Tag Archives: killer apps

What I Learned at Google (Part 2)

We didn’t intend to write a series on the symposium that Insurance Thought Leadership hosted at Google last week for C-suite executives of major companies and for regulators, but I want to build on the wonderful post yesterday by Iowa Insurance Commissioner Nick Gerhart, about the insights he picked up there. For me, the symposium underscored a crucial point about the pace of innovation — how it can be faster than we expect at times but can also be slower.

And it’s crucial to get the timing right.

The faster-than-expected part comes from a partner at one of the major Silicon Valley venture capital firms, which we visited as part of the symposium. All these firms track where entrepreneurs are seeing possibilities and where investments are happening, and the partner said that in all of 2014 the firm had been visited by exactly zero people hoping to innovate in insurance. Yet, just in the fourth quarter of 2015, the firm met with 60 companies looking to innovate in insurance.

Even as innovation has surged in fintech, in general, investment in insurtech start-ups has been minimal, about 1% of the total for fintech. But that may now be changing. Start-ups may accelerate the disruption in insurance.

You’ve been warned.

The slower-than-expected (at least for me) part comes from a consensus about driverless cars at the symposium. The group discussions at all five tables reached almost identical conclusions: that fully driverless cars will be feasible technologically in roughly four years but that it will be 10 before they are a major presence on the road.

In Silicon Valley-speak, saying something is 10 years out means it verges on science fiction. After all, 10 years at a pace set by Moore’s Law means that you have some 30 times as much computing power available to you at no increase in cost — if you need that much more power to make something happen, it’s hard to know for sure that it works 10 years ahead of time.

But the concerns of the insurance C-suiters and the regulators were more prosaic. They felt that anyone who might be left behind because of driverless technology would kick up a fuss and that state governments, likely led by the legislatures, could intervene on behalf of constituents to slow the transition.

Perhaps insurance agents would fear the shift of auto insurance from a personal responsibility to a corporate one, shouldered by the manufacturers of the driverless cars or by operators of fleets of the cars — if no person is involved in driving, how can an agent sell personal lines insurance?

Maybe car dealers, already fighting a rear guard action to prevent direct sales by manufacturers to consumers, would fear further loss of their intermediary role — why would a fleet operator need a dealer to purchase of tens of thousands of cars?

Basically, think of anyone who might lose business because of driverless cars and the promised reduction in accidents — parking garages, emergency rooms, whatever — and you can see an obstacle. Not everyone will be explicit about their complaints. It’s hard for an operator of prisons or funeral homes to demand more business. But our discussion groups were sure that opposition would surface in lots of ways and that politicians, always running for reelection, would lend support.

In fact, some technical concerns about driverless cars have surfaced in recent months. It turns out that Google cars have more accidents than human drivers do, albeit only minor accidents thus far and, most importantly, not because of any fault by Google — careless people seem to bump into Google cars a lot at stoplights. Google also acknowledges that the cars would have caused at least some accidents if not for intervention by the highly trained humans sitting in the driver’s seat. So, the technology still has a ways to go.

The pace of technical progress has still been faster than I expected when Chunka Mui and I published Driverless Cars: Trillions Are Up for Grabs nearly three years ago, and we staked out what was then a very aggressive position. The federal government recently stepped on the gas, if you will, by announcing a plan to spend $4 billion on driverless technology over the next decade and to reduce regulatory hurdles for adoption. The rationale — which we have long predicted the government would have to adopt — is that 25,000 lives could have been saved last year on U.S. highways if a mature form of the technology had been in use.

For me, then, the fundamental question from our symposium is: How do you position yourself for a technology that may be wildly important, yet whose timing is uncertain?

Two thoughts:

–A line that carries considerable currency in Silicon Valley is: “Never confuse a clear view with a short distance.” Even if you’re sure that something will happen as part of the transition to autonomous vehicles, keep in mind the issue of timing.

–Then think big, start small and learn fast — a dictum that just happens to come from another book Chunka and I wrote, The New Killer Apps: How Large Companies Can Out-Innovate Start-UpsThat means you get in the game now, with as big a vision as you can conjure up for yourself or your company. Then you start experimenting to see what works and what doesn’t — while spending extremely little money. You make sure you can kill the experiments as soon as you gather the needed information — no pilot projects allowed, at least not in the early days, and certainly no grand plans to go to market. And you keep iterating until both you and the market are ready. Then you start cashing checks.

Actually, one more thought: Consider coming to the Global Insurance Symposium that Nick and the fine folks in Des Moines (my dad’s hometown) are putting on in late April. Nick is as forward-thinking a regulator as I’ve met, and there will be lots of people there who can help you on your journey, whether that involves driverless cars or something else entirely. I’ll be there….

3-Point Plan for an Innovation Portfolio

One lament I often hear when I advise large company executives on the need to “Think Big” is that their biggest innovation challenge is not thinking big—it is thinking too much. Purportedly great ideas come from the front lines where the organization interacts with products and customers. They come from technology or marketing wizards keeping a sharp eye on disruptive market trends. They come from executives and board members grappling with questions at the organization’s strategic horizon. The challenge is that organizations are overwhelmed with more ideas than they can sort out, much less pursue. Perhaps the best advice on how to deal with the challenge of too many ideas comes from Peter Drucker, who offered this general principle:

Innovation begins with the analysis of opportunities. The search has to be organized, and must be done on a regular, systematic basis.” Don’t subscribe to romantic theories of innovation that depend on “flashes of genius.”

