Welcome to the latest Momenta Podcast. My name is Leif Eriksen, Insights Partner, here at Momenta, and our guest today is Peter Bryant, Managing Partner at Clareo, a leading growth strategy consulting firm.
Peter spent his career at the forefront of helping companies, both large and small, manage change in the face of digital disruption. In addition to large multinationals in the energy and manufacturing sector he has actively advised startups. He is Co-author of Growth Champions: The Battle for Sustained Innovation Leadership. Today we’re going to discuss Peter’s views on what the next decade looks like for the energy manufacturing and infrastructure sectors.
Thanks for joining us today Peter.
Thank you very much, I appreciate the invitation to join you on this.
So, Peter, let’s start with a bit about your professional background, how did you get into this business of growth strategy consulting, and how does your background form your views of the world, and the role of digital technology in it?
I have kind of a unique background, which gives me a unique perspective on this. So, first I spent 25 years in the enterprise software industry, I’m aging myself, I actually started in the early eighties which was really the advent of the enterprise software industry. So, through that experience I saw at least two or three digital transformations, starting with taking the very boring manual tasks of back office accounting, general ledger accounts payable, account receivable, and basically digitized all that. That was all the precursor of VRPs, and for 10 of those years I was in President roles, and that was good. Big software enterprise companies, companies like GE which had a software company back then, and computer associates, and then a couple of startups here in the US.
Secondarily, for the last 16 years when we founded Clareo I’ve been advising large companies on innovation transformation, and a lot of that revolves around how you’re applying digital technology within your business, but not exclusively. So, just advising those companies, and also how they work with the startup ecosystem, so done a lot of work with corporate venture capital, and the venture capital community in general.
I also sit on the board of Chrysalix which is a venture capital fund, I’ve been on that board for five years now, and the fund is actually around investing in the digital enablers of industry 4.0. The limited patterns of Chrysalix are all major-heavy industry companies from the utility, manufacturing, mining, oil & gas sector, so that gives us another perspective.
So, if you kind of triangulate those three things, there’s 25 years in software which makes me technically dangerous having lived through multiple digital transformation, advising large companies around that, and then sitting within the venture capital community, both working with the LPs as well as start-ups, I think that gives me a very unique viewpoint on what’s going on in this area.
Very true, and very interesting too because as you no doubt know, every one of those inflection points on that journey of served digitalization of industry, there’s been resistance to that change, whether it was going from homegrown systems to package systems, from ultimately package systems to software as a service, to the cloud etc. Any thoughts on that?
Yes, as I look back working with companies from the early eighties, until I left the software industry in the mid-2000s, every adoption curve has met significant resistance within companies, whether it’s digitizing manual tasks or enhancing productivity through precision support software back in the nineties. And a lot of that’s around mindset and culture, and I know we’re going to talk a little bit more about that. But yeah, it’s always to me the conventional thinking because, these are all disruptive and transformative by their nature, and just by definition the corporate antibodies as I call them, come out to try and stifle that, or resist it. That’s a kind of subconscious reaction versus ‘I’m not going to accept these things’, it’s very much a subconscious reaction.
Nobody says it explicitly, so that’s a good segue into where we’re at today, and where we’re going. If you think about the industrial sectors, manufacturing, energy, infrastructure, etc., it really hasn’t seen the kind of change or transformation that’s rocking retail and media, and even financial services, so what’s your thoughts on that, and how that evolves over the next decade. How will digital technology ultimately impact these industries, is it going to be an iterative incremental thing, improve a little bit of efficiency here, reliability there, or is there some transformative thing on the horizon?
To answer your question, I’d first like to bucket digital transformation into three distinctive areas at a metalevel, I think that’s important because this is a very uneven playing ground across the industry. So, we’re applying a lot of these new technologies, AI machine learning, additive robotics etc. into three areas.
- Every industry is trying to drive efficiency in productivity, that’s the first area within their cooperation’s.
- They’re being used to develop new product and services to grow their businesses, and to capture higher levels of value from their customers.
- One that’s emerging, companies responding to societal demands. Those include things like climate change, recycling of products etc. closed-loop economies.
So, I put it into three buckets, and I think digital technology is a key enabler of responding to each of those three areas. Then if you look across sectors, you’ll see there’s different responses, at different paths of their journey relative to each of those three areas. It’s very much an uneven playing ground.
