ML for Operations: Pitfalls, Dead Ends, and Hope

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Machine learning (ML) is often proposed as the solution to automate this unpleasant work. Many believe that ML will provide near-magical solutions to these problems. This article is for developers and systems engineers with production responsibilities who are lured by the siren song of magical operations that ML seems to sing. Assuming no prior detailed expertise in ML, we provide an overview of how ML works and doesn’t, production considerations with using it, and an assessment of considerations for using ML to solve various operations problems.

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ML for Operations: Pitfalls, Dead Ends, and Hope

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