Rather than relying on randomness or organizational influence to dictate which ideas find a receptive ear, here is a three-point plan for initiating a systematic process for uncovering, assessing and scaling the best ideas. 1. Inventory Opportunities Start by casting a wide net. For example, sponsor a series of innovation contests and workshops to educate, build alignment and uncover potentially good ideas. Hold scenario planning sessions with senior executives and board members to explore both incremental and disruptive future business scenarios. Questions to ask might include:

  • Can you augment your customer interfaces to reveal customer preferences and to customize the customer experience, as Amazon and Netflix do?
  • Are there opportunities to better utilize the big data being generated by your business processes, including customer, operational or performance data, for innovation?
  • How might you reimagine key business, customer, and competitive issues if you could start with a clean sheet of paper?
  • How do the six disruptive technologies affecting other information intensive companies apply to you?
  • What extreme competitive threats, i.e., doomsday scenarios, might new entrants wielding these disruptive technologies pose to your organization?

Opportunities should include both continuous and discontinuous innovations. Continuous innovations offer incremental or faster, better, cheaper-type optimizations, such as shedding costs, reducing cycle times and generating incremental revenue. Discontinuous innovations are those that rise to the level of game-changing potential. 2. Develop a Holistic View Using an Innovation Portfolio Next, assess each opportunity based on competitive impact and investment type using the portfolio analysis framework as shown in Figure 1. Figure 1 Figure 1: Portfolio Analysis Framework Competitive impact measures differentiation against what competitors might deploy by the time an idea is launched. Remember Wayne Gretzky (who famously said he skates to where the puck is going, not to where it is)! A key mistake is evaluating an idea against one’s current internal capabilities, as opposed to where the competition is going. This dimension forces an explicit calculation of an idea’s future potential competitive impact. Investments can be one of three types:

  • Stay in Business investments (SIB) are for basic infrastructure or non-discretionary government mandates. SIB investments should be assessed on how adequately they meet regulatory or technical requirements while minimizing risk and cost.
  • Return on Investment opportunities (ROI) are pursued for predictable, near-term financial returns. Standard measures, such as net present value (NPV), return on equity (ROE) or other well-understood metrics are applicable here.
  • Option-Creating Investments (OCI) are pursued to create business options that might yield killer-app-type opportunities in the future. OCI investments do not yield financial returns directly.  Instead, they build capabilities and learnings that can be translated into future ROI opportunities. Like financial options, OCIs should exhibit high risk and offer tremendously high returns.

After arraying opportunities in the framework, eliminate those that fall outside of acceptable boundaries. For example, companies should not pursue opportunities that, once completed, are already at a disadvantage against the competition. For the remaining opportunities, develop an initial sizing of investment levels and potential benefits according to each investment category. Filter as appropriate. For example, eliminate ROI opportunities that do not meet standard corporate hurdles rates. Eliminate OCI opportunities that do not exhibit extraordinary option value. Eliminate SIB ideas that do not adequately minimize cost and risk—be very skeptical of SIB opportunities aimed at providing ROI or OCI benefits. Such opportunities should be judged directly as those investments types.  Figure 2 illustrates how the analysis might look at the end of this stage. Figure 2 Figure 2: Portfolio Analysis Results 3. Balance the Innovation Portfolio In personal investment portfolios, it is important to not place all hopes in one or two investments. The same is true for corporate innovation portfolios. To ensure competitiveness in the near term and in the future, they should include a mix of incremental and disruptive innovations. The right balance and prioritization depends on a company’s investment capabilities and competitive circumstances. For example, as shown in Figure 3, a market leader might field a portfolio geared toward aggressive growth by enhancing its infrastructure, investing heavily in near-term profitable opportunities and developing a small number of killer app options for sustaining its competitive advantage.  (My experience is that the right number of such options is on the low end of the magic 7, plus or minus two. That is because the limiting factor is senior executive attention, which is very limited, not investment dollars. Market leaders have lots of money to waste, but no project with true killer app potential can succeed without significant senior executive attention.) Figure 3 Figure 3: A Market Leader’s Balanced Portfolio Other illustrative portfolio profiles are shown in Figure 4. Commodity businesses tend to minimize SIB and OCI investments. Companies that are retooling might emphasize infrastructure and near-term investments and make only minimal investments in future options. Underperforming companies tend to invest in programs that barely achieve competitive parity, or worse, and do little to prepare for the future in any of the three investment categories. Figure 4 Figure 4: Illustrative Portfolio Profiles

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By adopting appropriate financial and competitive metrics and measures for each type of investment, companies avoid planning theatrics where guesses are disguised as rigorous forecasts. This can happen, for example, when infrastructure and other SIB investments are required to demonstrate explicit returns on investment. Or, it can happen when advocates of OCI efforts are required to calculate net present value of very uncertain long-term initiatives. Such forecasts can, of course, be made by  savvy proponents. But the analyses are better testaments to rhetorical and spreadsheet skills than certainties about the future. At the end of this three-step process, companies should have a prioritized and staged investment plan that represents a coordinated enterprise innovation strategy and follows the think big, start small and learn fast innovation road map. Achieving an adequate understanding of the entire landscape of possibilities facilitates and encourages thinking big. Continuing management of the innovation portfolio provides clear criteria for evaluating other big ideas as they come up. It also demands the discipline of starting small and learning fast in the pursuit of disruptive innovations that will shape the company’s future strategic prospects.