What are the most commonly used demand forecasting techniques?

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What Factors Should Be Considered in Demand Planning Models?

Demand planning models take in a variety of factors to predict future demand for a product or service.

What Factors Should Be Considered in Demand Planning Models?
Here are some key considerations:

Historical Data: This is the foundation of most models. Sales data, ideally spanning multiple periods, allows you to identify trends and seasonality. The quality and richness of this data will influence the forecasting method chosen.
Product Lifecycle Stage: New products have less historical data and require different approaches than established ones. For new products, qualitative techniques like market research or surveys may be helpful
Seasonality: Some products have predictable sales cycles tied to time of year. Models should account for these seasonal trends to avoid underestimating demand during peak periods.
Market Factors: External events like economic conditions, competitor activity, and new regulations can all impact demand. Including these factors in the model can improve its accuracy.
Marketing Efforts: Planned promotions, advertising campaigns, and pricing strategies can influence customer behavior. Factoring these marketing plans into the model helps predict the resulting demand shift
By considering these factors, demand planning models can provide a more accurate forecast, which in turn allows businesses to optimize inventory planner levels, production schedules, and marketing strategies.

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