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Episode #21: Powering Up Energy & Utilities Providers’ Digital Transformation With Intelligent Automation & AI

In today’s podcast we interview Philippe Vié – Group Leader Energy, Utilities and Chemicals at Capgemini.

The Energy, Utilities and Chemicals industries are vital to our everyday lives today, & the digital world of tomorrow. Futurists envision amazing new technological capabilities that will rely heavily on these sectors. Yet these industries currently face so many challenges, there’s growing concern about their ability to keep pace with expectations. Enter Philippe Vié, Capgemini’s Group Leader for Energy, Utilities and Chemicals.

As an industry thought leader, Philippe advises many of the biggest Energy, Utilities and Chemicals players on how intelligent automation can accelerate their digital transformation. Recently, his Capgemini team published a report which found that the energy and utilities sector could realize $237 to $813 billion of cost savings if it were to implement intelligent automation in its target processes at scale. Philippe shares with us a number of insights from this report, along with the revelation that intelligent automation can not only cut costs for organizations, but also generate new revenue streams.

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Guy Nadivi: Welcome everyone. My name is Guy Nadivi, and I’m the host of Intelligent Automation Radio. Our guest on today’s episode is Philippe Vié, Group Leader Energy, Utilities and Chemicals at Capgemini, the world’s 2nd largest consulting firm by revenue based out of Paris, France. We’ve never had an expert on energy, utilities, and chemicals on our show before, but there’s a lot of interesting things going on in this space with regards to automation, AI, and machine learning. So we reached out to Philippe and asked him to join us, and he graciously accepted.

Philippe, welcome to Intelligent Automation Radio!

Philippe Vié: Thank you, thank you so much for interviewing me, Guy. This is the appropriate moment, since we have collected answers from 500 energy & utilities executives, and we have published May 20th point of view on intelligent automation for our industry. Thank you.

Guy Nadivi: So let’s talk about some of those findings, Philippe. What are some of the biggest ways automation, AI, and machine learning are impacting the energy, utilities, and chemical industries today?

Philippe Vié: First of all, energy & utilities are considering a lot of use cases for core business processes and super-functions too. It seems thanks to our studies in this sector but also in other industries, that 38% of energy & utilities players report at least one use case which has been deployed at scale, and 15% [report] multiple use cases at scale. But these figures show also that for the moment only a minority of players have been able to scale up their intelligent automation initiatives. For which benefits?

In average they answer that, 30-35% of executives report an operations boost compared to 15-30% in other sectors. 35-50%, there is a range because we have multiple KPI’s around these benefits, 35-50% of executives report top-line growth. And 70-80% increase in customer satisfaction, which is also ahead of other industries. And our calculations, and you will find it on the report we have published today, is that there is a put-on-shoulders savings range from $200 Billion to $800 Billion, depending on the way you consider automation & intelligent automations.

More than 30 use cases were reported in core functions & 50 for super-functions. Some examples – forecasting… forecasting, load forecasting, the typical example in core functions. Create behavior interface. Energy storage. Energy trading, in which you have a lot of possible automations. Vegetation management, meaning intelligent ticketing for transmission & distribution operators. Complaints management on the retail side of the business. Customer chatbots on top of costs of the classical and well-known predictive maintenance that is coded in any energy & utilities player.

All should be starting with quick wins, low complexity but tangible results. This is the landscape of potential benefits of AI & automation.

Guy Nadivi: So let’s talk a little bit about that greater landscape. Between June 2014 & January 2016, oil suffered a drastic decline in price, dropping by about 2/3, which led to many layoffs in the energy business. And in addition to that, it was estimated in 2015 that over the next 5 – 7 years, 50% of the workforce would be retiring, leaving behind a huge talent shortage. How has this massive personnel turnover affected adoption of automation, AI, & machine learning in the utilities, energy, and chemicals businesses?

Philippe Vié: 2 questions in fact, Guy, here. The first one on oil price’s drop, which was artificial. It was artificial because OPEC & Russia wanted to kill US shale oil producers 3 years ago.

It obliged US shale oil producers to make efficiency progresses, and they used automation for that. But this war is today over. Oil prices are more comfortable for all the players, floating from $60-$80 per barrel, and should remain at that level, if we trust the analysts. With demand growth, it depends on the economic health of the planet. We are not {unintelligible}. And international political tensions, President Trump against Iran, and US-Iran waivers.

On the last part of your questions, in our views, the adoption triggers for intelligent automation, for automation, resides more in technology adoption and performance improvement targets than in dealing with aging workforce & retiring personnel consequences.

Energy & utilities players are focusing on quick wins, as I already mentioned, rather than automating to replace [an] aging workforce, and the answer, and this is a good question, that the talent-related challenge remains, even with a high level of automation. Of course, not the same skills shortage, but skills shortage again.

Guy Nadivi: Philippe, You are one of the co-authors of a Capgemini report called “The Digital Utility Plant” which found that only 8% of utility companies have operations which could be described as digitally mature. Perhaps this is at least partially because so many utilities have natural monopolies structurally shielding them from competition, & insulating them from the need to automate or to innovate. What do you tell utilities executives to persuade them that now is the time to become what Capgemini calls Digital Masters, or innovation leaders by implementing AI, automation, and machine learning?

