Defining terms – Business Intelligence (BI) refers to skills, processes, technologies, applications and practices used to support decision making. Predictive analytics encompasses a variety of techniques from statistics, data mining and game theory that analyze current and historical facts to make predictions about future events.
Business intelligence provides valuable insight into the state of affairs within an organization. The information is critical to decision-making. But when combined with predictive analysis, synergies can be leveraged to improve business and operations.
The easy analogy between BI and predictive analysis can be described as follows. A good rugby player plays where the ball is, a great rugby player plays where the ball is going to be.
BI tools help users know what has happened and what is happening, while predictive analytics tools
Help to elicit more from this information by providing an understanding of why these things happened and in predicting what will happen.
For example, BI tools can report which sales region had the highest sales, how many widgets were sold in stores in different ZIP codes, the average spending per online customer vs. in-store customer, and how many customers stopped doing business with your company last year. All of this information is essential for developing new product and services, allocating resources, investing in marketing
campaigns, and so on.
Predictive analytics tools, though, can give deeper insight into why these things happened. For example, knowing the average customer spends $100 per visit to a store is one thing. Knowing that a certain 20 percent of the customers are responsible for 80 percent of all revenues and that they are more likely to buy particular products bundled together is much more valuable. Also, identifying which products influenced the purchase of others or the strength of the relationship between products purchased together would give more insight into specific buying patterns.
This added level of analysis can yield valuable results. It helps you understand how that prized segment of your customer base would respond to very targeted promotions.
Predictive analytics helps organizations look forward and make educated decisions that anticipate the future needs of customers. It combines known information about customers, sales, operations, or finances, with critical insight that helps solve problems, achieve business objectives, and uncover hidden patterns not easily identifiable through reports or dashboards. The combined knowledge is used to take actions that can improve business.