Strategizing for 2027 and Beyond: Benchmarking Your Innovation Investment

Anthony Schiavo: Hello and welcome to the webinar, Strategizing for 2027 and Beyond, Part 1: Benchmarking Your Innovation Investment. My name is Anthony Schiavo. I’m the Senior Director and a Principal Analyst here at Lux Research, and I will be moderating today’s session.

Presenting today is my colleague, Dr. Arij van Berkel. He is the Chief Product Officer here at Lux. Throughout this webinar, you can type any questions you have into the box on your screen. Time permitting, we will answer all the questions that we can. If your question does not get answered, please do not hesitate to email it to [email protected] and we will respond.

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Before we start the webinar, a quick word about who we are. Lux Research helps organizations make more confident innovation decisions about what matters next. As an independent research and advisory firm, we work with many of the world’s leading companies to identify emerging opportunities, evaluate technologies, and make high-impact innovation decisions.

Our scientists, engineers, analysts, and industry experts combine original research and methodologies with practical decision frameworks to help organizations separate signal from noise. Every day, we help our clients answer three critical questions: Where should we focus our innovation efforts? Which technologies deserve investment? And which partners can accelerate innovation?

Today’s webinar is an opportunity to share some of that thinking with you. With that, I want to hand it over to Dr. van Berkel.

