Knowledge Domain Analysis (KDA) activities are critical in identifying, maximizing, and sustaining benefits generated by a KCS implementation, and are described in detail in the KCS v6 Knowledge Domain Analysis Reference Guide. The people who do this work are often called Knowledge Domain Experts (KDEs).
The Knowledge Domain Expert is responsible for the health of a knowledge domain from a content point of view. The KDE must be a subject matter expert in the domain in order to identify duplicate articles, knowledge gaps, and the optimal approach to resolving complex issues. The KDE is also responsible for analyzing patterns and trends, and facilitating the creation of high value content.
KDE responsibilities may include:
- Ensuring efficient and effective problem solving by the team.
- Applying expertise in data mining to perform trend analysis and find the significant patterns in the data.
- Assisting in the fundamental development and maintenance of knowledge base quality and flow, including the knowledge base quality methodology, article standards, and process guidelines.
- Performing the New vs. Known Analysis
- Developing and analyzing reports on key metrics for business value of the knowledge base, such as article reuse rates, web-enabled call avoidance, and improvements to resolution times.
- Ensuring effective knowledge base operations by monitoring related information (organizational effectiveness, resource allocation, new article creation trends) and making recommendations to management to accommodate changing conditions.
- Advocating for changes necessary to maintain the knowledge base as an effective tool for achieving business objectives.
- Providing input for items that have worldwide impact. For example, monitoring and defining the KCS article metadata, prioritizing enhancement requests, coordinating training efforts where feasible, and planning for upgrades and systems integration enhancements.
- Influencing the owners of products, documentation, processes, and policies to make improvements
- Participating in the KCS Council.
The KDE function has a high dependency on reporting capabilities. Additionally, there are significant opportunities to use emerging AI capabilities (machine learning, automated pattern recognition, classification and clustering, sophisticated text analytics) to support the KDE in their analysis activities. Many organizations now employ Data Scientists who specialize in AI capabilities. Providing the KDEs with data science capabilities is a great way to compliment the KDEs' domain expertise.
Knowledge Domain Expert Workshop
This workshop develops Knowledge Domain Expert (KDE) skills, which are necessary for managing all the knowledge about a particular subject (a knowledge collection or domain). The KDE’s role is to monitor the health of the knowledge base as a collection of articles, the distinction between articles, and the patterns across articles. The number of KDEs will depend on the number of knowledge collections that make sense for an organization (assessed during the KCS Design Workshop).
New vs. Known Study
The KCS v6 Practices Guide describes a double loop process: the Solve Loop and the Evolve Loop. The Solve Loop practices enable organizations to capture and reuse the collective experience of the organization in supporting customers. The Evolve Loop enables organizations to learn from that collective experience and identify improvements in both the support processes and the products. The Evolve Loop is a continuous improvement process. The New vs. Known study is an example of an Evolve Loop practice.
Once customers are using self-service, understanding the ratio of new versus known issues coming into the organization is an indicator of the health of the knowledge flow and the effectiveness of the self-service model. A primary focus of the KDE is to facilitate the New vs Known study.
There are some key opportunities to learn from the content that has been captured at this point in a KCS Adoption:
- Improved capture and link rates
- Improved linking accuracy
- Improved the speed and quantity of articles published for self-service
- Promoted customer use of self-service
- Increased customer success of self-service