A Knowledge Strategy Senior Leaders Can Get Behind
If the KM team can supply hard data to validate its business case and demonstrate the impact of KM on performance, it will be in a good position to secure continued funding and/or argue for the expansion of the current program.
Getting It Done: Knowledge Analytics
If you're in the midst of launching KM or you have an older program that's stalled, it may sound like a lot of work to go back to the starting gate and revamp your strategy. But our research and experience confirm that the rewards are worth it, especially if you take advantage of practical tools to help you along the way.
Knowledge AnalyticsSM is what we call the seven-step process that shows you how to make smart investments by combining data from KM with other parts of the business. In the first two steps, you hone your strategy and business case along the lines we've discussed. You also make hypotheses about how planned KM investments will impact business needs. The next two steps are all about implementation: getting your KM tools and approaches up and running and collecting the data to fuel your analysis. Appropriate data may come from anywhere in the organization, depending on your original hypotheses.
The fifth step is where things get really interesting. Here, you apply a variety of analytic techniques to identify patterns relevant to the KM program, the business drivers and the hypothesized relationship between the two. The sixth step is critical thinking to evaluate the patterns you've uncovered and determine their significance to the KM program and the business. In the final step, you circle back with your leaders and talk about the implications of the findings.
Going beyond simply showing value, this new way of thinking can reveal how KM approaches interact with and illuminate a much broader spectrum of questions facing today's organizations. For example, can you detect broader trends from the conversations occurring in your communities of practice? Can you learn what new requests your customers are making by looking at what employees search for? Can you use workforce demographics and patterns of sharing to predict and prevent the loss of critical knowledge? And can you identify people with expertise not obvious on their résumés?
By bringing together disparate data sources, you can make the right decisions about knowledge sharing and collaboration investments. You can also predict future outcomes based on patterns of behavior and performance. If you apply knowledge analytics effectively, your business leaders will be able to spot relationships early on and seize business opportunities that might otherwise be overlooked.
APQC is a member-based nonprofit and one of the world's leading proponents of knowledge management, benchmarking and best practices business research. Working with more than 750 organizations worldwide in all industries, APQC provides organizations with the information they need to work smarter, faster and with confidence. Knowledge Analytics was developed in partnership with the KM teams at Baker Hughes, ConocoPhillips, Deloitte Touche Tohmatsu Limited, the Federal Reserve Bank of Cleveland, Marathon Oil, Rockwell Collins and US Army ARDEC. If you would like to learn more about Knowledge Analytics, visit www.apqc.org/kaworld or call us at 713-681-4020.