Measuring the lead times for inventory forecasting - Optimization Software

Measuring the lead times for inventory forecasting












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The lead time is a variable that is fundamental in order to properly how much inventory is needed to cover the future demand. A proper measurement of the lead time is required no matter which forecasting technology is used. The lead time, as needed for inventory optimization purposes, involves involves some subtleties. In this page, we illustrate how the lead time should be measured in practical situations.

See also the lead time definition and lead time forecasting.

Lead times are best computed based on your past purchase orders, looking at the delays between the orders and the deliveries. In particular, we suggest not to trust the "official" lead times given by suppliers; as they frequently over or underperform those values. If your business is using an app natively supported by Lokad, then Lokad auto-computes the applicable lead times automatically based on your historical data.


Lead time is expressed in calendar days

For each SKU, Lokad expects the lead time value to be provided as input. Salescast does not measure the lead time, this value is expected to be readily available when Salescast starts to process the data.

The lead time value should be expressed in days. Even if the forecast period is week or month, the lead time should remain in days. Then, the lead time is measured in calendar days, not business days.

Beware that agreements with suppliers frequently involve lead times expressed in business days, thus, those quantities need to be recalculated as calendar days.

A segment covering the future starting from the "present"

The quantile forecast used to generate the reorder point interprets the lead time as the segment to cover starting from the end of the historical data. Indeed, Lokad defines the “present” as the end of the data. Hence, the forecast starts where the data stop.

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In the illustration here above, we have a lead time equal to 4 days. It means that if Lokad computes a reorder point with this lead time, and say, a service level of 95%, the reorder point will be the minimal inventory value - as forecasted by Lokad - that is sufficient to cover the fluctuation of the future demand so that 95% of the time, the reorder point is higher than the demand (hence avoiding the stock-out).

Reordering delays

The lead time, as understood by Lokad, must embed all factors that delay the actual replenishment. In particular, there is almost always a reordering delay. Indeed, reorders (orders passed to suppliers) are typically not made in real-time as SKU units get sold or consumed. For example, some SKU may only be reordered once a week.

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In the illustration here above, we assume that reorders are made every 3 days, with a supplier lead time of 4 days. In this situation, it is tempting, but incorrect, to use a lead time of 4 days. Indeed, this delay does not take into account the 3 days of delay until the next reorder. If a lead time of 4 days is used, the reorder point suggested by Lokad won't properly cover the days 5, 6 and 7.

Here, the proper lead time value to be used by Lokad is 4+3 = 7 days. Hence, starting from Day Zero, inventory should last, not until the end of Day 4 when the first delivery arrives, but until end of Day 7 when the second delivery arrives. Indeed, the reorder B has no impact until end of Day 7, so whatever quantity gets reordered on Day Zero, it should cover all demand fluctuations until end of Day 7. From Day 7 and beyond, it’s the reorder B that is to be in effect.

Forecasting the same day twice

Looking at the illustration below, it might seem surprising that the same day gets forecast twice. Indeed, the Days 4 to 7 are part of the first quantile forecast starting at the end of Day Zero, but those days are also part of the second quantile forecasts starting at the end of Day 3.

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However, this behavior is correct. The forecast produced by Lokad here is a quantile forecast which is turned into the reorder point. Yet, the reorder quantity itself comes as the reorder point minus the stock on hand and minus the stock on order. Thus, a single day might be forecasted twice as part of the reorder point calculation, yet the same day is not going to be counted twice as far reorder quantities are concerned.

Sample scenarios

In this section, we review a couple of typical scenarios to further shed lights on calculating the correct lead time as required by Lokad.

Next day delivery with closed days

Let’s assume that a retail store wants to use Lokad with the following assumption:
  • Store is open every day of the week except Sunday.
  • Store is delivered every day, except Sunday.
  • Store reorder are made every day before 10am, and delivery happens the next day. Saturday reorder is delivered on Monday.
  • Data is pushed to Lokad every day at 5am. Sales data stops at midnight the previous day.

In this case, the lead time equals 2 days for all days, except Saturday where the lead time equals 3 days.

After next day delivery with semi-closed days

Let’s assume that a retail store wants to use Lokad with the following assumption:
  • Store is open every day of the week.
  • Store is delivered every day, except Sunday.
  • Store reorder are made every day before 10am, and delivery happens the day after the next day. Friday reorder is delivered on Monday. Saturday reorder is delivered on Tuesday.
  • Data is pushed to Lokad every day at 5am. Sales data stops at midnight the previous day.

In this case, from Monday to Thursday, the lead time equals 3 days, one day of reordering delay plus two days of supplier lead time. Then, on Friday and Saturday, the lead time equals 4 days. Indeed, for those two days, the closed Sunday, supply-wise, needs to be taken into account. In particular, the decision made Friday morning needs to last until Tuesday end of day, because the Saturday reorder has not impact on Tuesday.