Efficiency and productivity, the disruption is really coming from they’ve just got to drive that, and there’s good examples of where companies are doing well there. I think the new products and service areas will delve into that, I think this is a real challenge to build new products and new services around digital technology and make those grow rapidly relative to the disruption from start-ups and big tech companies.
Then I think potentially one of the bigger challenges is responding to these societal demands, in applying technology in a way that’s going to transform industry, whether it’s through a mission’s control, recycling etc.
Let’s key in on one of those, because that’s a particular interest to a lot of our customers and listeners, and that is around the area of products to services in digital products. It seems there’s been a lot of emphasis on that for a few years now, and a lot of companies are trying to move in that direction with limited progress. I know there are success stories out there, but there’s a lot of pilot projects, and we’ve tried this, but whether its resistance from the actual end customers, or the inability to transform their own organization, companies that are trying to turn products into services, and add digital services or not moving at the pace we thought a few years ago. Any thoughts on that?
I’ve got a lot of thoughts; it would take a few hours actually! But seriously, this is a really-really hard area for companies, and I think this is the area where the heavy industry is most open to disruption from that side. I don’t think they realize it, because I think heavy industry naturally thinks in an asset-heavy mentality, they own factories, mines, refineries, oil platforms, steel factories, etc. With digital production services they’re open to standard of asset-like models, so I think there’s a tremendous challenge for them.
I was at a Fortune Tech brainstorm in Aston last year, and one of the things I noticed was companies were lamenting how difficult it is to launch digitally based new products and services, so there’s tremendous challenges that they faced from within the organization, which I bucket them into traditional processes etc.
One of the things I say is, the mere ownership of these technologies is not enough. So, if you take 21st century technology, whether it’s AI machine learning, or whatever, and then apply a mindset business model, a business approach, a culture that’s 20th century, then you’ll fail. You’ve got to get both those things right, you’ve got to have the technology and the access to it, that’s easy. The second part is the really hard part, and unless you can marry those – and the danger for these industrial companies is you have two cohorts attacking them one industry at a time. Obviously, you have start-ups that are doing everything in the 21st century approach, and we know start-ups are really good at how to extract value out of the industry ecosystems and value chains.
But the second one, which is I think unique in this time is, you have companies that look and act like start-ups like in Amazon, that just have resources vastly superior to any industrial company, and also have a tolerance for experimentation, risking into products, and do something – throw away, so they act and behave in a 21st century manner, but they have the resources of massive companies, and that’s kind of unique in this day and age. So, I don’t see too many companies in the industrial space, I can talk about a couple of examples if you wish, that have successfully launched digitally based products and services into the market at scale. Again, we’re talking about the industrial sector, because there are other sectors where they have been.
It’s interesting you mention Amazon, because other players in the retail space, including quite large ones like Walmart, have cried foul in the rise of Amazon, because they weren’t measured or didn’t have to adhere to the same metrics that they did in terms of profitability etc. And of course, as you say, they get access to capital the way these traditional companies don’t. But that begs the question of course, when Amazon was much smaller, what were these other companies doing! That as their opportunity then to get out of the gate, but they waited until it was – not too late, they’re all still in the game, but it certainly has become much harder for them.
That leads to another question which as you know, you’ve worked with a wide range of major companies across a variety of industries, how would you describe the difference between organizations that have responded well to the threat of digital disruption, and those that have responded poorly? So, from a cultural and organisational point of view, what’s the difference?
That’s interesting. Companies are on different points of the journey, and I think needing that and visionaries versus early adopters etc. I think what I see is industrial companies, some are very visionary, but I think process that through the CEO and the leadership; you need to put in why you need to do this. I’ll use the analogue of safety would you believe, particularly when you’re talking about the sufficiency productivity part, safety used to be a safety departments job, and now it’s everyone’s job in every industry. The same with digital, I think the companies that are doing it successfully recognize that you don’t have a digital department at the end of the day, that ultimately you have to make digital part of your DNA, and therefore transform the whole organization.
