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Inventory is one of the working capital components that can be
influenced by poor demand information and can be a big drain in
the cash-to-cash cycle. Although not measured and
monitored from a supply chain perspective, receivables and
payables are as important to monitor in the business model.
Optimal inventory is defined as the inventory that is just
sufficient to meet your customer orders so you can hit your service
level targets. Since this is a balancing act, demand forecast
accuracy summarily determines both your inventory levels and service
levels. You can make a trade-off between the two for a given
demand forecast error:
1. Higher the required service levels, higher are the
needed inventory
2. Lower the forecast accuracy, higher the needed
inventory to attain a specific service level.
Yes, it is true you can achieve a 99% or more customer service
level by keeping extremely high levels of inventory, especially if
you are in the dark about your demand forecasts. Or, if the
organization has no idea how customer demand is generated.
You may hear a number of supply chain experts say that demand
forecast is tough and hence a waste of time. They may have
fancy solutions that advocate an expensive re-engineering of the
supply chain to accommodate any type of demand. Although that
is technically possible, it is not a useful way to spend
organizational resources. A small effort on the demand side
will result in tremendous benefits and improved demand information
to help the supply chain. Even if the demand is highly
uncertain, you can install a demand management process that will
link itself to the retail or the final customer demand to help
determine the order forecast for the lead time.
Historical demand forecast metrics affect the amount of inventory
cushion you need to hold to cover future forecast volatility.
This is done through the safety stock measure that in statistical
terms, is an estimation of confidence intervals using an one-tailed
test.
Safety Stock = Customer Service Level * Standard Error of the
Demand during the Lead time
Safety Stock = Customer Service Level * RMSE * Square-root of
(Lead time)
Safety stock is the margin of error required based on the
customer service level and the deviation of the demand during the
lead time. The customer service level is the z-value in standard
statistics for calculating confidence intervals.
In practice, people use the daily average of this historical data
as an approximation for the mean and in essence they ignore the
forecast. The correction to this method is to use the daily average
of the forecast. This also requires breaking out the monthly
forecast into weekly or daily forecast. This will result in two
components to the deviation namely
1. the total forecast error and
2. the daily distribution error.
Safety stock calculations need to be adjusted depending on how
wide the Lead Time is compared to how accurate the daily
distribution is. For example, if the monthly forecast is very
accurate but the daily distribution is incorrect but the Lead Time
is three weeks then, you may end up carrying incorrect safety stock
during the Lead time. Generally if the Lead Time is the same as the
forecast bucket, most problems are solved.
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