Corporate Performance Management: Predictive Analytics

Research shows that analytics-based decision-making can contribute significantly to the achievement of a company's strategic objectives.

Analytics is defined as the application of technology, research and statistics to solve problems, and realize opportunities, in business and industry.  It's intent is to optimize a company's performance by developing decision recommendations based on insights derived through the analysis of existing and/or simulated future data. Business managers may choose to make decisions based on past experiences or rules of thumb, or there might be other qualitative aspects to decision making; but as soon as those managers evaluate & analyze data when making decisions, they are employing analytics. Common applications of analytics include the study of business data in order to discover and understand historical patterns with an eye to predicting and improving business performance in the future

Predictive analytics can be used as a way to enhance corporate performance management because it improves the quality of decision making, as well as the speed of execution of those decisions. 

Performance management has 3 components.  At it's most basic level, performance management includes reporting on historical performance. The next level is the alignment of company strategy, resources and finances towards achieving a stated objective (i.e. the balanced scorecard).  The final step, and the one many companies forget about, is to continually improve performance by having accurate answers to questions such as:

• Which measures drive the business, and which do not?
• Why did a problem occur?
• Is there an opportunity we can take advantage of?
• Are we acting or reacting?

Once a corporate performance management solution is in place -- with KPI's that have been linked to a company's strategic objectives -- it allows companies to come together across multiple functions to look at their situation, to understand what’s happening in their business & explore why it is happening.  Predictive analytics takes the next step by applying scenario analysis to the information, helping a company predict what will happen if these trends continue.  This will allow them to determine best case scenarios that will help them achieve their strategic objectives.  Decision makers will have access to data they need, when they need it, wherever they need it, in whatever form.  It will help deliver better overall decision making capabilities in terms of sustainable shareholder value.

Predictive analytics are important because organizations are shifting away from managing by control and reacting to after-the-fact data; they’re moving toward managing with anticipatory planning. The goal is to be proactive and make adjustments before problems occur.