“It’s up to stakeholders to know what they want,” etc etc. Often when I speak to data people about this topic, I get the response that this isn’t a data team problem to solve. Gathering requirements… But first: Fighting ‘not-my-problem-ism’ We’ve all been burned here and the hard thing to acknowledge is that we also know the solution, but it’s a bitter pill to swallow. I’ve heard so many horror stories of this happening the deep dive analysis which took over a week from which the stakeholder only uses one chart, or the dashboard we built that never actually gets used. Now all this talk of ambiguous scope and wasted work can be quite triggering for data analysts. You have no idea where the hole is and you’re just swinging widely hoping you’ll get close… Doing analysis without a clear scope is like playing golf blindfold. Nothing has the potential to completely derail a data project like poorly defined objectives can. The other issues listed in the survey like data quality and dealing with stakeholder feedback are definitely pain points but when they happen they have localised impacts.

A data project is effectively a process and if you put rubbish in at the beginning then you’re going to get rubbish out at the end. When you step back this isn’t surprising. Now this was far from the most scientific survey, but nevertheless, the answer was pretty definitive and validated my suspicion… we waste most of our time working on the wrong questions! Here’s the “Toot” (Mastodon’s equivalent to a tweet 😂): Yes, this is the blog post which I mention in the Toot… it’s very meta. (Come find me at: Last week I decided to test out the platform’s polling feature to get some data on a topic I’ve been thinking about recently:- Why analytics often feels so inefficient? Where does our time go? Like many people in the data community recently I’ve decided to join Mastodon to engage with the community on all things data.

Randall munroe mastodon