Analytics platforms are essential tools in today’s organizations. Business leaders rely on them to facilitate fast, effective decision-making, while operations managers use such tools to deliver smooth execution of day-to-day processes. But it’s a mistake to think of analytics software as some kind of magic bullet.

CFOs at many organizations have found predictive analytics to be extremely useful when it comes to spurring growth and managing profitability, according to an article on CFO.com. But having a sound strategy is more important than the analytics platform alone. In order to leverage these tools successfully and encourage their broad adoption across an organization, there are three facts CFOs need to know.

  1. To make a real impact, analytics must be forward-looking. Business leaders need to understand past performance, of course. But when it comes to making good decisions about the future, robust, predictive analytics can help provide the necessary foresight.
  2. Analytics capabilities are only valuable if you ask the right questions. It’s easy to think of an analytics solution as primarily software, or a collection of functions. However, the most important part of deploying such a solution is the strategy behind it. According to CFO.com, the most significant factors a company needs to decide are which decisions and business issues to address with analytics, and how the insights from analytics will be used and applied.
  3. Predictive analytics can help clarify communication and goals at the executive level. At any company, different executives will have different agendas and ways of expressing them. CFOs can use predictive analytics as objective measures for steering conversations, and help the C-suite as a whole when it comes to decisions about evaluating performance, identifying business opportunities and establishing the priority of business initiatives.

As is the case with many business technologies, having a sound strategy for using predictive analytics is more important than the tool’s functionalities. An easy win might be mining the data in your organization's expense reports with the goal to uncover the true cost of sales.

What other tips would you suggest for developing a strong predictive analytics platform and strategy? Please share your thoughts in the comments section! 

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