Senior business executives need to identify unique opportunities for growth, organize resources for their pursuit, and extract a sound return on investment. Those who succeed are good at understanding that performance can be proactively influenced. They create an effective and cost-efficient predictive analytics process that encompasses a range of techniques dealing with the collection, classification, analysis, and interpretation of data to gain insight, reveal patterns, anomalies, key variables, and relationships.
Lawrence Maisel, a globally recognized authority on performance management, demonstrated how CFOs can use predictive analytics to gain a competitive advantage in his book Predictive Business Analytics. In an upcoming APQC webinar, Mr. Maisel will dig into what predictive business analytics can mean for the finance organization and how to build a path to progress. In preparation for the July 29 webinar, APQC sat down with asked Mr. Maisel to clarify some of the key principles and risks involved.
APQC: What should we convey when we refer to predictive analytics?
Larry Maisel: There is a lot of confusion about what those words mean, so let’s set the record straight. Predictive analytics refers to the organizational capability to use talent, tools, and technologies to help the organization achieve optimal results. Too often people confuse predictive analytics with data science, which denotes one technique or another.
APQC: If a finance team wants to go the route of predictive business analytics, will that mean dispensing with previously used approaches for product/service pricing, resource allocation, or target setting?
LM: There’s nothing to restrict finance from leveraging traditional analytical tools such as scenario planning within the context of predictive analytics. In fact, those traditional approaches to financial analysis can be an integral part of the expanded capability.
APQC: Please give us an example of how predictive analytics could be used.
LM: The analytics people at a mortgage lender could look at the patterns of change, month to month, in the number of mortgage applications, perhaps alongside the number of hours spent with the average customer, and then predict the likely impact on total revenue. That’s different from forecasting annual revenue based on the prior year’s financial outcome.
APQC: What are the must-have enablers to build this capability and have it generate true value?
LM: Process speed, the immediacy of data, and the ability to have a rapid response to the market are keys. Of course you have to have the right people—and that implies gaining insights around the skills needed and whom you have to hire. If you don’t have these pieces, then you will not win organizational trust. You will not be able to convince operating leaders that you know what you’re doing. Finally, the CFO has to be sincerely committed to an incredible playbook, along with the vision and confidence that will convince the rest of the C-suite that he or she can actually deliver game-changing analysis.
To learn more about using analytics join us at 11 a.m. on July 30 for our webinar 'Using Analytics to Re-envision Order-Management Processes for Improved Customer Loyalty'.