If you’re not relying on predictive demand planning to increase the accuracy of your financial forecasting, you’re not alone.
More than 45 percent of 1,500 CFOs surveyed by IBM say they’re not ready to call it quits with spreadsheets. Unfortunately, spreadsheet-based processes are laborious, inconsistent and can lead to numerous pitfalls. So why supplement your planning process with a fully automated, analytics-driven solution to manage a multi-billion-dollar business?
Jim Collins, performance management strategy executive at IBM, gives these three reasons: to be able trust the information, to reduce the potential for errors and to ensure departments are collaborating. Collins spent years in the CFO seat himself. Predictive analytics serve to make sales professionals more efficient, improve forecast accuracy and reduce inventory shortfalls while maximizing inventory availability.
Companies such as Huffy Bicycles and Mueller Co. have made the switch and are enjoying an improved planning process that enables them to deliver more insight and maximize product availability for their customers.
Take another example, McCormick & Company, which manufactures spices, herbs, and flavorings for retail, commercial, and industrial markets. The company didn’t have any visibility on the total impact of the changing price of nutmeg. Thanks to predictive analytics, McCormick was able to predict commodity pricing and saw impact not only on cost to company but allowed them to look at production scheduling, size and timing of buys to see significant savings.
Learn more in this webinar about how predictive technologies (not spreadsheets) can improve the accuracy of your own planning and forecasting.