"Data analytics will be central to the future of the energy retail and energy services business."
To some this might be a bold statement, but to us there is some very strong logic supporting this view. Both for conventional commodity retailers, and for companies that see the future as more distributed, customer centric, and service orientated. Our logic behind this is based on five drivers:
- The traditional utility business model is under pressure. Profits from generation businesses are falling in many markets, partly driven by the rapid rise of low / zero marginal cost renewables. These utilities are running – fast – towards the customer end of the value chain with a mission to develop services revenues to replace lost generation profits.
- Competition in the ‘commodity retail’ business is becoming more intense in many markets, with low-cost new entrants and price comparison sites driving high levels of churn (at least amongst some customer groups). The ultimate end point of a smart home automatically switching to the lowest cost provider is a scary prospect for retailers.
- A highly distributed ‘new energy world’ is already emerging enabled by new technology, new business models, and evolving policy and regulatory frameworks. For example smart appliances playing into demand response markets, behind the meter storage, and flexible distributed generation.
- The Internet-of-Things is gathering momentum – connectivity will soon be ubiquitous in appliances, controls and buildings.
- Companies from outside of the energy sector – who are already very strong in customer data analytics – are already entering or edging their way into the energy retail and energy services markets.
While different national markets evolve at different rates, we see plenty of evidence that these drivers are accelerating – in some cases very fast.
These drivers create opportunities – many of which have data analytics at their core. We see no shortage of new entrants (and some incumbents) using data analytics to exploit these opportunities. Here are some examples.
Analytics can be used to help pin point which customer will be receptive to which particular service offering, at which particular time. And it can help to both reduce the cost of providing the service, and provide added value services. Analytics can be used to increase net promoter score, to identify which customers are likely to switch, and identify which customers are of most value to a retailer, enabling retailers to better compete in challenging retail markets. It can help minimise ‘lost revenue’ from billing errors. It can be used to identify how long a heat pump can be interrupted for without affecting end user comfort in order to sell flexibility into balancing markets. And it makes sense of the tidal-wave of data coming from smart homes, predicting when a boiler is likely to fail, or pinpointing how much a particular home could benefit from the most appropriate energy efficiency measures for that home.
Some of these initiatives feature in our recent analysis of 36 cutting edge energy services business model innovations – companies that are in the market today and that, in our view, represent credible views of what the future market might look like. From our bottom-up analysis we generated ten lessons. Two of them are:
- The energy company of the future is a software company as much as it is anything else
- Tailored data analysis and insight will be a big part of the answer
So, we’ve decided to put our money where our mouth is, and invest in and launch a new research services to support our clients in customer data analytics. Over the next months we’ll be sharing more about our ‘Customer Data Analytics Service’. Click here to find out more.
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