posted 1 Jan 2001 in Volume 4 Issue 4
Mapping the value of knowledge managementThe successful implementation of a knowledge management programme often depends on an ability to demonstrate a clear return on investment to those sponsoring the initiative. Alexander P. Bünz and Gabriele Kirch-Verfuss describe a method developed at Degussa-Hüls to measure the value of KM activities in quantitative and qualitative terms.
Knowledge management has become one of the hottest management issues of the last three years. Primarily this is because knowledge is a hidden, largely undervalued asset, and the well-chosen management of it is considered key to gaining competitive advantage in the market place. Other benefits you frequently hear of are increased learning and output of research, more effective operations and processes, faster adaptation to change, cost savings and, sure enough, higher revenues and margins.
Does this sound promising enough to jump right into a costly knowledge management programme in your company? Have a look at some of the challenges we faced at Degussa-Hüls when we started our KM initiative with a variety of pilot projects.
First we had to find out that different stakeholders had different needs: The decision-makers of the participating business units asked for bottom-line values of KM activities to justify their investment with respect to personnel, time and money for appropriate IT solutions, support and training. Then, there were the people from the business units working with us in the pilot projects who wanted to see the effects of KM on their values. For example, the income-gaining value of newly acquired knowledge, the security value derived from on-going employment, and the prestige and personal growth value. Still other values were put on the agenda from the members of our KM steering committee. They wished to steer effectively and thus needed clear, transparent value propositions for all potential pilot projects, plus a method allowing for easy comparison of value propositions. Finally, we as the corporate KM team had to allocate our limited resources to the most value-adding pilot projects and select the most appropriate KM methods and tools.
So, the challenges were twofold. We had to select the right projects, and at the same time attain long-lasting support from the business units on all levels of management. This meant we had to address and fulfil the needs of all stakeholders by delivering quantitative and qualitative proof of the value of KM activities prior to actually running the projects. Simply showing a list of popular benefits would not do the trick. Our mission was to design a system for measuring the value of KM activities.
Let us first quickly scan what others have so far achieved in this field, before we dive into what we have done at Degussa-Hüls to complete this mission.
Skyrme (1998) distinguishes three foci of methods for measuring the value of knowledge:
Relating to the ‘asset focus’ are methods for calculating the Economic Value Added (EVA) and the Market Value Added (MVA) (Sawers, 1996). Basically, these methods are about calculating the difference between the operating profit and the cost of capital, or the difference between the market value (less debts) and the money invested in a firm. Sure enough, analysts like these methods, as they help them to value and rank companies. However, such methods will not tell you how to propel your company up the list of most valued companies.
Balancing performance measures in scorecards is an example of the ‘action focus’. At the core of the groundbreaking work of Kaplan and Norton (1996) are four dimensions for measurement: Customer, innovation and learning, internal processes, and finance. For each of these dimensions, measures are developed that are traced over time. In the last few years balanced scorecards have gained immense popularity. However, there are some serious pitfalls, one of which is that measures are not strictly linked to business objectives throughout all levels.
North et al’s multidimensional measuring system for knowledge (1998) has a clear ‘benefit focus’ approach. They look at the organisational knowledge base; at processes that lead to a change of the organisational knowledge base; at transfer effects and successes resulting from the change processes; and at the business results using appropriate indicators. The model may support the management in developing a suitable set of indicators in order to better understand the company’s knowledge base. However, it fails to present quantitative measurement of the relation between the KM activities and the business results.
We realised that none of the existing methods completely satisfied our needs, but a combination of aspects from existing methods would do so. What we needed was a value model for KM activities. Using the definition of Anderson and Narus (1998), a value model is a data-driven representation of the worth, in monetary terms, of what the supplier is doing or could do for its customers. Value models are based on the assessments of the costs and benefits of a given market offering in a particular customer application.
What follows is the story of how we developed value models of KM activities.Methodology
Let us first look at the methodology we used, before exploring the different steps taken. Figure 1 shows the methodology that combines aspects of the work by Birchall and Tovstiga (1998) and Anderson and Narus (1998).
To illustrate our approach, we used a knowledge intensive business process that has gained significant attention throughout the last ten years: The management of intellectual properties and intellectual assets (IP/IA management). At Degussa-Hüls, this process is carried through in close co-operation between the business units and the corporate functions: Patents & trademarks, technology transfer/licensing, information & documentation and the KM project team.
