Saturday, March 24, 2007

It's hard to sail against the ATP wind

I really don't know why I keep coming with the sailing theme when I want to talk about the ATP process.

Anyhow, when using APO there is a direction that can make life easier. A direction related to the change of sales orders confirmed delivery dates. This is mainly true in industries doing assemble-to-order, configure-to-order, etc. For pure make-to-stock the confirmed date does not matter. Either there is stock or the order will most probably be lost.

What means going with the wind?

Suppose an ATP system that gives a first confirmed date that is a bit optimistic. For example, a customer requests a product for a date 20 days from now and the ATP system says it can be done in 30 days and let's say there is 30% probability that this data will have a delay (that's why I call it optimistic). In this case the automatic planning (heuristics and optimizer) will work to minimize the delays. Planners may do some high level actions, like over-time shifts, but the system will mostly work alone to move the dates that cannot be fulfilled into a future date.

So what does it mean to go against the wind?

Suppose that ATP gives a first confirmed date that is pessimistic. For example, for the same order the ATP system gives a date 50 days in the future and there is a 99% chance of delivering in that date (although there is a good chance of delivering earlier). For a constant process variability, this extra reliability is achieved by having some empty plan space between the present and the confirmed date. But since no company will stop production having orders in the future something must be done to remove those empty spaces, which means increasing stock, or most likely improve the confirmed dates to something closer to the date requested by the customer. Unfortunately, automatic planning is mostly oriented to fulfill the confirmed dates, and thus it becomes manual work for the planner. Moving confirmed dates in the direction of the present is hard, like sailing a against the wind.

The bottom line: there are good reasons to be optimistic, not only in life (less diseases, etc) but also in ATP.

How to be optimistic?

There are many decisions that go along the optimistic path. When using CTP with PPDS, using finite planning in as few bottleneck resources as possible. With block planning using CTP bucket capacity. With product allocation (PAL) having few structures with very restrictive segment capacities (and going more for sequence of flat structures than for deep hierarchical ones). Also avoid modeling several times the same capacity constraints. The ATP checking horizon also goes well in the optimistic direction.

Music theme for this post: always look on the bright side of life.



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