There are many areas where businesspeople wish they had the proverbial crystal ball to foretell the future. Forecasting consumption demand is one of the trickiest of these areas.

Given the size of the portfolios and the dollars at stake, it is imperative to produce the right product, size, and quantity to meet consumption demand. Then you also have to ship it in the right mix to the right location at the right time. It’s easy enough to say. Why is it so difficult to actually accomplish?

Think of all the factors at work. Highly volatile trade and consumer environments and ever-changing trends enhance sales unpredictability. There are too many variables that impact consumer demand, including competitors’ activities and a combination of any number of other factors. And yet, despite the odds, we still need these predictions to go ahead with our business.

Why are accurate consumption forecasts so darned hard?

The Problem with Traditional Demand Projections

Typically, the annual budgeting process is a poor basis for forward projections. Predicting shipment demand based on orders from the retailer is also challenging; the order stream is often filled with ‘noise’ from forward buy distortions, indecisive buyers, order-type errors (for example, a sale is marked as a promotion when it’s really a re-order), one-time shipments, etc. Altogether, these form an unsatisfactory platform to build a future on.

The absence of a statistical framework to forecast consumption demand leaves decision makers with no option but to rely on their judgment. And this is especially challenging when you consider how important an accurate forecast can be.

The Value of a Good Forecast

To understand the value of an accurate consumption demand forecast, let’s flip the equation and consider the reverse. The potential costs from an erroneous projection are daunting: overtime production costs if the item goes big; overbuilds and inventory burn outs if it doesn’t. Add in the possibility of millions in missed sales and lower levels of customer service, and we can all see why so many companies are trying to find the magic formula behind a reliable consumption demand forecast.

On the other hand, the advantages of having realistic consumption forecasting and linking it to demand planning are unparalleled. More accurate sales forecasts are produced, which leads to improved sales, higher margins, and a better overall business performance.

What a Good Consumption Demand Forecast System Can Do

A robust system provides insight into the near-term predictable future. It facilitates business planning, risk management, budgeting, and goal setting. Potential early warning signs and risks in the sales pipeline can be easily identified, and corrective actions can be taken to reduce the gap.

This, in turn, leads to something quite different than the dire picture painted above: a more exact amount of inventory, higher service levels, reduced losses due to out-of-stock and markdown items, and ultimately more consistent processes and tangible bottom-line benefits.

Consumption Demand Forecasting is all about understanding the past and predicting the future based on certain identifiable patterns and potential events. Organizations can achieve better accuracy and forecasting process efficiency by improving the “forecast-ability” of consumption demand – and by employing certain fundamental and proven practices.

Authored by Imran Saeed, Director – Analytics at Absolutdata and Neharika Agarwal, Manager, Analytics at Absolutdata