Initially, this business process is mapped as a value chain comprising smaller process elements. Step two asks for the key success factors, i. e. those variables that are characteristic for the market place and thus hold true for all competitors. With step three, the analysis and findings of the steps above are combined to detect knowledge gaps and to find potential knowledge management activities or methods and tools that can bridge these gaps. Step four comprises the selection and the benefit evaluation of KM activities. Step five is the formulation of the results from step four as a value proposition to the stakeholders of the pilot project. Finally, step six provides a method to map and benchmark the different potential pilot projects against each other.
Clearly, steps four, five and six formed the core of our mission. We will thus focus on these crucial steps of the methodology in detail and invite the interested reader to study the literature on the remaining steps (for example, Tovstiga, 1999).
In step four of the methodology, we first had to involve employees from the business units that had just started to reengineer their IP/IA management processes. Then, we had to get quantitative benefits out of potential KM activities that resulted from the KM gap analysis.
It is our experience that personal involvement starts when people trust each other and feel valued for their ideas. Thus, we scheduled and executed interviews with a number of employees from R&D, application technology development, controlling and marketing, all of which were involved in the business process. The purpose of the individual, structured interview was threefold. First and foremost, it facilitated a build up of trust between the interviewer and the interviewee, as a prerequisite for every subsequent step in the process. Secondly, it served to map the business process together with the employees, thus giving them full credit for their own ideas and comments. And third, we extracted the success factors for the different process phases, selected promising KM activities and, finally, described the relationships between KM activities’ intermediate effects and bottom-line business results. For accomplishing that latter purpose, a novel diagram was used (see figure 2).Benefit analysis using a cause-and-effect diagram for KM activities
The diagram in figure 2 consists of three parts. Part one consists of boxes in the top row of the diagram where the interviewee places the most important KM activities selected during the interview. Even though no limit for the number of KM activities for the diagram was given, ten appeared to be a reasonable number to allow the development of the diagram.
Part two comprises possible transfer effects and successes in the six KM dimensions: People, management and strategy, processes and technology, innovation, customers, and market. These generic transfer effects and successes were collected from Skyrme (1998), Probst et al (1999) and Mayo (2000), and were preset in the diagram. However, the interviewee was encouraged to modify the set during the interview.
Part three shows a variety of business results, with the EBIT (Earnings Before Interest and Taxes) as the key financial performance measure placed at the very bottom of the diagram.
The purpose of the diagram is to describe and evaluate cause-and-effect relationships between the top ten KM activities and the transfer effects and successes caused or influenced by the KM activities. This is done by connecting KM activities with relevant transfer effects and successes, using arrows. Eventually, the resulting network of causes and effects is extended down to the key financial performance measure of the business unit (i.e. to the EBIT).
Apart from this qualitative description of cause-and-effect relationships, a quantitative description was formed. To do this, a measure of impact had to be added to each arrow. Three degrees of impact were suggested to the interviewee, low (L - corresponding to an impact factor of 1-10 per cent), moderate (M - impact factor 10-20 per cent) and high (H - 20-40 per cent).
With all relevant arrows drawn and all impact factors added, the calculation of the impact of KM activities on the EBIT was performed. To do this, all cause-and-effect chains of arrows (i. e. relationships) originating from a particular KM activity and ending at the lowest business result (the EBIT) were evaluated as the sum of all the impact factors attached to the arrows in the different lines. The resulting number is the overall impact factor for the particular KM activity on the EBIT. Adding up these numbers for all KM activities given in the diagram results in the overall impact factor of these KM activities.Results from the benefit analysis
As a direct result of five interviews with knowledge workers in a business unit, and of the calculations outlined above, the following questions could be answered:
1. Which are the most frequently named KM activities?
These activities reflect the importance of having the right tools (reverse citation of patents and evaluation method), the right environment (create meeting opportunities for knowledge transfer), and a long-term focus (IP/IA function within the BU) in order to make the IP/IA management process function more effectively.
It is worth noting that the frequency does not tell us anything about the perceived impact that a particular KM activity might have on the business result. However, it does tell us which activities the interviewees consider to be important elements of an IP/IA management process that works well.
