Toyota people learn about statistical variation and the implications of queueing theory this is reflected in the lean leveling principle to reduce variability and more generally in the lean focus on smaller batches and cycle times to move toward flow.īefore diving directly into the subject, note that lean is sometimes described as focusing on smaller batch (work package) size, shorter queues, and faster cycle time. And yet, telecom infrastructure development people (telecom is a domain of large products) rarely see that it applies to their system to reduce the average cycle time in their development processes. As a consequence, telecommunication engineers understand the basic insights.
This thinking tool is especially relevant for the large scale because big variable batches of work-so common in the traditional model-have a nonlinear impact on cycle time-they can really mess things up, This system has non-linear dynamics!Īn interesting incongruity: Queueing theory-the mathematical analysis of how stuff moves through a system with queues-was developed to understand and improve throughput in telecommunication systems-systems with lots of variability and randomness similar to product development. And queueing theory points to some ways to improve. It’s hard to fix a problem you don’t know you have. In such domains, it is particularly helpful to see that large batches and long queues actually exist and the problems they cause. In large-scale development, it’s common that ‘one’ feature (before splitting) is staggeringly gigantic. Queueing theory offers insight into why traditional development is unnecessarily slow-and what to do about it. The joy of engineering is to find a straight line on a double logarithmic diagram.
Continuous Improvement Towards Perfection.
Potentially Shippable Product Increment.
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