Various motives can drive a company to undergo a large-scale “transformation” of its systems – upgrade technology, improve business processes, change an operating model. Whatever the goal, transformation efforts typically focus on the process and infrastructure changes required to improve system functionality and expand organizational capabilities. Often overlooked, however, is another key element of effective transformation – data. Without complete, accurate and useful data, transformation efforts aren’t likely to reach their goals. A data-driven approach to transformation provides the foundation to support process and infrastructure changes and meet ongoing data requirements.

In the MIKE2.0 Methodology we provided some ideas around how organizations can take a data-driven approach to mitigate risk and provide greater information-based functionality. Some good areas to go to find out more include:

• The Solution Offering
• Guiding Principles of Data Driven IT Transformation

The Exec Summary provides a presentation that summarizes the approach. We”ve used this approach effectively and would love to hear any feedback on similar experiences or the approach.

I am continually struck by the lack of formal valuation models to information. Considerng how much organizations spend on building and maintaining information assets and how valuable they are to the health of the business, you would think it would be an area that would receive more focus.

While I’ve seen a number of academic papers on assessing the Economic Value of Information, the practically implemented cases are few and far between.  I have done some development on “Assessment-oriented” models that can be value in formulating a strategy, such as the Economic Value of Information model in MIKE2.0.

An Information Value Assessment should provide a mechanism to assign an economic value to the information assets an organization holds and  the resulting impacts of Information Governance practices on this value.   It could also measure whether the return outweighs the cost and the time required to attain this return.

Governance models are just one way of assessing value.  Other simple techniques could include:

• Mastering - how many systems hold this common data?

• Latency - if I load this data into a warehouse in an hourly fashion as opposed to weekly what are the gains?
• Quality - RI issues, accuracy issues
• Reach - how many people read my blog?  who are the readers?

I think this is an area where industry models will greatly improve, similar to what has occurred in the past 10 years in the infrastructure space.  The lack of model points to the immaturity of information management as a competency and the strict building of information with technology.   I would welcome any other opinions on technqiues.