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Cradle to Grave Cycle using Supply Planning Cloud and Global Order Promising

Cradle to Grave cycle is often used to describe how a material demand in terms of customer forecast progresses into a firm demand with an actual sales order and eventually dies after satisfying the customer commitment to fulfil and ship in time. In its journey, the demand goes through multiple changes and has to reposition itself to meet supply requirement through multiple backlog management activities. In this blog, you will learn the system behavior of Oracle cloud planning and global order promising modules for events occurring in the day of life of a planner.

The above diagram illustrates the journey of (1) Receiving the forecast from the customer (2) A nightly MRP plan run will pick up the demand and drive the underlying component supplies by suggesting work order and purchase order for Make/Buy items. In stage 3, which can happen after a much longer duration, the customer sends the PO which in turn gets booked as a Sales Order in Oracle. Stage 4 will make an initial scheduling call and provide the dates based on the lead time or supply depending on the configuration selected. In stage 6, MRP plan runs again and considers the firm demand and consumes the forecast and thereby re-adjusting the supplies accordingly. In certain cases, the customers can choose to drive supplies on forecast using a "Planning BOM" as the fine details and configurations might not be known by then. This is often a case with "Build to Print" contract manufacturing companies that are dependent on customer signals. Between stage 6 and 7, the order might go through multiple change especially in a high mix environment or companies that fall in the far left of the value chain (Component manufacturers or component equipment manufacturers). Finally, the order gets shipped out in stage 8 and thereby fulfilling the customer demand ensuring the lead time and operational metrics is attained.

Stage 1 & 2 - Receive Customer Forecast and subsequently run MRP

MRP Plan Suggestion

  • Planned Work Order for the Make Item
  • Determines the Suggested Completion Date based on the "Longest Lead Time Component + Resources" OR Request date whichever is later
  • Suggest Planned Orders for Components & Sub-Assemblies based on the Make Item Suggested Start Date
  • Calculate Material Available Date Based on the Planned Work Order Completion Date
  • Calculate Exceptions on Resources & Supplies
  • Suggest Expedites to meet the Request Date (RD) where  RD is inside the Assembly Cumulative Total Lead Time (TLT) and no on time supply exist

Stage 3 & 4 - Sales Order is entered and Initial Scheduling results is based on MRP plan

Note: Global order promising in cloud (Rel 20D) provides ATP dates only based on the collected data

chedule Ship Date (SSD) will match Need by Date (NBD) if:

  • Assembly On Hand is available
  • OR Supply Constraints identified against Forecast demand have been sorted and promised early or on time
  • Component On Hand is available OR NBD is outside Assembly Cumulative Total Lead Time 

Schedule Ship Date (SSD) will be delayed if:

       NBD is inside the Lead Time AND

       Assembly On Hand is not available some or all Component Supplies based on forecast do not exist or are delayed

       Component On Hand is not available

       SSD will be based on the Longest pole in PO promised dates or Component LT + MLT (manufacturing lead time) of Assembly

Stage 5 - MRP plan run after initial scheduling of the sales order

MRP results from Supply Planning Cloud will be when Schedule Ship Date is greater than Need by Date

  • Consumes Forecast based on SSD and consumption window (XX days backward & forward). Assumes the supplies earlier pegged to Forecast
    • Planned Work Order for the Make Item.
    • Determines the Suggested Completion Date based on the "Longest Lead Time Component + Resources" OR Request date whichever is later
    • Suggest Planned Orders for Components & Sub-Assemblies based on the Make Item Suggested Start Date
    • Calculate Material Available Date & suggestion Ship Date Based on the Planned/WO Completion Date
    • Calculate Exceptions on Resources & Supplies, Suggest Expedites

Stage 6 - Backlog Management

  • How do planners identify list of orders to pull in?

  • Use Backlog report to identify orders where SSD > NBD
  • Supply Plan provide exceptions

    • What would be GOP behavior after the Plan run if Sales Order is rescheduled?

  • Same as Initial scheduling, SSD will continue to be delayed until the supply picture improves

    • What steps should the planners follow to pull-in the order?

     Identify Components causing delay using
  • Expedite Recommendations on Demand Fulfillment
  • Late Supply Pegged to Sales Order
  • Use Supply Shortage Report (not an out of box report)
    • Prioritize Long Lead time items first
    • Supply Planner/Buyers work with suppliers to improve deliveries
    • Check Availability on GOP confirms the SSD can be pulled in and then reschedule


    Stage 6 - Backlog Management

    What would be the plan behavior post pull-in of NBD?

         1) Pulls in Planned Order or WO start dates, subject to the new longest pole date

    2) Reschedule in all Components to meet the new WO start date

    3) Raise exceptions, if any

    Constrained Plan in 20D Supply Planning Cloud

    Un-constrained Plan in 20D Supply Planning Cloud (Behaves similar to 11i/R12 MRP)

           Respects Material Constraints & Resource Constraints as Hard Constraints and pushes out planned Order dates due to component LT constraints when enforced Purchase LT is turned on.

           When turned off only Post processing LT is applied. Processing and Pre Processing LTs are considered as 0

           Within LT, only OH and scheduled receipts can satisfy demands


           Plan compresses the material lead time and resource requirements and overloads

           Window between the sysdate and WO start date becomes the lead time irrespective of the lead time and resource factors

           System assumes that the planners will expedite the supplies and also increase the resource availability by WO start date


    Note: This analysis has been done in a Cloud transformation program for Contract manufacturing client and had been contributed by Naveen Divakaran, Amruta Arunima and Chandra Poonachi

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