}

The Smart Forecaster

Pursuing best practices in demand planning, forecasting and inventory optimization

Most demand forecasts are partial or incomplete: They provide only one single number: the most likely value of future demand. This is called a point forecast. Usually, the point forecast estimates the average value of future demand.  Interval forecasts provide an estimate of the possible future range of demand (i.e. demand has a 90% chance of being between 50 – 100 units).  Probabilistic forecasts take it a step further and provide additional information.  Knowing more is always better than knowing less and the probabilistic forecast provides that extra information so crucial for inventory management. This video blog by Dr. Thomas Willemain explains each type of forecast and the advantages of probabilistic forecasting.

 

Watch Now 

 

Point forecast (green) shows what is most likely to happen.  The Interval Forecast shows the range (blue) of possibilities.

 

Probability Forecast shows the probability of each value occurring

 

 

Leave a Comment

Related Posts

Probabilistic Forecasting for Intermittent Demand

Probabilistic Forecasting for Intermittent Demand

The New Forecasting Technology derives from Probabilistic Forecasting, a statistical method that accurately forecasts both average product demand per period and customer service level inventory requirements.

How to Choose a Target Service Level to Optimize Inventory

How to Choose a Target Service Level to Optimize Inventory

When setting a target service level, make sure to take into account factors like current service levels, replenishment lead times, cost constraints, the pain inflicted by shortages on you and your customers, and your competitive position.

Ten Tips that Avoid Data Problems in Software Implementation

Ten Tips that Avoid Data Problems in Software Implementation

Once a customer is ready to implement software for demand planning and/or inventory optimization, they need to connect the analytics software to their corporate data stream.This provides information on item demand and supplier lead times, among other things. We extract the rest of the data from the ERP system itself, which provides metadata such as each item’s location, unit cost, and product group.

Recent Posts