The Transition and Scale-up Stage of the KMS, Essay Example

The transition and scale-up stage of the KMS and e-system development process is a potentially-challenging but nonetheless rewarding one. In Turban et al. (2010) knowledge distribution, knowledge utilization, and knowledge evolution can all contribute to transition and scale-up (p. 324). As knowledge is disseminated, it can be assessed and evaluated in order to ascertain how it might best be used, as well as areas for improvement. This in turn leads to the creation of new knowledge, starting the cycle anew (p. 323). The example of Infosys Technologies given by Turban et al. is illuminating: the company began with an initiative designed to acquire knowledge from employees, which in turn led to “a full-fledged KM effort supported by e-mail, bulletin boards, and various knowledge repositories” (p. 323). Over time, this was scaled up, with a corporate intranet and then a central knowledge portal, KShop, which also encouraged “local groups… to maintain their own content” (p. 323).

Davenport and Prusak (2000) describe this phase in much the same terms. Scaling up a KM system is all about creating and implementing new knowledge, moving new information “up the scale from data toward knowledge” (p. 7). Again, the example of Chrysler is salient: the goal of Chrysler’s Engineering Books of Knowledge is “to be an ‘electronic memory’ for the knowledge gained by automobile platform teams” (p. 7). In one instance, a manager tasked with a particular “’book’ was given a series of crash test results for inclusion in the repository” (p. 7). However, the manager “classified the results as data and encouraged the submitter to add some value” (p. 7). This is the foundation of transitioning and scaling up a KMS or e-system development process: eliciting, creating, and implementing new knowledge, interpreting data such that it becomes new knowledge. This new knowledge can in turn inform practice. Again, the example of BPX is salient: forty-two autonomous assets, each of which can generate its own solutions and processes (p. 18). The best solutions inform the whole.