Why Wales needs a Digital Living Laboratory


Most people who have read the headline will probably be wondering “what on earth is a Digital Living Laboratory?”, so let me explain what it is before explaining why Wales needs one.

The concept of a Digital Living Laboratory comes from the defence sector where it is used as a way to solve complex problems. It brings “Problem Owners” together with “Solution Providers” and by using data they are able to model complex problems and possible solutions.

The rules of engagement in a Living Laboratory are pretty simple: everyone leaves their competitiveness at the door; the focus has to be on solving the problem, not on selling a “solution” to a previous problem. Openness and cooperation are key if the teams present are to co-create a solution and any vendor that turns up with something to sell is definitely not joining with the right attitude of co-production of a new solution for the problem being considered.

For example: if the military were tasked to undertake a rescue operation somewhere in a hostile environment, they could call on the services of the living laboratory to bring in potential solution providers. Once assembled, they will all work at defining the problem in minute detail and also the desired outcome. In essence they write the exam question and the model answer.

They would then identify all the possible variables(resources, logistics, troops available, flight times, etc etc) that could impact the creation of a solution as well as all the data sets that are available to model the existing solution. And then they build a digital version of “as-is” before starting to experiment with changes that will take them to a new solution. By working this way they can de-risk their military options and increase the likelihood of success.

If you imagine that the laboratory is therefore like a playground and that the sand in the sandpit is actually relevant data, then the people involved in the process are playing in the sandpit towards creating a best possible solution. It is not a channel to market for solution providers.

And when the solution is generated it really ought to be fit for purpose, it will meet the needs of the problem owner, who will then (hopefully) buy it from the solution providers. It generates a win-win as both sides ought to be satisfied in the outcome, fit-for-purpose solutions that are acquired with minimal fuss.

So how is that of relevance to Wales?  Quite simply, we face some significant financial challenges and really could benefit from using all the tools and techniques available to solve those challenges. Our cities are getting busier both in terms of populations and transport usage, but also in terms of social demands generated by health, education and even crime. But cities can be modelled; there is a vast amount of data available to build a digital model of a city that would allow for experimentation to take place to produce the best and most cost effective outcomes.

Let me give an example and I do so lightly to emphasise the point: recently it was announced that the motorway junction near Port Talbot would be closed. 24 hours later and with thousands of signatures on a petition the decision was over-turned. There was no counter argument available or any benefit statements.

It would have been possible to model the traffic use of the motorway as there is a vast amount of traffic data collected every single day. This base layer could then be overlaid with critical traffic movements such as fire or ambulance services using the junction and a solid digital model of the problem could have been created. Options for improvement could then be run through the model of the junction and the best (or perhaps least worst) option generated. Every single scenario could be measured and compared to others and clear benefits could be identified for the chose outcome.

As a result, when the announcement was made it could have been made with clear “positives” and an understanding for all to see.

I know we don’t close motorways on a daily basis so let’s look at another option: our Ambulance service misses its target response times on a regular basis. So the problem might be: “how do we improve our response time to meet the Government target of xxxx?” There will be data sets available to all for the service to be modelled and for experiments to run. The result of experimentation will be a range of options to improve services. Such options these might include options to redistribute existing assets for greater effectiveness, could amend staffing patterns or might confirm a need for a larger fleet. Whatever the outcome, the need would be thoroughly auditable after the event.

Within our cities we face some challenges around public order, Saturday night drunkenness generates demand on Accident and Emergency units that we ought to prevent where possible and we need to work out options for dealing with it. City layouts, people movements and vehicle activity can be modelled and when the variables of the likes of time of day, temperature, football results, etc. etc are tipped into the model it is possible to forecast outcomes. So if we build this model we can alter city layouts, for example by closing roads at certain times, in order to find ways of reducing clash points that create visit to A+E.

The requirements for a Digital Living Laboratory are relatively light, but do require a coming together of minds. Attitudes to shared working and the co-creation of solutions are critically important as is the need to focus on the problem. The starting point however is data and the potential sources of data.

All local authorities in Wales will, for example, have Lowest Super Output data for individual wards. This can be utilised along with transport data, meteorological and flood data as well as crime and emergency services data sets and will all build a rich digital picture to produce a “pattern of life” provided that are made available and shared in the Living Laboratory.

And before anyone expresses concern about the potential danger of aggregating and releasing all this data, let me be clear: at this stage we are not talking about open data for anyone to access. The data needs to be aggregated into a controlled and secure data store that will manage and provide access to and maximise the benefit from sharing.

Once data is available the exciting work can then start: a city with a decision to enhance the quality of life for its citizens by reducing crime and the fear of crime could map, model and visualise the location of crime compared to CCTV and street lighting. Computer models could optimise coverage of this public safety infrastructure and would result in people feeling safer in and around the city.

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