Descriptive, Predictive and Prescriptive

Dateline: March 6, 2015

Welcome to our Friday WRAP – one thought-provoking idea to think about over the weekend.

Analytics is on the minds of every senior leader today.  Companies have data warehouses full of data just waiting to be mined for gems of actionable insights.  No one will argue against the goal of making better business decisions with data and analytics, but how to do that is a function of the analytics maturity of the organization.  I recently came across a great article that explained this progression in terms of descriptive, predictive and prescriptive analytics.

Data scientist Michael Wu, from San Francisco-based Lithium Technologies, described to Information Week how this progression works.

“Once you have enough data, you start to see patterns,” he said. “You can build a model of how these data work. Once you build a model, you can predict….the simplest class of analytics, descriptive, is the one that allows you to condense big data into smaller, more useful nuggets of information….The purpose of descriptive analytics is to summarize what happened.”  Wu estimated that more than 80% of business analytics…are descriptive.

Predictive analytics is the next step up in data reduction. It utilizes a variety of statistical, modeling, data mining, and machine learning techniques to study recent and historical data, thereby allowing analysts to make predictions about the future.

“Prescriptive analytics is a type of predictive analytics,” Wu said. “It’s basically when we need to prescribe an action, so the business decision-maker can take this information and act…. Prescriptive analytics requires a predictive model with two additional components: actionable data and a feedback system that tracks the outcome produced by the action taken.”

Where in this progression is your analytics program?  What will it take to get you to the next set of capabilities?

That’s a WRAP!  Have a great weekend.


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