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Knowledge Management By: Jenny Enderby and Chris Papin What is Knowledge Management? • According to www.brint.com – KM is “caters to the critical issues of organization adaptation, survival and competence in face of increasing discontinuous environmental change… Essentially, it embodies organizational processes that seen synergistic combination of data and information processing capacity of information technologies, and the creative innovative capacity of human beings.” Simplified • Knowledge – Refers to a set of information with which we have experience – Usually gained through work, school or other life experiences • Management – Refers to the ability of an individual or group to lead and organize others in business to produce a desired outcome The Knowledge Process The Knowledge Production Information Acquisition Individual and Group Learning Knowledge Claim Formulation and Evaluation The Knowledge Process Knowledge Integration Knowledge and Information Broadcasting Searching and Reviewing Knowledge Sharing Teaching Put it all together… • Knowledge production and integration compile together with non-electronic information as well as electronic information to for a database of knowledge that is the basis for KM. Electronic Information • Data Mining and Data Warehousing – Two tools that help turn information and data into useful knowledge Defined • Data Warehouse – A database that stores larges amounts of historical business data – Another way: Warehousing brings your data together for analysis • Data Mining – The practice of extracting data from a warehouse in order to analyze patterns trends and relationships – Another way: Mining sorts through the data you collected and turns up interesting and useful connections Why Use DM? • Firms identify patterns which generate valuable knowledge for the company How Companies Use DM • • • • • • • Market Segmentation Customer Churn Fraud Detection Direct Marketing Interactive Marketing Market Basket Analysis Trend Analysis Fraud Detection Example Wal-Mart Example How These Apply to KM • DM and DW can turn data into useful knowledge that can give companies a competitive advantage over their rivals • DM takes a proactive approach to selling products to customers rather than a reactive approach by predicting patterns, trends, and behaviors. Why So Difficult • Implementation of KM programs • How to estimate the return on KM • How to store KM data • Techniques on utilization of the knowledge Implementation Problems • Knowledge is Power – Incentive structures to share information • Resistance to Change – People are reluctant to change – 56% of executives say “changing people’s behavior” is the most difficult obstacle • “Sharing knowledge is an unnatural act. You can't just stand up and say, 'Thou shalt share knowledge'—it won't work.” HUBERT SAINT-ONGE, PRINCIPAL, SAINTONGE ALLIANCE Returns on KM • KPMG invests $40 million • Quality knowledge is the goal • “Data separates you from the competition” How to Store New Data • New techniques to “gather, store, process and distribute this kind of knowledge” • It isn’t contained in typical rows or columns • How do we store the human element? Utilization of the Knowledge • Problems with change • Dept. of Defense and post combat data • Management must encourage change Implementation Barrier • “94% of business executives believe that it would be possible, through more deliberate management, to leverage the knowledge existing in [their organization] to a higher degree” • BUT…. Implementation Barrier • “71% believe embedding knowledge in process, products, and/or services” • Why not in the people making these processes, products and/or services? Implementation Case Study • E&Y implements a knowledge management system in an effort to reach $1 billion in revenues by 1997. • Process called Future State 97 or FS97. E&Y • A major focus was to capture knowledge • Elected a Chief Knowledge Officer • Formed a Center for Business Knowledge E&Y • People were the key • Technology was the enabler • How do you adapt to the change needed? Similarities • E&Y had the same difficulties as others – Implementation was a new venture and risky – Returns are still not 100% clear, though they are assumed to be part of the KM program – How did they obtain and keep the data? – Problems getting the knowledge distributed Questions?