KCS 8.2 Structured Problem Solving – Knowledge Centered Support KCS
In some respects, problem solving is an art. However, we have found that a little bit of structure in the problem solving process can help improve the art. The structure of the KCS article also helps reinforce an effective approach to problem solving.
We can use an analogy that is helpful in making this point. Consider a crime scene: the first thing the police do when a crime is reported is to preserve and record the situation.
The first officers to arrive on the scene are trained to secure the area; they mark the location of the evidence and bodies and take pictures.
When the detective shows up to solve the crime, they first seek to understand the situation, then begin to ask clarifying questions, and then eventually go off to do research.
The Structured Problem Solving process involves application of the four practices in the Solve Loop. It helps the Support Analyst collect, organize, and analyze the information used in solving the issue. Note that there are different skills used in different steps in the problem solving process, and, as a result, different Analysts may be involved in each step.
Having explicit techniques in the workflow not only improves the problem solving process, but also creates KCS articles, as a by-product of the problem solving process.
The Structured Problem Solving Process in KCS includes two simple, yet powerful, concepts:
- Seek to understand before we seek to solve
- Search early, search often
First, we seek to understand the situation in the customer’s context, and we capture it to preserve it. Then we seek to understand what we collectively know about the issue (search the knowledge base). These concepts are not unique to KCS; Charles Kepner and Benjamin Tregoe outline these same problem-solving methodologies in The Rational Manager, as does Stephen R. Covey in The 7 Habits of Highly Effective People.
Just as in the crime scene, we start by preserving the perspective the customer has of what is happening. This is a very literal process. Next, we search the knowledge base to see if this is a known problem or to see what we collectively know about this type of situation. This idea is the “search early, search often” concept discussed in the Solve Loop. If a KCS article is found in the knowledge base, then we are done. If not, then we refine the search by collecting additional information from the customer.
Searching will sometimes result in finding articles that describe similar situations. While perhaps not perfect for our situation, the content often complements what we know about analyzing this kind of issue. If an existing article is not found after a few searching and refining our search, we start the analysis process. We tap into our problem solving experience and use whatever tools are relevant. We continue to ask clarifying questions. As we build a richer understanding of the issue, we check the knowledge base frequently. If we do not find anything pertinent to the situation already within the knowledge base, and we cannot resolve the problem, we then collaborate with others or escalate the issue for more research.
Many Analysts are too quick to move to the analysis phase of problem solving. If we move too quickly into diagnostics, we are likely to jump to conclusions, stop listening to the customer, miss the fact that there is already a KCS article in the knowledge base, or miss the opportunity to learn from others’ experiences in solving similar problems. KCS reinforces the need for the literal step to be the first step in the problem solving process.
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Content as shown in KCS Version 5.3 Knowledge-Centered Support Practices Guide (2012) S3 [27.1-9]. KCS v5.3 was written and edited by Melissa George, David Kay, Greg Oxton, Rick Joslin, Jennifer MacIntosh, and Kelly Murray.
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