Range-Based Planning: How supply chains can brace for uncertain futures by pushing range-based forecasts through the entire planning process
“Just as you need to decide whether to bring an umbrella before you leave home, and before you know what the weather will be later in the day, so do businesses need to commit to supply chain decisions before they know what demand will actually be,” according to Blake Johnson, Consulting Professor, Stanford University.
The role of demand planners is to accurately predict future demand, and the role of supply planners is to match the predicted demand. Some demand planners may be generating point forecasts to predict future demand (ex: we expect to sell 100 units in December). More mature demand planning processes produce range-based forecasts to better understand the levels of uncertainty in future demand (we have a 95% chance of selling 100-110 units and a 5% chance of selling below 100 or above 110).
Vanguard Predictive Planning
Even the more mature planning teams, however, might still be extracting a point value from the demand forecast to commit to a plan that can be utilized by the supply planning team. Unfortunately, as soon as the team commits a point value to the plan, half of the value of the forecast is lost.
Value of range-based planning
Range-based planning, or probabilistic forecasting, provides a spectrum of possible outcomes for any given time period. Contrary to point forecasts and deterministic planning, range-based planning allows supply chains to protect themselves from high levels of variability in demand. Typically, the higher the past demand variance, the wider the forecast range, and the higher level of safety stock should be held.
Many demand planning teams already understand the value of range-based planning. Passing this confidence range into inventory and supply plans is a key component of protecting the supply chain against demand variability, potential stock outs, and product obsolescence.
Carrying it through the planning process
Demand Planners have a crucial and challenging role in any supply chain. Not only are they measured by the accuracy of their forecasts, they have to take into account many factors aside from historical sales data to determine the best course of action.
To stay ahead of the curve, effective demand planners will work continuously as new information becomes available (inside and outside of planning systems) to improve the accuracy of the plan. A planning system that can do a bulk of that continuous planning in the cloud, incorporate demand uncertainty across all plans, and wait until the last moment to commit a single point value, will inherently produce more effective plans and better business outcomes.