Energy storage: generation’s forgotten twin

In recent years, the conversation around renewable energy sources has grown broader and louder. Although wind, solar, and their lesser-known cousins do not (yet) represent a majority of energy generation in the vast majority of countries, they form an increasingly significant part of the grid’s energy mix. Indeed, in 2017 – and for the first time in its history – Britain generated more of its electricity from renewable and nuclear sources than from gas and coal.

Great news. Onwards and upwards! But there’s a small hitch… Renewable energy is famously intermittent. The wind blows when it feels like it and, to the ire of many British beachgoers, the sun shines any time other than when you want it to. Ok, some renewable energy sources such as hydro are more predictable but let’s focus on the intermittent side of things for now.

Because of our historic dependence on ‘predictable’ conventional generation, we often overlook a critical component of energy provision in the next 10… 20… 100 years: storage. All too often, energy generation and storage are unhelpfully divorced from one another. Yet, we will never successfully achieve a renewable future without realising an equivalent investment in, and evolution of energy storage technologies. The yang to generation’s yin, if you will.

It is only really since the advent of Tesla that the world has started to think seriously about energy storage (good Tesla). We have been talking solar panels and wind turbines for several decades. Storage has some catching up to do. Indeed, it is the automotive industry which is really driving the flow of investment into energy storage technologies. This is also why many people are limited to thinking that ‘storage equals batteries’ (bad Tesla), predominantly lithium-ion. Yes, I know we use the same chemistry in the batteries that power our phones, laptops, etc. but this isn’t the coalface of chemical battery innovation.

The potential problem with this battery-focused view is that it will not be the best storage technology in all situations. Lithium-ion isn’t even that good: it doesn’t store that much energy, it’s expensive, and it’s not entirely safe. You can pick figurative holes in all batteries, all technology types, but my fundamental point is that this is not a ‘one size fits all situation’.

For example, a remote monitoring sensor requires short, large bursts of power that might be provided by a supercapacitor. Electric vehicles of the future might run on fuel cells, instead of batteries. And grid-scale renewable generation will need to be paired with grid-scale storage which could take the form of giant flywheels, compressed air energy storage in vast underground caves, or something we simply haven’t invented yet.

Successful innovation leaders will remain agnostic as to what future storage solutions will be required by each industry and application. My point is that, by focusing on batteries, we may limit the development potential of other technologies, some of which could be essential to our energy future.

Secondly, and to go back to where I started, we will need a myriad of solutions to support the energy transition to a cleaner, renewable grid. Unless we re-establish the critical link between storage and generation, innovation in the former will continue to lag behind. In practical terms, we will produce all the energy that we could possibly want from the sun and the wind, but it will have nowhere to go.

The allure of the ‘data is the new oil’ analogy

The commodities market is no stranger to data; a quick Google search will lead to streams of data showing price fluctuations and percentage deltas. Oil is back up to $70 a barrel and lithium is riding high on the projected growth of batteries and electric vehicles. One thing, however, that is not publicly traded on the commodities market, is data itself. A myriad of recent articles have hailed data as the new oil- the most valuable commodity over the last century. However, while the comparison of data and oil has some use, to label data as a commodity like oil is a misnomer.

The comparison is an attractive one. Data is seen as the fuel for our modern information economy. It is extracted in a raw and crude form and refined to produce something of real value. Yet, the analogy is overly simple and ignores some key differences. It is important that these distinctions are drawn to enable us to think about data and its value in the right way.

The data/oil/commodity analogy

For those of you who haven’t seen Billy Rey Valentine being condescendingly explained the commodities market in Trading Places, it’s probably good to start with a quick definition. Commodities are basic goods and raw materials that are extracted, exchanged and refined. They are agricultural products, coffee beans, gold, oil and of course frozen orange juice. As the alluring narrative goes, data too is mined and refined.

But, data lacks what economists call fungibility: the property of a good or a commodity whose individual units are essentially interchangeable. If I buy electricity from E.ON or EDF, I still expect both sets of kWhs to keep the lights on. In this case, crude oil is extracted, refined and barrelled for use in power generation and the value is the generation of power which is uniform in its output. That barrel of oil had the same teleological journey as the next one.

Data, on the other hand, is differentiated by type and quality. More importantly, the value of data comes from the insight and information one can extract from its raw form; these insights are highly subjective, largely influenced by methodology of analysis and therefore differ wildly through interpretation. Cambridge Analytica had access to a similar ‘barrel’ of data as everyone else. What they did with that barrel, the insights they drew, and their capitalisation of its value set it apart from others.

Another difference in the analogy is that once commodities are used, they often can’t be used again.  Data on the other hand is not a finite resource. It can be generated, used, reused and reinterpreted. Data can be stored and the accumulation of it is highly sought after in the modern information economy. Even when companies go bankrupt and assets get stripped, databases are often considered the most valuable assets. For example, when Caesar’s Entertainment- a gambling giant that pioneered its “Total Rewards” loyalty program- filed for bankruptcy, its most valuable asset was deemed to be this customer service database valued at $1 billion. No wonder companies are keen to get you to reply their GDPR consent emails!

