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Money isn’t the key to successful innovation. In fact, many companies spend far less than their competitors on R&D to achieve far better performance. To learn why that’s the case, strategy+business and Knowledge@Wharton spoke with Kevin Dehoff, a partner at Booz & Company, and Karl Ulrich, Wharton professor of operations and information management. In this first part of a three-part series, Dehoff and Ulrich discuss the relationship between spending on innovation and corporate performance, how projects are valued in a portfolio, and the importance of screening opportunities.
T R A N S C R I P T :
strategy+business: Kevin, talk about the connection between the amount of money companies spend on innovation and their financial performance.
Kevin Dehoff: We’ve [looked at] some of the relationships between corporate spending and performance over the last three years as part of our Innovation 1000 study. Probably the most fundamental conclusion that we came to is that we just could not find a direct relationship between spending and performance. So what that really meant was that this notion — that by spending more we can assure ourselves of a higher level of performance —was something that we just didn’t find. That had ramifications for a lot of the companies that we work with, in terms of our consulting services.
What we did find is that it’s much more important where you place your bets in terms of new products and technology, and how effectively and how efficiently you manage the R&D function itself. The companies that really stood out in the studies we have done are those that have been really focused on building capabilities across the entire innovation value stream — capabilities in areas like ideation, portfolio management, product development, and commercialization. It was much more about the capabilities that a company has and how efficiently and effectively they manage the R&D process, as opposed to how much they spend.
Karl Ulrich: Let me add a couple things to that. I’ve looked at the Booz & Company study and it is fascinating. And just to give a specific example: Apple Computer, if you were to look at the computer industry, is at the top or near the top in revenue growth and profit growth, and they’re in about the middle in R&D spending. So that is an example of a firm that is managing to get a lot out of its R&D efforts without spending very much money relative to the industry as a whole.
When you think about why that might be, one of the reasons is that it manages to find a set of very rich opportunities to make investments in. And if you think about taking a given set of opportunities that you have as a firm and just spending more money, you’re likely to not have a very good return because you’ll be spending on opportunities that are marginal, that aren’t so good. And so what I would add to Kevin’s explanation for the phenomenon is that generating more and better opportunities is a way to increase financial performance without necessarily increasing the amount you spend.
Dehoff: This is an issue that corporate executives really struggle with. In some cases, it’s a bit of a “black box,” right? They are under pressure to grow the business, to increase profitability, to improve return on investments. But they’re really unsure as to [the question]: “Should I be spending more or should I be spending less?” There are internal advocacy groups, and so the natural inclination is that “more is better” and at some point there are diminishing returns. You really want to have a process to focus on those projects where you are going to get the highest returns. And that’s why it is so important to have the processes and capabilities which enable you to do that.
Knowledge@Wharton: With R&D spending accelerating, what would you advise companies to do? If my competitors are spending more, I might feel compelled to keep up, for instance.
Dehoff: Yes, what we found — again in our most recent study with Innovation 1000 — was a focus on two things. One is just how important it is to ensure that your business strategy is aligned with the innovation model — that is, you are able to understand where the value is in terms of sources of innovation in the industry in which you are competing and that’s aligned in a way that you can ensure you can capture that value.
The second thing is also pretty fundamental. It’s around the connection with the customer. What we found is that those companies that have direct interactions, direct connections with their customers, [that] are engaged with customers throughout the entire innovation process, throughout the entire product development process — we actually found had higher rates of performance. And the importance of that interaction with customers is one of the things that really stands out in terms of where to focus.
Ulrich: Let me add something on that as well. I think the way that question is framed might not even be the right way to think about it. I think best practice would be to look at investment opportunities in innovation alongside other kinds of investment opportunities you would have in the firm. And calling it R&D spending, or tracking R&D spending, I think is probably the wrong way to think about it.
You want to say, “I have this project — we can call it an innovation project — but I have this project where I need to invest $15 million, but I think that it’s going to give me a 5X return.” That project ought to be looked at alongside maybe a plant and equipment proposal that would have a similar kind of return. The only time you run into difficulty in thinking about it that way is when you are looking at what I might call the “far horizon opportunities” that are sometimes very hard to analyze in financial terms. And then it might make sense to have a bucket or a budget for the whole portfolio of “far horizon opportunities” and to look at budgeting how much you invest in that category of activity.
Dehoff: I think that’s a really good point, because we also found that it’s not just about the R&D investment itself. In fact, we found that these are inherently cross-functional kinds of things. While the investment in R&D or an investment in technology is important, you need to think about it in the context of the fact that what is going to make or break these things is the marketing and the commercialization of that product and those sorts of things as well.
