Feature Spotlight: Capable to Promise

8/28/17 12:15 PM


Capable to Promise

During a recent demo with some of our partners, we were walking through some of the standard features of our software. One of the features we covered was our Capable to Promise functionality, where schedulers can input an item number for a finished good, and a delivery date. PlanetTogether will use both available material, and available capacity to give a realistic picture of whether or not you are able to fulfill demand within a given time frame by creating a simulated job. If the delivery date can't be met, PlanetTogether will provide a realistic delivery date.

Calculate ability to fulfill demand in a given time frame

Our partners were stunned, not only at the simplicity of this powerful feature, but that it was a standard feature of PlanetTogether. 

CTP is easy to implement. The only data points that are required in order to submit a CTP request are:

  • The Inventory (Warehouse and Item)
  • How much of that Inventory is required?
  • When it will be required by
  • What routing to use to create the Item

The PlanetTogether team can take these datapoints to create a template job that is used to calculate the timeframe to produce the desired quantity. Once the CTP has been submitted, APS will project a Start and Finish time, as well as whether or not it expects the Job to be late or early as determined by the current Optimization Rules. If the Job is projected to be late, APS will determine which constraints are bottlenecking the process. APS will also allow the CTP to reserve Capacity and Materials until a user-defined date, allowing the customer some time to determine whether or not to go through with the order.

If you’d like to explore Capable to Promise further, learn about other new or interesting features, or just refresh you knowledge of APS, we offer personalized training sessions. Book a session now by emailing support@planettogether.com

Related Capable Resource Video

 APS Resources

Topics: capacity planning, production planning, finite capacity, users, project management, APS, capacity, bottlenecks, constraint, resource


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