Who Needs an Accurate Forecast?

I once joked with a friend who works at a large funeral home that business must be steady since people pass away every day. But he quickly corrected me: “Not true.” Some days, half the funeral chapels are empty, while on others, they’re fully booked, so much so that they have to turn people away. In fact, there’s a surprising seasonal pattern to it. The demand often dips before Christmas and spikes right after New Year’s. It’s almost as if people can schedule their passing to align with the calendar! What this underscores is a powerful lesson: Even in businesses with a "sure" market, demand can still be unpredictable.

This uncertainty highlights the critical importance of forecasting demand—a fundamental component of any successful business strategy. Especially now, as companies invest in integrated planning systems (often called Enterprise Resource Planning or ERP), the need for a solid forecasting process has never been more crucial. But it’s not the ERP system that presents the challenge. It’s developing an accurate forecast to feed into the system.

Defining Key Terms

To get started, let’s clarify some key terms that are essential for any forecasting process:

• Demand Forecast: This is what customers are expected to buy, based on historical data, seasonality, and broader economic trends. It’s a prediction of how much customers will demand—nothing to do with what management wants.
• Sales Plan: This is what the sales and marketing teams aim to deliver. It’s based on the demand forecast but also includes the influence of marketing campaigns, promotions, and pricing strategies. It’s the controllable part of the equation.
• Sales Target/Quota: This is what management expects the company to deliver in terms of sales performance, often linked to organizational objectives and performance incentives.

A common mistake many companies make is conflating the demand forecast with the sales target. When this happens, sales targets—often overly aggressive or unrealistic—drive the entire ERP system. The result? Production plans and material orders are misaligned with actual customer needs, leading to either overstocked inventory or stockouts, both of which come with hefty costs.

The Core Challenge: What Will Customers Actually Buy?

The real challenge in forecasting lies in accurately predicting what customers will buy. It’s about gathering the right data and using it to create the best possible estimate of future demand. To do this, organizations need to:

• Use data that reflects actual market behavior, not just internal sales forecasts.
• Account for both historical trends and seasonal fluctuations.
• Be mindful of any unexpected spikes or dips—for example, a sudden surge in demand might occur when a previously out-of-stock item becomes available again, or a sales drop might follow a shift in a sales team's activity.

Data Analysis: The Key to Accurate Forecasting

Analyzing data is the easy part. When the data is solid, it becomes a matter of choosing the right tools or algorithms to generate the forecast. But it all starts with historical behavior:

• Are there recurring trends or seasonal cycles?
• Did unexpected spikes or dips happen in the past?
• Can we trace those fluctuations back to something specific, like an external event, a supply chain issue, or even a change in sales strategy?

In practice, these insights often reveal surprises. Maybe a product suddenly became a hot seller after an influencer promoted it, or demand dropped because a new competitor entered the market. The key is to dig into the data, ask the right questions, and look beyond just the numbers to understand the why behind them.

Accountability and Buy-in

Even if you have the tools, the data, and the algorithms, one big question remains: Who is responsible for developing the forecast?

Forecasting is not just about crunching numbers—it’s about getting buy-in from the various stakeholders across sales, marketing, and operations. No one wants to be the bearer of bad news when the forecast doesn't match what departments want to hear. That's why it’s essential for the forecaster to work closely with other teams and ensure that everyone understands the limitations and assumptions behind the forecast.

Forecasting Uncertainty: A Plan for the Unknown

At the end of the day, demand forecasting is never 100% accurate. The market is inherently uncertain, and things rarely go exactly as predicted. But a good forecast provides valuable insight into what is likely to happen, giving businesses the opportunity to plan and prepare.

What’s most important is to have a contingency plan—one that accounts for the fact that forecasts can be wrong, and that flexibility will be required in the face of unexpected demand fluctuations.

In today’s fast-moving business environment, demand forecasting isn’t just about predicting the future; it’s about being prepared for whatever comes next.

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