We interview innovation leaders from around the world and share their insights on corporate innovation.
The Swiss Re Group is one of the world’s leading providers of reinsurance, insurance and other forms of insurance-based risk transfer, working to make the world more resilient. Headquartered in Zurich, Switzerland, where it was founded in 1863, the Swiss Re Group operates through a network of around 80 offices globally. Jeffrey Bohn is responsible for driving R&D and innovation at the Swiss Re Institute (SRI), as well as overseeing the Swiss Re Institute focused on research supporting Swiss Re's clients, business units and group strategy.
Innovation is as much about culture and organizational dynamics as it is about technology and business-model disruption. When I started my career as an academic 25 years ago, I thought innovation would naturally follow from new technology and "out-of-the-box" thinking. I was wrong to focus narrowly on tech and ideas.
As we have transformed our innovation process in the last 12 to 18 months within our firm, I have come to realize that even the best ideas die when the culture and organization are not prepared. It is analogous to planting seeds in nutrient-deprived soil—the seed quality is irrelevant if it can't access the right environmental inputs.
Confidential computing and privacy-preserving analytics: In the past few years, several threads of research in both the hardware space in the area of trusted execution environments (TEE) and the software space in the area of applying approaches to generate analytics from fully homomorphically encrypted (FHE) data constitute promising steps toward unlocking new value for many industries, in general, and financial services, in particular. Here is the problem: Much of the most valuable data for developing better models to forecast time series, manage risk, develop personalized solutions, and support better decision making cannot be processed due to data privacy considerations.
With TEEs and/or privacy-preserving analytics, these (previously unusable) data will become inputs to new derived analytics in which no one in the analytics generation process (including the researchers and IT administrators) can access the raw, granular data. These technologies also add another layer of cyber safety. For example, data that are always encrypted (if one were to use approaches to derive analytics from FHE data) are much more secure given that even if the data are stolen from inside an enterprise's firewall, they would still be encrypted. (Note to be safe into the future the encryption will need to be post-quantum resistant i.e. uses encryption that can not be broken by a future, yet-to-be-developed quantum computer.)
Transformative innovation is almost always counter-intuitive and difficult to envision at first. For example, in the pre-smartphone era, how many people other than a few Apple executives could envision that so much of our lives could be managed with a small device that just has a glass input interface? Most corporate executives who are typically not in R&D or innovation (but decide the budgets) have trouble providing adequate funding and organizational support to a portfolio of transformative initiatives—most of which will fail. These same executives also tend to lack patience wanting to see results in 1 to 2 years. As a consequence, most innovation with the potential to transform an enterprise gets killed too early. The innovation efforts that stay alive are mostly incremental to the business. When budgets are decided, no one is that impressed by a portfolio of incremental innovation and complain that they don't see transformative innovation even though the budget process is doomed to fund incremental innovation only. The result is the innovation/R&D budget is cut until a new leader is willing to take the risk on funding uncertain, but potentially transformative, R&D. Said simply, corporate innovation regresses to the mean of unexciting incrementalism that limits the right scale of investment.
Overcoming this barrier is difficult and probably the primary reason why most transformative innovation comes from outside corporations. One solution is to ensure the CEO (who can override the naysayers) is committed to building an innovation portfolio that includes a sizable number of "moonshot" initiatives. The innovation team should then be given 3 to 5 years (at least) of CEO protection to try and realize this vision. Otherwise, the best one can do is educate and show many examples from the few companies who have resolved this tension between wanting transformative innovation, but only funding incremental innovation—and then complaining that the innovation portfolio is irrelevant to the company's growth. We are still in the middle of this education process.
More corporations will explore joining ecosystems of innovation development that includes universities, independent research institutes, government research departments, and start-ups. The barriers to transformative innovation in corporations mean that more widespread collaborations are necessary to find new technology, ideas, and business models. The pandemic has forced almost all of us to shift to a higher degree of collaboration virtually, which has massively reduced the importance of geographic separation. Once we (hopefully) return to a more (but likely changed) normal, I expect to continue to see virtual collaborations and increasingly, hybrid physical/virtual cross-entity collaborations as ways to increase the probability of finding transformative, enterprise-scale innovation.
The WorkFlow podcast is hosted by Steve Glaveski with a mission to help you unlock your potential to do more great work in far less time, whether you're working as part of a team or flying solo, and to set you up for a richer life.
This ebook explores the importance of interactions with customers, highlights organizations that are leading the way and provides insight on how your organization can start optimizing the customer experience.