What has been fascinating about the last few months is the way attitudes to technology and working styles have changed dramatically. This sea change is proof that often, the technology is available and sufficient to support all of our requirements, but we simply need to make better use of it.
Have you ever considered the volume of data collected about us, not only as individuals, but as a society, without us being aware? We are monitored from the moment we wake in the morning and check our smart phones, to leaving the house on that long forgotten (and now missed) commute to work, from arriving at the office and during our lunch break. However, this is not done in the dreaded ‘Big Brother’ manner, controlling what we do and where we go. This ongoing data collection is actually conducted largely for our safety, wellbeing and to improve our consumption of goods and services that, in theory, enrich our lives.
Yet, despite all that data, there is a perception we need more and, as a result, need to deploy more technology to capture it. But is there another way? If we were to simply maximise the use of what we have already, we may find we can really improve society and as a result, our individual lives.
Now is the time to put the theory into practice and look at how we can leverage technology assets to support the efforts of getting everyone back to work and help to re-start our economy.
A new era
One of the most critical issue for all organisations is securing the safety and wellbeing of their employees, a fact now hugely amplified by the threat of COVID-19. Whether these employees are transport staff without whom we cannot get to work or those travelling to an office, the need to be kept safe and healthy is the same.
Addressing employee safety is a complex issue and as with any such problem, it’s essential to get enough insight to drive informed and evidence-based decisions. This information could be personal e.g. “do I feel safe going back to work” or organisational “is it safe for my staff to come back to the work” and both give vital indications of what action is needed. As a result, employees and managers will have greater confidence in any decisions made and, given the fast-changing nature of the current situation, the quicker we identify a change and act on it, the more secure we will all be.
Ask key questions
The key questions we need to ask are: “what sort of data do we need”, “for what purpose will it be used” and “can I use it”.
As an example, let’s ask these three questions in the context of commutes and transport hubs.
- “what sort of data do we need” – security video footage
- “for what purpose will it be used” – to monitor numbers of people, spacing and behaviour i.e. social distancing and mask-wearing
- “can I use it” It can be used by the owners of the data, e.g. railway stations as there is no attempt to identify individual and the data is kept anonymous, simply exploiting an existing asset to improve the safetyof commuters and their confidence to travel.
On its own, this insight has limited value, but combined with additional data from other aspects of a commute, this information is hugely powerful and can be used to inform the public about the overall situation, empowering individuals to take responsibility for their own safety.
If we then extend this out into the wider commute, station platforms are already monitored as are most city streets and offices and other buildings, meaning that simply by utilising this existing information, overall public safety and confidence can be increased, which will ultimately be what drives people back to work.
The initial reaction to discussing technology and data analysis is often that it sounds expensive and will take too long. This does not have to be the case and in fact, a significant amount of this type of data is already available.
A great example is the city of Las Vegas, where NTT DATA deployed a solution aimed at improving the efficiency of local authorities, simply through the application of Artificial Intelligence (AI) and Machine Learning (ML) to locally captured video footage.
In this case, we looked at factors including occupancy and density of people in open spaces, to detect driving infringements and accidents, improve road signage and aid the deployment of emergency services.
We can now apply the same approach to other new use cases, using existing ML models, modified to suit the specific insight required and act as an accelerator, offering the potential to provide this learning to have a positive impact on personal safety and wellbeing.
Although I have mentioned just a couple of use cases, the real message is that as a society, we have a tremendous level of data available that can be used for good of society and drive better business outcomes. By focussing on the solution to specific challenges rather than be overwhelmed by the masses of data out there, we are able to exploit, navigate and gain insight from the relevant information, providing positive solutions for businesses and individuals.
If you would like to understand more about the potential of this huge sea of data rather than just risk drowning in it, please get in touch.