Skip to Content

Book: Principles Of Product Development Flow

tags
Product Management
  • It’s important to consider both the cost of delay and the utilization efficiency when developing products

    • Currently, companies only consider utilization efficiency when considering cost of development
  • We can’t suppress variability during product development as innovation demands variability.

    • Doing different things creates uncertainty thus causing variability
  • What’s important is to consider how variability affects the economics of product development

  • When we focus on observable phenomena, we can be baised as some things are more observable than others.

  • Empirical analysis and industrial queuing theory are often at odds with TOC.

  • Only by converting to a single economic unit can we weight the consequences of choosing between multiple options that affect numerous proxy variables simultaneously

    • The example used here is Life cycle profit impact
  • One mental model is to put a price on many variables of the product development flow.

    • Ex: Uptime, cost of delay etc
  • Above all else, prioritise calculating the cost of delay as this affects many aspects of the product development flow.

  • Speaking in the same language of economics across all levels using an economic framework considering all variables allows decentralized decision rules and alignment.

  • Many of these decisions follow a U curve on a cost vs time graph. Thus they have an ideal window of time to be made.

    • Thus it helps to decentralize these decisions
  • Consider marginal cost vs marginal profit of a product to avoid sunk costs

    • Thought: The marginal profit of development would increase the closer you are to shipping and that’s how we should think
  • Even when products aren’t successful, they generate info that reduce uncertainty thus creating economic value.

  • Strive to eliminate queues

  • M/M/1/∞ queues

    • The first M indicates that the arrival process is Markov
    • The second M indicates that the servicing process is Markov
    • The 1 indicates the total number of parallel processes
    • The Inf indicates the upper limit of the queue size
  • Percentage capacity utilization allows us to predict many variables of product development flow

backlinks
Product Queues, Markov Process,