So that realization has to happen at the leadership team. I think those companies that are doing better than others have that commitment and understanding at the leadership level. It’s kind of interesting, you can determine if companies are serious about this stuff, look at their boards, how many heavy industry companies have an innovation committee or a digital committee at the board level? You see this is quite common, and I recently did a panel discussion in Florence in Italy on energy, it was a global gathering of oil and gas leaders, and one woman on my panel she sits on the Board of Saudi Aremco, Baker Hughes, and Glaxo, and her thinking is that Glaxo has a Science & Innovation Committee with people that now their stuff sitting on that committee on the board, the other two companies don’t.
I think if you go around the industrial sector, the vast percentage of those companies do not have that, I think that just then ripples right through. If it’s not important to the board, how is it going to be important to the executive? It just kind of ripples through the organization, so I think those are markers that you have to put out. But having said that, there are companies and I’ll give you a couple of examples if you like?
I’m taking them on the buckets on the products that companies are doing, that have figured this out on the product and services… I’ll name it actually, so Exelon is one company, they again gas company, identified as one of the most innovative companies in the USA, and go through them for a utility. But they have spawned a multiple set of new growth businesses that are digital, they’re apps, around electrification, drone company, etc. They’ve recognized these will not thrive in the core business, so these are all spinouts housed in a different organization to Exelon as part of the innovation organization, but it allows them to hire more staff, hire risk, it’s all the metrics that a startup would allow to thrive, so it’s on the side of the business. I always call it insulated but connected, and that’s working quite well.
Baker Hughes is another example, a big oil services company and they’ve got things from additive manufacturing, to virtual reality, to digital predictive analytics products that they’ve done in partnership with C3.ai Tom Siebel’s company. They are all being spun out as separate individual companies, because recognize these digitally based new products and services will not thrive within their existing organization, because they’ll just throttle it.
So, they are two examples of how I think industrial companies need to think about new products and services. Another one which I think is interesting and you have some experience here is, I think through GE I’ve got a [inaudible 16:06] tattooed on my arm as well, but I think GE is two tales, the bookends of success and not such good success. I think on success I would say GE jet engines with the predictive analytics, so they’ve got a great bunch of predictive analytics and AI machine learning around jet engines. They changed the business model to charge by miles instead of CAPEX. So that’s just a shiny example.
I think GE Digital, and I’ve a lot of experience interacting with them over the last five years, I would say as an example of how not to do it right. I know GE is kind of the average safety net, but that’s a classic example of a nineties mentality being applied to a 21st century problem etc. etc. And that’s being redone now with the new leadership so that’s good. That’s that one.
Then I think you go into this kind of efficiency and productivity area. So, I think a couple of companies that I’ll pick out here, BP has done a really interesting job and applied AI machine learning, and other technologies into driving efficiency and productivity inside its business, as has Shell. What they’ve been able to achieve in the last 3 or 4 years has been quite staggering using AI machine learning, etc. to drive efficiency and cost reduction and production.
Another one is Anglo American which is a big mining company, and they have an innovation initiative called FutureSmart, for example they have a thing called The Intelligent Mine, and again that’s applying predictive analytics, AI and machine learning, into the environment to drive efficiency and productivity. So, those are some companies and examples.
Those are some great examples, and very interesting. Are they structured any differently than their competitors in terms of supporting innovation? I guess in general, is it even necessary to change how you’re structured as an organization to support innovation? Or is it simply doing what you do better?
That’s a really interesting question. I think innovation community, thinkers, have thought about this a lot, and I have a perspective. A lot of companies are like this, but industrial companies think a lot about organizations, and, ‘If I just get the organization right then it’s going to be fine’, and I think we need to look beyond organizations. To me that’s the lastthing you do, because I think it’s around culture and mindset and process. So, I think the dangers are that these companies don’t recognize that, so ‘If we just to digital team then we’ll be fine’, but they don’t actually think around how I change the mindset and culture of the company.
So, again I think the answer is different depending if you’re driving new digital productivity and efficiency within the business, versus developing new products and services. So a couple of things, first when you’re in the idea-investigation phase as we call it, when you have an idea for digital and you want to run a quick prototype pilot, that does need to be I think housed within an innovational organization, which is insulated but connected to the core business. But at some point, of that is working and works well, and will deliver value, then that needs to be transitioned and handed off to, if you like, the execution organization to drive the implementation and scaling within the business.
