Blueprinting the Technology Infrastructure

At any given moment, you cannot bring to mind all that your organization knows about any given customer or partner, KCRM technology attempts to help overcome that limitation. The following points are germane to the blueprinting step of the KCRM system’s design

KCRM technology must be experience centric: The objective is not one of boosting throughput and efficiency but that of enhancing the customer experience that leads to increased customer retention and loyalty. Interaction consistency, meeting and exceeding customer expectations, a balance between persona contact and automated efficiency, and future adaptability must therefore be considered.

KCRM is not limited to individual customers: It encompasses suppliers, partners, and   even competitors that the system must help acquire, retain, enhance, and maximize their relationship with.

Technology broadens reach: Technology’s role in building KCRM systems is that of broadening reach, enhancing the speed of knowledge transfer and real-time knowledge application, enabling informed decision making, mapping sources of tacit knowledge, communicating and integrating diverse channels and touchpoints, and facilitating collaborative success, Interoperability and leverage of existing systems are a crucial necessity. The system itself must be confused with intranets, extranets, data stores, or groupware.

Informal communications must be facilitated: web collaboration tools, multimedia, pointers, e-communities, voice-over-IP, and intelligent routing exemplify some mechanisms that facilitate informal associations in web-centric environments.

Business intelligence tools must be applied selectively: Flexibility, expert dependence, processing overhead, ability to deal with complex problems, accuracy, speed, tolerance for dirty data, and response time must be considered when making a choice about a business intelligence tool. Several tools such as artificial intelligence subsystems, intelligent data warehouses, genetic algorithm tools, neural networks, expert systems, case-based reasoning applications, rule bases, and intelligent agents can be combined to endow the customer knowledge management system with business intelligence capabilities.

You cannot use what you cannot find: Powerful search and retrieval mechanisms facilitate tracing and retrieval of valuable, actionable codified customer knowledge as well as codified “people pointers” to tacit knowledge. Various combinations of metasearching, hierarchical, tagged-attribute, combinational, and content searching may be used. Attribute tag searching allows searching through tags that define concepts not inherently captured in the content of a knowledge object.

User interfaces should meet actual user needs: Functionality, consistency, relevancy of context, navigability, customizability, and stickiness are key considerations.

The system must be future-proofed: Rapid technological change has brought and will continue to bring new information sources, as wells as unpredictable communication, information transfer, and knowledge-sharing services and requirements that accompany them. Open standards; mission focused design, results-driven design, modular integration, and a pragmatic outlook help build a system that can adapt to unpredictable future needs.