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Production Management Execution

The Production Management Execution data model provides a detailed view of work ticket execution in Sage 100, including production steps, activities, work centers, scheduling, quantities, and costs. It combines work ticket header information with operational step details, allowing users to monitor how production is progressing through each stage. Use it to review step status, compare planned and actual effort, identify delayed operations, and analyze production performance by work ticket, item, activity, and work center.

How to use this data model​

  • Monitor production steps by work ticket using step number, description, activity, status, and work center.
  • Compare planned and actual execution using scheduled quantities, completed quantities, remaining quantities, and labor or machine hours.
  • Identify delayed operations using production dates, due dates, step dates, and other scheduling indicators.
  • Analyze work-center performance to understand where production activity, hours, and workload are concentrated.
  • Review production costs across materials, labor, overhead, and other cost categories while tracing them back to the related work ticket.
  • Evaluate work ticket progress using status, quantities ordered, planned, completed, and remaining.
  • Trace purchasing dependencies through related purchase-order details when production steps depend on externally supplied items or services.

Available views​

ViewTypeWhat it shows
Work Ticket Steps (Operations)WorksheetShows work ticket steps by item, including activity, work center, status, budgeted and actual hours, and completion percentage.
Work Tickets by Work CenterStacked BarCompares work ticket quantities across work centers to highlight where production workload is concentrated.
Work Center PerformanceHorizontal BarCompares labor efficiency across work centers to highlight differences in production performance.
Work Center Load & EfficiencyCombinationCompares budgeted and actual hours by work center alongside labor efficiency to highlight workload utilization and performance.