Operational Excellence

Science and Methods.

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At PIMS, we obtain comprehensive data for each manufacturing plant and this data set forms the basis of our analysis. The input data can be categorised into the following:

  • Scale, complexity & configuration: Annual throughput; variety handled (e.g. number of unique SKUs, components); mode of raw material receipt; automation.
  • Operations: Overall Equipment Effectiveness (OEE); batch size; capacity utilisation; energy efficiency; Right First Time and On Time In Full (OTIF)
  • Cost and personnel structure: People costs (e.g. salaries, wages, contractor fees, pension funds etc.); non-people costs (energy & utilities, rents & permits, maintenance services, catering, etc.).

Analytics Software

The comprehensive Analytics Software yields answers to questions such as:

  • What are the cost thresholds to produce and dispatch a unit of finished product in my region and what is my delta to regional best practice peers?
  • What is the optimal number of Full Time Equivalents (FTEs) for a plant of my scale, automation and complexity? How can I make operational changes to drive labour productivity?
  • How can I improve the utilisation rates and minimise the planned/unplanned downtime of my assets to boost OEE?
  • How many units (kWH) of energy am I consuming to produce a unit of finished product versus look-alike operations? How much am I paying per unit of energy versus local competition?
  • What is the optimal balance of preventive/reactive maintenance?

Objectives and Benefits

Scientific diagnosis and prescription for each participant, based on best possible real world comparisons.

Optimise performance across the supply chain; Maintain confidentiality.

Link to implementation.

Phases and Steps

  1. Ensure sufficient benchmarking participants
  2. Define key data, set timetable, resolve issues
  3. Assemble and check data
  4. Benchmark against relevant peers
  5. Discuss results and set priorities for change.
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