Using BI for Prescriptive Analytics

Prescriptive analytics is about using data and analytics to improve decisions and consequently, the effectiveness of actions. After all, analytics should lead to more informed decisions and successful measures. So, given known parameters from predictive analytics, Prescriptive Analytics help businesses find the best course of action for a given situation.

 

Prescriptive Analytics not only suggests decision options for how to take advantage of a future opportunity but how to alleviate a potential risk. It can clarify the implications of decision options. An example is combining different data sets in the medical industry. The resulting information can be used to offer doctors recommendations for the best possible treatment for a patient.

 

Companies generate new data every minute. So new data can result in a revision of predictions based on events happening in their customer base and allow an organization to get accurate predictions and offer better decision options. A good example is online travel websites. Airline ticketing services, hotel websites, and car rental websites use prescriptive analytics to sift through these multiple iterations of travel, purchases, and customer variables, including demographics and psychographics. This information allows them an advantage to optimize their pricing and offers.

 

While only 5-10 percent of companies use Prescriptive Analytics, Retail is one area that has adapted it. Retailers have been collecting information about their customers for years to create focused campaigns and increase sales. Some are targeting individuals by suggesting specific products for their specific needs. By taking the knowledge from Prescriptive Analytics a step further, Retailers can determine a customer’s life changes due to previous purchases and then advertised specific products to the customer to create sales. Due to this success, businesses are now getting even more intricate in the manner of how they handle customer data.

 

Prescriptive analytics work 24 hours a day and continually processes new data as it becomes available to re-predict and re-prescribe solutions. A successful example of using on-going prescriptive analytics is route optimization for the logistics industry. By combining, then analyzing, hundreds of data sources it can push thousands of route optimizations per minute to delivery trucks saving the company millions of dollars on fuel a year.

 

We want to help you use your data to its fullest. At FocustApps, we can help you combine your data sources then use Prescriptive Analytics to create solutions to grow your business. For more information, contact Blake Patterson at 502-907-6593 to learn more.

Jonathan Gonzalez