A Beginner’s Guide To Predictive Analysis

The ride sharing app Uber tells you your car will be arriving in 3 minutes when you book a ride, and is mostly accurate.

A Travel website lets you compare how much a flight would be on different dates at different times even from different airports allowing you to find the best price and most convenient dates.

You ask Siri or Google assistant to check a movie time or tell you what the weather is like and get an answer almost immediately.

Everyday you interact with a type of machine learning known as predictive analysis.

But most executives, even those with a passing familiarity with artificial intelligence and the machine learning techniques behind them still don’t have a handle on exactly what predictive analysis is and how it works.

I will explain what predictive analysis is, how it works and how it is currently being used in everything from pricing to logistics in simple everyday language that will enable you to understand the advanced concepts and see how they could be applied to your business. Without the embarrassment of admitting that you didn’t understand predictive analysis.

What is predictive analysis?

The simple answer is the process of using past data to predict future events.

Predictive analysis is the process of using a variety of statistical techniques such as machine learning to identify opportunities, weaknesses, and threats by creating a model based on past data.

One of the challenges of predictive analysis is creating a model that is free of bias and standard deviations. Because data mining is one of the techniques associated with predictive analysis, the data must be checked to be free of errors. As Ronald Coase famously said “If you torture data long enough it will confess.”

Predictive analysis is important because it allows your business to become much more Agile.

Agility functions as both a noun and an adjective as it allows your company to begin working in a more iterative rapid manner when compared with the traditional waterfall approach to work development.

As companies gather more and more data, the ones that succeed will be the ones that are able to turn that data into insights and test them quickly and agilely and predictive analysis is a key tool to making your business more agile.

Currently predictive analysis is used in many fields such as :

• Actuarial Science
• Marketing
• Financial Services
• Credit Scoring
• Insurance
• Telecommunications
• Retail
• Travel
• Healthcare
• And more

Let’s tie everything together by zooming in on some specific ways that predictive analysis is used to achieve specific goals right now.

3 Ways Predictive Analysis is used to achieve a specific goal.

1. High Frequency Stock Trading. In High frequency stock trading or HFT computer generated models make hundreds sometimes thousands of trades in split seconds. These predictive analytics models are responsible for identify and correlating a wide variety of different signals in almost imperceivable amount of time. Many of the top hedge funds such as Sun have been using predictive analysis to trade stocks for years.
2. Fraud Detection. If you’ve ever gone on vacation and had your atm or credit cards get flagged for fraud, you’ve experienced predictive analysis. Banks like Wells Fargo and credit monitoring agencies such as Equifax use predictive analysis models to figure out if the purchases you make fit your customer profile and flag your card if they see a purchase made in another location or of an extremely expensive item outside of your profile.
3. Child Protection. In his groundbreaking book Everybody Lies Seth Davidowitz theorized that while child abuse statistics went down during the great recession, searches for terms like “My dad hits me” actually went up. Using data like Google searches other data points The American Enterprise Institute has been presenting data to various states and organizations on how to use predictive analysis as a second set of eyes during the assessment of child abuse and endangerment.

Predictive analysis is the process of using past data to make predictions about the future based on complex models and advanced statistical techniques such as machine learning.

Predictive analysis is important because it allows companies to become more agile allowing them to test things faster leading, to better processes and a more enjoyable experience for the end user.

Some examples of industries using Predictive Analysis include:

• Insurance
• Telecommunications
• Retail
• Travel
• Healthcare

We also looked at 6 different examples of ways predictive analysis is used in the real world to do everything from order you a ride to protecting children from abuse.

You now have a basic understanding of what predictive analysis is and how it works. Now is the time to deepen your understanding and see what companies like WorkFusion can do to help your business take advantage of this amazingly powerful technique.

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