Tenix Engineering Conference 06 V3

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Tenix Engineering Conference 06 V3

  1. 1. Business process management Improving a knowledge-intense business process using knowledge management Dr Peter Dalmaris Futureshock Research Dr Bill Hall Tenix Defence
  2. 2. About my project TENIX case study A framework for the improvement of knowledge-intense business processes. Validation of the framework. Company A Company B Theoretical Research (literature, theory-building)
  3. 3. Research objective <ul><li>To develop the Knowledge-Based Process Improvement framework. </li></ul><ul><li>The development was based on theoretical research and case-study based research. </li></ul><ul><li>Three case studies were completed. </li></ul><ul><li>Final case study was on a Tenix process. </li></ul>
  4. 4. Case study objective <ul><li>To apply, test, and improve a framework for the improvement of knowledge-intense business processes using knowledge management. </li></ul>
  5. 5. Why Tenix? <ul><li>Tenix is a knowledge-intense organisation. </li></ul>Definition : A knowledge-intense organisation is one that depends on business processes that are high in knowledge intensity and complexity.
  6. 6. Overview of the KBPI <ul><li>Based on Karl Popper’s evolutionary epistemology. Answers the question “what is knowledge”. </li></ul><ul><li>Describes a business process in terms of a formal ontology . </li></ul><ul><li>Uses an analytical methodology for identifying areas for potential improvement. </li></ul>
  7. 7. Overview of the KBPI This presentation focuses on these components of the KBPI
  8. 8. KBPI Process Ontology <ul><li>A formal language for describing a business process </li></ul><ul><li>Used to built a formal model of a business process </li></ul>
  9. 9. Normal Classes The KBPI Process Ontology is composed of the top-level normal classes and eight abstract classes (next slide).
  10. 10. Abstract Classes
  11. 11. How is this ontology used? <ul><li>Used to build tools that aid in capturing and analysing a business process instance. </li></ul><ul><li>Such a tool was build, based on Protégé, a free ontology editor from Stanford Medical Informatics </li></ul>
  12. 12. Improvement methodology <ul><li>Designed as a “how-to” guide for improving business processes. </li></ul><ul><li>Defines the process improvement process. </li></ul><ul><li>Composed of the Audit, Analysis, and Design stages. </li></ul>
  13. 13. Improvement methodology
  14. 14. Two levels of improvement
  15. 15. Process level improvement
  16. 16. Function level improvement
  17. 17. Visual analysis Label shows the actual format with which knowledge is encoded, the actual system utilised for its transport, and their general category The red line encloses process tasks that are involved in the processing of the same knowledge object. This is generally called a “knowledge path”.
  18. 18. KBPI deliverables <ul><li>An AS IS process report </li></ul><ul><ul><li>Provides a detailed description of the business process. </li></ul></ul><ul><ul><li>Identifies areas of potential improvement at the process level and function level. </li></ul></ul><ul><li>An AS COULD process report </li></ul><ul><ul><li>Addresses the areas of potential improvement identified in the AS IS report. </li></ul></ul><ul><ul><li>Provides recommendations for improvement. </li></ul></ul>
  19. 19. Importance of KBPI framework <ul><li>Offers a systematic way for improving knowledge-intense business processes. </li></ul><ul><li>As part of the improvement process: </li></ul><ul><ul><li>the organisation gains detailed knowledge of its own processes </li></ul></ul><ul><ul><li>Changes to the process are rationalised based on their impact to the process </li></ul></ul>
  20. 20. Importance of KBPI framework <ul><li>For the first time (to the best of my knowledge), process knowledge becomes a central resource and consideration for process improvement. </li></ul><ul><li>Execution is transparent and straight-forward. </li></ul><ul><li>Rule-based analysis: happy to get my self out of the job. </li></ul><ul><li>Predictable execution time. </li></ul>
  21. 21. How KBPI helped companies <ul><li>Company #1 (low-tech): Discovered and documented numerous “knowledge bottlenecks” between company and contractors. </li></ul><ul><li>Company #2 (high-tech): Discovered and documented knowledge system redundancies leading to overly complicated knowledge processes. </li></ul><ul><li>Company #3 (Tenix, mid-tech): Discovered and documented poor utilisation of existing systems leading to waste of time and effort. </li></ul>
  22. 22. Thank you <ul><li>Questions? </li></ul><ul><li>Also visit http://www.futureshock.com.au for a long paper of this presentation </li></ul>Dr Peter Dalmaris is a lecturer and consultant based in Sydney. He has a PhD in Knowledge Management and Business Process Management, a Bachelors in Electrical Engineering, a Masters in Information Systems Engineering, and a Masters in Knowledge Management. Recently he started Futureshock Research, a Sydney company that seeks to continue the development of the KBPI, introduce related products (especially software) to the market, and provide consultancy services.

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