So, you really do need to think about it holistically. And if you just think about it in the context of R&D, well, yeah we can design a better mousetrap, but there’s no guarantee that’s going to be successful if we don’t think about it in the context of the cross-functional interactions and what it really takes to successfully commercialize a new product or a new innovation.
strategy+business: How do you value these projects in a portfolio?
Ulrich: Well, let’s take the simplest way you could do it. The simplest way to value projects in a portfolio is just to add them up. So, if you have 10 projects and you can do a financial analysis on each one — and in business school we would teach you to do a net present value, some kind of financial valuation of those projects — the simplest thing you can do is just add them up.
That’s worth doing, but it fails in two basic ways. One is that there are certain kinds of projects that have — and I’ll use an academic term — have a sub-additive payoff. It means that they don’t strictly add up. A good example of that would be if you are Merck and you are developing a new drug for diabetes. You might have two molecular compounds that both target the same biological mechanism and you really wouldn’t want to add up the value of those two separate projects because you aren’t going to launch two diabetes drugs.
You really have to look at those two projects together and say, “What’s the value we expect from pursuing these two projects together, in terms of how likely we are to get a product to the market?” That’s one failure in the approach of just adding up the projects in a portfolio. The other failure you get is that, coming back to this idea of “far horizon opportunities,” you aren’t going to be able to do the analysis for certain kinds of projects, projects that are very exploratory in nature.
Even if you were to do the analysis, what you’d really have to do is think of that project in terms of an option on the future, an option for future possibilities. And that’s not usually something you can analyze formally. It tends to have to be a more qualitative assessment — “What kinds of opportunities would this project provide for us in the future?”— not strictly, “What’s the present value of that project?”
Dehoff: Another sort of failure mode we have found for many of our clients, this whole notion of the business case is often static as opposed to dynamic. That leads to a phenomenon we call “Ballistic R&D.” This is where once a project gets in the pipeline it is going to be forced through the pipeline as opposed to recognizing that, particularly for some of the longer-cycle development efforts, there are cases where you need to think about it in the context of an option.
And, most certainly, you need to think about it in the context of [the question], “Has something fundamentally changed as we’ve gotten into the development of this, in terms of a technological discontinuity or some significant changes in the market that would force us to come back and revisit the business case associated with this and think about it in the context of the option value of continuing?”
The result of not doing that is that often times, you get these development projects that have worked their way through this innovation pipeline, but we find that they have ultimately missed the mark because the mark has moved in the context of the two-, three-, four-year development cycle.
Ulrich: You know, it’s interesting, and I think there is another lesson from the pharmaceutical industry here, which is, most projects in the pharmaceutical industry are killed. So what is developed in the pharmaceutical industry is a fairly healthy attitude, which is killing a project early, with the best information, as a way to add value to the portfolio as a whole. And yet that logic, as Kevin suggested, often hasn’t made its way into consumer packaged goods or industrial products, where once that money has been approved and the project team has been put together, you want to do everything that you can to keep it alive. And that’s exactly the opposite logic.
Dehoff: In many of the companies in the industries that I work in, it is the hardest thing in the world to kill a project.
Ulrich: And yet, that’s a way to add a lot of value — if you’ve killed something that ultimately you’re just going to pour more resources into without getting anything out.
Knowledge@Wharton: Are there other elements of innovation that you can isolate that do affect financial performance?
Ulrich: If I were to add a couple more, returning back to a theme I started off with, the quality of the opportunities you put into the pipeline in the first place is a pretty good lever for increasing financial performance. Often, I think we don’t invest enough in generating a rich array of alternatives from which to choose early on. And it’s very hard to take a weak opportunity and turn it into a highly profitable innovation.
I see firms probably not investing quite enough on the front end to identify rich opportunities. And then if you identify those rich opportunities, a way to make sure you maximize financial value is to be efficient in the way you screen and filter and evaluate them, as we were just saying, so you make sure to kill the ones that really have no chance of creating tremendous value.
Dehoff: I completely agree with that. I think the front end is just so important because ideas are cheap, and if you are able to keep the funnel pretty wide at the front end and you have these rigorous screening processes that you use in terms of portfolio selection and portfolio management then that can have a big impact in terms of the overall performance of the portfolio.
I would also say that another thing we’ve observed is a lot of the stage-gate type processes that have been put in place recently are, in some ways, biased to sort of avoid the unsuccessful project, and that some of the selection criteria are geared toward that. One of the things that we’ve seen in some cases that goes too far is the type 2 errors; we worry that some of these stage-gate processes are starting to kill things before we really know what the value of the project is, or what the new product is going to be, as it comes out the other end.
