In August 2011 HP announced the acquisition of enterprise search firm, Autonomy, for $10 billion.
It is possible HP was just crazy and former CEO, Leo Apotheker, was desperate to juice up HP’s stock price. With Knowledge Management.
Within ITSM the potential value is huge. Value can be seen in tailored services and improved usage, faster resolution of Incidents, improved availability, faster on-boarding of new employees, and reduction of turnover. (Ironically, improved access to knowledge can reduce loss through employee attrition).
In 2011 Client X asked me for some background on Knowledge Management. I did prepare some background information on ITIL’s Knowledge Management that was never acted on. It seemed like too much work for too little benefit.
ITIL’s description does seem daunting. The process is riddled with abstractions like the Data —> Information —> Knowledge —> Wisdom lifecycle. It elaborates on diverse sources of data such as issue and customer history, reporting, structured and unstructured databases, and IT processes and procedures. ITIL overwhelms one with integration points between the Service Desk system, the Known Error Database, the Confirmation Management Database, and the Service Catalog. Finally, ITIL defines a whole new improvement (Analysis, Strategy, Architecture, Share/Use, and Evaluate), a continuous improvement method distinct from the CSI 7-Step Method.
Is ITIL’s method realistic? Not really. It is unnecessarily complex. It focuses too much on architecture and integrating diverse data sources. It doesn’t focus enough on use-cases and quantifying value.
What are typical adoption barriers? Here are some:
- Data is stored in a variety of structured, semi-structured, and unstructured formats. Unlocking this data requires disparate methods and tools.
- Much of the data sits inside individual heads. Recording this requires time and effort.
- Publishing this data requires yet another tool or multiple tools.
- Rapid growth of data and complexity stays ahead of our ability to stay on top of it.
- Thinking about this requires way too much management bandwidth.
In retrospect, my approach with Client X was completely wrong. If I could, I would go back and change that conversation. What should I have done?
- Establish the potential benefits.
- Identify the most promising use cases.
- Quantify the value.
- Identify the low hanging fruit.
- Choose the most promising set of solutions to address the low hanging fruit and long-term growth potential.
What we need is a big, red button that says “Smartenize”. Maybe HP knew Autonomy was on to something. There is a lot of value in extracting knowledge from information, meaning from data. The rest of the world hasn’t caught up yet, but it will soon.