, 1997). Consequently, such an IS cannot contribute to higher productivity, job dimension, and individual performance due to a lack of work related outcome (Joshi and Rai, 2000). Finally, the users retain their old systems, information preparation and communication tools.

Thus, the thesis summarizes all IS difficulties within the following four problem areas (Notger and Kiesel, 2001):

- volume
- communication
- quality
- time

All these problem areas depend on the specific IS, tasks, user conditions, and relationships. They reflect the main selection criteria for an appropriate information system model (section 2.3).

2.3 Procedure

Several authors include all possible IS influence factors within similar circle models in order to show their relationship ([Picot, 1988]; [Horváth, 1996]; [Krcmar, 1997]). The first model includes four different circles ([Picot, 1988]; [fig. 2]). The offered information circle is a company’s available information pool. The Objective Information Request (OIR) as well as the Subjective Information Request (SIR) is the user-related information pool. The user task determines the OIR and the user perception determines the SIR. The Info-Request is part of the SIR and represents individually expressed user statements. Nevertheless, user statements are often diffuse due to an inability of communicating needs in an accurate way (McClatchy, 1990).

Therefore, a second model combines the SIR and the Info-Request in one pool ([Horváth, 1996]; [fig. 3]). The three-circle intersection reflects an optimal IS frame, which should be the target for improving a status quo IS frame.

Moreover, a third model connects the four-circle model with the IT communication flow theory of sender, transmission, and receiver ([Wimmer, 2001]; [table 3]; [fig. 4]). A common basis of understanding offers the widest possible information flow if there are no disturbances. Therefore, it requires an equal sender and receiver character pool (Berthel, 1975). The character combinations must have the same meaning for both sides (fig. 5).

Consequently, Horváth’s model in conjunction with Wimmer’s model match all selection criteria. This model combination justifies the following research step order.

The first inductive step is to analyze the intersection between OIR and SIR in order to illustrate the optimal CIS frame and content. The bigger this intersection, the more information an IS could provide, if permitted by the available information. Later on, this section explains the used appropriate analysis methods in more detail.

The second deductive step is to extract needless information, which is part of the CIS status quo but not of the newly generated information pool. It only makes work without providing benefits.

The third inductive step is to include missing information and to make it available in order to fill out the intersection between OIR, SIR, and available information.

The fourth deductive step is the user-related reorganization of remaining and newly integrated CIS information. Hence, a research process must verify the user-specific purpose and it must adapt it to the user’s needs. Additionally, standardization and a company-wide acceptance reduce the disturbance risks. The final step is a benchmark comparing the prepared information with the quality of the output produced (QIP). This guarantees the work-related outcomes contribute to the user’s job satisfaction. This is the case if the output meets the user requirements (table 1).

Krcmar (1997) suggests the same research procedure. He argues that an optimal CIS creation based on the existing available information only leads to a higher (subjective) information request (fig. 6).

A further practical analysis supports this theoretical procedure (Havelka and Lee, 2002). They conducted, concerning a new IS implementation, a survey on Critical Success Factors (CSF) among development personnel and users. However, VARTA’s second phase-oriented improvement process still contains all first phase implementation elements. Therefore, it is also applicable within this thesis. It demonstrates that practical experience emphasizes the same procedure (table 4).

In theory, SIR and OIR should be congruent but in practice, they are not. Theory mentions various SIR and OIR analysis methods. Firstly, identifying important method areas is viable ([Horváth, 1996]; [Köhler, 2001]; [Bruhn, 2001]; [table 5.1]). Secondly, an allocation of methods to different information sides is feasible ([Koreimann, 1976]; [Krcmar, 2000]; [table 5.2]). Finally, it is possible to assign these methods to the different information obtaining strategies (Watson, 1993). All these allocations depend on the company condition and the IS lifetime phase (table 5.3).

These theories deal with different research levels. The vague strategy allocation only minimizes the selection amount. Afterwards, it is the task of the thesis to decide on several more detailed information side-oriented methods.

Therefore, this thesis suggests a vague strategy analysis in the beginning because the method selection process must first determine VARTA’s environmental circumstances and the IS lifetime phase. Thereby, a smaller method variety remains. Then, concerning the information side analysis, the planning process allows choosing from a smaller method range. Finally, repeating this control loop with different methods should deliver an appropriate method mix (fig. 7).

Watson (1993) states that “each approach poses some difficulties” and “because of the variety of problems associated with identifying executives’ information requirements, organizations have used a variety of methods”. Therefore, a major task is to find an appropriate and comprehensive method mix highly detailed and efficient.

First, the “asking” strategy relates to the SIR methods obtaining user statements. . For this reason, these methods could merely generate the Info-Request circle, which is only a part of the SIR. In addition, these methods often lead to diffuse problem statements ([McClatchy, 1990]; [Ahituv and Neumann, 1990]; [Shenk, 1997]).

