It doesn’t take away the more commonly used Return on Investment. Instead, using ROI to mean Return on Information reinforces the business value of the information the enterprise has access to. That is, if the enterprise can extract the right information from its data—albeit structured or unstructured. Data continues to grow by leaps and bounds with new terms like Brontobyte and Yottabyte beginning to take on meaning. However, we must remember to informationalize on that data with matters to 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
Data that matters 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.
insight << information << data.
However, the real question for enterprises is whether they are getting the Return on Information (ROI) from their data. 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.
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.