Q11: Can you next describe how to best use predictive analytics?

A look at how predictive analytics is used to help drive decision-making starts with a basic need to improve things. Someone once told me that despite all the advanced technology in our phones, cars, homes, workplaces… the world is a remarkably inefficient, wasteful place.

Two blogs ago, I defined predictive analytics as a process that takes data and extrapolates patterns to predict likely outcomes. Past, Present, Past Present, Future… the goal being too provided educated guesses on what is most likely to happen next. The primary use of predictive analytics is to predict outcomes using models that will mitigate risk and eliminate choices based on unlikely outcomes.

For anyone who is familiar with Lean or Six Sigma, there is a lot in common with predictive analytics and process improvement methodologies.  We take historical performance data and combine it with rules, algorithms, and occasionally external data to determine the probable future outcome of an event or the likelihood of a situation occurring. Once we see where we think things might go wrong, we make changes to prevent or at least mitigate the future.

Predictive analytics is used most extensively in places where you want to know the future like sales, marketing, and finance. To do this you need to build models. Models are not always simple and often take someone with both business experience and professional training in certain coding or programming languages.

In the hands of a good analyst, predictive analytics helps a business continually reinvent itself based not just on what happen, but what is likely to happen.

This allows a wide range of organizational activities to be improved by predicting the behaviors and outcomes of people, the futures of individual customers, debtors, patients, criminal suspects, employees, and voters. It’s that generality that makes this technology so awesome.

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Business that have good predictive analytics are much more likely to be successful over the long term. When you look at businesses that fail, its generally because they didn’t have an eye of the future.

If you are wondering how to take your descriptive analytics to the next level and start getting more into predictive analytics, let me know. I can help you figure out to starting using something besides the magic 8 ball to predict what lies ahead.

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