A good while ago I completed my undergrad at Victoria University. While that puts me in some sort of “highly qualified” percentile, it also makes me the least qualified person currently working at DOT Loves Data. And having come from advertising, the world of data analytics was a whole new space to navigate.
DOT was started back in 2014, with the premise to change the way the world uses data. Our approach? To produce data that was easy to digest, accessible, cost-effective and attractive. We’ve come a long way in three years, particularly in Australia and Singapore, where we have ongoing support from a number of clients. In this time, we’ve also undertaken a truckload of assignments and have built three products that are all currently in market.
Here’s a few of the key learnings from the past three years.
The first two years were a talk fest.
We’ve spent a lot of time in boardrooms, conferences, sales meetings – you name it! And all to talk about what’s possible in the world of data. From this, people are often inspired to utilise data in their own work, but when the rubber hits the road, organisations just aren’t sure where to start. Thankfully, more organisations are trying to use data to solve problems wider than just data problems. The world is certainly moving toward a more data-focused future, particularly in Asia.
Not all data is created equal.
There seems to be a mad scramble to collect anything and everything. And this often occurs on the back of a paranoia that organisations have developed around being left behind. This can be a pointless exercise as the amount of data collected is overwhelming. Data rich, insight poor is a common thread when we talk to businesses.
Look forward not back.
Looking backwards is helpful, but we’re best when we help organisations look forward. Using data, we have been able to help organisations understand what’s going to happen in the future and how it might impact their business. Our product, DDI (Dynamic Deprivation Index) does just that. It tells us the health of a community. And thanks to the machine learning models we’ve built, we know the levers a community can pull to improve outcomes for all. Whether they be pokie machines, sports clubs, mental health access, or pubs – both good and bad – we can predict the future, then track it in real time.
Go overseas straight away.
Travel broadens the mind. Us Kiwis are pretty easy to deal with and are pretty well regarded overseas. Unfortunately, there’s no real strategy we can offer for developing in these markets, other than try to get in contact with as many people as you can. And don’t worry about setting up shop over there – just do the work from New Zealand.
We love a good academic paper. We publish about 15 peer reviewed papers a year. They cover all sorts of areas, from deprivation, to understanding who the best IPL bowlers based on their impact on a game. Our strategy has been to become the data authority in a number of areas. In advertising we had awards. In data we have academic papers, conferences and case studies. I personally am a co-author on three papers now, which is three more than I’d ever thought I have.
Make it look pretty.
We were hot on this from day one. People are attracted to beautiful things, and so your data has to be beautiful too. Excel is rarely seen, and so are endless slides of nothingness. Less and beautiful is more.