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Can we disprove our hypothesis?
Supply chain professionals use several hypotheses to run and improve their operations. These are often rooted in assumptions underlying the supposed cause-effect relationship.
For example, a common hypothesis held by several supply chain professionals relates to forecasting… ‘The higher the forecast accuracy, the better the product availability’. Have we ever tested this hypothesis? Do we know about the underlying assumptions? Can we map out the cause-effect relationship?
The bigger question is ‘Can we disprove this hypothesis?’ Can we find examples where higher forecast accuracy is associated with poorer product availability? Do we know of other businesses which consistently do better on forecasting but their supply chain has many more stockouts? Do we know of a business which has extremely high product availability which doesn’t forecast at all?
The important point is that each of our hypotheses must be ‘falsifiable’. If it can’t be disproved, it’s not a hypothesis, but a conjecture.
Breakthrough improvements happen when we find a case which disproves the hypothesis. That’s when we start questioning the underlying assumptions and find additional causes for an observed effect.