K6201 presentation v3

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K6201 presentation v3

  1. 1. KM Foundation K6201 Team member: 1.Elvin Yeo Wee Kiat 2.Dorothy Ngai Yuk Lan 3.Fransiscus Dipuro Knowledge pays: evidence from a law firm (Ingo Forstenlechner, Fiona Lettice and Mike Bourne)
  2. 2. Introduction Objective: empirical case study to: analyze the impact of the introduction of knowledge management practices on the financial performance of a multinational law firm; and to refine the KM Balanced scorecard being used by the organization. Law firms chosen because they are good example of knowledge-intensive service organizations, where it is predicted that KM practices will impact organizational performance
  3. 3. The case study firm Law firm in case study is one of three largest law firms in the world High ratio of KM staff to lawyers: for every ten lawyers there is one dedicated KM professional (compared to the industry average 25:1) General investment in KM also above industry average The firm form practice groups with a specific legal focus (e.g. tax or labor law) in order to allow a higher degree of specialization – with the right experience, specialist can easily recognize patterns and apply familiar tools so that they do not need to reinvent the wheel
  4. 4. The approach to KM 2 Levels – Firm and Practice-group Firm level  Firm-wide KM lead by CKO  4 services functions (change management, technology projects, provision of information services and taxonomies) headed by non-fee earning lawyers and information professionals  KM methodologies are created at the firm level  Sets the direction for knowledge management and provides an infrastructure to facilitate KM among practice groups  Manages Core KM functions (library, legal research, professional development)
  5. 5. Approach to KM (2) Practice-group level Lead by fee-earning partners Adapt Firm KM strategies to local practice groups Knowledge Management Lawyers: lawyers by profession and members of the practice groups Review and maintain internal know-how collection and dissemination
  6. 6. Approach to Performance Mgt Balanced scorecard used to manage and measure the knowledge management function (in an effort to determine ROI of the KM function)
  7. 7. Success map built from the scorecard: the basis of knowing what to measure and why, defining cause and effect within the KM function It’s theoretical and untested -> this empirical research to test causal links within the success map
  8. 8. Research Methodology Success map is the starting point of this study Indicators in the success map had been measured over a year and entered into the live performance management system Origin of data: Usage data for various KM systems User surveys on KM services, tools and practices Data from HR function Organisation financial data Data was then analysed using statistical tool
  9. 9. Stepwise Regression Analysis Goal: To predict the most important indicators on the success map First: Choose which indicator you want to measure
  10. 10. Stepwise Regression Analysis Significant predictor? Drop the predictor Enter the model A list of predictors that may influence productivity: 1. Incentives 2. Training 3. Office layout 4. Innovation 5. Processes 6. ……. Yes No For each predictor For each predictor A list of significant predictors for productivity: 1. Incentives 2. Training 3. Office layout 4. Innovation 5. Processes 6. ……. A list of significant predictors for productivity: 1. Incentives 2. Training 3. Office layout 4. Innovation 5. Processes 6. …….
  11. 11. Ultimate aim of all KM work – improve financial performance Start with the most important perspective – Financial Want to know – Does KM improve Productivity? Analysis of the Success Map
  12. 12. Analysis of the Success Map Aim – To find out whether the arrows can be proven At this stage, the arrows are theoretical
  13. 13. For regression to work Need real data (predictor) to represent Productivity and all other objectives Use existing measures from Balance Scorecard Fee Income Availability and Quality of reusable know-how Ease of Use of know-how systems Analysis of the Success Map
  14. 14. Analysis of Success Map For example Productivity is represented by “Fee Income” figure Quality is represented by The ease of use of know-how systems Availability and quality of reusable know-how In total 48 predictors to represent the 12 objectives
  15. 15. Analysis of Success Map Want to find out what influences “Fee Income” All 48 predictors thrown into the regression model A*predictor1 + B*predictor2 + ….+ Constant = ‘Fee Income’ Question for Data Mining students Should linear regression or logistic regression be used?
  16. 16. Regression Result The following 5 measures have significant association with ‘Fee Income’ Checked with Prof Lee & Prof Khoo – R and R2 is cumulative so most important is ‘Value perception of KM among lawyers’
  17. 17. Interpretation of Result Counsel & legal opinions Ease of use of know-how systems Personal know-how exchange with peers News and current affairs Value perception of KM Fee Income Most Important !
  18. 18. Regression on Value Perception We know that Value Perception is most important, but what can improve Value Perception? Repeat regression, this time ‘Value Perception’ as dependent variable Most important to improve ‘Value Perception’ is Personal service from the KM Team!
  19. 19. Important Drivers for Fee Income Combine 2 results, we have most important drivers for improving ‘fee income’
  20. 20. Revised Success Map Repeat regression on all objectives Outcome: Revised Success Map that is proven to a certain extent Does it mean ‘innovative thinking’ and ‘standardization’ does not help?
  21. 21. Feedback on Revised Map Managers interviewed gave positive feedback on the revised map: identify key measures that are collated into a single mgt dashboard; assist in enabling measurement and help to provide more effective KM services to lawyers; improve the ability to measure and report on cost and resource allocation; improve the ability to efficiently track the changing value perception of KM and KM initiatives; improve responsiveness to financial and organizational issues as they arise; facilitate improved communication with partners about KM and the service the KM team provides; and assist in the process of determining ROI for KM applications and services.
  22. 22. Conclusion This research is a step towards measuring the value of an intangible resource - knowledge Value perception is key driver for fee income Personal service from KM team is key driver for value perception Infer that KM remains a discipline highly dependent on Human Interaction
  23. 23. Conclusion ‘News and current affairs’, ‘counsel and legal opinion’ important Infer that in time of information overload, important to identify which narrowly-defined know-how really adds value Is KM Useful? Assumption that KM have positive impact on income of professional service firms is supported by this research
  24. 24. Thank You!

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