The Buffering Law observed in Software Engineering

Railway buffer at the top of Pikes Peak, Colorado Springs CO

There is an informative slide deck on the FactoryPhysics website entitled A Fast Cycle Time Story. This slide deck was created by two Intel Products employees namely Tim Skowronski and Joan Tafoya.

The slides cover many aspects of lean manufacturing, one of the topics covered is The Buffering Law

Systems with variability must be buffered by some combination of:

  • Inventory
  • Capacity
  • Time

Tafoya and Skowronski explain the implication of this law

If you cannot pay to reduce variability, you will pay in terms of high WIP, under-utilized capacity, or reduced customer service i.e. lost sales, long lead times, and/or late deliveries.

The following variability buffering examples are provided:

  • Ballpoint Pens:
  • can’t buffer with time (who will backorder a cheap pen?)
  • can’t buffer with capacity (too expensive, and slow)
  • must buffer with inventory
  • Ambulance Service:
    • can’t buffer with inventory (an inventory of trips to hospitals?)
    • can’t buffer with time (response time is the key measure)
    • must buffer with capacity
  • Organ Transplants:
    • can’t buffer with WIP (perishable – very short usable life)
    • can’t buffer with capacity (we cannot ethically increase capacity)
    • must buffer with time

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    The X Penny Game

    The X Penny Game is a simulation game exploring the effects of WIP limits. It is a combination of Karen Greaves modified Scrum Penny game with Karl Scotland’s version of the Ball Flow Game.

    This game is geared to show the importance of limiting the work in progress and to explore the following formula (implied by Little’s Law)

    Flow Time = WIP/Throughput

    • Flow Time (Cycle Time, Lead Time) – average amount of time it takes to fully complete a unit of work
    • WIP (Work In Process) – is the average amount of units in the system
    • Throughput – average number of units being completed within a given time frame

    The game is designed to work with 6 to 12 people – we had 8 players and 1 facilitator

    The team divides into the following roles:

    • 1 – Customer
    • 5 – Workers
    • The rest are efficiency experts

    We had a total of 8 players (6 workers, 2 efficiency experts).

    The team organises themselves around a table. The image below shows how our team arranged themselves. Each worker has an empty area on the table directly in from of them referred to as a workspace.

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