Knowledge Analytics℠
An Outcome Focused Approach to Knowledge Management

Strategically support your greatest assets: your people and what they know

Knowledge Analytics℠

A Logical Approach to Knowledge Management

Even the best Knowledge Management and/or Organizational Learning approach isn't sustainable unless it is aligned to business objectives and its value measured and reported. Because it is inherently qualitative, measuring value is difficult. APQC in one of its Advanced Working Group (AWG) developed a model that it has labeled "Knowledge Analytics" which begins with understanding and defining business objectives and selecting a KM approach with process and tools aligned to the business objectives; and ends with measuring the change in business outcome that has occurred as a result of implementing the KM program. Cindy Hubert reminds us that it's important to "have a clear understanding of what is important to the business because knowledge maps needs context" (2015). Spend time thinking through and documenting the hypothesis that leads to the KM approach. Determine the business outcomes you will measure and give the program enough time to make an impact. Identify interim data that shows the KM program is creating desired change. Observe, measure, analyze, think, adjust and repeat. Measure the business outcomes and rethink alignment with [new?] business drivers. Make adjustments, continuously improve, set higher metrics. Above all, measure and report progress. Articulating the value of your KM program and reporting results are central to the success of your program.

Take a look at the original concept of Knowledge Analytics℠ as described by APQC (APQC, 2015).

This video is from APQC.org, a member-based nonprofit and one of the world’s leading proponents of business benchmarking, best practices, and knowledge management research. The APQC mission to help organizations around the world improve productivity and quality by discovering effective methods of improvement, broadly disseminating findings, and connecting individuals with one another and with the knowledge they need to improve.

Next Steps in Implementation

Adapting the Knowledge Analytics℠ model

My adaptation of the APQC Knowledge Analytics℠ model is based on my opinion of the importance of articulating the value of the KM program. I have added the step of documenting the outcomes that will be measured on the front end of KM implementation, and measuring the business outcomes outside of the knowledge management program feedback loop. The team implementing the KM program is concerned with how well the program is progressing, and as such makes decisions based on KM program metrics. Business leadership is likely not interested in the KM program per se' - their interest is in business improvement. If a KM program improves the business, "bring it on!" Our assertion is when the KM program is designed well and progressing, business outcomes are improving, albeit on a lag. It's therefore important to report to business leaders and decision-makers a compelling subset of metrics that are understood to be related to and changing as a result of implementing the KM program.

Hunter Adaptation of Knowledge Analytics℠ model

Deploy KM is the step in the Knowledge Analytics℠ model where the traditional KM or OL process and enabling system or tool is applied. While a critical component, this step is a single step in the comprehensive process of continuous business improvement using the knowledge as an asset. Your business already has access to this asset. Individual employees use it every day. Allow the enterprise to take advantage and use it too!