In industries with long timelines for benchmarks and measurement outcomes, turnover is the killer of analytics and decision making culture.

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When the very leadership accountable for the outcomes have moved on to another position before the results are in, analytics results are intrinsically devalued, and meaningful outcomes become difficult to define if defined at all. No amount of AI or well-engineered pipelines can account for this problem.

in fact, when companies like this invest in top-tier engineering, it's just more efficiently perpetuating the problem. I really enjoy engineering as well as analytics and ML, but when turnover happens at a faster rate than realized outcomes, it's all just window dressing.