Keywords: business intelligence, prescriptive intelligence, business analytics, data mining, predictive analytics
Traditionally, business intelligence (BI) has looked backward at what has happened. In today’s marketplace, enterprises need to look ahead. From predictive to prescriptive intelligence, we look at what businesses need most with David Clement, product marketing manager for IBM Business Analytics. Customers are looking at descriptive intelligence (what is happening now) and predictive intelligence (what is going to happen next). Ultimately, the goal is to get to prescriptive intelligence—what should I do and what will that do to my business. Forward-looking business intelligence is the way to go beyond descriptive intelligence—which has long been a staple—to predictive intelligence, which, in turn, paves the way to prescriptive intelligence.
How does forward-looking business intelligence help decision makers and lower risk?
Combining past, present, and future views of one’s data side by side allows analysts, department managers, and executives to make better, more informed decisions. By aligning with company goals and business plans, business users become more dependent and responsive to the data being used to validate their decisions. Although gut feel and experience are always going to play a role in how data is used to improve business choices and direction, validating those choices has become more important and liability has gone up. Backed by organizationwide data systems that articulate the position and predictive insights of the business prerogatives, using business intelligence and predictive analytics adds value and competitive advantage and lowers the risk of bad decisions.
What is the difference between data mining and predictive analytics?
Data mining provides the methodology for getting predictive intelligence out of your data from a technical perspective. Predictive analytics is a type of analytics and data mining is what a business user, business analyst, or data scientist actually does. Data mining at its essence is about finding the natural patterns, relationships, and outcomes within your data. Predictive analytics is more than just using algorithms and understanding models. For organizations, it’s about being able to use the results of data mining to effect positive business outcomes.
What are businesses looking to get help with?
Revenue generation is critical to a business. However, understanding how best to drive revenue growth can be arduous. Lines of business are looking to have precise awareness of their operations, and technology factors play a larger role than ever in maximizing this responsiveness to growing the business. Today’s small-to-large businesses have much more in common in terms of their needs to identify market trends, understand customer behavior, tackle inefficiencies sooner, make sense of the explosion of data to stay ahead of the competitive curve, and make impactful and smarter decisions that align with company goals. Read more...
