The Necessary Shift Required for Low Carbon Value Chain
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The Necessary Shift Required for Low Carbon Value Chain

By Jim Donaldson, Director of Innovation, Hitachi [TYO: 6501]

Jim Donaldson, Director of Innovation, Hitachi [TYO: 6501]

To quote the American psychologist, Abraham Maslow,

“I suppose it is tempting, if the only tool you have is a hammer, to treat everything as if it were a nail.”

Those of us who work in technology should remember this and avoid the temptation to declare that our latest AI / IoT / blockchain platforms are sufficient to bring the breakthrough required to transition society to a more efficient, sustainable future.This is not to say that these technologies do not bring huge potential, but they must be considered as part of the solution, to enable an outcome, rather than the solution itself.

Equally, those of us in the energy industry must not lose sight that in most cases, end users do not want to buy energy; instead they want to buy a warm home, or the latest movie on Netflix, or for companies, perhaps a method to transport their goods from factory to destination. Energy supply is a key common enabler in all cases, but not the end goal.

It is almost trite to state that we need to focus on outcomes rather than our own specific product offerings. But it is surprising how often this doesn’t happen. The reasons can be varied— short-term business pressures, organisational structure, skills in the workforce. However, for complex ecosystems and value chains, I think it is as much an issue of refusing to think outside of your silo. Problems can be viewed through different lenses and it is only through embracing this complexity and collaborating with other parties, we get the full picture. By optimising at the system level, rather than our own individual business level, we create the greatest value and give ourselves the best chance of success.

To choose a specific example, commercial fleets are now looking to transition to electric vehicles (EV). Often, we hear EVs referred to as ‘batteries on wheels’, which misses the point that those wheels need to turn and therefore the ‘battery’ may not be in the location required to deliver the forecasted energy system support. Or alternatively, that the pre-supposed charging flexibility is in reality not available, since business pressures enforce a rigid charging schedule.

"We need to focus on outcomes rather than our own specific product offerings"

Viewing EVs solely from a transport system perspective exposes equivalent problems. A typical fleet manager is an expert in reliably keeping large numbers of vehicles on the road for the lowest cost. Typically, they are not energy experts. A common scenario arises when a fleet manager plans to electrify their vehicles. They may not fully appreciate what type of infrastructure is required, for example the types, power rating and number of chargers. Having decided, they request additional connection capability from the local network only to presented with a higher than expected bill. This results often in a scaling back, or even cancellation of the initiative. Even if it proceeds, it is likely that the fleet has requested more network capacity than needed, resulting in an inefficient allocation of resources that ultimately results in higher costs for all parties.

The problem here is that neither the energy perspective, nor the transport perspective considers the total problem. But in principle, it is possible to do so. Those managing fleets (either logistics, maintenance, private hire etc.) have a wealth of historical data available from on board telematics and scheduling systems. Effectively, technology can help predict with a good degree of accuracy the future demand (in terms of miles to be driven) for each of their vehicles.

Equally, networks have increasing amounts of data regarding network capacity, which again varies depending on both time and geography.

By collaborating and sharing this data, we can phrase this as an optimisation problem. We have our primary constraint: energy supply must equal energy demand (the energy required to move the vehicles according to their schedule). Then every other parameter (network and charging infrastructure, charging schedules) are variables that we can optimise, to minimise cost and carbon.

Now, in order to realise this system, we may depend on those technologies that I dismissed earlier. But now the technologies are deployed as required to deliver a specific, quantified outcome with a positive business case. Additionally, the customer may not even be buying an IoT platform, or AI forecasting system. Instead, in this example they may buy a vehicle charging service, priced on a per mile driven by the vehicles, which internally leverages technology to achieve the highest value outcome.

Such business models are becoming increasingly attractive, since customers procure directly the outcome that they require, and avoid the risks of technology failing to deliver the promised value.

For suppliers, the best solutions will be delivered by those who collaborate and tie together different industry silos. In the evolving landscape, this could include utilities, technology companies, public sector or a host of others. Increasingly, innovation will be defined not only by the sophistication of your technology, but by how it knits together with other players and how the combined business model creates additional value. Time to put those hammers away and look at all the tools available to us.

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