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.
The Research paper on Qualitative forecasting techniques
Qualitative Forecasting Approaches Qualitative forecasting methods are based primarily on human judgement. Quantitative forecasting methods are based primarily on the mathematical modelling of historical data. Here we provide a brief overview of the most important qualitative forecasting approaches. In many environments the time horizon is closely linked to the type of forecasting method used. ...
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 Forecast Accuracy App Alternately, you could create a separate solution entirely focused on evaluating forecast accuracy – a standalone application that uses performance metrics, advanced statistical analysis, and sophisticated calculations to review multiple forecasts – such as financial, sales, and HR – simultaneously, identifying both trends and areas needing improvement.
Sophisticated advanced metrics let you review a wider range of factors, or see the cumulative effect of multiple forecasts. However, because it is actually a separate application, it takes more time to design and implement. With this option, you make no changes to your existing application, only adding the companion app. The Forecast Accuracy Review Committee With either option, you also need a forecast accuracy review committee – a small group of financial planners or analysts with some executive sponsorship.
The committee should evaluate the accuracy of each forecast, rather than its effect on the business (the variance in the forecast versus actual performance) – asking, “What internal or external factors prevented us from hitting the target, and how can we incorporate those factors into a more realistic forecast? ” One useful tool for the review committee: A dashboard to manage forecast metrics offers a quick visual representation that can help team members evaluate accuracy and craft a clear and immediate response.
