Excerpt
Table of Contents
1. Thesis:
1.1 Management summary
2. Introduction
2.1 Prerequisites
2.2 Selecting measures
3. Other Methods
3.1 Cash-value method, net present value (NPV)
3.1.1 Area of application
3.1.2 Frequency of use
3.1.3 Preconditions
3.1.4 Implementation
3.1.5 Advantages
3.1.6 Disadvantages
3.2 Variations of this method
3.3 Real Options
3.3.1 Evaluation of flexibility with real options
4. Transferring to value added network design
4.1 Monte Carlo Simulation
4.2 Introduction To Monte Carlo Simulation
4.2.1 How Does Monte Carlo Simulation Work?
4.2.2 Monte Carlo: Based On Probability & Chance
4.2.3 What Is Monte Carlo Simulation Good For?
4.3 Evaluating the methods:
5. What is my suggestion and why?
6. General Notes about KPIs
6.1 Targets and customer benefit for KPI implementation and controlling
6.2 General comments and guidelines on KPIs
7. Methodology and approach
7.1 KPI Diagnosis
7.2 KPI Design
7.3 KPI implementation
7.4 KPI Controlling
7.5 Embedding KPIs in organization processes
7.6 As an example:
7.7 Plan
7.8 Source
7.9 Make
7.10 Deliver
8. The limits to using indicators
8.1 Current indicator types in various corporations and industrial sectors
9. The classical indicator system
9.1 The Du Pont indicator system
9.2 The ZVEI indicator system
9.3 The RL indicator system
9.4 Measures portfolio
9.5 Plan: Measures in the “plan” area
9.6 Source: Measures in the “source” area
9.7 Make: Measures in the “make” area
9.8 Deliver: Measures in the “deliver” area
10. The context between improvement measures (enablers) – KPI and KPI elements
11. The Value Analyzer
11.1 Basics:
11.2 KPI data input mask
11.3 KPI element data input mask
11.4 Industry data input mask
11.5 Enabler data input mask:
11.6 Category data input mask
11.7 Improvement range data input mask
11.8 Share range data input mask
11.9 Calculation form:
11.10 Allocation factor:
11.11 Improvement factor:
11.12 Calculate
11.13 KPI values for Customer
11.14 Calculation for Customer Form
11.15 The Reports
11.15.1 Show improvement report
11.15.2 Show share report
11.15.3 Show allocation report
11.15.4 Show value added report (KPI)
11.15.5 Show KPI report
11.15.6 Refresh
12. Calculation Example
12.1 Sample Calculation KPI: Account Executive Push
12.2 The change of KPIs value
12.3 Input Value Validation 1:
12.4 Input Validation 2:
12.5 Value Analyzer
12.6 Calculation Form
12.6.1 Industry:
12.6.2 Customer:
12.6.3 KPI:
12.6.4 KPI Element:
12.6.5 Category:
12.6.6 Enabler:
12.6.7 Calculation Matrix Mask
13. The Reports
13.1 Improvement Report
13.2 Allocation Report
13.3 Prioritising Measures
13.3.1 Developing the mathematic formulas
14. Conclusion
List of Tables
Figure 1: Methodology and approach in KPI control and implementation
Figure 2: Generic corporate process structure
Figure 3: Extract from the KPI-Enabler- Matrix
Figure 4: Extract from the KPI-Enabler-Matrix
Figure 5: Extract from the KPI-Enabler-Matrix
Figure 6: Extract from the KPI-Enabler-Matrix
Figure 7: Extract from the KPI-Enabler-Matrix
Figure 8: Extract from the KPI-Enabler-Matrix
Figure 9: Extract from the KPI-Enabler-Matrix
Figure 10: Extract from the KPI-Enabler-Matrix
Figure 11: Enabler`s Impact on the Elements
Figure 12: Illustration of the relationships
Figure 13: Assigning the value range to a selected KPI-Element
Figure 14: Calculation structure
Figure 15: Assignment of the Share-Factors to the KPI-Elements
Figure 16: Assignment of the Allocation Factors
Figure 17: Assignment of the Improvement Factors
Figure 18: Illustration the Impact Factor Calculation
Figure 19: Illustration of Impact Factors
Figure 20: Illustration of the Impact Factor Matrix
Figure 21: Illustration Share Factors
Figure 22: Illustration of the relationship between Enabler and KPI
Figure 23: Illustration of the calculation results
Figure 24: The change of the KPI values
Figure 25: The impact of enablers on the KPI-Element
Figure 26: The impact of the KPI-Elements on the KPI
Figure 27: Illustration of the “Data Input Mask”
Figure 28: Illustration of the “Calculation Form”
Figure 29: Illustration of the “Value Analyzer – Calculation Matrix”
Figure 30: Illustration of the “Improvement Report”
Figure 31: Illustration of the „Allocation Report“
Figure 32: Change of Enablers
Figure 33: Illustration of Business Scenario
1. Thesis:
Calculating the Influence of Improvement Measures on Corporate KPIs
Improvement measures and key performance indicators – factors that influence corporate performance indicators - are not sufficiently calculated and prioritized by most companies!
