The KCS v6 Practices Guide describes the complementary processes of the Solve Loop and Evolve Loop. Each loop generates important knowledge by considering articles at different levels. To recap, Solve Loop articles are created and improved by knowledge workers (KCS Candidate, KCS Contributor, or KCS Publisher) during the normal Solve Loop workflow. At the time Solve Loop content is created, it is difficult to judge how important or valuable it may be. So, if an issue is worth answering or solving, it is worth capturing in the knowledge base for others to reuse. We want the knowledge base to reflect the customer experience. Capturing all the issues that customers experience contributes to the completeness and integrity of the patterns or clusters that emerge in the Evolve Loop analysis.
Solve Loop articles are developed “just in time,” based on demand. Solve Loop articles follow the content standard so that articles have a common structure, which improves their findability and readability. In addition, a single common structure enables us to identify patterns and trends during the Knowledge Domain Analysis. We can target our analysis of a collection or domain of articles based on similar issues or based on common cause and resolution.
Evolve Loop articles follow the same content standard, but they are designed around high-value content. They are usually created by Knowledge Domain Experts based on patterns and trends that emerge in a collection or domain of Solve Loop articles. Evolve Loop articles are considered to be of higher value because they are derived from patterns of reuse: the clustering of articles around a common theme or issue and/or frequently used processes and procedures. Evolve Loop content generally represents a very small percentage of the total number of articles in the knowledge base.
The reuse analysis performed in the Knowledge Domain Analysis also identifies pervasive issues that are opportunities for improvements. These may include changes in our offerings (products and services), processes, and/or policies. By analyzing the reuse patterns to identify pervasive or high impact issues, a Knowledge Domain Expert can assemble compelling evidence (business justification) to drive root cause analysis and corrective actions to remove the cause of these issues and therefore improve the customer experience and reduce our support (or responder) costs.
Root cause analysis and corrective actions can create tremendous value for the organization and our customers but it takes patience and persistence to achieve. Success in identifying and driving corrective actions is dependent on knowledge workers adhering to the Solve Loop workflow. The frequency - and more importantly the accuracy - of linking articles to incidents or requests is what allows us to meaningfully mine and act on patterns in the Evolve Loop.
Some examples of Evolve Loop content include:
- Procedural articles or step-level processes (how to do a specific thing in the optimal or preferred way)
- Resolution paths: a collection of linked procedural articles that defines a complex process (procedural or diagnostic) that will lead to the correct resolution. These collections of articles are created by Knowledge Domain Experts to address generic or high-level symptoms that have multiple possible resolutions.
- Hub articles for generic symptoms that have multiple possible resolutions but for which there are simple criteria for determining which resolution is the correct one for the situation.
- High impact issues (those that cause outages or pertain to new or strategic products)
- Articles created to fill gaps in the self-service mechanism—that is, based on self-service demand rather than agent-assisted demand
- Articles created based on harvesting high-value `content from communities and social networks
Distinguishing Between Reference and Resolution Articles
Another helpful distinction for articles is the ability to identify reference articles (those that are used to diagnose the issue and/or qualify the correct resolution) from articles that contain the resolution for the issue. Articles that describe diagnostic procedures or qualifying criteria on the way to a resolution can be flagged with a metadata attribute of "reference article". Reference articles themselves do not contain a resolution.
Unfortunately, this is not always an absolute attribute of an article; it often depends on how the article was used. I might look at three articles about a similar issue that provide some guidance or insight on how to solve the issue, but the issue I am solving has a unique, new resolution not covered by the three existing articles I referenced. The three articles that helped me solve this new issue should be linked as reference articles, and the article that I created to document the resolution to this new issue is linked as the resolution article.
Allowing knowledge workers to indicate, at the time of linking, how the article was used enables us to create accurate patterns of reuse for resolutions and to assess the value the knowledge base is creating by enabling knowledge workers to solve new issues based on how others have solved similar issues. When thinking about the value the knowledge base creates, it is important to consider both the efficiency gained through the reuse of articles that contain the resolution to a issue as well as the efficiency gained by having access to the collective experience of the organization as this helps us solve similar but new issues faster. Both the frequency of reuse and the frequency of reference are of interest and create value.