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Predictive Analytics and Business Value

Fern Halper of TDWI Research examines a pair of preliminary results from the TDWI Predictive Analytics Best Practices survey.

I am in the process of collecting data for my TDWI Best Practices Report on predictive analytics. The report will examine trends and best practices for predictive analytics. Some specific issues being investigated in the survey include: Who is using predictive analytics? What skills are needed to do so? Is it being used in big data analysis? Is it being used in the cloud? What kind of data is being used for predictive analytics? What infrastructure is supporting it? What value does it provide?

I define predictive analytics as a statistical or data mining solution consisting of algorithms and techniques that can be used on both structured or unstructured data (together or individually) to determine future outcomes. It can be deployed for prediction, optimization, forecasting, simulation, and many other uses. 

One of the first questions I asked in the survey is, “What is the status of predictive analytics in your organization?” To date, 37% of the respondents are currently utilizing predictive analytics, 53% are exploring it, and less than 10% have no plans to use it. Note that this survey is not meant to determine the adoption of predictive analytics. The group that answered the survey might have been self-selecting in that those who are not using predictive analytics may have chosen not to respond to the survey. One reason I asked this question was to be able to look at any differences between the two groups.

I also asked: “Would you say that analytics underpins your organization’s business strategy and drives day-to-day decisions?” Interestingly, those respondents already using predictive analytics were more likely to respond that analytics (in general) underpins their organization’s strategy and drives day-to-day decisions. About 37% of those respondents who are already using predictive analytics stated that analytics definitely underpins their day-to-day decision making, while only about 23% of those investigating the technology stated the same.  

Another way of looking at these answers is that 85% of those respondents using predictive analytics state that analytics is driving their day-to-day decisions in some way (i.e., answered definitely or somewhat), while only 65% of those who are investigating use analytics to drive day-to-day decisions and strategy. 

Does this use of predictive analytics to drive strategy and decisions provide a benefit?  It would appear so from preliminary results of the survey (of course, that's subject to change once all results are analyzed). Close to half of the respondents who now use predictive analytics have actually measured a top- or bottom-line benefit (or both) from their predictive analytics efforts.

These preliminary results are quite interesting and I’m looking forward to getting all the data and analyzing the results! The TDWI Best Practices Report will be published later this year. I will continue to provide some updates on my blog, along the way, so stay tuned!

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