Supply Chain Management
Demand forecasting
The forecasting of demand is fundamental to many commercial and operational decisions. It facilitates critical business activities such as financial planning, sales and marketing plans, material requirement planning, and production planning to name a few. Poor forecasting creates no end of issues in any supply chain.
The design and operation of the demand forecasting and planning process, including roles and responsibilities, systems, and required skillsets, should promote accuracy and, critically, reduce bias. The consistent generation of a reliable, data-driven, statistical forecast will help to drive supply chain and financial efficiencies.
What we do
At the outset, demand patterns are identified using our OP2MA Demand Diagnostic. An appropriate sample of sales data is taken to plot volume against variability (measured by coefficient of variation).
By segmenting demand, it is possible to assess how the supply chain is geared for satisfying different requirements; for example, high volume, stable demand can be supported by an efficient or 'lean' supply chain setup, high volume, volatile demand needs to be supported by a flexible or 'agile' supply chain setup.
Our assessment considers:
- the quality of data inputs to the forecasting process, both quantitative and qualitative
- the methods applied to create demand forecasts
- accountabilities for both data inputs and finalised forecasts
- cross-functional KPIs and incentives and how this might influence forecasting decisions
- forecast performance measurements.
Once demand patterns or segments are defined and current ways of working are assessed, combined with our OP2MA capability framework, it is possible to design specific, repeatable processes to drive efficiency at a scale that is effective in matching customer expectations.
Benefits
Business performance can be considerably enhanced with effective demand forecasting, resulting in numerous benefits including:
- increased customer satisfaction by improved service levels
- better decisions on which product portfolios to expand or scale down, to improve productivity and profitability
- lower safety stock requirements requiring less working capital
- reduced product obsolescence costs.