Projecting Emerging Technologies

By Paul J. H. Schoemaker, Ph.D.
Chairman and CEO, DSI

There are various frameworks, concepts and theories that can improve how we project new technologies into the future. In this article, we examine how emerging technologies evolve conceptual lenses that can be used to understand and project their future developments. We define emerging technologies as science-based innovations and applications that have the potential to create new products, services or markets. In some cases, they may create entirely new industries (as with personal computers) or profoundly restructure existing ones (as in book or music distribution). At any one time, numerous technologies vie for attention from entrepreneurs, investors, large business, government and eventually consumers. The path of any one technology is usually subject to many twists and turns, reflecting not just advances in the underlying technology, but shifts in market demand, applications, regulatory environments or competitor behavior. So, how should we think about the convoluted path a new technology, such as electronic medical records, embryonic stem cell research, or fuel cells, might take? Appreciating the twisting path of new technologies is crucial for managers in crafting strategies that balance risk and reward appropriately.

Humility is In Order

First, we should be mindful of the enormous difficulty of foreseeing and predicting the many forces that shape a new technology. Just consider for a moment the humble origins of some well-known and important technologies. The steam engine was first used to pump water out of mines; wireless communication traces back to the days of Marconi who helped ships send signals via Morse code (rather far removed from your teenager’s cool cell phone), and computers found their first large-scale practical application in calculating flight trajectories for the military. Although not quite a random walk, it is fair to say that technologies adapt to local and global forces in often surprising ways. Just in recent times, consider how experts on Wall Street and in the venture capital community oversold the promises of 3-G telephony or Bluetooth while under-appreciating the power of WiFi or Voice-Over IP. Billions of dollars were spent on technologies that failed to deliver the goods, while sleeper technologies took the world by storm.

Thus, any attempt to project the path of a new technology along smooth S-curves, or heaven forbid, a linear extrapolation, should be met with healthy skepticism. The best we can do – in most cases – is paint a wide range of scenarios, reflecting the lessons of history as well as the unique features of the present technology and its many possibly applications across markets. Especially hard to predict are the creative insights of bold entrepreneurs, such as Steven Jobs in PCs or J. Craig Venter in mapping the human genome, who can accelerate and redirect the trajectory of a technology. In addition, large companies and governments can often shape the pace and direction of new technologies, as in the case of the space program, healthcare and homeland security.

Adopt Multiple Lenses

Considering the high uncertainty surrounding new technologies, it is useful to explore them using multiple conceptual frameworks. Each of these lenses captures some important aspect of growth dynamics while none captures it all alone. To illustrate, we examine insights from economic models, diffusion models, a focus on standards, technological speciation, disruptive technologies and leap-frogging offer important perspectives on the development of emerging technologies.

Economics. The traditional lenses come from economics, where supply and demand analyses drive the projections. These models require good estimates of potential demand and some insight into the competitive terrain to assess how quickly advances can be made and on which features the players compete. For example, we can easily estimate how many doctors and other health professionals in the US are potential buyers or users of electronic medical records. Their usage patterns and price sensitivities can be studied. Likewise, we know that the hundreds of firms offering EMR services will not all survive and that a shakeout is likely over the next five years.

It is harder to assess what standards (such as platform independence or compatibility with HIPPA in the US) will drive adoption and when any one vendor or offering type has obtained sufficient critical mass to cross the chasm from just serving early adopters to the mass market. Also, the roles of governments, insurers and pharmaceutical companies will be critical since they impact the funding and reimbursement side of the equation. For example, President Bush has made clear that he will push for the increased use of EMR standards to reduce errors and increase efficiency in healthcare. The following chart, adopted from Day, shows the multiple factors that impact technological adoption in new markets. Within this context, there are various important concepts and principles to keep in mind as we project a specific technology forward in time.

