**PURPOSE OF ATP**

Available to Promise (ATP) is a tool used to show the inventory that is not reserved for existing customer orders and, as such, is available for the sales team to Promise to other customers for rapid delivery.

ATP is typically calculated using one of three methods

- Discrete
- Cumulative with Look Ahead
- Cumulative without Look Ahead

Which method you choose is more a matter of your business operation then calculation complexity or any other reason.

Discrete is best used in situations where the available stock will likely sell very rapidly or it will become unsalable quickly such as the case with foods and pharmaceutical product expiry dates or perhaps seasonal fashion goods. Both cumulative methods are best used with stock that has a long shelf life and is not likely to expire or fall out of fashion over the planning horizon.

Prior to calculating any ATP, you’ll need to calculate the Projected Available Balance (PAB) and Periods when there must be an MPS delivery event.

Remember, when calculating PAB, we use actual orders to the left of the Demand Time Fence and we use Forecasted demand.

DTF | PTF | ||||||||

Init | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | |

Forecast | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | |

Orders | 18 | 15 | 27 | 22 | 10 | 8 | 6 | 5 | |

PAB | 15 | 37 | 22 | 35 | 15 | 35 | 15 | 35 | 15 |

MPS | 40 | 40 | 40 | 40 | |||||

For purposes of this paper

Lot Size is 40, Safety Stock is 2, Demand Time Fence is at period 2, Planning Time Fence is at period 7.

**DISCRETE ATP**

Consider the master plan below. PAB is Planned Available Balance for inventory. MPS is the planned delivery of production/replenishment.

DTF | PTF | ||||||||

Init | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | |

Forecast | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | |

Orders | 18 | 15 | 27 | 22 | 10 | 8 | 6 | 5 | |

PAB | 15 | 37 | 22 | 35 | 15 | 35 | 15 | 35 | 15 |

MPS | 40 | 40 | 40 | 40 | |||||

ATP disc | 22 | -9 | 22 | 29 | |||||

To calculate in the FIRST PERIOD ONLY: ATP = On Hand + MPS (period 1) – Sum of customer orders starting at period 1 and up to but not including the period of the next MPS delivery

For our case above ATP(1) = 15 + 40 – 18 – 15

To calculate the other ATP values you only do the calculation at a point where there is an MPS entry

Then you use the formula ATP (period N) = MPS (period N) – sum of customer orders from period N up to but not including the period with the next MPS

In our case, we calculate ATP for Periods 3, 5, and 7 since those periods have an MPS entry

- Period 3 ATP(3) = 40 – (27+22) = -9
- Period 5 ATP(5) = 40 – (10 + 8) = 22
- Period 7 ATP(7) = 40 – (6 + 5) = 29

So what does this mean? When using the Discrete ATP method you are making the assumption that the goods that were identified as being available will either sell or expire before the next MPS period and therefore there is no carry over into future periods. Is this valid? Maybe. It all depends on your business. You’ll notice in our example that Period 3 has a negative ATP indicating that if all that available inventory was actually sold in periods 1 and 2 your business wouldn’t be able to fulfill the in hand customer orders in periods 3 and 4.

**CUMULATIVE ATP with LOOK AHEAD (ATP-CL)**

Here the operating assumption is that there is a good chance that inventory that was available in a prior period is still available in the next periods with an MPS event.

These are going to be materials that do not expire and/or have a long market lifetime.

The calculations are more complex but the end result may seem more satisfying to the typical; practitioner. The method also takes into consideration BackLogs so for shops that operate with the occasional backlog this is a good way to see how you can plan your way out of a backlog situation.

DTF | PTF | ||||||||

Init | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | |

Forecast | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | |

Orders | 18 | 15 | 27 | 22 | 10 | 8 | 6 | 5 | |

PAB | 15 | 37 | 22 | 35 | 15 | 35 | 15 | 35 | 15 |

MPS | 40 | 40 | 40 | 40 | |||||

ATP disc | 22 | -9 | 22 | 29 | |||||

ATP-CL | 13 | 4 | 26 | 55 | |||||

ATP-CL(period 1) = On Hand + MPS(period1) – Backlog(period 1) – Order(1) + sum(MPS(period N) – Customer Orders (N)) for all periods N up to but not including the next MPS where there is NOT a backlog.

In the grid above ATP-CL(1) = 15 + 40 -0 -18 + [ (0-15) + (40-27) +(0-22) ] = 13

ATP-CL (period N) = ATP-CL(per N-1) – Backlog (period N) – sum( MPS(period X) -BL (period X) ) for all periods X up to but not including the next MPS where there is NOT a backlog

Period 3 ATP-CL(3) = 13 – [ (40-27) + (0-22) ] = 4

Period 5 ATP-CL(5) = 4 – 0 – [ (40-10) + (0-8)] = 26

Period 7 ATP-CL(7) = 26 -0 – [ (40-6) + (0-5) ] = 55

What does this mean? The look ahead capability of this method allows us to reserve inventory for the demand situation in Period 5. You can see that as the reduced ATP in period 1 when compared to the discrete method. Be careful, this is only a valid tactic when the material you’re making has the shelf life or market life so it can be held in reserve for the required periods.

The observant reader will notice an alternate technique for calculating Cumulative ATP with lookahead. That is. Calculate the Discrete ATP first, then apply look ahead to those values to get the values for Cumulative ATP with Lookahead.

**CUMULATIVE ATP WITHOUT LOOK AHEAD ATP-C**

Here the operating assumption is that there is a good chance that inventory that was available in a prior period is still available in the next periods with an MPS event. These are going to be materials that do not expire and/or have a long market lifetime. The other assumption is that we only consider orders in periods where there is production. Orders in periods without production are not considered. This may be valid in environments where there is a significant amount of changes to orders or when cancelations are common.

The calculations are more complex than the discrete method but simplified when compared to the cumulative with look ahead method

DTF | PTF | ||||||||

Init | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | |

Forecast | 20 | 20 | 20 | 20 | 20 | 20 | 20 | 20 | |

Orders | 18 | 15 | 27 | 22 | 10 | 8 | 6 | 5 | |

PAB | 15 | 37 | 22 | 35 | 15 | 35 | 15 | 35 | 15 |

MPS | 40 | 40 | 40 | 40 | |||||

ATP disc | 22 | -9 | 22 | 29 | |||||

ATP-CL | 13 | 4 | 26 | 55 | |||||

ATP-C |
22 | 49 | 79 | 113 |

To calculate in the FIRST PERIOD ONLY ATP = On Hand + MPS (period 1) – Sum of customer orders starting at period 1 and up to but not including the period of the next MPS delivery

Period 1 15 + 40 -18 – 15 = 22

For all subsequent periods ATP-C(Period N) = ATP-C(Period N-1) + MPS (Period N) – Orders(Period N) Use MPS and orders in the MPS period only

Period 3 ATP-C(3) = 22 + 40 – 27

Period 5 ATP-C(5) = 49 + 40 – 10

Period 7 ATP-C(7) = 79 + 40 – 6

So what does this mean? First, you’ll notice that the values with this calculation can be much higher than the other methods in periods past the first. This is clearly due to not considering future orders in MPS periods. Is this a valid assumption? Perhaps only in environments that experience a lot of order changes or where aging inventory is much less desirable.