Predictive Analytics — The Evolution of Business Intelligence
Predictive analytics is the next step in the evolution of business intelligence. Most companies, even local small business, have already implemented business intelligence systems that help them understand what has happened, why it happened and what is currently happening. For example, most small businesses have implemented Quickbooks and Google Analytics that allow them to report, analyze and display data about their finances, operations and marketing.
The next step in the evolution of business intelligence is to understand what is likely to happen. Predictive analytics allows executives to learn from the cumulative knowledge of their organization. This systematized learning has the potential to help businesses and executives to make decisions that are less wrong, so that they can work smart. Imagine understanding your customers well enough that you only send discounts to profitable customers who are risk of leaving, and not to customers that are unprofitable or not at risk of leaving.
Predictive analytics is a technology that has proven itself in academics, medicine, government and business. By combining mathematics and statistical methods to discover patterns in data, predictive analytics differentiates itself from other business intelligence tools by being able to ‘learn’ from experience. It is the only business intelligence tool that doesn’t rely on the users ability to find patterns in the data and deduce meaningful insights.
When properly implemented, predictive analytics enables your business intelligence to move beyond information to insights about why something happened, what you should do next and what the future might look like. The following matrix highlights the information that traditional business intelligence provides, and the insights that predictive analytics provides.
Since predictive analytics produce insights that are customized specifically to your company, customers, employees, and competitors; it has the potential to provide your company with a unique and non-transferable competitive advantage. The return on investment realized from predictive analytics depends on the value of the business question that answered. Most research in the ROI of predictive analytics conclude that ROI is maximized when companies use predictive analytics to improve the effectiveness of their business processes, such as sales, marketing, customer retention, management and strategic planning. This is why CAN has focused on developing products that use predictive analytics to help people sell, market, retain customers, manage and plan smarter. Our mission is to reduce the cost and complexity of predictive analytics, so that businesses of all sizes can work smart.