Consequently, these methods never cover the proper Info-Request volume and a research must focus on supplementary methods. This is particularly the case concerning the management levels within the affected departments. Both departments observed are not on the lowest operational level (fig. 8). Therefore, there are more unstructured problems and poorly defined data needs.

The second strategy of “deriving needs from an existing IS” should merely enhance a method mix because it is the defectiveness of the existing systems that motivates the development of other new IS ([Houdeshel and Watson, 1987]; [Watson, 1993]). Furthermore, other IS within the same company often have different aims and target user-groups. Therefore, they cannot serve as a research principle.

The third strategy of “synthesizing needs from characteristics of the utilizing system” focuses on the object system (user) activities. There, it is important to use a method dealing with the IS-aim.

The last strategy of “discovering needs from an evolving system” is only applicable if a company already implemented a system. Nevertheless, the risk of this strategy is to transfer existing weaknesses into a new system generation.

Due to the IS man-machine dialog, the selection depends on its suitability regarding:

- user-groups (hierarchy level, task, requirements, problems)
- IS conditions (aim, lifetime phase)

The thesis focuses on the third and fourth strategy (section 3.2) due to their advantage over the other ones (table 6). It decides on a top-down approach, i.e. integration starts after the whole research is completed (Dick, 1991). The CIS existence, concerning this approach, minimizes the usual failure risk and allows continuously monitoring of operational business.

2.4 Reliability and validity

A thesis should consider two crucial issues: reliability and validity. These terms determine to which degree a research outcome corresponds to reality.

The thesis concentrates on the current organizational structure including actual tasks, perceptions and IS aims. Company conditions as well as employee’s behavior could change rapidly. Therefore, this thesis excludes SIR analysis methods to the extent it is possible and involves OIR methods as much as possible. This increases reliability because task-related characteristics are usually more solid. Nevertheless, this risk of rapid changes underlines the need for regular observation and adjustment.

Concerning VARTA this thesis is highly valid because it uses theory and adapts it to practice. The improvement process involving all relevant VARTA user-groups and considering the current CIS reflects this practical orientation. Moreover, the thesis evaluates all theoretical conclusions with regard to their practical suitability. Finally, the numerous theoretical method adaptations demonstrate the same intention.

3. CIS-model

A thesis must examine above all the user-group specific OIR and SIR intersection ([Horváth, 1996]; [Krcmar, 1997]). These circles are user-group-specific because they depend on user tasks and activities. Moreover, it must define the IS user-groups before it can decide on an analysis method because different analysis methods are appropriate for different user-groups. Afterwards, a suitable selection is possible. Finally, all selected methods must adhere to the CIS aim. Therefore, the thesis will examine this within the next section as well.

3.1 Determination of influence factors

The thesis utilizes the newest version of the CIS documentation for determining the relevant user-groups. It limits the method selection to two user-groups (ISC and ISM). The ISC department represents the first relevant user-group. Theory positions it on an operational management level in the management hierarchy (fig. 8). “ISC should assure that specific tasks are carried out effectively and efficiently” (Ahituv & Neumann, 1990). This also emphasizes the steering, regulating, guiding, and directing task (fig. 9) by supporting decisions and effective work. Therefore, ISC should provide information in a lucid and contributing manner. This means it should educe only ISM relevant information out of the whole company data pool (fig. 9). Additionally, it should search for further CIS enhancements and prepare their whole information flow. All these ISC activities depend on the ISM-related SIR and OIR circle.

The CIS, concerning ISC, plays the role of an information databank (table 7). It must store all available information. Hence, ISC can select and prepare ISM-relevant information of the whole pool. In fact, ISC reports are hardly ever self-initiated because receivers motivate their generation.

Finally, with regard to ISC, the thesis chooses the process analysis method (Valusek and Fryback, 1987). This method deducts the ISC insert and preparation necessities from the ISM information request. Therefore, it is reasonable to define ISC as the available information side. It provides the CIS information volume, splits the requested information into its single elements, searches for sources, and prepares it appropriately.

The ISM department represents the second relevant user-group. Theory positions it on a middle management level in the management hierarchy (fig. 8). “ISM should assure that resources are obtained and used effectively and efficiently to accomplish the organization’s objectives” (Dick, 1991). Therefore, concerning resource allocation within changing objectives, ISM must make information-based decisions (fig. 9). Thus, the CIS should play the role of a predicting and decision-making IS ([Mason and Swanson, 1981]; [table 7]).

