What forecasting demand mistakes should you avoid?

1 Relying on historical data only

One of the biggest forecasting demand mistakes is to base your projections on historical data only, without considering the current and future factors that may influence demand. Historical data can provide useful insights, but it cannot capture the changes in customer preferences, market trends, competitor actions, seasonality, promotions, or external events that may affect demand. To avoid this mistake, you should supplement your historical data with qualitative and quantitative methods, such as surveys, interviews, market research, scenario analysis, or machine learning, that can help you identify and account for the demand drivers and trends.

2 Ignoring variability and uncertainty

Another common forecasting demand mistake is to ignore the variability and uncertainty that are inherent in demand patterns. Variability refers to the fluctuations in demand over time, while uncertainty refers to the degree of unpredictability in demand. Both can affect your forecast accuracy and lead to overstocking or understocking issues. To avoid this mistake, you should measure and monitor the variability and uncertainty of your demand using metrics such as standard deviation, coefficient of variation, or mean absolute percentage error. You should also use forecasting techniques that can handle variability and uncertainty, such as moving averages, exponential smoothing, or probabilistic models.

3 Using a single forecast for all purposes

A third forecasting demand mistake is to use a single forecast for all purposes, without considering the different levels of aggregation and time horizons that may be required for different inventory management decisions. For example, you may need a different forecast for ordering raw materials, planning production, allocating inventory, or setting prices. Using a single forecast for all purposes can lead to inefficiencies, inconsistencies, and misalignment of goals. To avoid this mistake, you should use a hierarchical forecasting approach, where you generate forecasts at different levels of aggregation (such as product, category, or region) and time horizons (such as short-term, medium-term, or long-term) and reconcile them to ensure coherence and accuracy.

5 Neglecting communication and collaboration

A fifth forecasting demand mistake is to neglect communication and collaboration with other stakeholders involved in inventory management, such as suppliers, customers, or other departments. Communication and collaboration can help you improve your forecast quality, reliability, and acceptance, as well as reduce the risks of conflicts, errors, or delays. Communication and collaboration can also help you share information, insights, and feedback, as well as align your expectations, goals, and actions. To avoid this mistake, you should use tools and platforms that facilitate communication and collaboration, such as cloud-based software, dashboards, or reports, and involve your stakeholders in the forecasting process, such as by soliciting their input, feedback, or validation.