Source:George Day

Diffusion Models. Many authors have emphasized that technological adoption resembles the process by which a virus spreads through society. As people hear and learn about a new technology, many become “infected” and want to try the technology for themselves. Various mathematical models exist that capture this diffusion process, which often resembles a S-shaped curve when cumulative demand is plotted over time. The initial adoption phase may be slow due to sporadic use by early adopters. Next, an acceleration phase occurs where fast followers try the new product or service for themselves. Geoffrey Moore has observed that in many cases, there exists a chasm that seems hard to cross for new technologies. For those few that do break through, however, adoption may be rapid and indeed spectacular, as witnessed with fax machine, the Internet or cell phones. The diffusion curve levels off once a majority of the potential market has bought in, leaving slow adopters and laggards to complete the diffusion process. Malcolm Gladwell’s popular book The Tipping Point¹ elaborates on the diffusion concept in social as well as economic contexts, illustrating the complex dynamics of epidemiology when applied to adoption and innovation of products and services. These lenses can be a valuable way to think about the emergence of new technologies.

Role of Standards. A technology’s diffusion path may be further influenced by the role of standards, as illustrated by the epic battle between Edison and Westinghouse to get alternating versus direct current accepted as the national standard for electricity in the USA in the early part of the 20th century. Standards can accelerate as well as retard technological development. Once Microsoft established the Windows Operating system as the de facto standard for personal computers, many independent software writers fell in line, abandoning Apple, Unisys and Linux, in developing application software. But as Microsoft’s antitrust lawsuits in Europe and the USA underscore, as well as the recent revival of open architectures such as Linux, how the rent-seeking behavior of those owning the standards often stifles innovation while breeding resentment. The book Information Rules² by Shapiro and Varian offers an excellent conceptual analysis, including game theoretic considerations, as to how the compatibility of standards over time and across competitors greatly shapes the strategic game firms are playing. The notion of standards is related to that of path dependence, which is a broader perspective that highlights the role of history in the future developments of a technology. The classic example is the design of the QWERTY keyboard which owes its arrangements of letters to the days of the mechanical typewriter. To prevent the mechanical hammers from hitting each other under fast typing, frequent combinations of letters were placed on the key board so as to reduce interference. Although the mechanical typewriter vanished over time, the QWERTY keyboard remained since it had become a common standard. Although a superior letter layout for typing could now be achieved, the old system was deeply entrenched in the fingers and minds of present consumers. We see the same stickiness and path dependence in the US where attempts to switch to the metric system in measuring length, weight and speed largely failed. The language of inches, pounds, and quarts is too deeply entrenched to be replaced by the more rational system of meters, grams and litres as used in science worldwide.

Technological Speciation. A third conceptual lens through which to assess a technology’s potential derives again from a biological analogy. Speciation refers to the process by which nature selects for certain traits within a sub-population of species versus another sub-population belonging to the same species. Darwin noticed, for instance, that different subgroups of finches across the islands he visited exhibited markedly different beak shapes and other traits reflecting the different ecologies present on each island. If a technology changes its domain of application, from say commercial use to consumer application or vice versa, rather different characteristics may develop. For example, when the Internet expanded its domain from military and academic applications to the world of consumers in the mid 1990s, the world-wide web underwent a profound transformation. The additional funding from venture capitalists as well as large firms, steered Internet technology into new standards for sharing files, e-commerce, browsing and real-time transmission of streaming video or telephony. This revolution was less driven by technological breakthroughs, such as Netscape’s browser or wireless access, than the very different features demanded by consumers and firms. The jump in domain of application is what allowed a backwater technology to blossom into a global phenomenon. The notion of speciation, as explained by Adner and Levinthal in Wharton on Managing Emerging Technologies,³ constitutes a powerful lens through which to envision new scenarios for an emerging technology.

Disruptive Technologies. A related perspective is offered by Clay Christensen who studied disk drive manufacturers and noticed that very few managed to survive the transition from one technological era to another. For example, the early makers of drives – those that used floppy disks - focused on certain features and users, which caused them to favor a certain set of cost-functionality tradeoffs for their current customer segments. As they added more features and refinements to even better serve their most demanding customers, new entrants used improvements in the underlying technology to offer the lower end of the market a cost-feature bundle unattainable by the incumbents given their particular competencies and cost structure. Each successive generation of disk drives proved disruptive to the winners of the previous generations in terms of the competencies needed to compete. Christensen well known book the Innovator’s Dilemma⁴ examines technological disruption more broadly and showed its prevalence in a wide variety of industries beyond disk drives. Whether or not a new technology is disruptive depends not just on the technology but its impact on the business models of incumbents. The world-wide web was disruptive for Borders since it couldn’t easily match the discounts offered by Amazon given its real-estate-based business model. But that same Internet technology proved to be a reinforcing and enhancing technology for many financial service providers who used it as an additional channel to reach consumers. Early attempts to replace bricks with clicks, such as that of Wingspan.com, failed in finance and yet succeed wonderfully in selling books or music.

