The point of a dashboard isn't to use a dashboard
Every so often, an employer asks me to help make a dashboard.
Usually, this causes technologists to roll their eyes. They have a vision of a CEO grandly staring at a giant projection screen, watching the pretty graphs go up and down, and making real-time decisions about Serious Business. Ugh! What a waste of time!
The thing is - that's not what a dashboard is for. And that's generally not why a CEO wants it.
A dashboard shows that you have access to your data. And that is a huge deal.
If you are able to successfully build a dashboard, that means you have demonstrated that you have the ability to get:
- Live data
- Historic data
- Comparative metrics
- Access to multiple databases
- External data sources
- ...and a dozen more things.
Most data are locked away. Either in Excel sheets, or behind a dozen different logins for a dozen different systems - none of which can talk to each other. The data (if they are even kept at all) are each in a different format and mildly incompatible with each other.
A dashboard isn't there to be used. It is there to prove that the data are easily accessible, comparable, and trackable. Only once that is done can they be actionable.
Trapped data is useless data.
It's the same reason that some people launch Twitter-bots at hackathons (myself included!). Is there any great skill in making a data feed push a snippet of text to an API? Of course not - it's trivial! But it is a reasonably powerful statement that a novice can gain access to several different data-sources in an afternoon and do something - anything - with them.
Yes, I'm sure there are some Board Members who wake up every day and track whether the EBITDA correlates with the humidity in the call centre. And, no doubt, there's a CFO somewhere whose pulse races when they see a figure dip bellow two standard-deviations of some metric. But try to think of a dashboard not as an interface, but as tangible proof that data can be created, stored, retrieved, and compared.
Alex Gibson says:
In this story I am playing all roles, CEO, technologist and strategist, and the most critical audience for my dashboard will be a one off audit visit from a key customer, but this helped me think about what I want it for after they are gone.
To he best dashboards I have used (and helped make, at Sky) used red-amber-green states so you could see at a microseconds glance that nothing is on fire, then get an idea of current performance by looking over graphs, top stats etc, and dive deeper by selecting any of the stats to see logs, bigger graphs, tables that actually help to diagnose issues.
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Alex B says:
A SIEM without data is useless.
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Alistair MacDonald says:
Also they are also used to hide the data rather that show you have it. Recently I was asked to mine some employment data for insights in to equality. The catch was that I could only use the dashboard and had no access to the raw data. Eventually they got why I could not help without the raw data, but to them the dashboard was so powerful that it was a leap for them to understand it was not enough.
Personally I use a dashboard for three things. First to visually check everything is okay in passing when it is not critical enough to set up some kind of push notification. Second to give me some information that I might find useful (I include train updates on my work dashboard as it will alter my scheduling). Third to help identify where to look for problems when things start going wrong. A narrow use case perhaps, but who is to say what a "dashboard" has to be.
We also have a dashboard built in to the AV equipment. That gives us news headlines and internal adverts. I think that is just because it can.
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One implicit reminder here: when a stakeholder asks for a dashboard, that's our opportunity to say "What types of things do you want to know, and what do you do with that information?"
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Bruce Lawson said on :
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I'd not really thought about this, but it's a good point. Sometimes dashboards are just an exercise in finding data you can measure and report in the right way - which often has little relationship to the data that might be helpful to know and understand.
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