The following work covers the correct calculation of improvement measures and their influence on predefined key performance indicators or KPIs. In a business area constantly subject to change, corporations are also constantly forced to change themselves. Not only strategic approaches, but also methods by which business is carried out have to be constantly re- evaluated and possibly adapted.
In order to reach this change and the improvement of specific KPIs involved, corporate management has to introduce appropriate measures, which requires transparency – transparency in the company itself regarding its own performance indicators, opportunities for improvement, and the influence of these opportunities on improving performance indicators.
1.1 Management summary
In order to do justice to the increased requirements on project and business controlling, there is a need for a systematic approach tailored to the corporation involved. Many corporations have been shown to prioritize improvement measures insufficiently, if at all, despite increased requirements on the economic viability of projects. Since resources are limited in all companies, improvement measures with the highest relative output should be given preference. The usual methods used up to now have been either inappropriate or are no longer sufficient.
The Value Analyzer is a method-supported tool for estimating the expected improvement of key performance indicators as a part of a general improvement in corporate performance.
This makes it easy to focus on worthwhile measures and supports a general economic calculation to base a go/no go decision on before the start of an implementation project.
Based on general key performance indicators, specific scenarios can be created and then altered and/or simulated by changing the parameters or factors of influence. This is all based on a three-level principle in the calculation model:
- Definition of a primary goal, KPI (key performance indicator, for example inventory level)
- Breakdown into part goals, KPI elements (performance indicator element, for example finished products inventory level)
- Determination of appropriate measures for improving the part goal
In the calculation of business scenarios that follows, the exact impact of enablers and the optimal combination of appropriate measures can be revealed, or possible measures can be prioritized according to specific aspects (e.g. effort in implementation).
The more complex the situation, the higher the value added from the Value Analyzer’s structured solution.
2. Introduction
The following work covers the correct calculation of improvement measures and their influence on predefined key performance indicators or KPIs (key performance indicators). In a business area constantly subject to change, corporations are also constantly forced to change themselves. Not only strategic approaches, but also methods by which business is carried out have to be constantly re- evaluated and possibly adapted.
In order to reach this change and the improvement of specific KPIs involved, corporate management[1] has to introduce appropriate measures, which requires transparency – transparency in the company itself regarding its own performance indicators, opportunities for improvement, and the influence of these opportunities on improving performance indicators.
A recently published study by the Gartner Group concludes that 20 percent of the $2.9 trillion invested in IT worldwide in the year 2002 failed to create any positive effects; the money was therefore wasted.
Thus, it is no surprise that so-called ‘ROI studies’ (return on investment), that is, examinations on possible returns from a planned IT investment, and new methods for ROI evaluation are enjoying high popularity. However, assessing the economic sense of an investment is not easy; IT is a so-called ‘general-purpose technology’ with only very indirect financial impact on the financial result. Its productivity can only reach its full potential in combination with other factors.
Calculating single IT investment projects alone by whichever method is not the road to success. A good example of this is an American electricity provider, where more than 20 business cases for planned IT projects were presented to the IT steering committee. When the controller present added up the anticipated savings in costs and staffing, he concluded that if the company approved all of the IT projects, they could save on 110 percent of the staff.
