How Predictive Analytics Adds Business Value - dummies

How Predictive Analytics Adds Business Value

By Anasse Bari, Mohamed Chaouchi, Tommy Jung

In an increasingly competitive environment, organizations always need ways to become more competitive. Predictive analytics found its way into organizations as one such tool. Using technology in the form of machine-learning algorithms, statistics, and data-mining techniques, organizations can uncover hidden patterns and trends in their data that can aid in operations and strategy and help fulfill critical business needs.

Embedding predictive analytics in operational decisions improves return on investment because organizations spend less time dealing with low-impact, low-risk operational decisions. Employees can focus more of their time on high-impact, high-risk decisions.

For instance, most standard insurance claims can be automatically paid out. However, if the predictive model comes across a claim that’s unusual (an outlier), or if the claim exhibits the same pattern as a fraudulent claim, the system can flag the claim automatically and send it to the appropriate person to take action.

By using predictive analytics to predict a future event or trend, the company can create a strategy to position itself to take advantage of that insight. If your predictive model is telling you (for example) that the trend in fashion is toward black turtlenecks, you can take appropriate actions to design more black-colored turtlenecks or design more accessories to go with the fashionable item.

Endless opportunities

Organizations around the world are striving to improve, compete, and be lean. They’re looking to make their planning process more agile. They’re investigating how to manage inventories and optimize the allocations of their human resources to best advantage. They’re looking to act on opportunities as they arise in real time.

Predictive analytics can make all those goals more reachable. The domains to which predictive analytics can be applied are unlimited; the arena is wide open and everything is fair game. Let the mining start. Let the analysis begin.

Go to your analytics team and have them mine the data you’ve accumulated or acquired, with an eye toward finding an advantageous niche market for your product; innovate with data. Ask the team to help you gain confidence in your decision-making and risk management.

Albert Einstein once said, “Know where to find information and how to use it; that is the secret of success.” If that’s the secret to success, then you will succeed by using predictive analytics: The information is in your data and data mining will find it. The rest of the equation relies on your business knowledge of how to interpret that information — and ultimately use it to create success.

Finding value in data equals success. Therefore you can rewrite your predictive analytics equation as

Data mining + business knowledge = predictive analytics => success

How predictive analysis empowers your organization

Predictive analytics empowers your organization by providing three advantages:

  • Vision

  • Decision

  • Precision


Predictive analytics will lead you to see what is invisible to others — in particular, useful patterns in your data.

Predictive analytics can provide you with powerful hints to lend direction to the decisions you’re about to make in your company’s quest to retain customers, attract more customers, and maximize profits. Predictive analytics can go through a lot of past customer data, associate it with other pieces of data, and assemble all the pieces in the right order to solve that puzzle in various ways, including

  • Categorizing your customers and speculate about their needs.

  • Knowing your customers’ wish lists.

  • Guessing your customers’ next actions.

  • Categorizing your customers as loyal, seasonal, or wandering.

Knowing this type of information beforehand shapes your strategic planning and helps optimize resource allocation, increase customer satisfaction, and maximize your profits.


A well-made predictive analytics model provides analytical results free of emotion and bias. The model uses mathematical functions to derive forward insights from numbers and text that describe past facts and current information. The model provides you with consistent and unbiased insights to support your decisions.

Consider the scenario of a typical application for a credit card: The process takes a few minutes; the bank or agency makes a quick, fact-based decision on whether to extend credit, and is confident in their decision. The speed of that transaction is possible thanks to predictive analytics, which predicted the applicant’s creditworthiness.


Imagine having to read a lot of reports, derive insights from the past facts buried in them, go through rows of Excel spreadsheets to compare results, or extract information from a large array of numbers. You’d need a staff to do these time-consuming tasks. With predictive analytics, you can use automated tools to do the job for you — saving time and resources, reduces human error, and improves precision.

For example, you can focus targeted marketing campaigns by examining the data you have about your customers, their demographics, and their purchases. When you know precisely which customers you should market to, you can zero in on those most likely to buy.