Using decision trees you can capture procedures, guidelines, reactions, comments and decisions. Decision Trees are specifically designed to capture information that can not be read electronically, in terms of:
- A series of interlinked questions, answers and conclusions. The text of which can be combined with current operating parameters/data.
- Hyper links to descriptions and web pages that provide background information/terminology.
- Manual data inputs that can be used to steer a question session or used to perform some automated calculations, the results of which can be used in future questions.
UReason's Decision Support Agent, is the bridge between automated rule systems and the need to capture manual information from the field (for example) such that a rule has enough information to make a conclusion or decision. Decision support questions and answers can display current/live data as questions are displayed. Subsequent questions can also be influenced by current data.
For example: a quality inspector at a car plant, receives a Decision Support Event (generated from an automated rule). The event, informs him that a visual inspection is required to make a qualitative decision. He takes his mobile web browser on to the factory floor to visually inspect the car in question. His visual inspection is, however, guided by questions (and choices) contained within the original Decision Support Event (these questions may represent an electronic capture of well established inspection procedure). Once completed the Engineer commits his answers, UReason's products then utilities these answers to complete some qualitative diagnostic rule it was performing on the car production.