This is not an organizational design flaw, it’s a process flaw, a mindset flaw, as people get these hand-offs and transitions wrong. So, they have people that are doing ideas and investigation, which they live in the world of risk and ambiguity, they’ve let them stay with these ideas for too long for implementation, and that’s just not what they’re good at. Or vice versa, the people that are very risk-averse and drive implementation executors are given responsibility for these prototypes and pilots too early, and they don’t tolerate this kind of experimentation at the intuitive learning process. You could say that’s part of organizational design and process design.
The last area is, if you like, doing a cancellation is not one department’s job ultimately, but also it’s not every ones job at the beginning. One client of ours has used this used this term, ‘a permission slip’, how do you give a permission slip to everybody in the company, and everybody doesn’t have to take it, to be able to partake in this innovation, come up with ideas and really get engaged with the digital transformation going in the business. That’s one, and that’s probably the efficiency and productivity part.
The other one with new products and services, there’s exceptions here like GE with jet engines but I’m a total skeptic. I don’t believe it’s a strong thesis, always exceptions, but if I’m building a new business that is digitally orientated, I don’t think they can exist inside the four walls of an existing industrial company. I think what Exelon and Baker Hughes have done is recognized that to be the case, and to put those companies to the side and let them have their own management teams etc. Otherwise it’s going to be this WalmartJet.com situation, and they still may but this mitigates it to a degree which is, I get a fast-growing business, but eventually the corporation goes that you’re losing money, you need to turn a profit, and I always challenge them, ‘Do you want a small profitable company, or do you take the startup approach?’ Which is grab as much market as share as possible, the Amazon approach even, and just keep driving revenue.
I heard the Walmart CEO last year, again at this Fortune Conference, gave a public speech, how their ecommerce hasn’t had such a fantastic growth year, but now they’re under pressure to turn a profit, and I’m like, ‘If that was Amazon, it would be high-five, let’s put in another 100 million, or 200 hundred million’, and just after it. So that tension inside a big company tends to hold back these growth engines, and therefore then allows them to be exposed for disruption.
The last area is I think the muscle of partnering, so big corporations have to move more from just a transactional procurement approach they have with companies, particularly starts, and get into a much more strategic partnering approach. A lot of these things are going to be done in partnership of other people, and not just housed within your four walls, so that’s a different muscle. I’ve just put it down to culture, mindset, capability, and then this whole culture of experimentation, learning, iterative learning as I all it, and they say, ‘Fail fast, fail cheap’, method, and living with ambiguity. These are all kinds of skill that need to be embedded within components of the organization. I think industrial companies are really, really struggling with that, as are some other industries as well.
So, I’ll stop right there!
In some ways Peter it comes down to incentives, right? What are they, and how are incentives aligned in an organization for all of those things; whether it’s for partnering, whether it’s for running a side business that’s not immediately profitable and won’t be for a number of years? That’s not how the executives and members of the team are incentivized, which brings me to a point where you wrote in 2019 about some of the difficulties that these incumbents have and made a point about the role of shareholders in this. Can you elaborate on that, and talk a bit about where shareholders come in, in terms of their expectations in their role in this?
Sure. I find the term is no longer the innovators’ dilemma, I call it the incumbent right now, because it’s really got to a point now where the markets and the shareholders are setting an unfit table. We kind of alluded to this in the Walmart situation, look at all the industrial companies, their traditional shareholders are mainly in these companies of dividend yields, and if you look at the shareholders of somebody like Amazon, they’re more into equity growth. Even with Google and Microsoft, nobody’s there for dividends, they’re there for equity growth.
What we see therefore is the shareholders in the Amazons, and the Googles etc. have a high appetite for experimentation, they almost expect these companies to experiment on a lot of things, and potentially there’s billions of dollars in that process. The same tolerance does not exist for industrial companies, they expect no risk, they don’t expect heavy investment, they don’t expect experimentation and playing in the areas. So, the shareholders in the markets, one set of shareholders constrain the set of companies, and the other set of shareholders in the markets clearly allow almost unfettered innovation to occur.
Amazon made an announcement today which I think is at the core of this, we all know they set up these ghost stores, which are these cashless cashier-less stores where you just walk in and walk out. So, they set up three or four, probably the cost of those stores and the technology experimentation I would say is nine figures, that’s my guess. They announced today that they’ve figured out how to scale this, and now they’re making their whole cashier-less platform available to all companies, so they’re going to go out and market it.
