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Comment by nobrains | Hacker News Reader

OK, then what?

Then you find out why retention is low.

Then you brainstorm ideas to increase retention.

Then you attempt to apply those ideas. It is at this point that the person responsible for applying those ideas says "been there done that".

Point is, most data dashboards are non actionable. The challenge is to create a good actionable dashboard (i.e. if values cross a certain threshold, then the user should take some action on it).

Once you create an excellent actionable dashboard, you realize it doesn't need a dashboard. It can be a notification.

So, while the data is important, the questions around it might just lead to the same work that was being done anyway.

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In my experience it is generally worse than that. If a program has a retention rate of, say, 30% then it isn't like that is going to come as a surprise. Data generally reveals things that are very obvious. It is easier to read a situation by talking to a few people and asking simple questions. Which raises further questions about why a data-driven approach is needed.

The value in data driven approaches is high, but it takes a rare person to figure out why. Traditionally data has actually been a communication tool for things that are already known. That isn't at all how people expect it to be used, everyone seems to anticipate it is used to make decisions.

An organisation resisting data is bad news because it will struggle to talk about things that everyone knows to be true.

> The challenge is to create a good actionable dashboard

Huh? You don’t need a dashboard to make use of data. The best use of data in my mind is asking and answering questions.

Eg, maybe your program has a low number of graduating female engineers. Why? Maybe they’re dropping out along the way. Maybe female intake is low. With the data you can answer these questions.

The graduating rate of female CS students is low, but is it abnormally low compared to other schools? You investigate and - everyone has an equally low rate except one place where it’s 50/50. The data has led to a question - Why? What are they doing differently? And so on.

> Point is, most data dashboards are non actionable.

Maybe you find out that one specific class or set of classes is responsible for a lot of people leaving the program. So you zero in on that part of the curriculum and improve it. Sounds pretty actionable to me. We've actually done similar things on a smaller scale (week by week) to improve student success in my course.

But of course you don't know anything until you do the analysis.

Many times you need the data/visuals to get funding to actually implement ideas.

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