Obviously, an initial business case is still an important instrument for value management in IT investments. However, less importance can be placed on such a business case as a basis for the approval of a project regarding productivity improvement targets than is generally thought. Benchmark studies have shown that success in the actual realization of productivity improvements by the introduction of new IT components is mainly dependent on how such projects are managed – whether and how consistently progress is measured, and whether continuous decisions on optimization affecting the whole investment portfolio are met appropriately on the basis of this information. Projects have a better chance of success if they are based on the common initiative of IT and business or specialist division or department, and are therefore more likely orient themselves towards actual business benefit and practical applicability.
Successful project realization and the calculation of improvement measures involved is the subject of this work. Prioritization is necessary in assessing the best possible combination of improvement measures. The success of every single project can be measured by long-term improvement in the key performance indicators directly involved.
2.1 Prerequisites
This requires some prerequisites that have to be fulfilled before anything can be measured or calculated.
‘You cannot manage what you do not measure’
Intelligent indicators that match the company[2] and increase transparency have to be applied to business processes on a long-term basis and embedded in the company’s culture. Only those who have reached clear, transparent indicators can also use them to make accurate statements about opportunities for influencing them.
Some indicators affect each other, or even conflict. The intention to minimize inventory, for example, might conflict with the requirements for improved delivery capacity or the made-to-stock principle.
Thus, in this case, overriding corporate strategy needs to be straightened out as the first step. Developing suitable measures for improving one of either of these indicators follows as the next step. How exactly this should happen will again be treated thoroughly, leading up to the solution scenario.
2.2 Selecting measures
In the second step, the opportunities for influencing these indicators have to be weighed up and appropriate improvement measures defined. Usually, management is faced with a plethora of improvement measures, but it cannot implement all of them since the resources of any company are limited.
Consequently, the most appropriate improvement measures under the relevant considerations and circumstances need to be implemented. The selection criteria are diverse in type – according to ROI, categorized according to costs incurred in the future, or all measures that can be implemented under their own steam right away.
According to the situation, the appropriate mix for the situation involved needs to be found, and the construction of a business scenario is unavoidable. It must be possible to simulate this scenario with the relevant considerations in mind in order to play through various scenarios, create various business cases, and prioritise measures.
Most corporations underestimate these requirements for sensible improvement projects and prioritise their own improvement measure mix insufficiently, if at all. In the past, appropriate systematic approaches for corporate implementation have been few and insufficient. Most of these approaches are either too complex or they lack focus. They do not satisfy the requirements in prioritising improvement measures according to appropriate parameters.
3. Other Methods
Which other common measure calculation methods are used in companies?
Assuming a large number of diverse evaluation methods of varying quality, this work shall refer to the most common and most frequently used methods.
3.1 Cash-value method, net present value (NPV)
The cash-value method calculates the cash value of an investment. This is equivalent to the value that future payment would have today, that is, interest is discounted from the future value. Usually, the discounting period will start with the start of the investment and is not applied to the initial outlay. All further receipts and/or payments and their surpluses, that is, savings, are matched up to the period in which they are incurred, added together, and the discounted value is calculated[3].
The discount rate can be either the interest rate on the open financial markets or a certain internal preset interest rate. A positive cash value is equivalent to a capital value gain of today, but is only realized if the prognosis is correct. Calculating the cash value of the investment is then all that is needed to assess its advantage. If this is more than or equal to zero, the investment presents an advantage. In comparing several investments, the one with the highest cash value should be given priority.
3.1.1 Area of application
The cash-value method and its variations can be used in practically all investment decisions. This applies to both individual and project decisions as well as replacement decisions.
3.1.2 Frequency of use
The cash-value method is one of the most frequently used investment forecasting types, especially the internal interest rate method and in combination with the annuity method. In general, there has been a reinforced introduction of dynamic methods since the seventies. According to studies[4], the internal interest-rate and cash-value methods (in approximately two-thirds of all companies) are the most heavily represented.
3.1.3 Preconditions
The existence of a perfect market for capital is assumed; that is, funds can be invested and raised in unlimited quantities at a uniform interest rate.
Prognoses for the series of payments have to be as accurate as possible and reliably calculated.
