White Nights, Tight Wallets

Melbourne’s annual 12-hour festival is not all that it appears, and yet so much more

Big data paints a more detailed picture — one that is more complicated but also more interesting and authentic. It can be a true game changer. And if you want to keep playing, you’re going to have to lift your own game.

The Party

As a new resident of the City of Melbourne, I am well aware of the significance of the White Night festival. Hosted in February, the arts festival turns the entire CBD into an all-night celebration of culture and creativity, including exhibitions, street performances, illuminations, installations, film screenings, music, dance and interactive events. It takes over the CBD’s streets, parklands, laneways, public spaces and cultural institutions — and almost everything is free.

It really is an all-night party.

The CBD lit up during White Night. Source: visitmelbourne.com

Measuring, Not Modelling

We used Spendmapp, to investigate the economic impact of White Night. This is an online app we built to measure economic activity through bank transactions.

When we look at total expenditure in the City of Melbourne for the month of February, there is indeed a spike the day before White Night, especially in car and truck dealers. White Night itself also had a jump in taxi expenditure.

However, when we observe total expenditure in the City over a longer period (Figure 1), the White Night weekend is not that significant.

This could be due to several factors. The spike the day before White Night (driven by car and truck dealers) was likely the set-up activity, but also possibly people hiring cars to get out of town for a few days. But the lull during White Night is because the event itself is not really about drinking and dining in the fixed establishments in the City. As most of us who go to White Night will tell you, everyone prefers the food trucks (which don’t register as local expenditure — this means Spendmapp records the transactions occurring elsewhere).

By comparison, there were far greater spikes in local expenditure associated with:

· Usain Bolt and the Nitro event (the weekend of the 4th February);

· Justin Beiber’s concert (weekend of the 11th March);

· Adele’s concert and Arnold Schwarzenegger’s Arnold Classic event (weekend of the 18th March);

· The Formula 1 Melbourne Grand Prix (weekend of the 25th March); and

· The opening weekend of the Melbourne International Comedy Festival (weekend of 1st April).

Figure 1: Total Expenditure, City of Melbourne, January 1st — April 17th 2017. Source: Geografia

If we compare the weekends of these events with the average spend for the rest of the year, they are particularly big spikes. They are clearly drawing a lot of people into the City of Melbourne who are then going on to spend on food, drink, transport and other goods and services. But not so much during White Night.

So, while White Night is unambiguously a major event, and probably beneficial for Victoria and Melbourne as a whole, it doesn’t really benefit City-based traders.

Change with The Game, or Be Left Behind

So did White Night have any net economic impact whatsoever?

The answer, in this case, is not as much as we might have thought and certainly not that much in the place in which it occurred (the CBD). However, White Night is the sort of event where we would expect significant social and intangible benefits. Yes, fun! This speaks to the ongoing debate about how useful (or appropriate) it is to try and quantify arts-related events. We say we value the intangible benefits of creative activities, but then we rush to monetise it. Maybe we should refuse to play that game.

Back to the story. The lower (local) economic benefit of White Night might not be what some might have hoped to see. But for we data analysts, the news is good. We no longer have to model or simulate this event to estimate its impact — we can see virtually in real time the exact impact it had and the nuances of that impact. No estimation necessary.

The important conclusion (for us, at least) is that, by using ‘big data’, we have a much clearer idea of what is and isn’t happening.

To continue relying on the old method of modelling and simulating data won’t just give you potentially wildly inaccurate numbers. State and Federal Governments will also become increasingly suspicious of funding submissions that don’t employ the most reliable (and increasingly accessible) data, putting funding applicants who are slow to adapt at a decided disadvantage.

More reliable data may show an unexpectedly large positive economic impact for another event (or a series of smaller events), which otherwise would have been entirely overlooked instead of funded and supported. But it’s hard to know if you don’t have the right data to tell you the real situation in the first place.

Economic impact analysis needs to lift its game in the era of big data to get a little closer to the truth.