> then improving the quality of data in the organization is absolutely part of your job, most likely the most important one
You're absolutely right, but it can be hard to get management to bat for this kind of stuff. The biggest hurdle I've seen with getting "good" data is fixing the issues involves other teams prioritizing the work on their backlogs. Depending on the company and where the teams lie on the org chart, fixing things might require a multi-quarter directive from the CTO. Which isn't happening.
so then ... confidence intervals are going to be so use as to be useless. and every second week the data science team can present a 2 slide presentation, where the first slide says bad data = bad result, and the second says good data = good results, and then furiously flip between the two during the Q&A.
You're absolutely right, but it can be hard to get management to bat for this kind of stuff. The biggest hurdle I've seen with getting "good" data is fixing the issues involves other teams prioritizing the work on their backlogs. Depending on the company and where the teams lie on the org chart, fixing things might require a multi-quarter directive from the CTO. Which isn't happening.