The thesis suggests applying the decision analysis method (Jenkins, 1984) because ISM-related decisions are the basis for the OIR analysis. Firstly, this method determines all necessary ISM decisions to perform related tasks. Secondly, it inspects supporting information for enabling users to generate their specific decision making patterns and priorities. Although the popular CSF method was also applicable, it would include all company-related critical success factors. However, as this research method only affects one department, this would generate higher efforts than necessary.

The CIS supports both user-groups in their operative business tasks and activities (table 8) on an application-level. In addition, this thesis applies the “6 W” method within the fourth strategy. It contains the following elements:

- who (user)
- what (information)
- why (reason)
- what for (aim)
- which form (layout)
- when (time)

The previous ISM decisions illustrate the aims within this method regarding the other two methods (decision and process analysis). It enhances the current method mix because it observes the analyzed OIR once more and includes the SIR. All these endorsements derive from included CIS experimentation and user activity examination, e.g. additional habits of information adaptation, frequently used information, and rejected data. Moreover, it specifies the method mix more precisely by adding the reasons for a certain information request. This enables ISC to observe if a request is really an ISM task and if this information could support an ISM decision. In the end, it observes if the IS output-related layout and time aspect adheres to all table 1 features (section 2.2).

IS aims set out in writing are often imprecise and could change over time (Stelzer, 2001). Nevertheless, as this improvement process should not develop a new system, it must clarify the already implied aim. An improved IS must still maintain the original one, i.e. the analysis in section 3.2 must correspond to this aim. According to Horváth (1996) and due to customer orientation, the CIS plays an information-providing role for the whole customer plan and control system within the management system (fig. 9). This has a severe impact on the ISM decision analysis because only decisions contributing to this aim should be included.

The available information and its preparation provide ISM with satisfying information. Nevertheless, the main problem is the information overflow (Dorn, 1994) and the divergent user understanding. Therefore, a CIS should highlight, compress, and filter specific information by employing various preparation methods. However, concerning ISC, this could lead to a high insert and preparation effort in order to match all quantity and quality-related needs. Finally, the available information research must consider all insert, time, and preparation areas.

3.2 Analysis of influence factors

All these theoretical methods concentrate on different objects or they have different starting points. Therefore, this paragraph comprises three parts.

The first part applies the decision analysis, which is the primary basis for using the other two methods. A decision is the only obvious managerial activity output (Emmanuel, Otley, Merchant, 2001). The thesis determines three major ISM decision areas regarding the delimitations (table 9). Every decision area contains several minor decisions supporting the main one. Nevertheless, this detailing procedure is essential because it allows a more thorough examination of the relationship between decision and information request. The sum of all information requests defines the ISM oriented OIR and SIR intersection content.

In the second part, the “6 W” method enhances the decision analysis. The information requirements deriving from all minor decisions represent the basis for this method. It describes the already determined information request in more detail by adding four additional aspects. Moreover, it emphasizes the ISC planning and controlling issue. Thereby, it is possible to maintain the CIS aim. The “6 W” method is the only method containing a reason analysis. This increases ISC’s understanding of a specific information purpose. Thereby, ISC can customize a preparation process more accurately to meet a request. Moreover, ISC is able to secure a specific ISM request matching the CIS aim. Consequently, ISC can assess if the CIS is the appropriate tool for this information supply. Additionally, it must secure this information insert. Finally, this method integrates time and layout aspects into the CIS output. This affects ISC’s layout preparation. Thereby, the process analysis may neglect this layout issue.

The last part focuses on the ISC process analysis. It uses the decision-related requirements as basis for deducing all necessary CIS inserts. The minor decisions in conjunction with their aims and reasons allow determining an accurate data insert volume. The layout aspect is only included insofar as it concerns time characteristics. Furthermore, the operative business characteristics of ISM lead to additional preparation requirements, such as high precision, simple layout, predetermined period, high update frequency, and straightforward calculation methods.

Finally, all data inserts and preparations generate the available information circle. The intersection of all three circles displays an optimal CIS information frame and content.

The “6 W” method is supposed to maintain the CIS information flow. Therefore, it does not consider ISC as an independent CIS influence factor. A further illustration of this relationship is the ISM decision analysis as the basis for the ISC process analysis.

ISM decision analysis (table 9)

The main ISM objective is to increase VARTA’s total profit. The common operational cash flow calculations emphasize the same objective. Moreover, they demonstrate that doing business with customers is an essential component for a company’s profit. Every customer is a contributory factor to the whole income. The single customer profit derives from subtracting all customer-allocated costs from the customer’s net sales. The single Selling Key Unit (SKU) net sales generate these customer net sales. Finally, the SKU profit results from SKU net sales minus all product-specific manufacturing costs and minus allocated customer-initiated costs:

Consequently, VARTA’s profit depends on two key factors: customer consistency and battery prices within a customer’s portfolio. These are the starting point for every profit calculation. Therefore, they represent the main decision areas of existing customer development and customer pricing. The third decision area, potential customer development, derives from customer consistency. Moreover, potential customers in contrast to existing customers do not contribute anything to VARTA’s profit. Therefore, it is reasonable to differentiate between existing and potential customer consistency.

