Manufacturing: Supply Chain and Planning

Supply chain planning covers demand review, supply and capacity planning, material requirements planning runs, exception handling and release of production and purchase proposals. Planners spend significant time reviewing MRP exception messages, adjusting parameters and consolidating forecasts from several sources in spreadsheets. The work is spread across SAP S/4HANA, Kinaxis or o9, Excel, Power BI and Microsoft Teams.

Manufacturing Supply Chain and Planning

Supply Chain and Planning in Manufacturing

Supply chain planning covers demand review, supply and capacity planning, material requirements planning runs, exception handling and release of production and purchase proposals. Planners spend significant time reviewing MRP exception messages, adjusting parameters and consolidating forecasts from several sources in spreadsheets. The work is spread across SAP S/4HANA, Kinaxis or o9, Excel, Power BI and Microsoft Teams.

29
Planners analyzed
943
Planning exceptions analyzed
18,429
Events captured
5
Opportunities ranked
Manufacturing Supply Chain and Planning: Process Inventory
Process Inventory

Example product views. Figures shown are illustrative.

What Pyze Measures

  • Time spent per planning cycle stage by planner role
  • Exception message handling sequence and rework between systems
  • Spreadsheet usage alongside planning platforms
  • Distribution of exception volume across planners and plants

Typical Findings

  • Planners export planning data to spreadsheets to reconcile forecasts from sales, finance and the planning platform before each review.
  • MRP exception messages are reviewed one at a time in the ERP, with repeated navigation between material master and stock overview screens.
  • Expedite and reschedule requests are coordinated through chat and email before the change is recorded in the ERP.

What the Opportunity Register Supports

  • Supports prioritization of exception categories that can be triaged by an AI agent with planner review.
  • Quantifies the effort spent on forecast consolidation and identifies where a shared data source would apply.
  • Supports a standard approach to parameter maintenance across plants.

Example Opportunities

  • 1.MRP Exception Message Triage Backlog AI Agent Agentify
  • 2.Forecast Consolidation in Offline Spreadsheets Integration Simplify
  • 3.Planned Order Conversion Keyed Between Systems RPA Automate
  • 4.Inconsistent Safety Stock Parameter Updates Standardization Standardize
  • 5.Expedite Requests Concentrated on Few Planners UX Rebalance

See This on Your Own Work

A measured baseline before anything changes, then a priced and owned list of what to do about the gaps.