How Do I Make Intelligent Inventory Tradeoffs To Drive High Service Levels and Revenue Growth?
Every supply chain planner wants to deliver high service levels to support revenue growth. But relying on forecast accuracy alone cannot achieve the goal, because it is nearly impossible to generate a perfect demand forecast. And as business complexity grows and demand volatility increases, it becomes harder just to keep from falling further behind in meeting forecasting KPIs.
But there is a solution: modeling demand and uncertainty and using that knowledge to make intelligent inventory tradeoffs that enable high service levels and customer satisfaction. Traditional forecasting systems can't do this because they are “deterministic”—their internal processes view all data as exact. They take exact values as input and they output exact values, so the forecasting calculation is oblivious to the uncertain nature of the demand. Any deviation in demand, no matter how normal, is considered as error.
Demand modeling works differently; everything is “stochastic” (probabilistic). Stochastic modeling systems train their sights on a more accurate forecast, but by modeling probabilities and then factoring in random behavior. The outcome is a value within a range, and each value has a certain probability of occurring. This leads to higher service levels and revenue growth. Here’s how.