Arij van Berkel: Yes, thank you, Anthony, and welcome, everyone. I’m very happy to be here and present this webinar to you. This is a series of two webinars. Some of you may remember that we did a similar series last year around this time, focused on a couple of topics that are of interest to you, or should be of interest to you, as you’re getting ready and planning for next year. I don’t know about any of your particular situations, but back when I had P&L responsibility for a big project portfolio at my former company, one of the things that always struck me was that CFOs are completely out of sync with the rest of the world in terms of vacations. In summer, they are diligently working; around Christmas, they are also diligently working: around Christmas to close out the year, and in summer to prepare the budget for next year. So I would come back from vacation to find lots of spreadsheets in my mailbox requesting inputs for the budget for next year. Then I had to make decisions, of course: Do I want to make changes in my budget? What kind of shifts do I want to make? And that, of course, should also be based on your strategy. So today, we’re going to look at benchmarking your innovation and, more particularly, benchmarking your innovation inputs. Are you doing enough innovation, and are you doing innovation in the right areas? We’ll talk about what I mean by areas in a moment. Part two, which will come up in about a month, is about outputs. It’s all fine if you have calibrated your inputs and if you’re right that, at least, you’re running the system and it has enough money and resources and the right people in it. But then, of course, is it also producing, and how do you know? That’s for later. Today is about inputs, and you have to do both. Don’t just focus on the outputs. That is not useful unless you have a clear view of the inputs in your innovation system. That’s what we’re going to talk about today, and what I want to give you a good framework for today. We start by realizing that innovation is, for a large part, about rowing against the stream. Since we were talking about vacation, this year, as in any year during vacation, I took some quality literature. Sometimes it’s fiction. This time, I reread Peter Drucker’s main book, The Practice of Management, which I had already read about eight years ago. Of course, there’s this famous quote in The Practice of Management, quite near the start: Any business enterprise has two, and only two, basic functions: marketing and innovation. Of course, I work at Lux, so I really like this quote because we provide services to the two main functions in any company. Those two main functions are marketing and innovation. But what does it really mean? Why does he say this? We all know that a business enterprise has many other functions. So why are they not basic functions? There’s manufacturing. That’s important: If you want to sell something, you probably need to make it first. There’s trading, human resources, and all sorts of functions. You can envision any organization that manufactures something, has a way of selling it, keeps the organization going, and maintains it in a continuous fashion to continue doing that year after year. That organization, if it doesn’t also try to expand its market and evolve the product it’s offering, is not a business enterprise. And there are organizations like that. We can have a debate about it, but take a university or a school. It’s not a business enterprise. One might argue that they do innovate and respond to changing demands, but they don’t innovate the product as a course of business. It’s not their basic function. Similarly, governments are not business enterprises. If you have a business enterprise, you need to innovate. The issue, of course, is that everyone else is doing the same, and that means you have to have a certain level of innovation just to keep up. We’ll talk about this in part two as well, when we’re looking at outputs, because the assumption that innovation should lead to growth is not a correct assumption. The assumption should be that the first function of innovation is to prevent your business from shrinking and to maintain your business. If you don’t innovate, then your business just goes backward and you lose business. Of course, innovation should also enable growth. So when looking at growth and innovation, you also have to be clear about how you’re organized to innovate. That’s what we’re talking about today. Just as an example, this is something that we did a couple of years ago. We looked at all of the annual reports of Volkswagen Group. Why Volkswagen Group? I think it’s a good example of a good industrial company with a very stable product portfolio, and they also digitized all of their annual reports. So it’s a very good subject for analysis. We looked at capital intensity and R&D intensity. Both are defined as capital spending, or spending on R&D, divided by gross sales in that year. You can see that R&D intensity was not even reported until the mid-1970s. Capital intensity was high and then diminished. This is, of course, the effect of just-in-time operations and a lot of outsourcing. Here, you can actually see what Peter Drucker was trying to say. Manufacturing cars is not a basic function. Of course, it has to happen; it is a necessary function. But if you can outsource a lot, that is actually beneficial. On the other hand, R&D intensity has risen over time. As R&D intensity has risen, the product life cycle has decreased. This is the Volkswagen Golf: Between the Mark 1 and Mark 2, there were 10 years. Then to the Mark 3, it was nine years; then eight, six, five, and four. You can see how the product life cycle is diminishing. Products need to be refreshed, your product portfolio needs to be refreshed faster, and that is in line with R&D intensity. So R&D intensity and product life cycle are somehow connected. That is a good clue, and this is where we’re getting into whether you’re spending enough on innovation, and how you know how much is enough. There’s