I’m not sure that would happen in any industrial company, or even in retail, because that could have all gone pear-shaped, and Amazon would announce, ‘Oh well, we spent $300 million and it didn’t work. Onwards and forwards we go’. The market wouldn’t tolerate that within a traditional company, so I think it’s a big obstacle, and therefore I think the CO’s of industrial companies need to educate their shareholders more around innovation, that’s why we need innovation committees, or digital committees on boards, it’s all part of this approach of messaging upwards if you like.
It’s an interesting dilemma, that’s for sure. One of the biggest challenges Peter that many of these companies face, is we talk a lot specifically in the energy and industrial worlds about all the data they have. As you know very well, for many years providing software to the industry, there’s a ton of data in these organizations, but getting that data out and even sharing it more broadly internally; I used to joke as an analyst with clients that data moves faster outside of your organization than inside, but they’re getting that data out, and exposing it to a broader audience, both inside and outside the organization, is a challenge. What are your thoughts on this, and how do we overcome it?
That’s a really interesting topic. Let’s just use AI machine learning as that sandbox on this question if I may. I’ve bucketed it into two areas, one is how do I make my data accessible and useable, to whatever digital AI machine learning, and machines I’m going to have. Then I think a rising area that we’ve seen in some of our clients is the ownership of data, and where that data has been generated from. So, with accessible and useable, we all know, and I would say AI machine learning is in its third or fourth iteration, we used to call it decision and support in the software industry, and then we went into business intelligence.
The software company I was with in the late nineties, if we were working with neural network agents embedded on the edge of routers, and how to work with the utility industry to make decisions on the edge, to do remedial action and then send the data back up to the central system. But that was fraught with problems because you couldn’t get the processing power on the edge back in the late nineties, the network pipes weren’t big enough to take the data, so this is not new. The challenge then as it is now, I have vast amounts of data, how do I normalize and standardize that data in a way that’s useable uniformly. Because you have these stovepipes with data in different formats, and different generation systems, and there’s a lot of articles I know, that talk about 80 percent of the effort and the expense of getting to true AI machine learning, is getting my data ready to be used.
I don’t think companies recognize the enormous effort, and this is where my IT infrastructure becomes an impediment to progress, which actually becomes another risk if you like, or exposure industrial companies have to potential to destruct edibility to deliver new products and services. So, that’s one.
The other one I find fascinating, is the ownership of data. Some companies I’ve spoken to, there are battles and this happens in autonomy, it can’t be many companies, but for example if data has been generated by machines that are owned by one company, and being used by another company, the company that owns the machines claims ownership of the data that those machines are producing, even though the customer owns the machine. Then once the charge gives swathes of money to the user to have access to its own data, and I know that’s a huge tension in a lot of relationships. The reason this is happening is because the OAM of the machines knows that its future’s in digital, and I think wrongfully thinks it has to own the data to make that happen, because everyone wants to deliver these new products and services. The user goes, ‘Well, I need to drive efficiency and productivity in my system’, or, ‘I need access to this data. I’m not going to pay for it, it’s data that my business is generating’.
So that ownership, I think it’s going to be a rising area of tension between industrial companies, as we go forward into the future. I think we’re seeing elements of that, and I can see the rationale and motivation for both sides of that equation, but it’s pretty hard to say if I’m generating data even though on your machine, you own it and then you’re going to make me pay for it twice. I’m not sure of that, that’s like saying IBM would say, ‘All the data that’s coming out of my servers, I own that data even though you own the server. You have to pay for that’.
Interesting to see how it plays out. There may be a big role for lawyers in all of this, right?
There are always lawyers!
Exactly. Let’s wrap this up by pulling out your crystal ball again, in terms of where we started, and get back to earth, and spend a few minutes to summarize what the next decade looks like for the energy mining infrastructure sectors. Is there a worse case and a best case for the existing players in the industry? When you think about it, 2030 is only a decade away and a lot is going to happen between now and then, the pace of change is not going to slow down as you and I both know, so what’s your view of how things are going to play out over the next 10 years?
I think it’s an exciting time personally. I want to predict, actually I will predict, I’ll be like a weather forecaster, ‘It’s 50/50’. This is not about industrial companies going out of business, I feel that in most industrial sectors, the most valuable companies in most sectors in 10 years… that actually most of them don’t exist today, that’s a prediction, and there’s a difference in valuable company. Those valuable companies will probably be companies that are asset light, companies that have figured out how to extract value from the value chain without owning the assets. But I think in all the industrial sector some of the characteristics that we’ll see in the next 10 years, we see some of that already in manufacturing business. I think most functions, and energy, mining, and heavy industries sector will be done largely without people.
