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In this article we want to have a look to the Advanced Available-To-Promise and reveal the functionality along with an example scenario. Let us get right into it…

You send out the invitation for an upcoming party at your house and out of the 7 loved ones you invited, only 3 confirmed and one, your uncle living in another city, promises to try his best to come. As you are looking forward to the party, you already have the cake in mind you want to serve to your quests: It will be your famous cheesecake!

It is close to 3:30 pm and you open the fridge, pick up the wonderfully baked cake and start cutting out pieces. Since, only four guests have confirmed, you make 5 equal pieces. Assuming everybody eats one slice you are good to go. At that point in time the world looks great.

This is when something unexpected happens…

The bell rings and you open your door. You count 4 people (one of the guests wanted to surprise you) standing in front of you and smile. At that time, you realize that the demand for your cheesecake is larger than the available supply. You have 6 people (including yourself and the uncle, who is yet to arrive) and you have 5 pieces of cake.

While sitting together talking about the latest news and gossip, the first order for a piece of cake arrives. One other guest also want to be served at once and you couldn’t resist to put a cake on your plate as well. Now, three pieces of cakes out of 5 are already consumed.

Since the cake was delicious the first guest requested to be served one more piece. Out of politeness, you couldn’t say NO to the request. After serving four slices out of the available 5, one other guest with an empty plate in front of him calculated the situation correctly and place an order for the last piece of cake.

Then suddenly your phone rings. It is your uncle, informing you that he is running late as he is stuck in a traffic jam. However, as soon as he will arrive, he expects to be served with a slice of your delicious cheesecake. As you do not dare to disappoint him, you assure him of a slice. By the end of the call, you realize that you have promised 6 out of 5 slices (including the one you already have consumed).

Let’s see the current situation:

By using advanced ATP, you can make your party a success by preventing such a situation!

How? Let’s have a look…

Advanced ATP comes with different methods and tools that address the different issues that we face on our party.

When summing up the number of promised slices, we realize that you promised 6 with a supply of 5, and therefore you have a classical over-confirmation situation. By using Product Availability Check (PAC) you can avoid over-confirmations and double-booking by real time order confirmation considering present and future supplies.

Another aspect we find in the scenario is the late arrival of an important order, the one from your favorite uncle. Basically, you knew from beginning that he loves your cheesecake and in case he will make it to the party he will definitely demand a slice. Supply Protection (SuP) provides the mechanism to reserve quantities for certain order characteristics during supply shortages. In our scenario customer would be the characteristic and the reservation go for our uncle. This one slice reserved for him will in the first place not even be visible for the other guests and hence cannot be used for promising their orders. Especially when you are aware or can predict that orders from higher priority customers or channels arrive later, you can use SuP to protect quantities for competing demands.

Having confirmed a request in the first place might turn out later to not meet your business and profitability goals. We can easily see this in the way that there is a slice of the cake on your plate but there is a guest with an empty plate. We would in this situation naturally redistribute the cake from your plate to the guests one. Backorder Processing (BOP), the framework to confirm orders en masse, can select the orders in a batch job according to order priorities and NOT necessarily based on the usual First-Come-First-Served principle. At the same time all ATP methods – e. g. PAC, SuP, PAL – are considered during the mass processing. By putting ourselves at the end of the prioritized list, we will find the slice moving from our plate to the plate of our guest who until now has an empty plate.

However, we face another unfortunate situation: We have a greedy guest piling up stock … uh… cake of course 😉. But Advanced ATP offers a solution for such circumstances, the Product Allocation (PAL). By allocating quantities to customers (or other characteristics like region, country, …) you can prevent the situation that few customers buying the entire available quantity and leave others high and dry. For the cake situation we would go for the allocation that each of our guests only get one slice, hence we apply a sales constraint for cheesecake.

By applying advanced ATP we are calming down the tensions and reach a situation like following:

Of course, you still do not have a slice of your awesome cheesecake. But hey, wait a moment. Advanced ATP offers a mitigation also for that kind of situation!

In case of such unavailability of supply you can fulfill the order by applying substitution with Alternative-Based Confirmation (ABC). In our scenario we are going to substitute the slice of the cake with 2 chocolate cookies.

As you can see, with Advanced ATP you are best prepared for your next party!

(you)