That really only solves part of the problem. Clean up your data. Clean up your processes. Then decide which processes can actually be improved in a meaningfu

That really only solves part of the problem. Clean up your data. Clean up your processes. Then decide which processes can actually be improved in a meaningful way by ML. I've gone down the ML road twice now with companies that didn't do the second part and both times we had to kill the projects because the processes were so fuzzy and full of gotchas that no ML model could ever hope to be a net positive addition.