Leap-frogging. A phenomenon closely related to the dynamics of disruptive technology is that of technological leap frogging. Often new firms will leap-frog the dominant players by rendering their existing platform of technological and other capabilities obsolete. By the time the incumbents notice the threat, which often comes from the flank outside the purview of the incumbents’ main customer base, it may be too late to develop the new capabilities. For example, Merrill Lynch was late in responding to Schwab’s discount broker model, which was then followed by an on-line model, because Schwab initially attracted customers outside Merrill Lynch’s area of focus and concern. In addition, the new low-cost model did not fit Merrill Lynch’s full-service brokerage model which entailed a large network of full-time brokers as well as a bundled pricing strategy that combined research, advice and account management with the execution of stock trades. Leap-frogging occurs when a new technology broadly replaces an old one across the board. In many parts of China and India, cell phones are jumping over the traditional phase of landlines; telephone poles are no longer erected in most locales. Solar-powered, low-energy LED traffic lights are replacing traditional systems, eliminating the need to wait for electricity to come to remote areas. By definition, leap-frogging entails disruptive technologies in that an older regime gets replaced, in a relatively short period of time, by a new technology. But not all disruptive technologies involve leap-frogging and thus it is a distinct dynamic. Both phenomena can be classified under the rubric of “creative destruction," which, as Joseph Schumpeter noted, is by its very nature chaotic and thus hard to predict in terms of timing, magnitude and direction. The best we can do here is to consider multiple possibilities and lay out various scenarios. By looking for opportunities to use technology in disruptive ways or to create leapfrog strategies, managers can better design strategies or anticipate the potential trajectories of new technologies.

In Conclusion

Emerging technologies will always exhibit surprising twists and turns since much is unknown about both the ultimate capabilities of the technology itself as well as its use in a variety of applications. We cannot with any confidence predict now how functional genomics will spawn new diagnostic tools and therapeutic regimes in the future for various diseases. Just as we could not have predicted in the early 1970s how advances in micro-processing technology would give rise to personal computers, cell phones, PDAs, fuel injection engines and medical implants, many of today’s technologies will surprise us.

And yet, the trajectories are not entirely a random walk either. Especially in hindsight, we can see that the evolutions of technologies, industries and markets exhibit systematic as well random elements. The role of standards proved critical in the case of PCs and the notion of speciation helps us understand the sudden rise of the world wide Internet. But random elements relating the visions of entrepreneurs such as Steven Jobs and Bill Gates, or the actions of courts as in the case of Microsoft’s antitrust woes, often contain unpredictable elements in terms of timing, magnitude and counter-responses. Consequently, a sound approach to assessing technological trajectories must balance the predictable aspects with the role of uncertainties and wild cards. We find that scenario planning let’s us do this, provided that we imbue the scenarios with the proper conceptual lenses.

We cannot see exactly where emerging technologies may be headed. Yet by examining them through different lenses, we can better anticipate their potential trajectories. Each lens reveals a different perspective on the potential for the technology and insights on the path it may follow. We recommend that managers use the lenses above, as well as other lenses, to examine the technologies that are important to their businesses. Trying to predict the unpredictable is folly. But not including lessons from the past is unwise as well. If we approach emerging technologies with sufficient humility and the benefit of multiple perspectives, we may be able to craft strategies that will let us successfully navigate the uncertainties of the future.

Notes

¹ Gladwell, M. (2000). The Tipping Point: How Little Things Can Make a Big Difference. NY, Little Brown and Co.
² Shapiro, C. and H. R. Varian (1999). Information Rules: A Strategic Guide to the Network Economy. Boston, MA, Harvard Business School Press.
³ Day, G. and P. J. H. Schoemaker, Eds. (2000). Wharton On Managing Emerging Technologies. Wiley.
⁴ Christensen, C. M. (1997). The Innovator's Dilemma: When new technologies cause great firms to fail. Boston, MA, Harvard Business School Press.