Philippe Vié: The publication of this “Digital Utility Plant” you mentioned was a long time ago, in 2017. 2 years is a very long time for digital transformation. And we have observed since that, growing appetite for digital operations to save costs up to 20-30% savings {unintelligible}. Digital operations for centralized generation assets, decentralized generations assets – renewables, and also transmission and distribution networks.

So this potential for digital operations is today’s top priorities of the players when they go digital, and they are all going digital. They have all started by the customer experience.

When you see for example EDF, the French leading utility is the 2nd-largest utility in the world, they are going full blast in nuclear engineering digital transformation, and they are trying to create a digital twin for each reactor, new reactor, or to-be-retrofitted reactor, to expand their lifetime. This is a huge project and a huge investment, but very profitable. When you see smart grids deployment at scale after years of experimentation in several world-leading distributors, in EDF for example in Europe and many in the US also. This is a clear signal that energy & utilities are really moving forward on the digital transformation route.

So our arguments are to push concrete histories related to techno-leverage, not only AI & RPA, but also IoT, Cloud, and other digital nuggets, to help decision-makers to move forward with “of use, use cases”, low complexity, or big profit potential, easy to develop & deploy on the 3 pillars of the customer experience, digital operations, and new business models around digital transformation, but also on worker enablement in any section. The selection of key use cases based on their value is very, very useful to select the appropriate initiatives with which you should start.

Guy Nadivi: Now Philippe you mentioned costs there, and automation, AI, and machine learning are often applied as ways of optimizing resources and cutting costs. In the utilities industry though, I understand these technologies are also being touted as the basis for entirely new services. So can you tell us a bit about some of the more interesting use cases Capgemini is involved with where Automation, AI, and machine learning are creating new revenue streams for utilities?

Philippe Vié: Yes, let’s start with some use cases and with the profit that can come out of their implementation and their deployment. Just a long list of possible use cases, I will bring 6-8: • Online self-services & self-sales. • Smart charging / smart discharging for electric vehicles • Energy management solutions software for building microgrades • Automated demand response for getting access to flexibility to better manage load & the demand • Smart lighting • Transactive energy solutions offers personalizations and far more What kind of KPIs the energy & utilities are considering when they get through these new business models is new revenue streams.

First of all, the answer is that 47% of them, the executives answer that they can get quicker access to customer data and more reliable customer data.

41% of them insist on the faster time to market.

45% of them an increase in inbound customer leads.

And 40% of them in quicker break even for these new business models.

Very tangible results in which the utilities are really engaged and they have demonstrated this value.

Guy Nadivi: According to Capgemini’s March 2018 Automation Advantage report, 46% of firms are refraining from innovation due to concerns about cybersecurity. Philippe, what impact are concerns about cybersecurity having on utilities executives’ decision to move forward with the kinds of digital transformations that automation, AI, and machine learning can produce?

Philippe Vié: First of all, electricity, gas, water, [and] oil are critical assets in any country, and it’s not because of digital transformation. They are critical assets, meaning that energy & utilities players are used to deal[ing] with cyber security threats. With threats in general, and cyber security threats, which is particularly true for exploration prediction, generation, transmission, and distribution. This is less real for retail and energy services.

So they start by selecting cyber-proofed or certified platforms with a national agency certifying cyber security of some products, and they work also mainly with serious players, well-known for managing cyber security threats. System integrators, for example, and really taking into account these cyber security threats. It seems that these threats don’t prevent them to move forward, which is good, but can make the automation project longer and more expensive. But that’s it. They have no choices as they want to move forward. They have to move forward to get the value out of the intelligent automation projects, and they have to manage on the other hand cyber security.

Guy Nadivi: You were quoted in La Tribune as stating that of the forty plus energy suppliers in France, ultimately, only 3 to 4 major players will survive. You then encouraged them to accelerate their digital transformation, in particular by making better use of AI. What are the top 3 ways Philippe, that you would recommend that AI, machine learning, and automation be used by utility companies to survive into the future?

Philippe Vié: In European markets, which are open to competition since more than 20 years now, all European markets. This is {unintelligible} and you see 40 competitors in France, 70 in UK, far more in Germany & in Austria, and only 3 to 5 will get significant market share, and some of them are dying every day in the smaller countries.

Considering AI, machine learning, automation – our recommendations are to move forward with quick wins first, then evaluate & choose carefully pragmatically intelligent automation use cases which can be the more profitable or the more interesting in terms of competitiveness in the market. To integrate & optimize the right processes for deployment, and deploy at scale as soon as they have demonstrated the value of their use cases. Quick wins are the most profitable ones, but more complex. And finally, to involve their workforce to invest in their capabilities, to put their money on the table to be successful, and to drive dedicated change management program around these new processes which change the life of their workforce, and also the way they interact and sell to their clients and the new value they can bring to the market.

