This month saw the government-backed Transport Catapult’s Imagine Festival take place at their new “Imovation” lab in Milton Keynes. Over two weeks in June, several tailored days were organised under the broader festival theme of Intelligent Mobility.
Between myself and two colleagues, we took in four events in total. The two I saw, Sentiment Mapping and The Data Challenge, considered aspects of future transport systems’ development and integration that could one day shape how we travel around.
But what is the catapult? The UK government’s innovation arm, the Technical Strategy Board, actually supports fourteen catapults, with transport being one of them. These catapults are considered to be high-impact issues in our future world, and one where the scope for innovation is enormous. The TSB’s main aim is this respect is to connect academia with industry and put some of our country’s great ideas into business.
Certainly, at the events I attended, there was a great deal of representation from universities all over the UK. I must admit that initially, I wasn’t sure if the content was for me as an industry worker, but given that the innovation processes I use on a daily basis are all about trialling and measuring new approaches or ideas, I quickly saw the immediate benefit of the catapults. Industry needs innovation and fresh, creative thinking, while the universities will often need somewhere other than a lab to play in.
The Sentiment Mapping day was made up of a handful of interesting demonstrations followed by five speakers. This type of social monitoring goes beyond scraping tweets and listening to conversations; it works in context. So for example, a tweet complaining about a rail service has some use, but if you know it actually took place while the user was on a train lends a different, more valuable meaning.
On show was a app provided by start-up CommonPlace, that invited users to enter details of the journey that day to the Imagine Festival event. They could measure sentiment by mode of transport from a map with granular data, such as real-time tweets and other types of social mentions, alongside useful aggregated information like colour-coded hotspots. Later, we saw this idea abstracted further into a nodular map of London. The city was shown as a block in the middle, with the eight blocks surrounding it representing each of the major train operators in and out of the capital. The blocks were coloured to match sentiment on any given day, or rolled up over time to dessiminate travellers’ thoughts.
We also saw a video that showed the output of work between Nissan and The Royal College of Arts, looking at what transport would look like in 2025. When asked today, we’d immediately think of electric cars or pods, which is partly true, but the video described an innovative, integrated transport solution that was far beyond anything I’d have expected. Car ownership is reduced to varying levels of membership (red, silver and gold) for occasional users up to daily drivers. Mileage can be converted into eco points for more low-cost driving if lift-sharing takes place or when traffic delays or sentiment is shared.
Data visualisation is all the rage right now and this goes hand in hand with sentiment mapping. Pie charts, graphs and even infographic dashboards are great, but they leave out the context of the message; such as when, where and by what mode of transport a participant was using. It enriches customer feedback for companies far beyond just what my opinion is on any given day about a brand. Context is here to say and like the growth in data analytics, it has an obvious real-time slant about it.
Staying with data, I returned to The Pinnacle in Milton Keynes in the second week for the Data Challenge day. The agenda was completely different this time, with a much more cooperative focus as we set to work in random groups on our tables. Prompted by a selection of questions, each team were tasked with developing a list of challenges to debate later on.
The discussions were genuinely very interesting. I could only lean on my commercial experience to support ideas and answers, while the views provided by the PhD-educated contributors was fascinating. The most common issue was that while the benefits of working with Big Data are very clear, actually obtaining the data sets – and being able to trust them – is quite difficult. Enablement is another issue to consider. There are probably many companies who would gladly give up their data, even develop APIs, but the cost of doing this is prohibitive. It could then leave a difficult sales pitch to deliver an interface when the return on investment, while offering potential even amongst competitors, is rarely understood.
The potential is very easy to understand. Imagine you run a shop and you’re able to produce a private sales data set representing your business. Let’s say you merge this data alongside a public feed, such as the Met Office weather feed. You can start to draw insight from customer behaviour on rainy days versus sunny ones. Indeed, one participant on my table described an experiment his colleague had undertaken, which looked at the London bicycle hire numbers on warmer days. His conclusion was the demand was virtually unlimited on sunnier days; these are two free data sets you can begin to work with now.
My overall feeling from experiencing the event is that we are all pushing in the same direction. The TSB should be congratulated on what they have started here; there is little doubt that the Transport Catapult has got its strategy absolutely bang on. I think what struck me most was the sheer connectivity of what lies in wait around the corner in technology. Big Data, contextual mapping, visualisation and the Internet of Things are all heavily dependent on one another. Our smart cities in the future will be the products of this connectivity, but it won’t be an expensive big bang that will deliver it. Instead, it will be niche innovations building upon each other.
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