Too many science-based companies lose their investment in knowledge soon after their staff generates it. Once the problem is solved, the improvement is realized or the R&D project is complete, the knowledge work including the data, analysis and resulting predictive models are lost, or at least inaccessible to others.
Regenerating analytical knowledge carries higher risks, incurs unnecessary costs, and delays achieving business goals. The future success of technical problem solving and process innovation requires a modern knowledge management strategy. Companies that adopt a modern knowledge management strategy will dramatically reduce the amount of time and effort in the daily work of engineers and scientists, thereby not only preventing the needless duplication of experiments, but also extending the use of past experiments and improvement initiatives.
Wayne will present a use case to demonstrate the power of managing analytical knowledge through CoBase, an enterprise-level knowledge management system that enables engineers and scientists share access to and collaborate mutually on past analyses and relevant supporting data.