The Future of Data: Interview with Paul Joyce of Geckoboard

The Future of Data: Interview with Paul Joyce of Geckoboard


After years in data modelling, it became clear to Paul Joyce that there was a big problem with data. The companies he worked with churned out masses and masses of data to be analysed by data scientists, culminating in reports that were emailed or saved to a company Wiki, which Paul describes as a “huge waste of potential.”

So in 2010, Paul left the world of corporate data to found Geckoboard – a data visualisation tool aiming to improve communication around data by demystifying it and displaying it through easy to read, glanceable data dashboards. We caught up with Paul to discuss his startup journey and what he sees in the future of data…

Sharing as the key to data

“It is really clear that we’re very good at generating huge amounts of data” says Paul. “I think everyone would agree that data is incredibly important; even a small amount of data is better than years of experience or intuition when it comes to decision making.”

One of the biggest issues around the way businesses deal with data, Paul says, is communication. “It seems to me that sharing data would be a real force multiplier in an organisation; a way to get a lot of people making a lot of great decisions and creating more confidence. It seems strange to me that there was no solution in place that allowed for data to be communicated in that final mile after you’ve mastered and stored and analysed it, that last bit of getting it into the heads of people to help them make better, more confident decisions” This is the gap Paul created Geckoboard to fill.

“We call it a data communication problem” Paul explains, “and we would position Geckoboard, not as a business intelligence tool, but as a data communication tool.”

Paul discusses how we’ve all experienced complicated data, whether it’s in the form of “wild, uncontrolled” spreadsheets, Salesforce reports or outputs from any number of business tools. “Unless you’re spending all day becoming very familiar with that data, it can be quite an intimidating and scary thing.”

Geckoboard’s mission, simply put, is to make data “less scary and intimidating… We open that data up in an organisation, we humanise how we consume that data by removing cognitive barriers and we remove resistance to looking at data so that it becomes something that has as a seat at the table.”

Vanity metrics

One common issue Paul sees is the “temptation to put a bunch of metrics [on a Geckoboard dashboard] that aren’t actually core to your business and there’s a few reasons for that. First of all maybe the data is easier to get hold of, maybe it’s more fun.”

The thing about vanity metrics, Paul says, is that “often people will start with them, and then realise that actually, it’s not the most useful thing and it will grow and evolve. Our best customers don’t see dashboards as a static thing. They see them at that as something that evolves as priorities and the team and the organisation change.”

By giving users limited screen space, Geckoboard aims to help users focus on what matters.

“Putting [data] up there not only keeps people engaged with it, but by virtue of the fact that there’s only a limited amount of real estate on the screen, you have to be choosy about what you put up on there.

“You have to make active decisions about what is the most important stuff, so when somebody looks at the dashboard they can reasonably assume that these are the most important things. That gives people a lot of confidence. It’s human nature that if you see a number you want to improve on it. If your priority is front and centre, that it is a great way of keeping your focus and ensuring that you don’t get distracted on low impact stuff.”

Humanising data

“I think the temptation, when it comes to data, has historically been because we can do certain things we should” Paul explains. “A lot of people really believe in the power of data and it’s very easy to go down the rabbit hole that is about making it flashy and adding movements and lots of colours because it’s shiny and it’s novel. However there are brain systems in place that are more amenable to digesting huge amounts of data quickly.”

Paul explains that there are two main routes that data can take to “get into the cognitive area of your brain. One is using the frontal lobe which is about language processing; it’s serial and it takes quite a long time to really understand something. It’s about telling a story, which is a very important part of understanding large data sets, but that isn’t the same as glancing at data and getting it straight away.

“Another brain system that humans have evolved is the visual cortex which you can imagine as a fat pipe into the cognitive area of the brain. Now the problem is that the visual cortex is very fussy about how data should be presented.”

The Geckoboard team work with research about how the brain makes sense of data. “To consume it in the best possible way” Paul explains, “you need to think about the human systems that are involved in transmitting data effectively. If you can exploit that, then looking at the data becomes so much easier and it becomes understandable much faster.”

The future of data

“For us”, Paul says, “we’re really still exploring. It’s still very early days in terms of data communication and I don’t think that problem has been solved. We feel like we can add a lot to how data is communicated and how it can be best fit for human consumption… That’s the area that is most interesting for us and that we’re most excited about in the coming few years.”

Paul thinks the not too distant future holds a lot of promise for data. “There are a few companies working on natural language exploration of data. But I think even more interesting than that is software that uncovers the most interesting stuff automatically, so instead of simply exploring data and asking questions, [a tool could] surface deep insights that have real value.”

The beauty in more intelligent data assistants is that, “it would almost be like a safety net” says Paul. “You still have people who could interpret findings but that could be supplemented with software that was smarter than a simple tool for exploration and analysis data; something that augments human expertise with what machines excel at, that would be very exciting.”

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