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5 Demand Sensing Myths

By September 7, 2022September 11th, 2022Blog

Demand sensing is often mistaken as a conventional demand forecasting tool. However, there is much more to it. Let’s debunk five common myths about demand sensing.

Myth #1 – Demand sensing isn’t needed because my forecast is already accurate.

Your long-term forecast may be accurate, but demand sensing is critical to capture signals and plan for short-term fluctuations in demand. And while it’s still important to consider the past when predicting the future, given the unprecedented supply chain disruptions over the last three years, relying solely on historical data isn’t enough. The ideal way to forecast demand is to combine internal data and historical trends with real-time external demand signals.

Myth #2 – Short-term demand signals can’t be captured without POS data.

While POS data can be fed directly into machine learning algorithms to identify patterns, it is not a prerequisite for demand sensing. Short-term patterns can be identified by looking at your most recent sales, order, shipment and forecast data.

Myth #3 – Daily forecasting will disrupt my existing forecast.

The whole idea behind demand sensing is to bring deeper granularity to your existing forecast, which can then be leveraged to make better planning decisions. Think of demand sensing as an enabler to reduce lag between supply chain events and your response.

Myth #4 – Our business cannot be forecasted.

For slow-moving items with long lead times and uncompetitive pricing, demand sensing may not feel relevant. However, certain planning elements, like material price and customer delivery rates, can still be forecasted, which can make your supply chain more resilient.

Myth #5 – Demand sensing is difficult to implement.

Demand sensing is a complementary technology to demand planning and needs a logical framework to finalize the datapoints to be used in the model. Both human management and a comprehensive view of the framework are required to ensure success. The effort is worth it, as demand sensing has been proven to improve forecast accuracy by as much as 40%.

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