Performing AI-Assisted Predictive Labor Demand Planning

The function AI-assisted predictive labor demand planning was introduced with SAP S/4HANA Cloud Private Edition release 2023 FPS3. It contained the following features:

• Historical workload from RF Pick and Pack
• Planned workload duration on outbound delivery order (ODO) and warehouse order (WO)/warehouse task (WT) level

With release 2025 FPS0 of SAP S/4HANA Cloud Private Edition, the feature AI-assisted predictive labor demand planning has been enhanced. The following solution scope has been provided for this enhancement:

• Enabled for RF-based Pick and Pack
• Planned workload on outbound delivery order (ODO) and warehouse order (WO)/warehouse task (WT) level
• Forecast on FTE , duration, weight, volume, number of items for next days or weeks
• Can be (optionally) used with Labor Management

Feature enrichment in release 2025 FPS0:

• Workload forecast for RF Pick and Pack steps
• Merged forecast based on executed data and planned workload
• Workload forecast in SAP Smart Business UI, for duration/FTEs, weight, volume, capacity consumption, and number of items

This leads to the following benefits:

• Transparency on the current and future workload in warehouse outbound process
• Streamlined and efficient warehouse operations

Prerequisites for the use of this feature are:

• EWM in SAP S/4HANA Cloud Private Edition, and an advanced EWM license are needed.
• The historical workload needs to exist for the forecast logic to work.

You can use this QR code to open the SAP help documentation for predictive labor demand planning.

You can use this QR code to open SAP note 1903854, which contains information on how to calculate the duration of historical workloads.

Before the calculation of the planned workload, outliers are removed by averaging similar workload records. This is done using inter-quartile range (IQR) test in HANA predictive analysis.

This is done using database table /SCWM/LDP_HIST.

You can use the report /SCWM/R_REORG_LDP_HIST to delete outdated historical workload records. You should run this report regularly to control the size of the database table which stores the historical workload records. The retention time for historical workload records depends on how they are used in the scenarios mentioned above.

A prerequisite for this is that the log for LDP has been activated using transaction /SCWM/ACTLOG.

The SAP S/4HANA PAL algorithm referred to as Triple Exponential Smoothing utilizes confirmed warehouse tasks from the previous 30 days to estimate future workloads for the following days.

This works as follows:

1. Existing documents creating workload are:

   • Outbound deliver order items
   • Warehouse orders and warehouse tasks
2. Predict workload based on historical data: confirmed warehouse tasks up until 30 days back are included.
3. Merge workload from both sources.
4. KPIs: FTE, workload duration, volume, weight, capacity consumption, number of items

The plan is to incorporate the Joule warehouse resource agent with AI-assisted predictive labor demand planning:

Challenges companies currently face are an increasing labor shortage and expensive warehousing operation costs. A solution for these challenges can be the Joule resource agent. This agent ...

• … actively anticipates potential resource shortages.
• … efficiently reallocates available resources to avoid delivery delays.
• … collaborates with the external Joule Agents to secure temporary workforce solutions, ensuring smooth operational continuity.

This leads to the following benefits:

• Streamlined and efficient warehouse operations
• A further optimization of productivity
• Reduced labor costs
• A seamless workflow

You need to activate labor demand planning in SAP S/4HANA Cloud Private Edition for EWM. You can use the following menu path in Customizing: SCM Extended Warehouse Management→Labor Management→Labor Demand Planning→Activate Labor Demand Planning.

In SAP S/4HANA Cloud Private Edition for EWM you need to:

• Activate pLDP via the app Intelligent Scenario Management.
• Activate pLDP model EWM_LDP_FORECAST2_00.

You then need to schedule forecast report /SCWM/R_LDP_WORKLOAD_FORECAST on a regular basis (daily) for corresponding activity areas and process steps that are relevant for pLDP.

• The function AI-assisted predictive labor demand planning was introduced with SAP S/4HANA Cloud Private Edition release 2023 FPS3.
• With release 2025 FPS0 of SAP S/4HANA Cloud Private Edition, the feature AI-assisted predictive labor demand planning has been enhanced.

• Feature enrichment in release 2025 FPS0:

  • Workload forecast for RF Pick and Pack steps
  • Merged forecast based on executed data and planned workload
  • Workload forecast in SAP Smart Business UI, for duration/FTEs, weight, volume, capacity consumption, and number of items

• This leads to the following benefits:

  • Transparency on the current and future workload in warehouse outbound process
  • Streamlined and efficient warehouse operations