Knowledge Centered Principles for Innovation Management
Knowledge Infrastructure seem to distinguish themselves from the other conventional management approaches as summarized below (Harkema and Browaeys, 2002; Davis and Botkin, 1999; Miller and Morris, 1999; Skyrme and Amidon, 1997, Davenport, 1993).
1. Understanding Innovation Value System (not Value Chain) – A value chain is linear and static, while a value system is non-linear, dynamic and represents interdependent relationships that need to be understood, considered and developed for Knowledge Infrastructure;
2. Formulating Collaborative Knowledge Strategy (not Competitive Information Strategy) – The latter strategy creates win-lose scenarios due to competition for the same information pie, while former strategy encourages win-win situations through symbiotic relationships by sharing and growing the knowledge pie;
3. Developing Strategic Knowledge Networks (not Strategic Business Units) – The latter applies isolated islands of information assets while the former fosters the flow of knowledge assets among partners, customers, suppliers, and other stakeholders including competitors for innovation pursuits;
4. Constructing Hybrid Human-Technology KM solutions (not Machine-based KM solutions) - Human beings are better at ‘knowledge skills’, while machines are more adept at ‘information tasks’. To fully harness knowledge for innovation, humans and machines must complement each other.
5. Fostering bottom-up knowledge processes (not top-down knowledge processes) – Creative and useful knowledge works, carried out by knowledge workers, require less top-down intervention and more bottom-up spontaneity.
6. Focusing on Customer Success (not Customer Satisfaction) - Customer satisfaction meets today's needs only, while a deliberate focus on customer success helps identify future requirements and unmet needs, which form the competitive forces for firm growth and business expansion.
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