Getting ahead: How CFOs can align minds and machines to reinvent forecasting

Introduction

Maybe CFOs should have seen it coming: a time when the future no longer even seemed predictable. But in the wake of the COVID-19 pandemic, triggering congested supply chains and climbing inflation, some finance leaders may worry that their agility and adaptability are being put to a test. As a result, they want as much insight as possible into what might happen next.

Their concern, however, coincides with the fact that machine-powered forecasting—also known as predictive analytics—is quickly migrating from a nice-to-have productivity advantage to becoming a key capability for CFOs seeking to navigate changing market conditions and keep pace with strategic objectives.

An increasing number of companies, in fact, have invested in sophisticated forecasting tools that enable their businesses to overcome analytical bandwidth constraints. Some of those companies, however, have yet to unlock the full potential of machine-powered forecasting.¹

What could be holding them back? In some cases, CFOs may be hampered by fragmented data, inconsistent processes, and limited reserves of talent. Or maybe finance leaders have yet to master data quality or to aggressively pursue the replacement of outdated systems.

Even CFOs who have gotten that far may overlook an entire category of issues that has less to do with acquiring the technology, and more to do with the training of those who are using it. After all, investments in financial forecasting technologies are only as strong as the trust users put in them. Recognizing such challenges—and identifying the complex dynamics underlying them—can be crucial to deploying algorithmic forecasting solutions.

In this edition of CFO Insights, we’ll examine how CFOs and their teams can address the issues that may be preventing the business from successfully integrating machine-powered forecast technology into the financial planning and analysis (FP&A) function.

Endnotes

¹ “Building trust in a machine-powered forecast,” Deloitte Consulting LLP, 2021