From punctuality to reliable adherence to deadlines (ATP)
This article will show how quickly we reach our own limits with everyday experience. It is about the everyday term “punctuality”, which plays an eminent role in supply chain management. Above all, reliable punctuality, the binding commitment to deadlines across long supply chains – even during peak loads – is a considerable challenge for all those involved in the supply chain. In technical terms, this is known as ATP – Available to Promise – and means something like a “firm delivery promise” that supply chain participants can rely on.
From punctuality to adherence to delivery dates
The SC manager needs measurable – operationalizable – statements. Without measurability there is no measurement and without measurement there are no concrete instructions for action. Without concrete instructions for action, there are no concrete plans and no concrete implementation. But these are precisely the crux of the matter in SCM business practice. It is crucial that the everyday term “punctuality” is precisely defined and operationalized and thus becomes, among other things, a controllable supply chain element“adherence to delivery dates“.
“What you can’t measure, you can’t manage.” (Peter Drucker)
On-time delivery is the ratio of on-time deliveries to the total number of deliveries. In the technical literature, on-time delivery is based on frequency theory and probability theory. If, for example, we have made 1000 deliveries (a) for a just-in-time delivery(JIT) and 990 of these were on time (b), then we are talking about an on-time delivery rate of b/a = 0.99 (this corresponds to an on-time delivery rate of 99%). This data can be used both in retrospect – ex post – and in advance – ex ante. The on-time delivery value is therefore a reliability value that expresses the “delta” between the “confirmed delivery date” and the “actual delivery date”. This delta can be converted into a probability statement using a sufficiently large sample. In SCM practice, logistical simulation is often used for such calculations.
SC managers and adherence to delivery dates
What data does the SC manager need in order to be able to make a reliable statement about time and on-time delivery? He needs a specific customer deadline requirement, which is expressed in the form of an on-time delivery value, he also needs the delivery times measured in the near past, and finally he can use statistics to determine the delivery time fluctuations, i.e. the average deviation from the average delivery time. The near past of the measured values is regarded as a correlate of the near future.
Practical example of adherence to delivery dates
Our customer requires our deliveries to be 99.9 percent on time; under no circumstances does the customer want them to be delivered late. The average delivery time was determined to be 35 minutes from a large number of delivery time measurements. The average deviation (standard deviation) is e.g. /- 6 minutes. We can therefore meet the customer’s deadline compliance requirement if we start the JIT delivery 53 minutes before the agreed latest date.
How the time strategist calculates
The customer’s requirement of 99.9 percent corresponds to a so-called 3-sigma requirement (so-called safety factor). The sigma stands for 1 standard deviation. 3 sigma therefore stands for 3 standard deviations. This means that you only have to add 3 standard deviations to the mean value of 35 minutes: this results in 35 minutes plus 3 times 6 minutes = 53 minutes. In order to guarantee 99.9 percent adherence to delivery dates (degree of safety), the delivering JIT truck, for example, must start at least 53 minutes before the planned – correctly scheduled – late arrival. In this model example, a number of assumptions are made that correspond to logistical reality in many cases: The arrival distribution is assumed to be a normal distribution, the fluctuations in delivery times are regularly stochastic. Outliers (e.g. extreme exceptions) are extrapolated, etc.
The trained SC manager can use basic statistical knowledge and the corresponding logistical expertise to calculate all possible delivery requirements across a complex delivery network – given the corresponding data availability. SC managers are ultimately “time strategists” who deal intensively with the “laws of nature” and the numerous peculiarities of time, time consumption and adherence to delivery dates and arrive at reliable (robust) delivery date commitments – in accordance with ATP.
Information on costs in SCM can be found under “The cost of unused opportunities in supply chain management”.
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