The minor decisions influence the major decision areas (King, 1975). Minor decisions are independent from each other. Therefore, ISM has the possibility to make all of those minor decisions at the same time. Firstly, the commercial partnership strategy constitutes the whole customer selection and planning process. It is necessary in order to harmonize all VARTA conducted customer-specific activities. Secondly, the customer resource assignment represents VARTA’s investments in a customer in order to improve the commercial partnership. Thirdly, the customer portfolio structure implies a customer-specific product-mix, e.g. highly or lowly contributing batteries. Changing this mix would directly affect a customer’s contribution. The decision analysis excludes the battery manufacturing side because it is not ISM’s task to manage these costs.

ISM needs the following planning information in the field of commercial partnership strategy decisions:

The customer status quo and the estimated status quo together must provide enough data to make decisions about either commercial partnership intensification or slowdown possible. Nevertheless, concerning strategy justification, the estimated status quo is more important. This is due to the prediction of a future contribution rate and its close relationship to planning.

The contribution benchmarking process mainly serves as an evaluation and adaptation tool when searching for commercial partnership strategies. Planning evaluation is always a crucial issue within the whole planning process. Firstly, the CIS must integrate the customer status quo as well as the estimated status quo into the benchmarking process. Thereby, ISM is able to evaluate the intended strategy. Secondly, the CIS examines if a customer reaches a defined target position or if a chosen strategy leads to a planned target position. Thereby, ISM can evaluate a strategy’s efficiency. Moreover, it can compare the strategies of different customers by focusing on various gaps between the status quo and the estimated status quo positions. Finally, it is possible to evaluate an already implemented strategy ex post by integrating new customer status quos into old benchmarking processes. Thus, the CIS compares its current position with the before declared target position.

After having defined customer-specific development strategies, ISM must decide on further parameters influencing the existing customer decision area.

The first parameter refers to the available company resource allocation, e.g. customer-initiated business and monetary efforts. Both comprise rebates, promotions, received invoices, sales personnel visits etc. ISM needs the following planning information to make a decision about this allocation:

The customer status quo enables ISM to decide on an appropriate customer-specific investment volume by taking a customer’s potential in covering these allocated costs into account. This potential also comprises product-manufacturing costs not even ISM can influence. Manufacturing costs accrue because it is always a company’s purpose to supply its customers. The proximate shipment causes these costs to become customer-related costs.

Nevertheless, the estimated status quo is essential for planning purposes. Thereby, ISM can examine if a customer is also in the position to cover the costs, plus additional investments, by its future profit. Consequently, based on this budget information, ISM can evaluate an investment decision currently at issue. The second parameter is the customer portfolio structure containing battery types, battery mixtures, and sales volume. ISM needs the following planning information in order to perform its tasks:

This parameter is similar to the first one because the customer development strategy determines the direction.

The customer status quo enables ISM to examine the relationship of profit and costs as well as the relationship between different cost types of different assortment groups, assortments, battery types, and SKUs. In general, SKUs with a high contribution rate enforce the whole contribution rate of battery types. The higher the battery type contribution, the better the assortment contribution. Therefore, a customer portfolio should mainly consist of highly contributing SKUs. ISM must always consider a higher SKU contribution if it makes decisions about changes within a customer portfolio.

The estimated status quo predicts future consequences, which could justify current decisions, e.g. increasing versus decreasing the contribution margin.

Finally, ISC must provide ISM with information about reasons and sources for deviations. This enables ISM to evaluate their strategies with measurable values and by understanding their previous mistakes. Consequently, this provides the opportunity to improve forecasting strategies and adapting them to new conditions in irregular intervals. The included re-deciding processes about current strategies could initiate additional more detailed research reports.

The existing and potential customer decision areas are similar because both deal with customer consistency. The sole exception is the existing impossibility of basing estimations on current data because no customer status quo information is available. This decision area concentrates on commercial partnership approvals and disapprovals as ISM-selectable strategies. Therefore, ISM needs the following planning information:

The potential status quo is similar to the estimated status due to common timeorientation characteristics. Nevertheless, the first potential status quo is more imprecise. Therefore, only a contribution benchmarking process could provide sufficient data for approval or disapproval decisions. Moreover, benchmarking enables ISM to examine if a specific customer increases or decreases VARTA’s total profit. In case of an approval, ISM could evaluate the selected strategy in the same way as in the existing customer decision area.

As in the first decision area (existing customers), ISM must make decisions about the other influence parameters.

