Turning data into actionable information

Data-driven retail - why your energy business needs it

Need ideas for staying nimble in energy retail? Look to your high-street peers for lessons on turning basic data into advanced insight.
Published: Mon 12 Mar 2018

In deregulated energy markets like the UK, the regulatory pulling of strings to create a competitive consumer-friendly retail sector is starting to play out.

The number of new entrants to the UK energy retail market reached historic highs by mid-2017 with 12 new retailers offering services, bringing the total to over 50 companies or 18% of the market share, according to a KPMG audit.

The report - ‘2018 - A turning point for UK retail energy’ - released in January 2018 finds a wide range of businesses entering the market including European utilities, international oil companies and grass roots organisations.

Customers are switching in small but growing numbers and usually in search of a better experience.

Customer experience division KPMG Nunwood found that utilities remain one of the lowest performing sectors for customer experience excellence. The research points to legacy infrastructure making it difficult to adapt to modern customer needs, while new suppliers can “differentiate themselves by offering customers a more digitally enabled service”.  

Data-driven high street retailers

But although energy retailers are operating in an increasingly competitive market, it is possible to adapt and survive. Their counterparts in grocery retailing and telecommunication companies (telcos) have been doing it for years.

John Malpass is Supply Chain Practice Partner at analytics data solutions company Teradata International.

Having worked in the UK retail sector for the past 30 years including with major grocers, Malpass sees how energy suppliers can forge a similar path to better understand the customer and improve customer experience through an optimised supply chain.

And the answer lies in a data-driven retail approach.

“Grocery retailers used to check weekly sales reports, then they moved to checking daily data and now it’s every 15 minutes,” he says. “ Having a real-time view of demand was a massive step change - not only as an internal mindset shift but also in terms of opening new business opportunities.”

Compare this with energy retailers having access to their customers’ energy consumption through 30-minute interval smart meter reads.

Malpass says: “The volume of data that smart meters is going to generate allows energy suppliers to move away from standard reports into new predictive reports that change the way you do business.”

On an operational level, if you can better understand demand than you better manage supply.

To illustrate the point, Malpass explains how Teradata helped a grocer adopt a data-driven approach to a supply chain problem.

The retailer was running out of stock on its freshly baked counters too early in the day. The result was two-fold - customers had a bad experience when they found the shelves were empty and the retailer lost out on revenue from the early-evening buying peak.

The solution was lying in the retailer’s data, says Malpass. “We built a model based on 15 months’ of historical data. We then overlaid this with 15-minute feeds of sales data. This allowed the customer to create a bakery schedule for each store that was granular to the point of how much to bake and when.”

Relating this again to smart meters consumption data, Malpass says utilities can build a similar model based on historical data then integrate weather and real time data to better forecast demand and drive efficiencies through the supply chain, improving operations and lead times.

Network experience

Network experience: Telcos use data along the value chain to ensure the customer has a good experience using their networks

Telco retailing - lessons for energy sector

Although supermarket retailing is a less likely source of inspiration for energy retailers, the telco sector is often held up as holding more parallels with both adapting from regulated to non-regulated environments.

Head of Telecommunications Consulting at Teradata International Jonathan Penrose has worked with operators across the EMEA region.

He tells Engerati how he has observed high-level priorities for telcos, most of which will ring true for utilities.

Telcos are keen to grow and maintain revenue streams by maximising customer experience and customer satisfaction. Interestingly though they recognise the customer network experience is crucial to achieving the first aim - if the mobile coverage is bad then need near real-time insights into what the customer is doing.

To help spot which customers might churn, and conversely which customers are satisfied and may want to upgrade, Teradata flexes its core capability of integrating distributed data pots.

Penrose says: “To achieve a 360 degree view of the customer across the entire organisation, we help telcos to integrate online self-care portal into the wider customer journey.”

But this can be tough to execute. “Data warehousing and analytics is the easy part,” says Penrose. “The notion of data ownership can make it hard. And the organisation’s challenge is to integrate distribute data sources, often contradictory, while building trust with those data owners.”

Once this is achieved, the retailer will have an enterprise-wide data view of its customers. Telcos, with a basic data set comprising customer, device, location and activity, can derive a lot of value, depending on the questions you ask, says Penrose, and the advancement of the analytics.

One outcome of a data-driven retail approach allows companies to undertake what Penrose describes as value-based network planning. For example, with the roll-out of 4G and 5G networks, telcos no longer need to take a blanket approach to deployment. They can work out where are their highest value customers and prioritise their investment accordingly.

So as mature retail players are discovering, there are commercial edges hidden in the data but as the advice here is to keep as much raw data as you can.

Penrose explains: “It is short-termism to make economies on data storage and analytics by editing data. Don’t make decisions on the value of data before you even know what value that could lie within it. And be open minded about what you’re going to find.”


Data is the new oil