3.1.4 Implementation
First, the initial outlay and the annual payments are calculated and forecast. Additionally, an interest rate needs to be set for the calculations, which can be an internal interest rate or the market rate. After that, payment or receipt surpluses are matched to the period and the discounted time value is calculated. If the cash flow cannot be matched accurately enough to a period, discounting can be applied on a continuous basis. At the end, the discounted values of the annual cash figures are added up and the whole cash value is then used as the decision criterion.
The decision is now based on whether the cash value is high enough, or especially whether it is positive, and how an alternative investment would develop.
3.1.5 Advantages
- Little calculation effort
- Expressive
- The dynamic method takes several time periods into account, and is therefore closer to reality than static methods
- By applying a minimum interest rate, a certain level of security is also included
3.1.6 Disadvantages
- The various options for tying in capital at the beginning or during the period of observation are not included
- a large number of prognoses and assumptions and necessary in calculating the data
- Does not include risk analysis
- The assumption of a perfect market for capital does not correspond to reality
3.2 Variations of this method
One variation is the internal rate of return method. This corresponds to the calculations in the cash-value method. However, not the capital cash value is calculated, but the internal interest rate that results from a cash value of zero. In analyzing the advantage of the investment, this interest rate is compared with the market rate to find out whether it is higher or not[5].
The end-value method is also a variation. Here, no discounting is applied to the starting point of the investment, but interest is applied to payments at the end. Also, any other period can be taken as the point of reference.
Yet another variation is the annuity method, where the cash value refers to equally high payments each year, referred to as an annuity.
Further methods are also accounted for by calculations in various forms for the series of payments. Apart from initial outlay and net revenues, disposals, tax payments etc. and diverse interest rates can be included for consideration.
3.3 Real Options
An option is a right – but not a duty – to purchase (or sell) an investment within a certain set period at a certain preset amount[6]. Exactly the same definition applies to a real option, only a real option does not only apply to financial markets but also to ‘everyday’ deals. For example, if you invest in a first generation of a certain kind of microprocessor, you gain the right – but not the obligation – to develop a second generation of processors in a preset time period (window of opportunity) at a preset price (the desired investment for the development of the second generation).
The real options approach uses the theory of financial options, of which the Black-Scholes model[7] is the best known, as a basis for calculating the future value of real investments. The main advantage of this approach is flexibility for corporate management for the point in time that certain investments are activated being included in the investment value calculation.
However, the real option approach is not easy to implement in practice, and requires a clear understanding of the basic preconditions. Project and portfolio devaluations in corporations should be carried out in the same way as the booked financial option value is determined – time points for investments and flexibility for future decisions are thus improved for management since a clear understanding of the basic risks involved is present.
3.3.1 Evaluation of flexibility with real options
As competitive pressure increases, increased demands are made on corporations for option allocation with the scarce resources available. If decisions have to be made on several investment alternatives or prioritization of alternative improvement measures, corporations need processes for objective assessment of various investment opportunities or alternatives.
Complex projects can be broken down into subprojects that are separated from each other by milestones. Deciders should have the possibility of observing and analyzing the various periods.
Based on that, corporate management can adapt or confirm decisions made in the past to match the changing economic situation. This freedom of action for corporate management represents the flexibility that affects investment project value. A well-founded assessment of investment and project alternatives therefore requires processes that also take into account the value of this flexibility[8].
The analogy between real and financial options can be illustrated by three main features. These features were originally used to describe the characteristics of financial options, but are perfectly suitable for explaining the behavior of real options.
They are as follows:
- Flexibility: the bearer of an option has the right to carry out a certain transaction or to let the option expire, in other words not to realize the improvement measure, depending on how the base value develops.
- Uncertainty: option value development depends on the development of the base value, and under certain circumstances, on stochastic influences, and is therefore relatively uncertain.
- Irreversibility: options lose their value when they are either exercised or allowed to expire by the bearer. They are therefore irreversible since the rights conferred by the option expire when the option is exercised.
The requirement for a formula that considers all relative parameters and delivers a clear result for the value of an option was developed in the seventies by Black, Scholes and Merton, which brought them the Nobel Prize.
The basis for a well-founded evaluation is a classification of real options oriented towards the diversity of actual economic flexibility. The following illustration of interactions is not free of overlap; especially in projects for improving a certain KPI, individual improvement measures can often overlap or repeat themselves.