The first parameter refers to investment and resource allocation. Thereby, the potential status quo information allows estimating a customer’s capability in covering these additional costs in the future. Additionally, it supports ISM in defining and deciding on an appropriate investment mixture.

The second parameter, concerning the portfolio structure, provides ISM with enough knowledge to find a proper product mixture. Even during customer negotiations, sales personnel could decide either if VARTA should deliver requested batteries or if it should reject this sales volume and offer other batteries instead.

Finally, the deviation analysis, as an improvement and controlling tool, constitutes the last ISM information request. Pre-evaluating an intended customer strategy is impossible. Therefore, a detailed analysis ex post is even more important in order to decide on ongoing customer-related activities, strategy efficiency, and improvement activities.

The third decision area, which represents the second core issue (price), deals with battery pricing. The information provided should facilitate battery price planning and decision-making. Thereby, it must take customer conditions, product conditions, and the market price level into account.

In general, prices derive from cost calculations, which assume specific sales volumes. However, these estimated sales volumes are never precise. Moreover, several costs (e.g. fixed costs) are independent from sales volume. This definitely applies within specific sales volume ranges. Moreover, cost-oriented pricing disregards other influence factors (production, customer, market). Therefore, this approach is insufficient. These price settings may not match an approved market price level or customer perceived price value. Consequently, price guidelines must eliminate this discrepancy by including all other missing influence factors, e.g. paying behavior, average market price level, and manufacturing costs. In addition, these price guidelines allow ISM to monitor fore-mentioned factors influencing customer- oriented price levels.

ISM / ISC “6 W” - method

The first customer status quo-related reasons (WHY) derive from the decision analysis. They induce the following supplementary information flow consisting of aim (covered in decision analysis), layout, and time [(section 3.1); (table 10)].

Firstly, the customer status quo should provide a detailed customer profit and cost examination on SKU level. Thereby, it is possible to monitor customer profit contributions on various cost allocation stages. Secondly, it is possible to observe the interdependency of different profit and cost features, e.g. characterization of strong and weak ratios. ISM could detect if a customer-specific cost-net sales ratio matches the company average. Thirdly, the customer status quo permits evaluating previous investments in a customer (time-oriented benchmarking). Thereby, it supports generating effect diagrams and distance measurement (section 6.3).

The layout (WHICH) of the information output should contain only little key information. Nevertheless, it should condense all customer profit and cost features. The resulting quantative information allows applying calculation methods. Consequently, this prevents a data overflow.

The CIS should provide this customer status quo information in predetermined monthly periods in order to ensure permanent analyses (WHEN). Therefore, ISM can rely on these reports and own reporting becomes superfluous. Nevertheless, a high update frequency boosts the risk of including seasonal buying behavior.

The second benchmarking-related reasons (WHY) comprise a time and statusoriented feature. In general, ISC must provide the information, which determines a customer’s position among all customers (Thiel, 2002).

The time-oriented current-to-current, past-to-current, and current-to-future comparisons evaluate a customer over time. The status-oriented comparisons rate a customer’s current value among all commercial partnerships, e.g. key account or buying association.

Consequently, contribution benchmarking provides timesaving customer evaluation and customer comparison. However, it is rather vague compared to a customer status quo analysis.

This method’s information flow requires more insert and output information due to the high data variety, e.g. features of status quo, estimated status quo, and potential status quo (WHICH). In addition, it comprises additional benchmarking-specific calculation methods enlarging the information pool.

The CIS provides this information merely in annual intervals (WHEN). Therefore, reducing key figures and information volume is irrelevant. This low reporting frequency derives from the risks of benchmarking (pipeline-filling, holidays). These seasonal fluctuations could severely manipulate the result (section 6.3). However, broadening the basis of annual average values almost eliminates these risks.

The third estimated status quo-related reasons, concerning existing commercial partnerships, depend on historic customer experience and knowledge (WHY). Firstly, it makes forecasts based on historic customer information possible. Thereby, ISM can anticipate future customer-specific profit and cost situations. It reveals the customer target position in the contribution benchmarking process. Secondly, it allows precise evaluation and measurement. Thirdly, it facilitates generating strategy- related scenarios comprising best to worst case ranges. Thereby, ISM can decide on countermeasures in advance in case a customer deviates from a previously defined bandwidth.

Estimated status quo reports require monitoring every profit and cost type feature (WHICH). This guarantees accurate forecasting and allows comparisons between status quo and estimated status quo because all sources are researchable. This request naturally induces higher forecasting efforts because an individual estimation for every single feature is necessary. Nevertheless, key figure condensation reduces data overflow.

