It is with no shadow of doubt that in today’s corporate world, data is increasingly becoming a valuable asset. However, unless subjected to analysis and manipulation for the company’s benefit, data on its own has no inherent value. That’s why companies seeking to gain a competitive edge over their peers are channeling massive resources towards data analytics. The problem is that many companies are torn between using predictive analytics and prescriptive analytics in the analysis of data.

Predictive analytics, as its name suggests, is used for prediction. A company can extract information from its data set through analysis and use the information to determine future patterns. The information can also be used to try and predict future outcomes and trends.

Basically, what predictive analytics does is to forecast the future. It involves ‘what-if’ scenarios and the assessment of risk. A company will therefore use its statistics and models to predict its future performance, outcomes and other variables.

Some of the ways through which predictive analytics can be beneficial to a business include:

1. Understand Your Customer

Predictive analytics can help businesses understand their customers much better. A company can use predictive analytics to try and predict the future behavior of a customer based on their past behavior.

For example, a company that is a financial institution can use an individual’s information regarding their payment history, employment history and loan application to gauge the credit worthiness of the individual and whether he or she is likely to pay or default on a loan. Basically, it employs past data to predict future trends.

This type of analytics will help a company know who its customers are and how best to engage with them. A company can therefore use predictive analytics to predict which kind of activities the customer is likely to participate in and what kind of products he or she is likely to purchase. This type of analytics can also enable a company to study the website browsing patterns and behaviors of a customer and predict which customers are likely to convert. The company can better calculate when to reach out to their customers and what kind of messages to relay to them. It can also predict when customers are likely to leave and thus help a company take steps and measures to retain its consumers.

Thus, predictive analytics can really help a company to understand its customers and to create a much better and personalized experience for them. This will in turn boost growth and profits for the company and increase customer loyalty.

2. Recognition of Future Risk

Predictive analytics can allow a company to use past data to predict future risk within the business. This is particularly important for companies dealing with credit and insurance claims. For those dealing with credit, this type of analytics can help them know which consumers are likely to default on loan payment. A credit score can be used for this purpose.

For companies dealing with insurance claims, past data can be analyzed and used to predict where more or less risk lies. This will allow the company to determine insurance premium rates and detect fraud claims. It will also allow the insurance claims to better allocate risk. Health insurers can use predictive analytics to know which patients are at most risks of chronic disease and therefore allocate risk accordingly.

Other benefits that companies can reap from using predictive analytics include prevention of fraudulent activities before they occur, marketing of products and maximizing on company operations. Airline companies can use predictive analytics to adjust their price tickets while hotels can use this type of analytics to know when customers are likely to increase and thus take measures to ensure maximum occupancy. Predictive analytics can be used by all kinds of businesses, from airlines to insurers to manufacturers and healthcare.

Prescriptive analytics on the other hand involves finding the best course of action under given circumstances. It comes after predictive analytics and can help a company take the direction that would be most profitable and beneficial after making the predictions.

This type of analytics will suggest actions to benefit from the predictions made on outcomes and future patterns. More than that, it will also suggest the ramifications that may come with settling on each of the actions. It goes beyond anticipating what will happen and when it will happen. It anticipates why certain outcomes will take place.

Prescriptive analytics will help a company translate its predictions on outcomes and trends into feasible plans. It will also suggest ways through which a company can explore a future opportunity or mitigate a future risk.

Basically, both sets of data analysis are equally important. While predictive analytics will help forecast what might happen in the future, prescriptive analytics will help companies draw up specific recommendations in an effort to change the future and therefore maximize company profits and growth. Both components can help turn descriptive analytics into insights and decisions, and in turn help create a stronger and effective business strategy. Companies using both predictive and prescriptive analytics will be in a better position to improve operations and make faster, more intelligent decisions.

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