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Can’t keep up! How to put the “I” back in Information Management!


In “What every business leader should know about IT management,” I shared that it is possible for business leaders to understand “what’s going on” in IT by understanding the five value chains of IT:


-strategy to portfolio

-require to deploy

-request to fulfill

-detect to correct

-data to information


In this final post on the IT value chains, I will review the fifth value chain, data to information, having reviewed detect to correct in my last post.


Data to information

There’s no denying that the CIO’s role is changing. A recent Booz and Company article (the one that I wrote about last week) predicts: “CIOs will be freed up to concentrate on helping the entire company develop the analytical sophistication needed to make the most of the rapid digitization of every aspect of business—effectively reasserting the importance of the ‘I’ in CIO.” If this is accurate, a core element on the CIO’s agenda will become harvesting data and turning it into actionable information. Put simply, the data to information value chain is about how well your IT organization manages two things: protecting your business data and transforming this data into information.


What is the goal for data to information?

To successfully manage this value chain, your IT department must first ensure that business data and information are protected from unauthorized access, damage, and inference. As such, storage and retrieval requirements must be set, and the performance of each must be set to your business needs. At the same time, the quality of data recovery and integrity must be confirmed regularly—you need to know that they work before disaster happens. From an information perspective, this means that information sources are not only identified but also classified. For this this to be truly successful, make sure that your IT department is creating knowledge that business users actually use (because they deem it as important), and that IT drives the ability to share information. IT must ensure that knowledge sharing is part of the enterprise culture—the value of this is immense. Finally, you want to make sure that the creation of knowledge is not an ad hoc event, but something that is continually updated and improved.


Measuring whether improvement is indeed happening

Your IT organization should be continually improving how it manages the data to information value chain. IT should be tracking its performance against a number of key performance indicators (KPIs) and metrics. This includes measures that are truly proactive by nature, such as access control. You want to know the percent of nodes with compliance issues so you can learn about the potential for unauthorized access, damage, or inference. Meanwhile, the success rates for backup and restore operations tell you how well IT backs up data and gets it back into use. The volume of protected data is another KPI worth viewing, since it will explain the scope of your business’s exposure to data loss. Next, the time elapsed since the last backup will tell you risk exposure in terms of how much new data could be lost. From an information management perspective, the percent of information categories covered, the volume of information classified, and the percent of categorized information validated give you a sense of how much information is accessible and useful. Two other measurements matter here as well: the percent of available knowledge used and the number of users trained in using/sharing knowledge. These numbers tell us whether all the work we are doing really has value to the enterprise. A final measurement is the frequency of knowledge repository use. This is important for several reasons. For example, if knowledge isn’t used, inefficiency could creep into market research (unneeded additional studies might be procured) or into product design (unknown customer issues might not discovered or tackled in the next release).


Where do you go from here?

Start by asking your business about its data to information value chain. And then make sure they are actively working to improve this process—just so it is clear, data to information is never-ending work.


Related links:

Solution page: IT Performance Management

Twitter: @MylesSuer

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About the Author


Mr. Suer is a senior manager for IT Performance Management. Prior to this role, Mr. Suer headed IT Performance Management Analytics Product Management including IT Financial Management and Executive Scorecard.

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