… to get it wrong.
That was another conclusion from a Smarter City workshop and I think it’s so important.
Not every good idea will work in every area in every city. But not every idea that fails in one area will fail in another too. So don’t be afraid to trial things.
After all, it can be expensive and hard to implement a solution city wide, especially when so many of those that are in the name of sustainability come with results that can be hard to quantify in advance. So, try them out in a couple of areas; a Proof of Concept is not a bad thing.
Then understand why an idea was successful, or why it was not. And keep a record.
Of course, wouldn’t it be nice if you *could* predict whether something will work? And that’s where predictive analytics comes in. Wikipedia’s definition is “Predictive analytics encompasses a variety of techniques from statistics, modeling, machine learning, and data mining that analyze current and historical facts to make predictions about future events”.
So, a local authority can use a variety of data (e.g. the demographics of where a solution is be applied, asset management in the area, historical data about similar solutions in this city and others) to model the implementation of the solution and the likelihood of its success across the city. A small investment up front in the analytic solution can mean resources are better applied to sustainability: whatever shape those resources come in (funding, people, tools, etc.). Spend wisely to spend even more wisely.
I’ve been thinking about this ever since I sat down in a workshop with Sustainable Glasgow to discuss the future of the city centre in Glasgow and what changes are required, with limited resources, to cater for future needs.
The climate is changing, and it’s likely to get wetter and warmer. Anna Beswick, of Adaptation Scotland, presented on the subject, and some solutions which assist. Take a look at their website to find out more.
What jumped out at me was the need to implement solutions that can address more than one problem, thus maximising any investment. For example, green walls and roofs assist with CO2 challenges, but also provide a level of insulation which reduces fuel consumption and therefore costs to domestic households, and to businesses, and carbon emissions by the energy providers. Of course, this would not be appropriate for every property, but where applicable more than one challenge is being (in part) addressed by one solution.
I know less about these non-technical solutions than ones which are provided by technology, but I believe the principle applies to technology also. One of the benefits of a system such as IBM’s Intelligent Operations Centre, is that it is a platform which allow reuse of technologies which have been applied to one requirement of a city – and of the learnings from that technology – for additional requirements of the city. For example, it can be used to integrate asset management of roads and demographic data (typically data held by different functions in a local authority) so that it is possible to work out which roads and pavements should be gritted first in winter based upon the people that use them. The next step could then be to integrate with CCTV provided by organisations external to the local authority to monitor traffic on the roads, and enhance the gritting plans based upon that. (Ordinarily this example would be appropriate for this time of year, but perhaps I need to change this to dealing with flooding and floodwater instead.)
Two (or more) for the price of one is always an attractive proposition.
The challenge now is assisting cities with how to allocate cost internally when one solution helping more than one department…