a clue here about the link between R&D intensity and your product life cycle. Comparing R&D intensity and knowing how you compare to other companies in your general ecosystem is very difficult to do, and we’ll see how difficult it is in a moment because I don’t have a full solution for it. But I have a couple of thoughts that will help you make a fair and defensible comparison here. First, you need to look at your baseline by industry. The picture I’m showing here is R&D expenditure in thousands of U.S. dollars per full-time-equivalent employee. Why am I showing this? In the rest of this presentation, I will show R&D intensity as it is usually done, which is R&D expenditure divided by gross sales, as a percentage of gross sales or gross revenue. Here, I’m showing it per employee. First, it gives good numbers that are relatively easy to remember, and it gives you a basic idea of the magnitude. For medical equipment, the median is about $24,000 per full-time equivalent. The 15th percentile shows that 15% of companies in medical equipment are spending less than $8,500 per FTE. The dark bar is the 50th percentile. Employment is a little less whimsical than sales, and that’s why I like this number. I won’t use it in the rest of the presentation because it’s not how it’s commonly shown, and I want to leave you with some numbers that you can refer to and see in other reports as well. But sales can be very noisy. Sales may be high one year and lower another year, whereas R&D expenditure is often tied to the size of your R&D organization, which is not so dynamic. So using a number like this, comparing it in dollars per full-time equivalent, is a bit steadier and gives you a better idea of what a normal average number should be. If you’re at the median and you’re, say, in specialty chemicals, you should expect to spend roughly $12,500 per employee. It’s interesting how—and this is slightly counterintuitive—commodity chemicals looks like it has a higher R&D intensity than specialty chemicals. That’s counterintuitive, and if you compare it to sales, you will see that that’s not, in fact, true. However, you need to keep in mind that commodity chemicals is quite labor-extensive. There are not a lot of people employed in the commodity chemicals business compared to specialty chemicals, which is more labor-intensive. So there’s a downside to expressing it like this as well. I just want to leave you with these numbers as a first benchmark. The fact that different industries have different R&D intensity base levels correlates quite well with product life cycle. If you look at this, you can see R&D intensity in the common definition. So now it’s R&D expenditure divided by sales. You can see how R&D intensity increases as the product refresh rate, which is one divided by the product life cycle, increases. The refresh rate is a kind of frequency; the unit is one per year. So if you have a refresh rate of 0.3, it means that, on average, you rejuvenate or change your product portfolio every three years. If we look at car OEMs over here, they’re at about 0.25, roughly every four years. Car manufacturers need to bring a new model to market for all of their cars and all of their models. So R&D intensity correlates well with product refresh rates, or with the inverse of product life cycle. If you have to change your products faster, you need more R&D. That’s the mechanism behind why different sectors have different intensities. Of course, there’s also something inherent to the product. In biotechnology and pharmaceuticals, things go really fast and are very knowledge-intensive. Oil and gas doesn’t need a lot of R&D intensity because the product is quite stable. It has been the same fuels for quite a while. The other thing to note is that larger companies tend to invest less. This was also remarked on by Schumpeter, and it’s actually true. You can see it in the data. For oil and gas, it is less pronounced, so I think for oil and gas companies, that is not entirely true and not good guidance. But for most other sectors, you can see that as the company becomes bigger, R&D intensity decreases. Of course, because the company is bigger and sales are bigger, they still spend more on R&D in absolute terms than small companies. It is also quite nice to note that in the extreme case of a startup, where firm size is basically zero in terms of revenue, R&D intensity goes to 100%. So even mathematically, the limiting case supports this. What does it mean? How can you benchmark whether you’re doing enough? You can look at your sector, you can look at your sector median, which is shown here, and you can correct for company size if that’s important in your environment. Then, within a sector, you can once again look at product refresh rate and your R&D intensity normalized for your company size. You can see something like this. I’m showing just one picture. This is for specialty chemicals. You can see that there’s still a mild dependence on product refresh rate. If you, as a company, want to change your product portfolio faster than your peers, you will need to spend a bit more money. Where things get interesting now is with the line that you see here. This is where we get back to rowing against the stream. We distinguish between two types of innovation. One type we call operational innovation. This is the rowing-against-the-stream part. In operational innovation, you’re doing innovation just to keep up with your product portfolio. So this is Volkswagen, which knows it has to release a new product regularly. It used to be once every 10 years, and now it’s once every four years. They have to release a new product, and to do that, they need innovation and they need to invest in R&D. They need to add new features to the car in a regular rhythm. Operational innovation is required. It’s not optional. If you don’t do it, you will simply lose revenue over time. It has hard milestones. There’s no wiggle room. You have to release that new model. Maybe you can postpone it by three months, but that’s already creating uncertainty