So, I think the emergence of heavy use of robotics which we do see in auto manufacturing, but I think will be ubiquitous across most of these sectors, and a lot of its going to be driven by AI machine learning platforms, that allow pretty sophisticated decision-making. So, whether it’s an oil platform, a mine, or a steel mill, I don’t think there’s going to be a lot of people running around in any of these facilities. I think we’re going to see much higher rates of productivity and efficiency as a result of that, so whether it’s just the economic output of these facilities will go up exponentially potentially, and I think conversely the amount of energy, water and other resources they use to produce that I think will be reduced significantly. So, I think there’s an enormous opportunity for innovation, particularly digital.
The other area is, I call ‘Small is the next big’. So, I think one of the opportunities whether its additive manufacturing or whatever, is scale is no longer going to be an advantage, because I can do everything in a microscale because of technology. We’ve seen that in mining, we’ve seen some emergency technology where you have… they call it swarm mining, where you have little robots that are swarm mining, all being coordinated, and again that’s a kind of combination of autonomy, AI machine learning, and robotics all working together, which creates these small-scale situations. I think small being the new big is a really interesting area that may emerge.
Then finally additive is huge, and I don’t know if you know a company called Rocket Lab, it’s a New Zealand company, it’s always advertised that it’s sending out micro satellites. It’s a company that has built a rocket using advance materials and patents from Americas Cup boats, it 3D prints the engines, and it’s not into satellites like SpaceX’s, they’re disposable satellites. They launch generally 2 or 3 million… dedicated launch I think they did one for the NSA recently, I think 7 million all-in to launch these micro-satellites. So, there’s an example of a company that’s not only manufacturing and launching, it’s a digital make of company using advanced technology to innovate in space, in ways we hadn’t even imagined five years ago. It’s based in Southern California, a very unique company, as an example of where I think the world is going.
Yeah, taking people out, very interesting. Of course, as you know, it doesn’t just improve effectiveness and efficiency, it also will ultimately improve reliability, safety, and sustainability, in other words minimize the environmental impact.
Typically, in these things Peter, if you could share what you’re reading or what you’ve read recently which you think would be interesting to our audience, it doesn’t have to be on the subject du jour, but whatever you think is interesting, then that would be valuable to them.
I’ll do three things. It’s kind of interesting, on the topic I think there is actually not a lot to read, and here’s why I say this for industrial companies, because everything that’s written is largely written about technology companies, and I always tell industrial companies, ‘Do not look at the Amazons of the world for inspiration’, these are digital companies, they’re digital transformation, and destructive innovation is in their DNA. I think what happens is, too many people pedal the technology industry examples as things that forward for industrial companies. I think it is doing a negative service for those companies.
So, one book that I would recommend is Thomas Siebel who I met recently. He’s written a book, ‘Digital Transformation, Survive and Thrive in an era of Mass Extinction’, he is coming at that from more of a non-tech industry sort of example, so C3ai’s one of the leaders in the series, so that’s a book I would recommend, that’s very focused on the area that we’ve just talked about. I would discourage people from reading books about technology industry, that use the technology industry as the examples for digital transformation. I think you will get depressed, and I think the applicability is not there.
A second book that I would recommend which has nothing to do with digital transformation, is a book I’ve just recently read called, ‘The Choice’, which is by Dr Edith Eger, this is kind of relevant, it’s how do we free ourselves from the prison of our minds, because we have a choice. Dr Edith Eger is a psychologist who works with trauma, she’s one of the top in the US. I think The Choice is interesting, how we make choices in life, I think it has both a personal and professional reflection.
Then just on a newsletter basis, I really like some of the AXIOS newsletters that come out, Pro Rata podcast is another one which is really good, very fast paced thinking around digital and that’s more practical. So those are my non-callout, and callout.
Great, those are great, some very diverse suggestions there, and I’m sure valuable reading. Great, thank you very much, it’s been a very interesting and informative conversation, and I appreciate you taking the time today.
Thank you very much, and I really appreciate the opportunity. Thank you.