So, as we have explored above, there are real limitations to the data/oil/commodity analogy. But why does it persevere to be alluring? The strength of the data/oil/commodity analogy lies in the fact that data is a valuable asset that is revolutionising business models and driving technological innovation. The ability to collect data and valorise its raw form into insight and information is the fuel of lucrative new businesses and innovative new models—much like oil was at the turn of the last century.

 

Data’s use

Of course, when people think about data it is the tech giants of the modern world such as Facebook, Google and Amazon that come up first. Although Facebook was slightly dented by recent events following the Cambridge Analytica revelations, data still reigns supreme. Google’s recent demonstration of their AI Assistant had people simultaneously in awe and shock at the pace of development of natural language processing and artificial intelligence.

It is not just in Silicon Valley and with internet companies where data is revered; industrial giants and deep-tech early stage companies alike are waking up to the strategic value of data and information. The two largest industrial giants, Siemens and GE are both preparing for the future of industry, where data and the services it can enable will form a key part of corporate strategy. Industrial behemoths like these are increasingly moving towards collecting data and utilising it to improve their ongoing customer relationships and open up new value-added services. This transition will lead to changing business models- a process already under way. Rather than industrial customers buying machinery (products) and maintenance contracts, the likes of Siemens and GE utilise data to provide a continued and long-term service to their customers. Contracts are no longer about just selling products, but delivering ongoing solutions that rely on data. It is an extension of Rolls Royce’s “Power by the Hour” concept developed- well, trademarked in fact- in the 1960s.

Data is spawning innovative technologies from the obvious smart algorithms to engineered hard technologies such as hydro-powered turbines to power smart water networks, novel approaches to asset monitoring and innovative ways to harvest energy to power the sensors that underpin these. Technologies span from smart approaches to data collection and methods to power sensors through to intelligent methods of analysis. The ability, appetite and vision to adopt these new technologies and develop models that the resultant data/information can enable, will lead to winners and losers across different industries. Data isn’t only the fuel of companies like Amazon and Google; it is a lucrative asset that will prove increasingly valuable industries such as energy, manufacturing and farming (to name just a few).

Conclusion

Data, then, can’t be called a commodity and it differs in comparison to sticky, black crude. It is an asset whereby its value stems from the interpretation and transformation of data into information. This information is an important component of our modern economy and will drive strategic diversification in some industries and kill of players who don’t move fast enough with it. Like oil was at the turn of the 20th century, data is a valuable asset that is changing the way our economy operates. It is no wonder that the reformist Saudi Prince, Muhammad bin Salman, pledged $45 billion to SoftBank’s Vision Fund whose focus is on the internet of things, robotics, AI and ride hailing.

Rapid Innovation: Goodbye to the Red Lion, Hello to the King(sway)

Today Rapid Innovation left Red Lion Square, its home since 2010, for a new office at 103 Kingsway – less than five minutes’ walk away.

The move comes as the company is expanding its breadth and depth of activities, although it maintains a focus on a portfolio of high-promise, deep technology companies – all of which have the potential to be world changing and world beating.

Schrödinger’s Mongrel (and pricing equity in early-stage deep-tech)

I’m one of those annoying people that thinks Schrodinger’s Cat is an apt substrate for pretty much any old mixed metaphor that I can drag in. Apologies in advance.

It’s an age old question – how do you support valuation, at the point of seeking investment in a tech company that has zero, or very little, revenue, but shows exceptional promise. The reason it’s an old question is because it’s hard to answer, but here’s a clunky stab. The exceptional promise/ the pot of gold/ the cat is either alive or dead – which of these states it is in has simply yet to have been observed. It hasn’t been observed yet because we perceive time in a linear manner, but to a super-dimensional observer, the cat is, right here and now in spacetime – either alive or dead.

The mission for the entrepreneur looking for a strong valuation is to ensure that the likelihood is that it is alive. To put it another way, the business leader destined to chaperone the cat into the future, must be able to demonstrate to investors that the path through the fog-shrouded woods towards the goal, is well understood; that all the threats along the way have been considered, strategized and mitigated long before they jump out; and that the cat’s future wellbeing is a natural product of the work that has already been done to plan and manage risk. Risk in this context can be conceived of as existing on a series of spectrums such as technology, scaling, market, economic, investment, counterparty etc. An investor looking to push back on a valuation will generally be doing so by applying risk multipliers. Sound strategic commercialisation seeks to manage future risk through today’s action by pushing these spectrums ever closer to proven.

Good commercialisation therefore drives valuation, because it drives down risk. Bad or non-existent commercialisation is akin to leaving the future to chance. To put it another way, curiosity may actually save the cat…

Regardless of the state of the cat, I fully acknowledge that the metaphor is now as dead as a parrot.