in the market. It’s also market-driven, so even the timelines are not optional for you. If your competitors decide to go faster, then you basically have no option. Some people think it’s incremental innovation, but that’s not always true. It could mean that you have to add entirely new, non-incremental things to your product. To stick with car manufacturers, at some point, they had to add things like airbags or catalytic converters to the car. Those were alien things to the industry. They did not necessarily have the required knowledge or even the people who could do that in-house. So this was clearly a non-incremental innovation but still pertinent to the current product portfolio. If you want to measure operational innovation, you have to measure it in the same way that you do manufacturing. It’s about efficiency, delivering on time, and quality. That is what you need to measure for operational innovation. For expansive innovation—and this is expansive with an A, so it’s about expanding your business—that is much more of an investment proposition. This is where you aim for company growth. In operational innovation, you can aim for growing your market share, of course, so you can try to make that about growth as well. The minimum requirement there is that you maintain your position. Expansive innovation is where you try to grow. This is optional. There are companies that don’t feel the need to do this; they grow in other ways. They grow through mergers and acquisitions, for example, or they don’t grow. This is still time-sensitive. You need to grab the opportunity when it arises, but usually the deadlines are not as fixed as with operational innovation. This can be incremental innovation. For example, you make an incremental change to a product to make it suitable for an entirely different market all of a sudden. That is entirely possible, but very often it’s also disruptive or transformational. Success here is measured using investment metrics. It’s like investing in another business or, for that matter, investing in a startup. If you look at that and if you look at this picture, where you see a minimum line, you can see that this orange line here is the minimum that most companies get away with. This is the 20th percentile line. So 20% of companies invest this much or less and apparently are getting away with it. We don’t go to the absolute bare minimum, like the fifth percentile line or something like that, because we need to allow for the possibility that some of these companies actually made a mistake and are not actually getting away with it. But you can say that the 20th percentile line is a safe line. This line sort of characterizes what you can get away with in terms of operational innovation. Everyone above this line is either not being efficient or has decided to spend a lot on expansive innovation, above and beyond the operational bit, which is not optional, to do a lot of optional innovation as well. So what does that amount to? How does it work out? For different sectors calculated in this way, you can see the median share of expansive innovation here. For heavy equipment and building machinery, it can be up to 60%. I doubt that’s all expansive innovation. This is also sometimes because some of that equipment is much more complicated than other equipment. So I expect that in this sector, there is a lot of variability. Let’s move up to oil and gas. For oil and gas producers, it’s about 55% expansive innovation, and in my experience, that sounds about right. Oil and gas companies do look around a lot, and they do look at things like renewable energy, or they invest in additional chemical capabilities. They have a very wide view outside the remit of their own product portfolio. You can see all the others here. I won’t go into every one, but if you would like to discuss any of these bars with us, then, of course, we’re more than happy to jump on a call with you and discuss. So if you do all that—look at your sector, look at your portfolio, differentiate between operational and expansive innovation, look at how much you invest in each, and then compare that to your peers, size-adjusted if possible—then you have a good idea of where you are. Are you spending enough on innovation? Are you supposedly spending a lot on expansive innovation, but you find it hard to figure out what exactly those projects are? Maybe there are some efficiency gains to make. You can get all that from doing an analysis like this. But then the question is: How and where are you actually spending all of this? What is the machinery? What is the engine—your innovation engine? What does it look like, and is it fit for purpose? For us, when we’re looking at the innovation engine, we tend to look at the components of the engine first. So how complete is your engine? Here, you can see that you can act on three horizons. I’m assuming everyone is pretty familiar with the horizon model. Horizon one is your core activity, really focusing on your core products and markets, which could still be expansive innovation if you develop additional products for the same market, for example. Horizon two is about adjacencies, and horizon three is really transformational, usually involving long-term investments. Across those horizons, there are three basic modes of operation, or modes of innovation, that you can deploy. One is building, another is partnering, and then you can invest. You can see, for each of these, the kind of activity and the kind of departments or units that will do that. If you’re building on horizon one, typically that’s your division or business unit R&D doing that. On horizon two, it tends to be your corporate R&D, and on horizon three, it’s still corporate R&D, and sometimes you also have incubators there. For partnering, horizon one might mean you’re partnering with a supplier or with a customer, or you’re doing some co-creation, maybe with an adjacent business as well. In horizon two, you might be running innovation challenges or accelerator programs, something like Shell’s