We all have encountered presentations where the presenter is sharing the same content, over and over, and not telling you anything new. People have an innate ability to recognize redundancy, and discard it as additional information that doesn’t add anything new. Similarly, we must only informationalize data that matters for the enterprise. In other words, duplication of data does not increase the volume of information —a key point highlighted by Dr. Michael Wu, Ph.D., Principal Scientist of Analytics at enterprise blog platform provider Lithium in a recent piece in TechCrunch. Wu provides multiple examples of redundant re-tweets, and video logs from multiple video cameras, to make his point.
Wu provides a simple inequality:
information <= data
So we can assume for the enterprise that all data is not information. But the pertinent data used with context can realize valuable information.
A new definition for ROI
Additionally, Wu characterizes insights derived from data as information even though all information is not necessarily insight. Hence, Wu provides a second inequality:
insight << information <= data.
However, the real question for enterprises is whether they are getting the Return On Information (ROI) from their data. Enterprise organizations are familiar with the acronym ROI as meaning Return On Investment. But in the world of Information Optimization, ROI stands for something different. It’s a simple, but important distinction. Here is a simple equation for calculating the new ROI:
Return on Information = Value of Data / Total Cost
Let us see how Wu's inequalities apply here.
- If data gets duplicated, there is no incremental value added even though there is additional cost incurred to store and process the duplicated data. Increased Total Cost. Lower ROI.
- The more insight information provides, the higher the Value of Data and therefore, higher ROI.
Five essential steps to maximize the new ROI
It is important that enterprises take the following steps to maximize their Return On Information:
1. Exercise Data Governance. Big Data is experiencing tremendous growth with new prefixes being coined to characterize unimaginable volumes of data way beyond tera- and peta-bytes. Exercising Data Governance is vital to ensure that this happens in a controlled manner.
2. Migrate Data. Redundancy of data can be eliminated when data is consolidated through strategic migration.
3. Informationalize data. As characterized by Harvard Business Review Blogger, Thomas C Redman, it is important that the data available is "informationalized" for strategic use.
4. Apply technology. There are tools today that can glean information with context out of unstructured data. Humans have turned the tables on computers when it comes to processing data without casting it into rows and columns.
5. Work with a Trusted Advisor. Just as enterprises are best served with a Transformation GPS when embarking on the Applications Transformation journey, it is important that they work with a trusted partner to execute the combination of strategies that maximize the return on information. How about an Information GPS?
What is your Return on Information? How do you maximize the value of the data generated in your enterprise? What is the total cost of maintaining the data in your enterprise? Please let me know.