Despite their justified confidence in their ability to significantly improve most of their
processes, lean companies know the limitations of their ability to accurately forecast.
Instead, they invest great effort in being able to use pull production to quickly respond
to current actual customer demand data (as opposed to anticipated demand) as part of
their data-driven philosophy. Liker (2004, pp. 224-225) quotes Tadashi “George”
Yamashina, president of the Toyota Technical Center, as saying: “At the root of all of
that, we try to make decisions based on factual information, not based on theory.
Statistics and numbers contribute to the facts, but it is more than that”. The “facts” from
downstream customers in a pull system are a more reliable form of data than what is
often used for forecasting in a push system (e.g. qualitative factors influenced by
harmful System 1 biases and statistics based on historical data that get applied using
theory to anticipate demand).
Despite their justified confidence in their ability to significantly improve most of theirprocesses, lean companies know the limitations of their ability to accurately forecast.Instead, they invest great effort in being able to use pull production to quickly respondto current actual customer demand data (as opposed to anticipated demand) as part oftheir data-driven philosophy. Liker (2004, pp. 224-225) quotes Tadashi “George”Yamashina, president of the Toyota Technical Center, as saying: “At the root of all ofthat, we try to make decisions based on factual information, not based on theory.Statistics and numbers contribute to the facts, but it is more than that”. The “facts” fromdownstream customers in a pull system are a more reliable form of data than what isoften used for forecasting in a push system (e.g. qualitative factors influenced byharmful System 1 biases and statistics based on historical data that get applied usingtheory to anticipate demand).
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