GameChanger, for example. On horizon three, you may have structural university alliances or work with an institute, something like A*STAR, Battelle Labs, or Fraunhofer. On investment, it is the same thing. Horizon one could be mergers and acquisitions, mostly driven from the business unit, so immediately tied to your current products. Horizon two may be more strategic venture investments or establishing joint ventures, for example. DSM has a rich history of creating joint ventures, which were all horizon-two-ish. Horizon three may be much more corporate venture capital, for example. So which one of these units do you have? As it says here, how complete is your innovation engine? I was hesitating on the word complete because complete doesn’t mean that you need to have all of these units. This is your menu, but complete means that you have the elements from the menu that you believe you need. So if you don’t think you have a need for CVC, or if you don’t even think you have a need for anything on horizon three, that is a strategic decision by you and your company. If you don’t need it, then a complete innovation engine might be just these first six blocks. Or if you think you can do without any investment activity, fair enough. That is a decision; this is not a prescription. This is only one part of it. The other part is whether your engine is actually running. So there, we look at how you are managing things through these blocks. For example, can developments graduate from horizon three to horizon two? Do you have activities in horizon three where, at one point, you say, we need to move this to another mode of working? We’ve explored it, we’ve done the broad research, we’ve done the university collaboration. Now we need to take this development and move it to horizon two, which means we are going to involve our business units, maybe, and we’re going to involve our strategic business development. Do you have a way of describing how that process works? If you don’t, you score low, obviously. If it’s ad hoc and you have one or two examples but no process, then you score a bit higher. If it’s well defined, but you don’t really have any examples to show that whatever you defined works, then, of course, you score a bit higher, but still not high. Then, of course, you have managed and optimized. The other elements here are scale-up, so moving from horizon two to horizon one, and integrating. Can you take something external, like a startup, and have you shown success in taking the startup and integrating it into your own operations? Something that’s often neglected is spinouts. Can you take internal, no-longer-relevant developments, or maybe even serendipitous developments—where you happen to develop something but you really have no use for it—and are you effective in spinning that out? Do you have a licensing business, or do you have a spinout or startup incubator or something? And then, are you able to steer? Do you have enough influence on your ecosystem to move your ecosystem or change your ecosystem in a desired direction? And are you able to sense? Can you sense changes in your ecosystem and respond to them? Does a changing ecosystem affect your planning for innovation? We’ve done this analysis for quite a few companies, and I’m showing a couple of those results here. I’m not showing the actual companies. Throughout this presentation, I’m not showing company names, and that is very much on purpose. Benchmarking is a sensitive activity, and the results should be discussed, not simply thrown out there. So you won’t see us showing a big picture with company A here and company B over there, because that is not useful for anyone, and it’s prone to a lot of debate that is not productive. You need to look at where you are and then consider where you need to be. The purpose isn’t for everyone to be in the top-right corner of this chart. The purpose is to be in the place where you should be, which is appropriate for your investments, your innovation efforts, and your innovation targets. That’s what this is about. You can see here how energy companies, chemical companies, and industrial technology companies—the likes of ABB, GE, and Siemens—fit on here. So what does it mean while you’re preparing for 2027? We’ll get to the outputs in part two, but meanwhile, get grounded in both how much you’re spending and how you’re spending compared to your peers, and in how you’re organized. You need to differentiate between operational and expansive innovation. Compare that to your peers in the way that I described, normalized to your sector and, if possible, to your company size, and decide if that is a reasonable investment and a reasonable distribution. Is the split between operational and expansive innovation as you found it in your portfolio on par with what everyone else is doing? Or maybe you’re being inefficient; maybe you’re spending too little on operational innovation, or you’re falling behind without noticing it yet because you only notice that you’re falling behind on operational innovation after one or two product life cycles. So if your product life cycle is three years, you will notice after about five years that you’ve been doing not enough, which, of course, is too late. Now look at your organizations. Do you have all the functions that you need? Are those functions right-sized? Are the ratios between those functions as you like them? And do you find evidence of a flow between those different functions? Is that working? Then set your priorities. What changes do you want to make next year? Maybe you don’t want to make changes. Good. As long as that’s a conscious decision—that you think everything is fine and you’re doing well—don’t change a winning team. Good. As long as that’s a decision and not an automatism. Then look at what products you want to prioritize for your operational innovation and where you see opportunities for expansive innovation. With that, we’ll conclude this first part. I’ll leave it to my esteemed colleague to see if there have been any questions. Probably not.

