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Informationalize your data while transforming your applications

Harvard Business Review blogger Thomas C Redman introduces a term -- Informationalization – in his post titled Integrate Data into Products, or Get Left Behind that focuses on a key element of the overall transformation program for an enterprise -- data. Data matters -- if you glean the valuable information from it with proper context. When rationalizing and transforming applications as part of an enterprise transformation program, the modernization strategy applied to a given application influences the manner in which the underlying data is processed -- it is migrated or archived or transformed or replicated -- all in the context of the set of applications being transformed. Redman's article suggests a more holistic approach to data during the transformation program pairing up with the rationalization of applications.

 

Here are the top 5 techniques to informationalize data during this process:

 

Informationalizing through Usage. During the transformation process, we need to look at how a given application is using the underlying data. Is it adding more context and using the data to provide valuable information to the end user? Redman cites the example of knowing how cold the beer is just by seeing the graphic on it. The applications transformation process provides a good opportunity to check out the manner in which the data available is being used and presented.

 

Informationalizing through synthesis. Applications have access to data across different repositories. Redman suggests that the GPS device in the car has reduced the traditional conflict with the spouse on reading maps during the journey. (My spouse and I still argue on whether we configure the GPS by speed or distance!) The GPS knows where the vehicle is positioned at any point of time and also has information about the location of restaurants, motels, gas stations, etc. It can synthesize this data and bring it to life by informationalizing it. Around noon each day, it can display a lunch icon that shows the restaurants in the nearby locale when the car is in motion x miles away from home. Synthesis. Are the applications using the available data from multiple sources in a synthetic fashion to realize such benefits for the end user? A question you should ask yourself when you embark on a Transformation program using a GPS -- believe it or not, even the city of Las Vegas should!

 

Informationalizing unstructured data. We have trained ourselves over the years to operate with structured rows and columns of data. Software available today can turn the tables on computers by making them think and discern information like humans out of combinations of unstructured data. Redman points out that half the value in the delivery of a shipping container from halfway around the world would be in the data associated with the container. True. But imagine software that is able to identify the serial number of a container from the cell phone photograph of a shipwreck to determine that there will be a significant delay in the delivery of those goods to their end users. Application transformation is a great opportunity to explore the possibility of applying software like Autonomy from HP to informationalize unstructured data as well.

 

Informationalizing through Integration. Even though data integration has been done for many years, the applications rationalization and transformation process provides opportunities to position predefined integrated views of the underlying data. Usually such integrations are most effective with structured data. Integrated views could offer opportunities for informationalization that may not have been available otherwise. Redman talks about mothers doing an in-depth analysis of the ingredients of the food being served to their infants. Imagine mothers having an integrated view of the nutrients that are being fed across all the meals their children eat on any given day. Informationalizing through integration.

 

Informationalizing securely. Redman does alert us to the sensitive nature of the informationlized data -- especially when it comes to retaining intellectual property, adhering to compliance regulations, etc. Informationalization is most effective when it is done to the audience that is likely to use it to deliver on outcomes that matter to people we care about. Even the most valuable information discerned can be disastrous if it falls into the wrong hands. Security must be given renewed consideration while informationalizing data during the applications transformation process.

If you really think about it, when you are embarking upon an enterprise transformation program, there are multiple ways to address the landscape of applications once you have established the business processes in the context of the overall business objectives. One of the routes is to look at the applications. Redman's article triggers a complementary approach in my mind. How about looking at the collection of data that is available across the multitude of repositories within the enterprise and determining how it can be effectively presented to the right users at the right time across the application landscape?

 

Gives you something to think about, doesn't it? Informationalization. My favorite word processor highlighted every instance of this word in this post as being incorrectly spelt. So what? I love the term. Thank you, Thomas C Redman.

Comments
| ‎10-24-2012 03:59 PM

I have to disagree a bit. Data doesn't matter. It is the action the data may help initiate that really matters.

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