With regard to interactions, three basic kinds of option can be distinguished – learning option, growth option, and insurance option.
Learning option:
- Wait option: The investment can be delayed until definite information has been received.
- Call option: Subdivision of the investment in part investments, where each part investment is evaluated under consideration of new information.
Growth option:
- Innovation option: The investment is generated by the accumulation of know-how options on subsequent projects with considerable earnings potentials.
- Expansion option: Option for expanding existing capacities in order to realize higher outputs of existing product or service ranges in cases of favourable market development.
Insurance option:
- Capacity change option: The investment generates options and the flexibility to adapt the existing capacities to altered market conditions.
- Switch option: The option to switch between alternative production factors, products, locations, and suppliers in order to react flexibly to altered market conditions.
- Exit option: The option to abandon a project or measure due to unfavourable development before its completion.
Especially insurance options enable corporations to react to favorable and adverse market changes, particularly in the supply-chain management field. Corporations confronted with high levels of risk and market fluctuation mainly profit from switch options[9].
4. Transferring to value added network design
Of all of the real options, especially the so-called switch options can be used according to their flexibility for corporate risk management. Likewise, it is also possible to control projects with regard to changing environmental influences.
Here, project flexibility is the most important factor. In principle, investments can be divided up for exposure flexibilization in measures to decrease complexity and to increase operative flexibility.
Once the decisive information for project control is made available, an optimized solution can be found.
The goal of the real option approach is to represent the value contribution of decision flexibility, or the ability of management to adapt its executive strategies to changing economic conditions. These options can especially be accepted and evaluated in preparation for the future situation.
4.1 Monte Carlo Simulation
4.2 Introduction to Monte Carlo Simulation
Monte Carlo simulation is a stochastic technique used to solve mathematical problems[10]. The word ‘stochastic’ means that it uses random numbers and probability statistics to obtain an answer. Monte Carlo methods were originally developed for the Manhattan Project during World War II. However, they are now applied to a wide range of problems - nuclear reactor design, econometrics, stellar evolution, stock market forecasting etc.
4.2.1 How Does Monte Carlo Simulation Work?
The term ‘Monte Carlo’ comes from the name of a city in Monaco. The city’s main attractions are casinos, which run games such as roulette wheels, dice and slot machines. These games provide entertainment by exploiting the random behaviour of each game.
Similarly, Monte Carlo methods randomly select values to create scenarios of a problem[11]. These values are taken from within a fixed range and selected to fit a probability distribution [e.g. bell curve, linear distribution, etc.]. This is like rolling a dice. The outcome is always within the range of 1 to 6 and it follows a linear distribution - there is an equal opportunity for any number to be the outcome.
4.2.2 Monte Carlo: Based On Probability & Chance
In Monte Carlo simulation, the random selection process is repeated many times to create multiple scenarios. Each time a value is randomly selected, it forms one possible scenario and solution to the problem. Together, these scenarios give a range of possible solutions, some of which are more probable and some less probable.
When repeated for many scenarios [10,000 or more], the average solution will give an approximate answer to the problem. Accuracy of this answer can be improved by simulating more scenarios. In fact, the accuracy of a Monte Carlo simulation is proportional to the square root of the number of scenarios used.
4.2.3 What Is Monte Carlo Simulation Good For?
Monte Carlo simulation is advantageous because it is a ‘brute force’ approach that is able to solve problems for which no other solutions exist. Unfortunately, this also means that it is computer intensive and best avoided if simpler solutions are possible. The most appropriate situation to use Monte Carlo methods is when other solutions are too complex or difficult to use.[12]
Monte Carlo simulation is therefore one possibility of solving problems and answering questions using a stochastic approach. The disadvantage is that experience and influencing factors cannot be properly included. The solution should always be as close as possible to events that occur in the future, not to stochastic figures.
4.3 Evaluating the methods:
The cash value method, including sensitivity analysis and Monte Carlo simulation, has a decisive disadvantage compared to real options. The strategic alternatives and the view into the future are strictly limited or not possible at all. The decisive factor, flexibility, is no longer sufficiently taken into account.
