Discovery Machine has developed a methodology and technology based on years of cognitive science and artificial intelligence research for capturing the processes, strategies, and best practices of experts. Our methodology involves technology that starts with scoping out the problem that will provide the most value to the organization and ends with the creation of a deployable model that can be embedded in existing software environments. The phases of the methodology are:
- Scope Domain
- Test and Deploy
The methodology starts by identifying a domain and the scope of work that will lead to the highest return on investment for the enterprise. This is followed by working through a set of scenarios representing actual situations encountered by the expert in performing the activity. The scenarios form a representative set of current, historical, typical and limiting cases for the activity. The solution to each of the scenarios is sketched and successively refined by the expert with the help of a knowledge coordinator into a graphical representation of the expert’s process. The Discovery Machine technology and methodology enable the expert to refine the sketch into a formal representation. Formalization also enables the expert to define the data that is used in solving problems. The formal representation can then be quickly refined into an operational model that carries out the expert’s process through a job aid, training system or automated utility. The testing and deployment of the model then integrates the process with databases and applications throughout the enterprise.