Showing posts from December, 2019

Humans-in-the-loop forecasting: integrating data science and business planning

by THOMAS OLAVSON Thomas leads a team at Google called "Operations Data Science" that helps Google scale its infrastructure capacity optimally. ln this post he describes where and how having “humans in the loop” in forecasting makes sense, and reflects on past failures and successes that have led him to this perspective. Our team does a lot of forecasting. It also owns Google’s internal time series forecasting platform described in an earlier blog post . I am sometimes asked whether there should be any role at all for "humans-in-the-loop” in forecasting. For high stakes, strategic forecasts, my answer is: yes! But this doesn't have to be an either-or choice, as I explain below. Forecasting at the “push of a button”? In conferences and research publications, there is a lot of excitement these days about machine learning methods and forecast automation that can scale across many time series. My team and I are excited by this too (see [1] for reflections on