Where Are You on the Data Analytics Maturity Model?

 analytics maturity model

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4. Predictive Analytics

The most advanced analytics methodology is predictive analytics.

Through the use of predictive analytics executives can stop using gut feelings and base decisions on projected future impacts. For example, some companies use it to determine the discount amount they will offer a customer when on the call.

By anticipating what discount level will entice individual customers, the companies minimize the price cut, increase the probability of a sale, and yield better margins. Companies like Progressive Insurance use the information to determine which individuals they wants to insure and which ones they want to send to competition based upon the expected margins gleaned from past behaviors and known changes in lifestyle habits.

Another use for predictive analytics is to identify in real-time potential equipment failures so that repairs can be made before an outage occurs.

In addition to predictive analytics, businesses are adopting newer techniques such as text analytics (analyzing unstructured text), social media analytics, geospatial analytics (analyzing location-related data), and clickstream analysis (analyzing customer behavior on websites). All are being used to drive business value and are slowly working their way into the operational mainstream.

Summary

Analytics and business intelligence is not new but the way they are being applied today is much more advanced than just a few years ago.

CEOs in mid- to large corporations rate analytics as the top factor contributing to an organization's competitiveness. This change in the executive mindset to incorporate fact-based analysis (versus gut feels) into the decision-making process will make it more difficult for those companies to survive that do not make it integral to their business planning and execution.

Business and IT executives should understand what information they need for business forecasting and planning decisions as well as for the real-time information required to improve margins or revenues, reduce risks, or increase customer loyalty through personalization.   

Related articles:

Competitive Advantage Through Analytics

Finding the Right Data Resource: Asking the Important Questions

The True Value of Data

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About the author

Cal Braunstein

Mr. Braunstein serves as Chairman/CEO and Executive Director of Research at the Robert Frances Group (RFG). In addition to his corporate role, he helps his clients wrestle with a range of business, management, regulatory, and technology issues. 
He has deep and broad experience in business strategy management, business process management, enterprise systems architecture, financing, mission-critical systems, project and portfolio management, procurement, risk management, sustainability, and vendor management. Cal also chaired a Business Operational Risk Council whose membership consisted of a number of top global financial institutions.

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