In early 2012 The Economist Intelligence Unit (EIU) teamed up with BuzzData to challenge people to determine what the best city in the world to live in is by using the EIU’s Worldwide Cost of Living and Liveability surveys along with other sources to output a new ranking of their own.

On Tuesday July 3rd, 2012, Filippo Lovato was announced the winner of the Best City Contest.

This interview with Jon Copestake – the Senior Editor of the EIU’s Cost of Living and Liveability surveys – highlights his reflections on Filippo’s winning submission, the other contest short list entrants, what he learned and more.

1. What was it about Filippo’s submission and approach that marked him out as the Best City Contest winner?

Many of the better entrants to the competition could be split along two lines. Those with visually impressive or functionally interactive expression of the data and those with a methodological “value add” which incorporate new series for improvement.

Filippo’s entry seemed to tick both boxes. The visualization expressed the change in methodology and the new ranking expressed as a both a score and as a map indicator. But more impressive was the groundwork Filippo put into adding value to the final index. Some entries merely reweighted the standard liveability offering, while others drew on sources which could be easily incorporated into the scoring system. However, Filippo created a whole new category made up of 7 indicators, each of which comprised one or more detailed sub-indicators. Fillipo’s additions in terms of green space and other assets reflected a mix of quantitative factors such as pollution levels and qualitative judgments such as using Google Maps to assess and score sprawl. His area of focus also touched heavily on a weak spot in the current methodology, which is that of pollution and how “green” a city is – which has enabled some practical possible solutions to an area of the survey we were looking to improve upon anyway.

2. Filippo’s submission identified Hong Kong as the best city in the world – did this surprise you? What happened to Vancouver, Melbourne, Vienna, etc. – the “usual suspects”?

It was surprising to see Hong Kong up there – but interesting to see the impact that this new category and reweighting had on the survey. For Fillipo’s ranking many of the top liveability cities were absent since his assessment was based only on the 70 cities he could create a full dataset for. So Vancouver, Melbourne and Vienna were absent from the ranking altogether. By adding scores for factors like connectivity Fillipo brought some larger cities into the mix while keeping the integrity of other areas of the survey. The Australian and Canadian cities of Sydney and Toronto both featured in the top 10.

3. There were a couple of other entries that the judging panel was particularly impressed by – Christian Muise, Roxana Torre and Ewan Nicholson – what was it about each of their submissions that caught the eye?

The app developed by Christian Muise was an ideal tool for engaging with an audience. By allowing people to define their own parameters with a series of questions Christian enabled people to see what the best city for them would be based on their own preferences. This in itself adds a great dimension to create a dialogue with users. But in addition to that Christian recorded the submissions to crowdsource a means of weighting the liveability index by question. This ultimately means that the EIU liveability score can be tested against a consensus score as well as by scores and weightings by country.

Roxana and Ewan both created visually interesting entries which showed the scores expressed as a “circle of liveability”. As a result there was an instant visual representation of which areas a city was strong in and which areas a city underperformed in. In Ewan’s case the visualization for each city was smoother by revealing the circle of liveability when hovering over a location. But Roxana’s index also added value in the form of additional categories (life satisfaction and environment – from other surveys) and offered a means of benchmarking city rankings against population, human development and carbon footprint.

4. How are you looking to change the EIU’s Liveability index based on the contest submissions?

The survey has given us a lot to digest. It has supplied us with some practical solutions and innovative approaches to finding other means of benchmarking locations. So there is a lot for us to take away and think about.

Primarily our aim is certainly to add categories that reflect greener aspects to a city, as well as to utilise new sources to add value in existing categories. Creating an interactive means of allowing people to weight their own scores also strikes me as something that can really add value to what we offer.

That said, submissions commonly used a reduced city set. This is because finding data for all cities in our survey to enhance the index may be hard, or even impossible. This is also something that needs to be considered in terms of how we can proxy score cities where there is no data.

5. This is the first time that the EIU has run a contest on – essentially crowdsourced – the EIU’s Liveability index – what did you think? Would you do it again (for the Liveability index or other indices and research projects)?

I think it’s been a fascinating insightful and very useful project. I wouldn’t hesitate to do something similar for any of the products I work on or for wider EIU products. There is so much value that can be added by opening a product up to feedback and reinterpretation of this kind. I also see this kind of interaction between data providers and their audience opening up even further as time goes by and social and digital media remove the barriers between businesses and their markets. Since the launch of this competition with BuzzData I’ve also seen a number of similar endeavors taking place in the media – including the recent announcement by NASA that they intend to release data for a public competition to create an app for them.

6. Finally, what did you think about the other entries on the shortlist not mentioned above – why they made the shortlist, what impressed you, etc.?

OK in no particular order…

Alexander Kosenkov’s entry was impressive because of the variety of normalization techniques he applied to come up with his results. This produced a range of visualization of data correlations, which culminated in an impressive series of appendices that mapped out the links between rich and poor cities.

Martin Magdinier made the index interactive by allowing people to select language and eliminate weighted categories. He also added value with additional subcategory index scores using Hofstede cultural analysis as well as incorporating a language element.

Abhineet Gupta was one of the few contestants to make a dedicated effort towards combining the cost of living data with the liveability data – which provided a liveability “value” index based on affordability as well as liveability. The concept of creating a visualization through a data globe was also an impressive approach to take.

Tathagata Sarkar took an interesting approach by linking liveability to its ability to fulfill Maslow’s hierarchy of needs and also by ascertaining that the most liveable locations were not those causing the most satisfaction but those which prompted the least dissatisfaction. The additional tailoring of weights to the performance of cities in certain areas related to Maslow’s hierarchy was also an innovative angle to take compared to applying flat category weightings.

Jeremy Albisser’s entry was all about letting the data speak for itself. The interactivity of the tool here and the different means of visualising and correlating different scores among cities was a lot of fun and very interesting and informative for exploring items.

Ben Jones entry won us over with its relative simplicity. Creating an intuitive app that allowed an audience to tangibly customize the category weights to find a city that suited their needs. It was interesting testing the impact of different weightings and also provided a well constructed visualization by drilling down to location on a world map.