2. Which are the most important KM activities, and what is their impact on the business results?
Figure 3 shows the five KM activities with the highest impact factors, expressed as a percentage of the key financial indicator, the EBIT.
Similar to the conclusions drawn above, the results of figure 3 reflect the importance of having the right tools (reverse citation of patents and evaluation method), the right environment with openness and trust (introduce team/tandem weeks), a good understanding of how the process works (do a smaller IP/IA project covering all aspects of the IP/IA process rapidly) and a high visibility in the business unit and in the company (implement the IP/IA management concept in top management reports) in order to deliver the impact on the business results as perceived by the participants of the interviews.
For a thorough value analysis, the cost elements have to be considered in conjunction with the benefit elements (i.e. the impact factors).
The cost of implementing KM activities depends on the specifications, for example the number of people involved in the project ‘tandem/team weeks’, or the number of hours required to make the ‘knowledge transfer at new meeting opportunities’ a sustainable success. Figure 4 lists the top three KM activities ranked according to the expected impact-to-cost factor.
3. Which are the most important KM dimensions (people, management/strategy, processes/technology, innovation, customers, markets/products)?
The top three KM dimensions in terms of the sum of impact factors placed within these dimensions are:
The KM activities that aim at results in these dimensions thus have a higher leverage on the business results than KM activities targeting other dimensions.Value proposition
With the results of the complete benefit analysis at hand, the value proposition (step five of the methodology) can be developed. As previously mentioned, it has to address the needs of all stakeholders by delivering quantitative and qualitative proof of the value of KM activities. As an example we present the value proposition for the employees in the R&D and application technology department of the BU:
1. Free time and money allowance as an indicator for a climate of creativity will give you the chance to explore new fields of research and interest and connect with people from your profession, enrich your skills to increase your employability and flexibility.
2. Free access to more process data, regularly updated patent information and the distribution of worst practice studies in the field of IP/IA management will help you to understand the competitive situation better and build up trust more easily in order to share with each other knowledge from which you learn and develop new potentially ground-breaking ideas.
3. Creation of an IP/IA function within the BU, and testing and implementing evaluation methods for IP, will give you a better grip on IP/IA matters, including a better evaluation of your R&D results with respect to a potential return on investment.
1. The reverse citation of patents will be an integral part of the IP portfolio management to help you understand what your current and potential competitors are doing and planning, and to detect gaps in your R&D activity portfolio: Your estimated impact on the EBIT is 4 per cent.
2. ‘Tandem weeks’ (impact on EBIT is 4 per cent) and ‘creating meeting opportunities’ (your estimated impact on EBIT is 1 per cent) will give you the chance to regularly exchange knowledge and ideas, which will also give you the opportunity to look at things from your colleagues’ point of view and to network, helping you to solve your daily challenges faster.
3. Two key transfer effects and successes in the process of IP/IA management will be ‘creating new ideas’ and ‘exploring new markets’: Your estimated impact on EBIT is 2 per cent and 3 per cent.KM project portfolio as support for project selection
Resources with which to undertake a KM project are scarce, and there are usually more requests and proposals from business units than there is personnel and money available. Therefore, a transparent and unbiased selection has to be performed (step six of the methodology). Ideally, the decision is based on multiple criteria, of which one is the impact on the business results, for instance the EBIT, as discussed in this paper.
Inspired by Ernst (2000), who uses patent portfolio matrices in analogy to the well-known growth-share matrices introduced by the Boston Consulting Group (Kotler, 1997), we suggest using a similar approach for comparing and presenting potential KM projects. Due to the existence of multiple criteria for evaluating KM projects, the multi-factor portfolio matrix pioneered by General Electric appeared better suited as a basis for the development of a new matrix than the BC Group method. Figure 5 shows the new portfolio matrix for KM projects.
Each KM project is rated in terms of two major dimensions, attractiveness of environment and project strength. To measure these two dimensions, the decision-makers or stakeholders have to define the underlying criteria, rate them and combine the results into an index. The rating of the criteria is done on a scale from 1 (very unattractive) to 5 (very attractive). Examples for attractiveness of environment are:
Examples for project strength are:
The circles plotted in figure 5 represent the different KM projects to be evaluated. The size of each circle stands for the potential internal market for duplication of the KM project. This potential can be expressed as an estimate of the total number of people in the company who can benefit from the implementation of such a KM project. The pie part of the circle stands for the ‘market’ covered by the current KM project (also expressed in head count).
