Colliding Exponentials
Executive summary: Solutions to many unmet customer and market needs are enabled by the convergence of exponentially improving technologies. Convergence science requires intensely collaborative and sustained value creation methodologies.
At the Internet of Things (IoT) conference in China last fall, with a thousand participants and many from manufacturing, I listen to Alibaba’s Jack Ma. He talked about his early career and some of the mistakes he made. He then, surprisingly, told the audience that they were all losing money, whether they knew it or not, because most of them were going away.
Ma described how rapidly improving technologies, business models, and societal trends would fundamentally transform their businesses, including those engaged in manufacturing. His advice was to understand and exploit the technological and market transformations of our age, something he said he was not good at when he started in business.
The key was to see where these developments would be in five or ten years and to make make sure to leverage them to your advantage. Ignoring them would lead to failure. Almost all information technologies, for example, are still in their infancy, improving by 100% every 2 to 5 years. They must be understood and exploited if one is to survive.
A point he did not emphasize, but that is equally important, is to understand the convergence of multiple technologies, especially those improving exponentially. Many significant new opportunities are addressable when several technologies converge or “collide.” Ma’s ability to create and expand Alibaba is due to his ability to exploit these interdisciplinary developments.
With the Dean of Engineering at Worcester Polytechnic Institute, Winston Soboyejo, several of us were discussing many of the transformative opportunities that require the convergence of technologies. Siri, which we developed at SRI, is an excellent example. It consists of speech and natural language processing, semantic networks, machine learning, and more. Following one technology, like Moore’s Law does not provide sufficient insight into the new opportunities. By bringing those different technologies together to address the problem of mobile web search, Siri defined a whole new category of personal computer assistants.
Siri was just the start. As seen with Alexia, Cortana, and Viv, there will be personal computer assistants for most services, whether for banking, entertainment, or knowledge acquisition. The Internet, which is already the ultimate example of technological convergence, has enabled thousands of new web-based products and services. Personal computer assistants add one more dimension to that space.
Winston noted that because of the importance of convergence, academics must change how they do research. Most academics work on single technologies as individual principal investigators (PIs). Significant innovations are always possible, but within a single discipline, most research results are incremental. For example, the efficiency of amorphous solar cells has improved by a few percent per decade. In such cases, the opportunity space being explored is along a line.
If two significant technologies are combined, like with biomechanical engineering, the opportunity space to be explored expands and is represented by an area. When three or more disciplines are combined, they can define a multi-dimensional volume of potential opportunities. The number of unmet innovative opportunities is often large.
When I was CEO of SRI International, we continually looked for “colliding exponentials,” where two, three, or more rapidly improving technologies could come together to open up a new “white space” — a space with many unmet opportunities and little competition.
A significant part of SRI’s success came from our ability to combine the rapidly improving technologies that were opening up the new white spaces. We were following Jack Ma’s model and looking out three to five years at multiple technologies and asking what new opportunities they enabled. They lead to innovations like digital video (HDTV and satellite video broadcasting), robotic surgery (Intuitive Surgical and Verb), and computer assistants (Siri and Kasisto).
Our “secret” for success was to look for these opportunities and use our value-creation best practices (i.e., “Innovation for Impact,” as described in this website) to get the answers needed fast and efficiently. Our methodology brought the different technical disciplines and other skills together in an ongoing and intensively iterative value creation process. It is interesting to note that since relatively little is known at the beginning of a new initiative, we never ended up exactly where we first thought. But since there are so many opportunities within these white spaces and our value creation methodology was so effective, we usually ended up in a valuable place.
Note: A major 2017 study on value creation best practices by the National Academy of Engineering recommended renaming NSF’s large Engineering Research Centers (ERCs) Convergence Engineering Research Centers (CRECs) to emphasize that multidisciplinary R&D often allows the most impact. Interdisciplinary R&D requires funding agencies and universities to change how they perform R&D. The same principles apply to companies, which rarely use the value creation best practices required. I will have more to say on this in the future.
