What do you do when you are forecasting an intermittently demanded item, such as a spare part, with average demand of less than one unit per month?  Most of the time the demand is zero, but the part is significant in a business sense; it can’t be ignored and must be forecasted to be sure you have adequate stock.

Your choices tend to center around a few options:

Option 1:  Round up to 1 each month, so your annual forecast is 12.

Option 2:  Round down to 0 each month, so your annual forecast is 0.

Option 3:  Forecast “same as same month last year” method so the forecast matches last year’s actual.

There are obvious disadvantages to each option and not much advantage to any of them.  Option 1 often results in a significant over forecast.  Option 2 often results in a significant under-forecast.  Option 3 results in a forecast that is almost guaranteed to miss the actual significantly since the demand isn’t likely to spike in the exact same period. If you MUST forecast the item, then we would normally recommend option 3 since it is the most likely answer that the rest of the business would understand. 

But a better way is to not forecast it at all in the usual sense and instead use a “predictive reorder point“ keyed to your desired service level. To calculate a predictive reorder point, you can use Smart Software’s patented Markov bootstrap algorithm to simulate all possible demands that could occur over the lead time, then identify the reorder point that will yield your target service level.

You can then configure your ERP system to order more when on-hand inventory breaches the reorder point rather than when you are forecasted to hit zero (or whatever safety stock buffer is entered). 

This makes for more common-sense ordering without the unneeded assumptions that are required to forecast an intermittently demanded, low-volume part.


Spare Parts Planning Software solutions

Smart IP&O’s service parts forecasting software uses a unique empirical probabilistic forecasting approach that is engineered for intermittent demand. For consumable spare parts, our patented and APICS award winning method rapidly generates tens of thousands of demand scenarios without relying on the assumptions about the nature of demand distributions implicit in traditional forecasting methods. The result is highly accurate estimates of safety stock, reorder points, and service levels, which leads to higher service levels and lower inventory costs. For repairable spare parts, Smart’s Repair and Return Module accurately simulates the processes of part breakdown and repair. It predicts downtime, service levels, and inventory costs associated with the current rotating spare parts pool. Planners will know how many spares to stock to achieve short- and long-term service level requirements and, in operational settings, whether to wait for repairs to be completed and returned to service or to purchase additional service spares from suppliers, avoiding unnecessary buying and equipment downtime.

Contact us to learn more how this functionality has helped our customers in the MRO, Field Service, Utility, Mining, and Public Transportation sectors to optimize their inventory. You can also download the Whitepaper here.



White Paper: What you Need to know about Forecasting and Planning Service Parts


This paper describes Smart Software’s patented methodology for forecasting demand, safety stocks, and reorder points on items such as service parts and components with intermittent demand, and provides several examples of customer success.