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Availability to Promise
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ATP CALCULATION

Calculating ATP is relatively simple. The formula is as follows:

AVAILABLE TO PROMISE = Total Supply - Total Actual Demand where, Total Supply = Quantity On Hand + Quantities On Order and,     Total Actual Demand = Quantity on Customer Orders

The quantity on hand includes any safety stock, since safety stock is not allocated to any particular customers and is therefore available to promise. The total actual demand excludes sales forecasts, since they are a prediction of future demand and the inventories to cover them are not allocated to any customers. Figure 1 shows the calcula­tion of ATP for a make-to-stock item.

There are some problems with the ATP calculation in some of the newer ERP software packages. Several of these packages deduct safety stocks from the on-hand quantities before calculating ATP. Their argu­ment is that safety stocks are for emergency use only and not normally available for sale. Since most of these safety stocks have been calcu­lated based on the variability of demand against the forecasts, they are planned to cover those expected variations and not just for emergen­cies. The users of those packages can often be found either manually adding back the safety stocks to the ATP or ignoring ATP altogether.

Another common problem is the exclusion of system planned orders from the calculation. These systems only consider released and firm planned orders. The argument in this case is that system planned orders change frequently and are therefore not reliable enough to base promises on. The result for companies that take or­ders now for delivery at customer requested dates in the future is that the calculation runs out of supply before it satisfies all the de­mand. Manual calculations show that the order can be covered by the planned orders that are being ignored. In fact, the planned orders are the plan. The system will always cover demand if there is de­mand to be satisfied. They should become firmed as they approach the item's time fence and released at the lead time. This problem becomes much more serious if the software does not provide for time fences and firming messages when system planned orders cross them. If the system is allowed to plan orders inside the time fence and in the first few weeks of the horizon, available to promise will show very little, if any, supply to satisfy the customers if these or­ders are excluded. It will show ATP that is impossible to meet if it includes planned orders when the system is allowed to plan them inside the time fences.

There have also been arguments that supply order deliveries often cannot be trusted because the components to produce them are fre­quently not available. Or, if a supply order is to be pulled up to an earlier date, it is important to be able to drill down to see the availabil­ity of the components before moving it. There has been much ado about the need for "drill down" capabilities in the software. In reality, how­ever, only a small percentage of companies are in a position to use this kind of information. As an example, take a company whose product has 100 components and four levels in its bill of materials. A customer requests a quantity greater than is currently planned. We drill down to look at all these components and find 20 of them would be short if the next order is pulled up to satisfy this request. This is to be expected since the order is greater than the original plan. What do we do now? Call 10 suppliers and check on availability? Analyze the work centers for capacity and the raw materials for the manufactured items to see if it can be done? Do we do all this before promising delivery to the customer? And what if this scenario happens many times every day? Is all this detail really better information than we can receive from ATP? Do we have time to analyze it?

It may be practical to drill down to the details in companies whose products have small bills of material and whose processes have a few short paths. We learned a long time ago that it was not practical in many companies to manage our plants at the detailed component lev­els. It was one of the reasons we emphasized the need to manage our master schedules and drive the decisions made there to the component levels. Having the technology to manipulate the details does not nec­essarily make it the right thing to do.

To Be Continued


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