A CIS should report this estimated status quo information at a predetermined point in time after each quarter or at least after one year (WHEN). The possibility to allocate annually forecasted customer values to the different quarters facilitates this one-year range. Moreover, this annual reporting reduces human labor expenditures. The annual benchmarking and the fluctuation risks emphasize the appropriateness of this frequency as well. On the other hand, such long-term forecasts are difficult to manage and more imprecise. Therefore, it is impossible to take countermeasures caused by deviations in time.

The quarterly reporting lowers these risks because adapting annual forecasts to new circumstances and eliciting deviations within shorter periods is feasible.

The fourth potential status quo-related reasons (WHY) are equivalent to the estimated status quo reasons. The sole exception is the unavailability of historic customer experience. It mainly serves as an estimation and comparison tool for profit and cost features. Therefore, the customer status quo reasons additionally enhance the fore-mentioned reasons. The actual status quo cannot define recently acquired customers because they do not feature historically evident figures. Therefore, the only solution is to equate the potential status quo with the customer status quo. This integrates all potential customers into all reports (ISC process analysis - precision requirements). The differing definition of status quo-related planning and potential status quo-related prognosis demonstrates this discrepancy as well. The term prognosis expresses a more tentative data preparation due to missing experience. This influences all allocation and calculation methods regarding the process analysis.

The thesis compares the terms prognosis and planning with different sorts of headlights. High beams show a dark road’s direction. The supplementary low beams show all details on the surface and in the near surrounding, e.g. black ice and the median. Both devices are necessary in order to keep a vehicle on the track. The first device avoids going in the wrong direction and it provides an overview. However, the journey remains dangerous without the second device. It ensures safety on the track, e.g. evasive maneuvers to avoid an accident. Therefore, the prognosis (high beams) represents a rather vague procedure. Precise planning (low beams) guarantees security during all business operations by emphasizing necessary countermeasures (Deyhle, 2000). The potential status quo must report the same information as the customer status quo and the estimated status quo. Therefore, it comprises the same preparation and layout characteristics (WHICH).

In general, only contracts provide high security regarding negotiated customer arrangements, e.g. pricing, sales volumes, investments (promotion, merchandising, POS-material), and portfolio structure. Therefore, contract articles serve as the best basis for prognosis preparation. ISM and ISC must prepare at least one prognosis after each contract completion (WHEN). One year after the first delivery, the estimated status quo takes charge of reporting this previous potential customer.

However, other circumstances also make a prognosis necessary, e.g. worst and best case scenarios during negotiations. Therefore, repeating it must be uncomplicated with regard to various assumptions.

The fifth deviation analysis-related reasons (WHY) depend on accurate information inserts, which comprise customer, estimated, and potential status quo.

The deviation analysis enables ISC to measure distances between previously determined targets and current situations. ISC is able to discover reasons for inaccurate or false forecasts and estimations. Hence, ISC can rate the impact of deviations on customers. This allows ISM to improve their forecasting and estimation processes. Moreover, ISC can assess all ISM forecasting and estimating activities.

Before conducting an analysis, it is unsure which details could be relevant. Therefore, the deviation-related reporting must monitor all profit and cost types in advance (WHICH). Then, key figures must condense this detailed information flow for ISM.

The CIS must provide these deviation analyses in regular three-month intervals (WHEN). The estimated and potential status quo reporting frequency validates this interval as well. However, due to the CIS being a predictive query system, it is also possible to meet irregular ISM demands. Consequently, executing continuous deviation analyses would be necessary.

The last pricing-related reasons (WHY) primarily derive from different customer, product, and market conditions. In general, pricing must consider commercial partnership durations, customer-initiated costs, customer portfolios, manufacturing costs, customer-roles in markets, and customer value perceptions. A shift in value perception especially affects other product pricing strategies. Many companies disregard this last but most crucial issue.

Firstly, it permits generating several price overviews, e.g. products in general, products within a specific customer portfolio, and products within a specific market. Secondly, ISC can prepare different kinds of price ranges and price guidelines reflecting special condition mixtures (customer, product, market), e.g. “if-then” or “from-to” guidelines.

Prices represent key figures in the first place (WHICH). Ranges consist of several prices. Therefore, price ranges comprise several key figures. They must suitably support ISM’s decision-making process. Consequently, this information flow is independent from additional information elements.

The CIS must provide price information in predetermined annual intervals (WHEN). This frequency guarantees regular price adaptations to new environmental circumstances. Moreover, concerning occasional variations, the possibility for irregular adaptations must be available, e.g. new customer acquisition, new customer contracts, new markets penetration, or new product launches.

ISC Process analysis

The decision analysis and the “6 W” analysis generate output requiring data insert and preparation. These must correspond to the fore-mentioned information areas (decision analysis), operational business characteristics (table 1), aims (section 3.1), time, and layout characteristics (section 3.2). The ISC process analysis is responsible to guarantee this compliance.