Guy Nadivi: Aside from doing those things because you need to, to survive, is there a single metric other than ROI that best captures the effectiveness of automating IT operations in the utilities, energy, and chemicals businesses?

Philippe Vié: In fact, as already mentioned, we have 3 dimensions – customer satisfaction, operations boost, and top-line growth. And for each of them in our paper, you will find about 10 KPIs and probably more in some energy & utilities players, on which you can make real measurement of your successes. Depending on the chosen use cases which can be divided in this circle of KPIs, let me give you an example for each pillar – customer satisfaction, operations boost, and top-line growth.

Customer satisfaction, you can reduce the number of steps in customer interactions. You can improve your customer experience through faster response. You can be more customized to your customer needs and bring the appropriate answer.

On boosting operations, you can definitely improve your workforce efficiency & agility, and you can measure that with related KPIs.

On top-line growth, I have just mentioned before the typical KPIs, quicker access to customer data, faster time to market, increase in inbound customer leads, quicker break even, and so on and so forth.

Guy Nadivi: Chatbots or Virtual Support Agents are playing an increasingly important role in the automation of IT operations by enabling end user self-service. What do you envision Philippe, will be the role of Virtual Support Agents for companies in the utilities, energy, and chemical sectors?

Philippe Vié: Virtual Support Agents can bring various advantages to a company in IT, but also in many other domains of operations & core business support functions. Let me choose an example – applications diagnostics, customer credit check, real-time conversation with your customer analysis, payroll management, employee data management, finally a lot of use cases you will find and a lot of Virtual Support Agents you will find in our paper too.

Guy Nadivi: Philippe, for the CIO’s, CTO’s, & other IT executives from utilities, energy, and chemical companies listening in, what is the one big must-have piece of advice you’d like them to take away from our discussion with regards to implementing automation & AI for their operations?

Philippe Vié: Difficult for me Guy, to answer with only one. Generally these profiles, meaning CIOs, CTOs, IT Executives, they don’t need explanations or particular focus on intelligent automation potential advantages, because automation started very, very early in the 80’s, 90’s to automate their information systems.

They all, when you interview them, they all have one or two compelling stories to tell about the gains or savings they’ve recorded through these technologies. On data quality, on application diagnostics, on monitoring protocol compliance. If I were just to mention one or two benefits, I would say first – reducing complexity, the number of applications.

We have seen a lot of energy & utilities players moving from thousands of applications to hundreds of applications, and this has realized the ability to simplify the portfolio of their applications.

And the second one I would mention would be cost saving[s] on the run side, which is very important today. Servers, infrastructures, the run [side] is very important & shrinks their ability to make more developments. So this is cost saving on the run to enable more developments.

Guy Nadivi: One last thing Philippe, please tell our audience once more about the report Capgemini just issued & how they can get a hold of it for themselves.

Philippe Vié: So you go to, you have industry-specific reports, and you will find on energy & utilities/chemical this report, published May 28th. You can download it. You can download also an infographic of this report with key figures of the report. Again we have interviewed 540 executives from energy & utilities, specifically on this topic – intelligent automation. And you will find a ton of figures in this report, 40 pages report. And we will be very pleased to engage a conversation in any country with you around this topic and around our great experiences and also our fails on bringing intelligent automation to life in many utilities and what are the advantages against that we can report to you. Guy Nadivi: We’ll be sure to include a link to that report also from our website, along with this episode so people can download directly from there.

Alright! That’s all the time we have for on this episode of Intelligent Automation Radio.

Philippe, merci beaucoup for coming on to the show and giving us great new insights on the state of automation & AI in the energy, utilities, and chemicals sectors. We’ve really enjoyed having you.

Philippe Vié: Thank you, Guy. Thank you, and enjoy reading this report and going through intelligent automation for the benefit of your companies.

Guy Nadivi: Philippe Vié, Group Leader Energy, Utilities and Chemicals at Capgemini. Thank you for listening everyone, and remember – Don’t Hesitate, Automate!

Philippe Vié Headshot


Group Leader Energy, Utilities and Chemicals at Capgemini

Philippe joined Capgemini in 1997, after a career in software, where he founded an early 80’s startup. He is now Vice President, Capgemini Group and Energy Utilities and Chemicals sector leader, based in Paris.

Philippe has over 25 years of Energy and Utilities industry experience and dedication, with a strong focus on Utilities Transformation projects, digital or not. His tenure has also notably covered the deregulation and market opening period. His many roles within the Energy, Utilities and Chemicals sector include:

  • Thought leader, managing strategic studies and shaping Capgemini group EUC offers portfolio
  • Leading the annual World Energy Markets Observatory by Capgemini (
  • Performance benchmarks (DNO – Distribution Network Operator – and Retail)
  • Writing multiple POVs and press articles
  • Creating Capgemini offers: Digital Utilities Transformation, Utilities to Energy Services, Utility in a Box, Digital edge, and training Capgemini representatives to sell and deliver the related services
  • Delivering keynotes on industry trends

Philippe Vié can be found at:

Office: +33 (0)1 57 99 19 83

Mobile: +33 (0)6 12 72 82 67



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