Anthony Schiavo: Yeah.

Arij van Berkel: Quite clear, right?

Anthony Schiavo: Everything was clear. There are no questions. Now, thank you so much. We will be taking questions. There are a few questions. Again, if you have questions, you can type them into the questions box. If we don’t get to your question on this call, someone will be in touch after the webinar.

I do want to be a little sensitive to time here, but I do want to get to at least one or two questions. So there are a number of questions here about some of the specific innovation approaches, things like CVC, for example, that you touched on.

But I think another category of questions I’m seeing is more about how we operationalize this. If you’re an innovation leader, you maybe don’t have all of the capacity to make these kinds of structural changes, or at least not make them quickly. So do you have any thoughts about what people can do maybe in the next six months, or the remaining period of this year, and how they can take some of this and operationalize it in a more immediate, on-the-ground sense?

Arij van Berkel: Yeah, I think that the quickest win, if you’re talking about operationalizing, where people mostly have opportunities, is really to look at the flow between the different elements of your existing innovation organization.

Adding an element, or for that matter removing an element, is a lot more work. If you don’t have a CVC and you say, as the Chief Innovation Officer, we should really have a CVC arm, that is going to take you a year to organize because you need to get the whole senior leadership of your company behind it.

Then you need to start creating a CVC. You probably want to start as an LP of a venture capital fund, so you’ve learned the ropes a little bit. That’s a way to get started quickly. But maybe there is no venture capital fund that is aligned with your interests. So there are a lot of things to do there.

However, if you look at your existing elements—so you have business unit R&D and you have corporate R&D—how are they working together? Do you find evidence of developments or projects that get handed over from corporate to business units? Do you not find that evidence? Why is that? This is where you can quickly operationalize a lot of things.

So focus on the flows first. Once the flows are working, it will also become evident quite quickly if you are missing one of those elements, where you say, “Well, someone is ready to receive something, but nobody is creating the thing to receive.” I would say that to operationalize quickly, focus on the flows.

Anthony Schiavo: On this point about flows, we have a couple of questions here. I think they’re related to one of the themes that we’ve pointed out, which is that it’s gotten more difficult, or at least the perception of innovation has gotten more difficult.

We showed a slide from our most recent innovator survey webinar, and the perception of difficulty has gotten a lot higher, especially in the last few years. So do you think that that’s because these flows are getting more challenging to manage, i.e., it’s more difficult to hand off, as you’re describing? Is that purely external? How do you think about this sort of increased difficulty that we’re seeing?

Arij van Berkel: So there are a few things here. One is—and I cannot stress this enough—it’s about managing the perception of innovation, which has, in my view, been too much about innovation as a growth engine.

Innovation is a growth engine, make no mistake, so that is not untrue. But there is a baseline where innovation is a not-shrinking engine, and you have to acknowledge that baseline. There is a certain amount of innovation you’re doing just so that your company doesn’t become smaller. Once you’ve dealt with that, you can start to do innovation so that your company becomes bigger. That depends on your competitive environment. So that’s just level-setting the expectations.

Now, about the complexity of those flows, I think there’s definitely an acceleration in the types of changes in the skill sets that you need to deal with innovations. I’ve talked about the car industry, which suddenly had to use catalytic converters and airbags. Those are chemical devices. At the time, the industry employed mechanical engineers almost exclusively, with a couple of electrical engineers. They had no skill set whatsoever to deal with catalysts.

So they had to not only develop that system quickly, within five years, but also, within that same time span, become proficient in developing that system. That was five years. Now I think that, for a lot of new developments, you have about two or three years to become really good at it from zero and implement it in a product.

Flows have not become more complicated, but they have become tremendously accelerated, and that requires that they become much more integrated. The handover needs to be much smoother to keep up with that kind of speed.

Anthony Schiavo: All right, well, that is going to conclude our webinar for today. The slide presentation and the recording from this webinar will be sent to all attendees via email today.

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