The thesis divides the ISC process analysis into customer status quo, contribution benchmarking, estimated status quo, potential status quo, deviation analysis, and pricing output clusters (table 11).

In general, decisions influence two cost areas, which affect these decisions vice versa (Hansen and Mowen, 2000). Therefore, a company’s cost structure points out the following two major cost parameters:

- customer-allocated costs (cost object: customer)
- product-allocated costs (cost object: product)

The first parameter is directly ISM relevant due to customer orientation. The second parameter is only relevant as far as it concerns customer allocation of manufacturing costs. However, it must be possible for the CIS to access all customer and product- related profit features and cost types (excluding indirect manufacturing costs). Consequently, the thesis separates each CIS output cluster into three different input clusters at most:

- customer hard-facts information
- product information
- other customer’s information

The first customer hard-facts cluster comprises the following quantitative profit and cost information (for a specific customer):

- sales volume
- price
- rebates
- outbound costs
- special direct sales costs
- sales costs
- marketing costs
- logistics costs
- sales administration costs
- working capital costs (WCC) for receivables

The second product information cluster contains the following quantitative cost information (for a specific customer’s products):

- inbound costs

- direct material costs
- indirect material costs
- direct labor costs
- indirect production costs
- WCC for stocks
- overhead costs (distribution, sales, research and development)

The “other customer information” cluster comprises this information (customer hardfacts, product information) for all other VARTA customers, e.g. to enable comparisons within benchmarking processes (section 6.3). All included quantitative values could express a current, estimated, or forecasted situation.

The first output cluster is the customer status quo. It requires customer hard-facts information and product information insert. The time aspect, concerning both insert clusters, derives from the previous month. This monthly reporting in contrast to day- to-day reporting lowers possible fluctuation risks (defining delivery dates, transportation distance, order processing). However, monthly reports still contain seasonal fluctuation risks affecting the sales volume, e.g. holidays, pipeline filling, or special customer promotions. Consequently, a company must weigh up the advantages of taking immediate countermeasures (monthly reports) against fluctuation risks.

The information features included in the customer status quo must be very precise. Monitoring on customer level is insufficient because structure-oriented portfolio decisions (decision analysis) require a more detailed diversification. Therefore, the CIS should monitor these features (profit elements, cost types) on label, assortment group, assortment, battery type, and SKU level.

The output layout must be concise. It must report merely ISM relevant and dense quantitative figures. Supplementary key figures (ABC-clusters, benchmarking evaluation) provide ISM with the opportunity to obtain timesaving overviews.

The CIS must offer selection possibilities allowing ISM to summarize several monthly reports, e.g. to unite several months into one quarter, several quarters into one year, or into several years. This compression improves average value generation by employing a broader numerator and denominator basis. These broader bases are more reliable, because ISM can utilize its knowledge about customer fluctuation behavior. Despite this, the CIS must maintain providing standardized longer selection periods on its own because ISM cannot know all fluctuations by experience, especially concerning potential customers. Consequently, these selection possibilities reduce the risk of basing decisions on unintended fluctuations.

As a side effect, ISM can examine a customer’s seasonal behavior. Therefore, ISM must observe the different periodical (monthly, quarterly, annual) sales volumes provided by standardized reporting. However, this examination creates high efforts (long time horizon and continuity).

The customer status quo output requires a high update frequency due to high up-to- date and short-term reporting characteristics.

The applied customer status quo calculations and key figures pertain to the cost accounting area. Nevertheless, ISM must also be familiar with the included terms and types of arithmetic calculations, e.g. absorption costing, direct costing, and profit contribution. This assures a common understanding.

The thesis compares this generated theoretical status quo frame and content with the actual CIS structure within section 5.1. The expired customer status quo reports should remain within the CIS because they allow generating time-oriented overviews. Moreover, the CIS could function as a knowledge database because it contains all historic figures and information.

The second output cluster is the contribution benchmarking. It requires customer hard-fact information, product information, and other customer information insert, e.g. customer status quo, estimated status quo, or potential status quo. One-year-old contribution benchmarking reports are sufficient because they back up tactical decisions (versus operative business characteristics). The requested insert (accumulated current values) of last year’s values meets this tactical request. The design and update frequency must also match these tactical characteristics.

Fluctuations easily manipulate the benchmarking result. Therefore, a benchmarking process is never as precise as a customer status quo analysis. However, a CIS output in less detail could at least dilute the severe impact. Consequently, it should merely focus on customer, assortment group and assortment level.

The CIS layout must comprise this huge insert and calculation method volume by maintaining a clear design. Therefore, it must provide only core messages and key figures, e.g. charts. Additionally, qualitative variables including gap, position, and cluster values (section 6.3) enhance the accounting-related key figures.

