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How do we tackle the biggest obstacle in improving forecast accuracy in Supply Chains?
Several leading companies use demand forecasting to run their supply chains. Their biggest pain point revolves around poor forecast accuracy, with efforts focused on improving it. However, their attempts haven’t yielded significant results over past several decades. What’s really coming in their way?
In my opinion, it is a behavioural issue. Since forecasting is generally done several weeks, in some cases months, in advance, the market demand undergoes significant changes as we come closer to the forecast period. These differences are more pronounced at the granular level where it matters the most.
If the market demand changes, shouldn’t we incorporate it in the forecast? I often find a huge resistance to such revisions and an implicit unwillingness to accept market reality.
If we get such useful feedbacks from the market, why not be humble and just get out of our way to improve the forecast accuracy?