I've worked in what you could call "data science" consulting for about 6 years. I also know data scientists that work in-house in data centric businesses, and h

I've worked in what you could call "data science" consulting for about 6 years. I also know data scientists that work in-house in data centric businesses, and have some acquaintance with in-house data science groups in bigger traditional businesses. In all honesty, almost all firms that are hiring consultants to do data science projects (based on the sample I've been exposed to) fall firmly into the situations the article describes. It's all about appearance and justifying existing decisions or plans, and even the suggestion of changing something swamped out of existence by the bureaucratic immune system of these orgs. On the other hand, I see (especially in advertising but also e.g. fintech and others) cases where an internal data science team really does drive the agenda, and thing like AB testing are used for real in order to make changes that result in more money. Lastly, the in-house team at a legacy company. Although I have less experience here, the ones I've seen closely mirror "innovation" or transformation groups that are supposed to come up with new initiatives or changes but inevitably are ignored because they have no links to operations. So over all, the article resonated. As a data scientist , there is meaningful work at companies where data is closely linked to operations, mostly in "new" businesses. As a consultant, I find it interesting to understand legacy businesses and their data, and learn about what potential upside there is, even if I know they won't listen to me.