Analytics & Marketing Metrics

What CFOs Need to Know for Financial Analytics Success

CFOs know their numbers, but analytics is still a bear for just about everyone in the beginning. A particular problem for businesses right now is that resources are getting tapped out just in the process of producing analytics reports—which leaves no resources leftover to actually interpret them. In an article for Digitalist Magazine, Elizabeth Milne examines the nuances of using analytics in a way that actually pushes business forward.

Pillars of Success

Drawing from best-in-class SAP customers, Milne identifies three core areas of benefits that come from successful analytics: (1) process benefits through automation, (2) improved cycle times, and (3) reduced IT burden. How does a business achieve this success? There are what Milne describes as “four pillars of financial analytics success,” and a successful business will engage in at least three of these four:

  • More automation and self-service
  • Improving forecasting and planning
  • Upgrading to real-time performance
  • Strengthening governance and controls around reporting

Pursuing automation is an invaluable first step toward more daring digital pursuits. Good governance will ground these efforts in a measurable, structured environment. Meanwhile, improving forecasting and planning will be equally valuable:

In terms of planning, [successful businesses have] often closed the gap between financial results and planning by using the same system to manage both sets of data. On the leading edge, FP&A teams are using predictive modeling to explore alternative business outcomes, scenarios, and plans with simulation modeling, and beginning to explore technologies like machine learning to build more accurate forecast models. Enterprise performance management (EPM) suites provide a range of capabilities to conduct “what-if” analysis, compare scenarios, and reduce planning-cycle times, while the latest predictive analytics provides a range of prebuilt machine learning and statistical tools to apply to financial forecasting.

For a deeper discussion of these points, you can view the original article here:

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