Work-in-process (WIP) inventory turns

This asset management measure is typically calculated as the cost of goods sold (COGS) for the year divided by the average on-hand work-in-process material value (i.e. the value of all materials, components, and subassemblies representing partially completed production) at plant cost for the most recently completed fiscal year. Plant cost includes material, labor, and plant overhead. This measure is part of a set of Process Efficiency measures that help companies optimize the performance of their "produce product" process by minimizing waste and refining resource consumption.

Benchmark Data

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Measure Category:
Process Efficiency
Measure ID:
104225
Total Sample Size:
2,642 All Companies
Performers:
25th Median 75th
- 15.0 -
Key Performance Indicator:
No
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Compute this Measure

Units for this measure are turns.

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WIP inventory turn rate in turns

Measure Scope

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Cross Industry (8.0)

  • 4.3.2.1 - Manage raw material inventory (10310) - Administering the inventory of raw materials. Manage the total cost of all component parts in stock but not yet used. Manage the cost of the direct materials (i.e., materials incorporated into the final product) and indirect materials (i.e., materials not incorporated into the final product but consumed during the production process).
  • 4.3.2.2 - Execute detailed line schedule (10311) - Creating and implementing the detailed line production schedule on the ground level.
  • 4.3.2.3 - Report maintenance issues (10319) - Recording and reporting any deviations or issues in the maintenance schedule, in the performance to the production management team, and for unplanned maintenance.
  • 4.3.2.4 - Rerun defective items (10313) - Reproducing the items produced defectively. Assess the produced items by conducting quality and standardization tests in order to diagnose any discrepancies. Reproduce defective items.
  • 4.3.2.5 - Monitor and optimize production process (19566) - Integrating different resources in the production process: material, personnel, equipment, robotics, etc. Includes automating and controlling the plant, performing advanced process control and real-time optimization. This activity also includes managing plant alarms and alerts.
    • 4.3.2.5.1 - Automate and control plant (19567) - Creating and applying technology to monitor and control the production and delivery of products and services. Automation involves a broad range of technologies.
    • 4.3.2.5.2 - Perform advanced process control (19568) - Including a broad range of techniques and technologies implemented within industrial process control systems that are routinely reviewed, audited, and improved, advanced process controls typically address particular performance or economic improvement opportunities. An advanced set of process control measures can be used to reduce variation and identify primary improvement options. Results of analysis are fed back into process design for incorporation into production.
    • 4.3.2.5.3 - Perform real-time optimization (19569) - Helping organizations increase performance and efficiency, real-time optimization is a category of closed-loop process control that aims at optimizing process performance in real time for systems. It is normally built upon model-based optimization systems and is usually large scale. Real-time optimization automatically detects errors, and can modify and eliminate both random and non-random errors, as well as analyze and monitor all systems involved.
    • 4.3.2.5.4 - Manage plant alarms and alerts (19570) - Applying human factors and instrumentation engineering and systems thinking to manage the design of an alarm or alert system to increase its usability. Typical challenges include having too many alarms in a plant, poorly designed alarms/alerts, improperly set alarm/alert points, unclear alarm/alert messages, etc. Poor alarm management is one of the leading causes of unplanned downtime.
  • 4.3.2.6 - Assess production performance (10314) - Analyzing and benchmarking the production process to judge its effectiveness and efficiency. Create production metrics to numerically calculate the performance of the production process.