New contribution benchmarking reports must retain the customer-specific values of previous benchmarks. This provides time-oriented overviews in addition to statusoriented comparisons. Therefore, time-oriented measurement methods are necessary. Annual standardized reporting keeps update frequencies low.

ISM does not need to be familiar with these more complex calculation methods because the qualitative message directly derives from common ISM key figures. If a deeper analysis is necessary, ISM can use information from the customer status quo report. Additionally, ISC could prepare irregular more problem-oriented research reports. The thesis compares this generated theoretical contribution benchmarking frame and content with the actual CIS structure in section 5.3 and section 6.3.

The third output cluster is the estimated status quo. It consists of customer hard-facts and product information insert clusters. In addition, it is similar to the customer status quo. The output anticipates forecasted customer status quos. The insert values represent quarterly budget values. If these values were unavailable, annual budget values in conjunction with supplementary allocation methods could replace them. Short quarterly intervals allow an easier and more accurate forecasting procedure because ISM can anticipate irregular customer development.

The customer assortment is the minimum preciseness level. A forecasting below this level is merely “wild guessing”. A sales department could determine a customer assortment mix (Alkaline, Photo, Maxitech, and Value Pack). However, it is nearly impossible to determine which battery type-specific sales volume (4003, 4006, 4012, 4015, etc.) a customer will order.

The output layout may only contain key information and key figures condensing all profit and cost elements.

The CIS must provide this estimated status quo information within predetermined intervals (each quarter and each year). The quarterly reporting serves as a supplementary tool. It aligns previous annual budget values with current environmental circumstances. Therefore, the update frequency is higher.

The calculation methods comprise direct and absorption costing. ISM must be familiar with applying these calculation methods. The thesis compares this generated theoretical estimated status quo frame and content with the actual CIS structure in section 5.1.

The fourth ISM-related information output cluster is the potential status quo. It contains customer hard-facts and product information. The potential status quo is an acquired customer’s status quo and an estimated status at the same time. Therefore, product information-related inserts comprise forecasted manufacturing costs. The customer hard-facts inserts contain estimated values. These estimations derive from vague negotiations or assumptions. Forecasting and estimation processes pertain the next quarter and year. Consequently, concerning negotiations, current values derive from the actual state of affairs or the latest contract.

This potential status quo, mainly based on negotiations, is rather imprecise due to the numerous individual statements involved. Even contracts as a basis, do not make it completely precise because it is unreasonable to include all eventualities. Nevertheless, ISM must estimate the most precise SKU level because the potential status quo substitutes the yet unavailable customer status quo. This customer status quo requires this SKU preciseness. Usually, a contract lists SKU-specific sales volumes and prices. Therefore, it is rather easy to perform this task (SKU level reporting).

The CIS must provide this potential status quo information in a comprehensible way comprising only influenceable and relevant key information and key figures.

The ISM necessity for creating scenarios and prognoses varies. Therefore, update frequencies depend on their requests (no predetermined periods).

Direct and full costing calculation are basic calculation methods. In addition, cost drivers referring to all customer-oriented activities are necessary. They ensure accurate data inserts by detailing cost causing activities. ISM must report non-cost- oriented drivers, e.g. hours, visits, outlets. Therefore, ISC must decide on appropriate cost drivers completely matching these cost characteristics. Thereby, ISM could perform standardized and exact forecasting. The thesis compares this generated theoretical potential status quo content and frame with the actual CIS structure in section 5.1.

The fifth output cluster is the deviation analysis, which consists of customer hardfacts, product information, and other customer information (see customer status quo). The deviation analysis either analyzes the deviation reasons of two status quos differing in time of the same customer or of two simultaneous status quos of two customers. Therefore, the thesis divides this insert cluster into customer status quo, estimated status quo and potential status quo.

A deviation analysis must provide precise values concerning SKU. Firstly, a research process could exactly identify deviation sources. Secondly, it could measure the deviation. Finally, it could anticipate a deviation’s effect on future business.

The information preparation must provide a concise ISM output allowing quick analyses. Therefore, concerning ISM, the CIS should merely highlight deviation areas and it should illustrate their impact. In case a deeper examination was necessary, ISM could ask ISC or it may utilize other information outputs. This ISM-related information flow should solely contain key information and key figures.

A CIS must report deviations in monthly and quarterly intervals in order to initiate countermeasures in time. This prevents overloading the information flow because the data volume is small but essential. The monthly interval request derives from monthly status quo reporting. The quarterly interval derives from the necessity to exclude fluctuation impacts from reports.

ISM should only receive condensed results because they contain complex calculation methods. Those reports are supposed to highlight crucial business processes for ISM purposes. The thesis compares this generated theoretical deviation analysis frame and content with the actual CIS structure in section 5.3 and section 6.2.

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