Although he real-option approach is difficult to apply due to the problems mentioned above, it certainly has serious advantages in comparison to traditional evaluation methods. This especially applies to the kind of decisions that involve a lot of uncertainty or risk[13].
However, in all of the approaches already mentioned, mainly the figures themselves and the possible level of result need to be examined. However, the individual factors of influence and the relationships they have to one other are far more important than just the figures. A future scenario full of variation can only be constructed and simulated under a defined structure of relationships and regulations. This creates the flexibility and variety of information so that deciders have the material they need to determine the optimal solution or solution mix in a constantly changing business environment[14].
5. What is my suggestion and why?
As we have seen in the analysis above, there is no sufficiently appropriate method for determining or simulating the effects of improvement measures on key performance indicators (KPIs). None of the methods above can sufficiently provide calculation results or comparison, if at all, of measures taken in response to environmental influences.
In this context, it is important to consider the impact of individual measures on the key performance indicator (KPI) involved, especially if a KPI can be divided into several subordinate KPI elements, and one measure has influence on more than one KPI element, or vice versa, several measures have an impact on the same KPI element. There can also be cross functionality that cannot be presented using the usual methods. The more complex the business scenario that develops, the more important it is to develop a uniform systematic approach for evaluation. In order to reach this goal, several prerequisites need to be fulfilled.
The indicators must have meaningful definitions, and they especially need to be embedded in the business processes on a long-term basis.
Based on corporate indicators, specific scenarios can be developed and finally altered or calculated by changing the parameters or influential factors. As a basis, the three-level calculation method is always used:
- Definition of a primary goal or key performance indicator (corporate indicator such as inventory level)
- Division into part goals, KPI elements (an indicator element such as level of finished-goods inventory)
- Determination of appropriate measures for improving these part goals
The impact of the measures on the KPI elements on the one hand, and the influence of the KPI elements on the KPI that actually needs improvement on the other, are assessed.
The business scenario thus created can be simulated and altered regarding the measures until an optimal mix is extracted from the portfolio of measures available. Thus, corporate management can flexibly react to the changing business environment creatively, using simulation.
Answering the question, ‘what happens if I do not reach the defined result with a certain measure from my mix?’ is far more important. How can you change the interaction of forces within the measure mix to keep the impact on the KPI consistent? Calculations and simulations of this type can be made with the ‘Value Analyzer.’
6. General Notes about KPIs
‘You can not manage what you do not measure’
In keeping with this principle, that is, the ability to use KPIs as a dimension in the sense of corporate control, much sensitivity is needed in defining and selecting KPIs. In the following, I will cover the general points that have to be fulfilled so that the systematic approach for corporate control using KPIs can be sensibly applied.
6.1 Targets and customer benefit for KPI implementation and controlling
- Continuous success measurement for business activity
- Transparency in the economic viability of activities
- Efficient risk management in business activity – fast identification of transformation and project risks
- Prioritisation and flexible control
- Turning individual activities into a system
- Alignment of all activities to transformation goal
- Increasing implementation speed as well as employee motivation by issuing clear goals and instructions
- Opportunities for establishing incentive systems for staff involved in the program
6.2 General comments and guidelines on KPIs
The KPIs refer to the total functions across the organization, however it is organized (e.g. degree of decentralization) or provided (e.g. degree of outsourcing)[15].
For education authorities, this should include schools for administrative but not for curricular use.
All information should relate to the current financial year, but all costs should relate to the out-turns for the previous financial year Where trading accounts are operated, costs should be used, not the charges made to internal customers Costs should be collected in accordance with the CIPFA Best Value Accounting Code of Practice or similar body for non-public service organization Wherever possible, the definitions take a user perspective, rather than that of an ICT specialist The figures presented to should be the final figures with no further calculation required. Unless specified otherwise, they should always be rounded to the nearest whole number.
There is space attached to each KPI to add qualifying comment. This allows members to add any information about the way they have interpreted the KPIs, or any inclusions / exclusions etc. These comments can be analyzed later when the KPIs are formally reviewed.
KPIs should not be an end in themselves. They are only a start to a proper informed debate that should lead to a plan for improvement. In other words, they are no more than an aid to management[16].
They should be seen within their local context and have much more meaning as a comparison over time than as a comparison between organizations. They should be used to indicate improvement and not as a league table of performance Local government is diverse by nature of size, geography, politics and culture. The local context has to be understood when interpreting KPIs.