The portfolio matrix is divided into three zones; the three cells in the upper-left corner indicate strong KM projects that are high potentials for execution. The diagonal cells (lower-left to upper right corner) indicate medium overall attractiveness. Immediate execution of a project located in this zone should be carefully considered. The three cells in the lower-right corner indicate low overall attractiveness. If no additional criteria are to be considered, they should not be executed.Conclusions
The methodology outlined is suitable to map knowledge intensive processes, to detect relevant success factors and potential KM activities with their KM dimensions, to value their impact on bottom line results of the business under investigation, and to compare different KM projects.
In spite of the temptation to take the calculated results of the impact on the EBIT as rock solid, they are not! The calculated impact factors are based on the estimates and the experience of the interviewees.
The cause-and-effect diagram as a tool for visualising and calculating bottom-line effects of KM activities can assist top and middle management in shifting their attention to the value creating KM activities with high impact-to-cost ratios. The calculated figures are realistic as expressed by the majority of the participants in the feedback loop of the interviews. However, the final selection of KM activities and KM projects should always be based on a set of criteria, of which the calculated impact on the EBIT is one.
The pilot project IP/IA management that was used in this study as an example for the application of the new measurement system is the first one to be evaluated this way. Up to now, KM projects were initiated based on a set of criteria not comprising calculated economic benefits. The new measurement system has added significant criteria and offers a more transparent and unbiased format for selecting the most attractive KM projects.
Possible ways to improve the methodology include the use of software that supports the generation of the cause-and-effect diagram and the calculation of impact factors. This would significantly reduce the level of participation of managers and employees of the business. On the other hand, more time from the participants of the interviews and the workshops is required in the identification and selection of transfer effects and successes.
Valuation prior to a KM project, with a strong link to bottom line results and with the participation of the employees in the business units should be considered for other projects as well, particularly in the IT sector. Such projects are sometimes initiated based on a rather diffuse understanding of the potential benefits. A valuation comprising values addressed by all stakeholders would not only give a better overall understanding, but would also lower the barriers against the implementation of new IT systems and tools. KMReferences
J.C. Anderson & J.A. Narus, Business Marketing: Understand What Customers Value (HBR, November-December 1998)
D.W. Birchall & G. Tovstiga, Methodology for Assessing the Strategic Impact of a Firm’s Knowledge Portfolio (8th International Forum on Technology Management, Grenoble, France, 2 - 6 November, 1998)
H. Ernst, ‘Patente als strategische Informations-
ressource’ (Presentation at Degussa-Hüls production site Marl, February 2000)
R.S. Kaplan & D.P. Norton, The Balanced Scorecard - Measures that Drive Performance (NBR, January/February 1992)
P. Kotler, Marketing Management, Analysis, Planning, Implementation, and Control (Prentice-Hall, Inc., N.J., 1997)
A. Mayo, ‘Measuring, Managing and Valuing Intellectual Capital’ (Pre-Conference Workshop 2, Knowledge Management & Organisational Learning Conference, 28 February - 2 March 2000, London, UK)
K. North, G. Probst & K. Romhardt, Wissen bewerten: Ansätze, Strategien und Fragen (ZfO 4/98)
G. Probst, S. Raub & K. Romhardt, Wissen managen (3rd edition, Frankfurt/Main, 1999)
A. Sawers, ‘Value is back in fashion’, Business Age (June 1996)
D. Skyrme, Measuring the value of knowledge - Metrics for the knowledge-based business (Business Intelligence Limited, London, UK, 1998)
G. Tovstiga, ‘Methodology for identifying and assessing the strategic impact of your firm’s portfolio of capabilities’ (Research paper and working format for the lecture strategic management at TSM Business School, Enschede, 1999)
Dr. Alexander P. Bünz is a knowledge process consultant at Degussa Hüls. He can be contacted at: alexander.buenz@degussa-hüls.de
Dr. Gabriele Kirch-Verfuss is project manager knowledge management at Degussa Hüls. She can be contacted at: gabriele.kirch-verfuss@degussa-hüls.de