Craig kicked off proceedings by detailing the relationship between McLaren and the IoT. A story that began in 1975 when sensors were first placed on a race car: technology that generated 14 different data streams, even if the vehicle had to be brought into a garage in order to extract the information! Fast forward to today, and the latest cars have between 300-400 sensors during a free practice session, and approximately 150 during the race itself – sensors that monitor everything from engine temperature to lateral G, and generate around 100GB of data over the course of a race weekend.
As Craig was keen to highlight, “we’ve been collecting data since 1993, and I would estimate McLaren now has over a trillion data points to work with. This to me is what the IoT is about: sensing technology, sending data, a robust communications network, and a storage mechanism that let’s you get to work analysing the detail.”
The question of course is what does McLaren Group use the data for? To quote Craig again, “we certainly don’t use all of it. One of the challenges of big data is in actually finding the nuggets of small data that can make the difference, which is what our analytics platforms are tasked to do. We run up to 1080 simulations on a race weekend to help optimise our overall race performance. Yet we still need to maintain a ‘human in the loop’, and have a person sitting at the pit wall who’s reviewing all the results – and factoring in a range of other aspects such as the weather and what our competitors are up to”.
We also touched on the work McLaren is doing in partnership with a number of healthcare providers and hospitals to help extend their analytics capabilities, and extending IoT into the field of ‘human telemetry’: a device that is used to monitor vital signs, with the resulting biometric data used to make proactive diagnosis on any possible health problems. Then there was connected transport, and extending McLaren’s Wifi technology, including sensors being placed on trains to enable proactive maintenance and identifying passenger levels to help with smarter journey scheduling.
In other words McLaren, like most businesses today, has access to a lot of sensors generating a lot of data. The question however is whether IoT brings with it the commercial aspects needed to make it a true business disruptor? Can it be a game changer, and if so how far away is it from mainstream adoption?”
What we can say with confidence is that many leading companies are already performing a range of IoT-related activities – but without any central coordination. Yet importantly most efforts to date are being directed toward feeding data into various applications for analysis. To reach the next stage, and to demonstrate a growing maturity around IoT, requires this data to be fed back in a meaningful way.
This was the point where ‘game changer’ as a phrase can be applied to IoT, because it’s here that the technology helps bring to life new and adventurous business models. Or as Craig put it: “the linkage between these types of technologies, whether they be big data or machine learning, is that they’re all connected technologies. The challenge now is to understand the best way to monetise their networked potential”.
Yet how to make this happen? Equally, what is the cost? A question being asked in many a boardroom today is whether IoT requires vast new investment to make it work, or whether existing technologies can shoulder the burden. The consensus from attendees on the day was that that current investments can and should offer the foundations for exploiting IoT, with new technology required out on the ‘edge’ to help extract different data in a different and more agile manner. Put another way: while front ends could evolve at breakneck speed in the months ahead, the underlying back end systems will remain fairly static – thereby helping move IoT beyond the ‘peak of inflated expectations’, and into the realm of ‘business critical’ within the next two to five years.
Then there’s the topic of practical value, and the IoT’s potential for delivering real measurable results. As Michael Wentworth-Fitzwilliam from Reckitt Benckiser pointed out: “we’re not looking to run before we can walk. As mentioned, a lot of the technology is already out there. In fact, I was at one of our factories the other day, and we’ve got machines that are 35 years old, and I can still connect with them because they run on electricity – and have sensors that tell me if they’re either on or off. So whether that qualifies as IoT or not, I’d suggest that companies should strip their operations back to basics and review every piece of equipment from the perspective of what value can be derived from it”.
But what about IT itself, and what will IoT mean for the evolution of its role and responsibilities? It’s an interesting part of the overall IoT conversation, which drew from Craig an insightful response: “I see the fundamental change being a shift in the function from being exclusively concerned with making the business run faster, smarter, and more efficiently, to one where it’s embedded in the back end of some of the actual products being sold”. This is the view that sees IT playing the role of service providers, and running the entire digital infrastructure behind a customer facing service – and being increasingly responsible for the experience and service quality. Such a development is bound to challenge businesses to start shaping new delivery models, and aligning IT output to them – and away from a traditional view of the function being dedicated purely to internal support.
So what does all this mean for IoT achieving mass adoption? As we know there are volumes of research on the topic, alongside associated statistics that highlight the eight billion IoT devices globally connected in 2017 – and how this is set to rise to 20 billion by 2020. Yet such numbers can also be misleading, as two thirds relate to smart TVs and other consumer technologies – with only a third described as ‘business operating devices’. In addition, it should also be noted that a lot of press coverage on IoT refers to ‘preventative action’ – the proposed AA black box for diagnosing faults on cars and prescribing fixes in advance being one example. Maybe we should therefore be challenging this current narrative, and asking when the focus on ‘negatives’ will turn to helping human society progress?
An example provided by Craig was the addition of sensors to cars that provide the insights into known routes the driver takes to get to work (for example), and integration with a smart satnav to proactively advise the driver on when to leave early if heavy traffic jams are reported – as well as offering alternate routes. Or train passengers at stations where their favourite coffee is prepared in advance of their arrival, and where the service schedule can adapt in real-time to meet spikes in demand – rather than working to inflexible, pre-defined timetables. This is where predictive analytics meets big data. The result: your car knowing in advance when it’s needed, and driving itself to your front door in time for when you leave. Think also of a connected toothbrush picking up on how you brush your teeth, and feeding such data to your dentist if a problem is detected.
All in all, some of these applications may seem incredible and life changing, while others could appear rather pointless to begin with. But this is the starting line for IoT, and the springboard from which new innovations will leap forward to help inspire true societal transformation.
So, in summary, what can be said of the challenges that exist to enabling this brave new world? For Craig, the first concern was increased collaboration between different sectors, different companies, and the eco-system challenge with our partners and providers. “There’s a lot of mutual, open and trusted cooperation needed to bring new business cases to life, and I can only see this accelerating over the next few years as no one wants to get left behind”.
This is a good point. To this I would also emphasise that developing such partnerships will remain heavily reliant on clarity of purpose, and a clearly articulated business model. This requires any business to understand in depth the unique direction for any application of IoT, as well as having a clear process in place for monetising it. This can also include changes to the corporate culture itself if necessary. The days of any one company thinking they can do everything themselves are, in most instances, limited. Today, and certainly into tomorrow, developing an extended ecosystem of partners will be critical to helping IoT advances make it to market – and scale accordingly.