For example, different approaches to the internal market influence information about costs.
A set of performance indicators should be balanced. Measures of efficiency should be set against measures of effectiveness and measures of cost against quality and user perception.
The indicators set out here are only indicators. Sometimes it is suggested that they exclude measurements on all aspects the service. For example, some indicators examine costs (e.g. connections to the data network) but do not cover all aspects of cost (e.g. centralized operating costs for facilities such as mainframes). The KPIs are not intended to be comprehensive in this way, but merely highlight those elements of cost that are an indicator of cost efficiency.
Measures of effectiveness are very difficult to determine and best practice research from across industry sectors (e.g. from Gartner Group) confirms that this is a question causing difficulties everywhere.
This means that this set has no measure of effectiveness.
KPIs will change over time. This is particularly true of ICT as the technology develops. For example, service availability may have once been a KPI but improvements in reliability of equipment and software have improved performance to the extent that it may no longer be worth measuring.
The set of KPIs described here are only a first step. In time it is expected that they will be updated and extended.
It may be that in time models such as the EFQM Excellence Model will provide a more solid foundation for performance measurement.
7. Methodology and approach
An incremental, clearly defined approach is of paramount importance so that a uniform process for the creation of KPIs can be implemented. This ensures that KPIs have a uniform quality and are created according to the same ‘blueprint’[17]. The result is a basis of comparison, not only inside the company between the individual departments, but also especially in corporations that consist of several different members that have been consolidated[18].
Abbildung in dieser Leseprobe nicht enthalten
Figure 1: Methodology and approach in KPI control and implementation
This serves as a basis for both corporate control and employee motivation.
In the following, I will give a more detailed description of the individual elements in controlling and implementing KPIs since these will then provide the basis for performance indicator-based simulation using the Value Analyzer.
7.1 KPI Diagnosis
This first phase will deal not so much with the KPIs themselves, but rather the circumstances and activities inside the corporation involved, as well as an inventory assessment of the relevant processes and the KPIs already available
Content:
- Corporate activity inventory
- Segmentation and matching of activities to processes, areas, and departments
- Reconciliation of individual projects: testing for redundancy, intersecting data, interactions, etc.
- Inventory of existing KPIs, dimensions and metrics
- Determining contact persons and employees responsible
- Agreement on results with the program management
Goals:
Finding answers to the following questions
Summary of business projects and therefore transformation status
- What projects are there, and how do they a match up to each other (segmentation)?
- How can the projects be evaluated (importance, prioritization)?
- Have these projects or activities already been measured, and has there been clarity as to their status of implementation or project results up to now?
- How can the measurement quality be evaluated?
Creating a basis for phase 2: narrowing business fields down to those that should have KPIs defined for the specific case at hand.
[...]
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[2] Horvath, P. , München 1996, Controlling
[3] Brigham Eugene F. , Financial Management, 10th Edition
[4] Blohm and Lüder, Investitionscontrolling, München 1997
[5] Eugene F. Brigham and Michael C. Ehrhardt, Financial Management: Theory and Practice
[6] Markus Schärer, Pascal Botteron (Schweizer Treuhändler 11/01)
[7] Kevin Rubash, Bradley University (A Study of Option Pricing Models)
[8] in the sense of Liebermann & Montgomery, 1988
[9] in the sense of Liebermann & Montgomery, 1988
[10] Duane Bong, visionengineer.com, Monte Carlo Simulation
[11] Herbert C. Frey, Gero Nießen ,Monte Carlo Simulation, 2001
[12] Duane Bong, visionengineer.com, Monte Carlo Simulation
[13] Markus Schärer, Pascal Botteron ,How to Evaluate the Value of Strategic Projects
[14] Verstaen von, Jens, Müllner, Andreas, Strategisches SCM Management durch SCM Assessment, München, 2002
[15] Krause, Prof. Dr., Logistikcontrolling 1997
[16] Österle, H, Prof. Dr.,HSG, Wissensorientierte Führung, 1999
[17] Siemens Business Services, Guideline for KPI Implementation, 2001
[18] Siemens Business Services, Management Consulting, 2002