I wonder how many of these issues are applicable to human processes ("headcount ML"). Glue code and correction cascades pretty much describe the average corpor

I wonder how many of these issues are applicable to human processes ("headcount ML"). Glue code and correction cascades pretty much describe the average corporate reporting/BI department, with layers of complex Excel-based manual processes nobody really understands which are there both due to piles of "corrections" ("we need it in 2 hours, just get it done dirty") and due to Excel limitations (like effectively reimplementing sharding and map reduce in Excel with humans, because you've hit the 1m row limit). It is a wonder some of these businesses can reconcile their P&L with cash flow. Entanglement and feedback loops definitely apply to a lot of things like A/B testing or online marketing budgeting, and many so-called "data driven" processes designed by managers miss out on a lot of important features/variables (and especially, interaction terms), assuming they even worry about significance in the first place.