-
What Markets Do and Don’t Get About Innovation
September 28, 2013 Editor 0
In 2007, Clayton Christensen co-founded Rose Park Advisors, a hedge fund devoted to investing in disruptive companies. The idea was to transform his theory of disruptive innovation into an investment thesis. Disruptive innovation can take several forms, and the market understands some types better than others. But do markets really follow the logic of an academic theory?
Great investments are both non-consensus and correct, and examining the valuation process shows that consensus tends to coalesce differently around each type of innovation.
Four types of disruption
Disruption theory reveals four innovation types that could shape an investment thesis:
- Low-end disruptive – a dramatically cheaper way of producing worse products for customers who are over-served by existing options
- New market disruptive – a cheaper, more accessible, and worse-performing product that turns non-consumers into customers
- Quality-sustaining – Christensen’s “sustaining innovations”: incremental improvements to product performance, leading to higher cost; companies’ bread-and-butter when products aren’t yet good enough
- Efficiency-sustaining – incremental innovations that make products cheaper and businesses more efficient; these are important all the time, but particularly when product performance becomes “good enough” for most customers; the realm of LBOs and the iPhone 5C
Why the market values some kinds of innovation better than others
Sustaining innovation inhabits the world of incremental change, deliberate strategy, and most financial and management theory. Disruptive innovation, on the other hand, is more difficult to value — and potentially a more fertile ground for investment. Investors’ core valuation methods (comparables and discounted cash-flow analysis) both extrapolate past performance into the future — but they fail to predict when the future will be radically different from the past.
Sustaining innovations are more easily quantified than their disruptive counterparts, and hence easier for the market to grasp. Efficient-sustaining innovation is essentially cost-cutting, and should be the easiest of all four categories to predict. Costs are concrete and immediate. And incorrect analysis often falls into well-understood categories — the overestimation in M&A synergies, for example.
Quality-sustaining innovations also tend to follow well-known rules: expected sales yields of marketing investment, established norms for product improvements and price increases. But forecasting revenues requires identifying market shifts, particularly the point where products go from being “not good enough” for many customers to “good enough.” As a result, sometimes, changing circumstance strips away expected results, or strategy leads products to outperform historical precedent (consider HBS marketing professor Youngme Moon’s examples of Reverse, Breakaway, and Hostile positioning in brands like Ikea, Swatch, and Red Bull). Mostly, though, markets get things right.
Disruptive innovations, however, entail a discontinuous shift from “how things worked” in the past to how they work today. Without theory to tell us how the rules are changing, many tools of management and finance seem to break down.
New-market disruption is more complex. Because products and customers are entirely new, it’s harder for analysts to mistakenly force these innovations into the old paradigm. As a result, outlooks are more likely to be positive or mixed.
The recent influx of capital into low-cost 3D printing is a good example. Desktop 3D printers are a classic new-market disruption: fundamental changes in technology allow much cheaper, more accessible, and worse performing products to become available to new customers. And many investors intuitively recognize this innovation as a new-market disruption that could unleash a wave of creativity in product design and revolutions in the manufacturing, retail, and software industries. So money piles into the sector, and crude bets based on disruptive potential become increasingly risky. The task shifts from merely identifying innovations to evaluating strategy, tactics, people, and prices.
The difference between low-end and new-market disruption is that, in pure low-end disruption like Nucor, the market tends to miscategorize disruptors as if they were low-quality incumbents. Because a low-end disruptor’s customers are the incumbent’s worst customers, and because its products are low-quality substitutes, it’s easy to miss the discontinuous change in a product’s performance trajectory and the inevitable sustaining innovations that will allow the disruptor to move up-market. As a result, analysts have higher confidence that the disruptor is playing by the same rules that are effective in valuing incumbents, and incorrect consensus is more likely — creating a big opportunity for investors who recognize the signs of disruption.
Instead of just crunching the numbers on less valuable sustaining innovations, market analysts ought to be looking for signals of disruption. For instance, over-served customers in markets where sustaining innovations have overshot customer demand. Instead, markets often miscategorize low-end disruptors as low-quality incumbents.
Next, market analysts should look for new-market disruptors — companies that are converting non-customers with a worse product. Because growth from non-consumption is often fast, we expect new market disruptors to be consensus bets much more often than low-end disruptors. First, analysts should look for a lack of consensus: when analysts are betting against new-market disruptors. Only then should they consider consensus bets, to evaluate whether the market is ignoring any part of a darling’s disruptive potential.
The tools of financial analysis are particularly ill-suited to disruptive innovations, because they offer no insight into when circumstance changes so that past rules no longer apply. This is when disruption theory can inform investors on the value of innovative companies. This creates opportunities for investors who understand disruption and are willing to bet on it.
Knowledge management and measurement: a critical review Design Lessons From iOS 7
