To consistently manage performance, companies need timely and accurate forecasts that can guide decision making in near real time, as well as support strategic goals in the long term.
The best forecasting practices are highly flexible – able to model multiple scenarios and adjust to rapidly changing conditions.
When executed correctly, forecasting can help you streamline processes, respond to changes, evaluate business drivers, and improve processes and workflows. In the absence of a proven psychic, the best forecasts are built on accurate, relevant data plus a healthy dose of process automation.
In today’s dynamic business environment, forecast accuracy should be managed and measured as each forecast is prepared – weekly, monthly, or quarterly. To help oversee the forecast processes, a forecast review committee can set guidelines that shape and improve methods that will impact the accuracy of future forecasts. Assuming you have accurate data feeding your flexible forecasting process, there are two ways to manage forecast accuracy for the best possible decisions.
Method 1 – Managing From Within
You can manage forecast accuracy from within your chosen forecast application or solution, adding elements or supplementing with additional dimensions, scenarios, and capabilities.
For example, you might add a dimension to your revenue scenario that allows you to evaluate revenue by product, customer, or timeframe. Or you could add best- or worst-case scenarios, balancing scope of change with projected value of the forecast accuracy.
With this approach, you perform evaluations within the context of immediate forecasting needs, creating real-time comparisons for immediate feedback. You can evaluate variances against previous and current forecasts, or run quick calculations to measure a particular forecast against reality. This option does require making slight design changes to your existing forecast solution.
Method 2 – Managing with a Companion...
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