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Design of a Problem Determination Tool for Customers Disclosure Number: IPCOM000012974D
Original Publication Date: 2000-Apr-01
Included in the Prior Art Database: 2003-Jun-11

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A design is described for a web-based problem determination tool to aid end users in solving problems on their own, using a series of intuitive steps that reduces the end user's cognitive load. End users who encounter a problem with a product may be frustrated because 1) end users may not understand what their problem is and 2) end users may lack or not want to spend the time to isolate the problem using technical documentation. This application consolidates problems into categories with familiar tasks, questions, or symptoms that end users can quickly understand or recognize, which reduces their cognitive load. For example, a familiar set of tasks is identifying problems with print quality. An end user might not know whether this is a problem with paper, toner, or the printer. By grouping problems, such as 'toner too light' into a category, an end user can look at the category and easily recognize a symptom and then follow the decision tree to solve that problem. This approach puts the emphasis on enabling end users to recognize symptoms, tasks, or even questions instead of trying to determine what information or terms they need to formulate a search query or what question they need to ask. The essence of this design is that by reviewing existing end user comments and support calls, end user questions and problems are anticipated and grouped into logical categories. The advantage to this design is to enable the end users to recognize their problem instead of forcing the end user to formulate their problem and then obtain help. This design anticipates their questions and provides answers based on what questions they may need to ask. Other vendors have implemented troubleshooting assistants to enable end users to solve problems but most implementations require the end user to be able to formulate their problem. For example, a common technique is for an end user to select a problem area, and then rifle down until the end user solves the problem. This approach places a heavy cognitive load on the end user as the end user must either determine what type of problem they have, such as hardware or software, or they must formulate a problem statement. This design enables users to look at categories with easily recognizable tasks, symptoms, or questions and then make a choice. Simply put, this design enables users to recognize familiar patterns which requires less cognitive load than trying to identify a problem or formulate a problem statement. 1