Tag Archives: the new 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.

8 Make-or-Break Rules for Innovation

In my last posting, I laid out three reasons for why large companies should out-innovate start-ups to capture the disruptive opportunities that are being enabled by a perfect storm of technological innovations. In this post, I offer eight rules for how they can do so.

Based on research on thousands of innovation efforts—both successes and failures—that went into The New Killer Apps: How Large Companies Can Out-Innovate Start-Ups, corporate innovators should apply these rules to help their companies get out of their own way and leverage their assets. By doing so, they can take better advantage of innovation opportunities than start-ups can. The eight rules fall under three general categories that distinguish winners from losers: Thinking Big, Starting Small and Learning Fast.

Successful innovators “think big” by considering the full range of possible futures. They facilitate innovation by daring to pursue “killer apps”—new products and services that might rewrite the rules of a category.

By contrast, failed innovators tend to “think small.” They assume that change will be a slight variant of the present and just look for incrementally faster, better or cheaper innovations.

Here are three rules designed to help you think big:

Rule 1. Context is worth 80 IQ points. As you start to “think big,” you must understand the information-technology environment in which you are operating. Six technological innovations—combining mobile devices, social media, cameras, sensors, the cloud and what we call emergent knowledge—are reshaping both what is possible and the competitive landscape in every information-intensive industry.

Mary Meeker, the noted business analyst, argues that these technologies are putting more than $36 trillion in market value up for “reimagination.” ($36 trillion is the total market value of the 10 industries most vulnerable to change over the next few years.) You must understand all the traditional forces inside your industry and come to grips with these six technological megatrends, both individually and in combination.

Rule 2Embrace your doomsday scenario. Thinking big is not just about bold aspirations; it also requires understanding the starkest threats facing your organization.

One reason to look for doomsday scenarios is that it helps spot vulnerabilities and spark improvements even if doomsday never comes. Another reason is that it helps to build alignment. Getting beyond vague views and developing detailed, shared views of existential threats and how quickly they might arrive can help management teams develop consensus on timing and move forward in unison. But people tend to avoid thinking about truly worst-case scenarios, so this rule is designed to make sure that they do so.

Rule 3. Start with a clean sheet of paper. A markets change, large companies’ strategic assets too often become liabilities. Success brings with it priorities to juggle, budgets to protect, bonuses to maximize, resources to defend, loyalties to reward, egos to stroke. People have all sorts of incentives in big organizations to slow or halt innovation, and many manage to do so.

That’s why it is important to periodically start with a clean sheet of paper and think about key trends and looming inventions, then envision how everything could come together to transform the business—without worrying about what people, capabilities and other assets have to be added or subtracted to become that perfect version of the business.

Start Small

Successful companies “start small”after thinking big. Rather than jumping on the bandwagon for one potentially big idea, they break the idea down into smaller pieces for testing and take the time to make sure that key stakeholders are working in unison.

By contrast, companies that fail in the face of a disruptive technology tend to swing from complacency to panic. Initially, they not only don’t see the opportunities; they can’t accept that they’re in danger. When they finally see the disruption, they panic. They make a last-chance, massive bet on a single idea—only to have it not pan out. Here are three rules that ensure you are starting small:

Rule 4. First, let’s kill all the finance guys. To start small, make sure you don’t settle on financial projections too soon; they can’t be accurate, and they hamstring innovation. By definition, disruptive innovations deal with future scenarios that are hard to read and where the right strategy is not clear; the right strategy has to emerge over time.

This rule, then, is a reminder to take a more iterative approach to understanding the finances of new businesses. A culture has to be established, beginning at the very top of the organization, that says newborns get to crawl and walk and maybe even start preschool before their talents are evaluated.

Rule 5. Get everyone on the same page. While the tendency is to leap into action as soon as a possible killer app is identified, it is crucial to take the time to step back, assess where the organization is and identify possible impediments to change. One challenge is to understand who wins and who loses if the envisioned innovations succeed. If an innovation has to kill the core business to succeed, it won’t be possible to get everyone to embrace it. Those in the existing business will always try to kill rather than be killed. In some cases, you can delay an uprising by being discreet. In other cases, where those not on the same page can’t cripple you, you can be overt and simply pit a new business against the existing one (while protecting the new efforts sufficiently).

Another challenge is to understand the cultural implications of the desired innovation. Many executives believe they can change a culture to suit a strategy, rather than try to make the strategy fit the culture. That route is possible but usually takes longer than most are willing to admit. Sometimes it is better to work with what you’ve got. The key is to understand that there is no silver bullet to managing change. Instead, you must form a cleared-eye view of the particular circumstances that must be addressed and manage accordingly. Remember Nelson Mandela’s admonition, “Lead from the front but don’t leave your base behind.”

Rule 6Build a basket of killer options. Once you are ready to start building killer apps, make sure to invest only small amounts and test a number of possibilities. At the early stages, any fledgling killer app is more likely to fizzle than sizzle. Do not waste a lot of money plunging toward The Answer. What you really want is a finely nuanced understanding of The Question. Do this by employing the discipline associated with financial options. Rather than investing tens or hundreds of millions of dollars to build out a full-fledged business, invest in iterative experiments that can be expanded as they prove out, or be set aside if they don’t.

It is important to limit the number of options to a handful. Innovations of transformative potential require CEO attention—which is limited—to make sure the efforts are protected from the organizational antibodies; to make sure they do not take on a life of their own; and, to shepherd them to scale if their potential proves viable. (In most organizations, only the CEO can play this role.) Our experience is that the right number is around three “killer options” and no more than five.

Learn Fast

In addition to thinking big and starting small, successful innovators “learn fast.”They take a scientific approach to innovation. They figure out how to gather comprehensive data and quickly analyze both what’s working and what isn’t. They have the institutional discipline to set aside or alter projects based on that analysis. By contrast, companies that fail have neither the time nor the inclination to learn. They fall into the “it’s all about implementation” trap and end up expertly implementing a failed strategy. Here are two rules to make sure you are learning fast.

Rule 7. A demo is worth a thousand pages of a business plan. Too often, early success or optimism about a big idea quickly transforms it into a conventional business development program: a long march where the only acceptable outcome is to get a product to market. As a result, people do all the analysis they can, however imprecise, and the result becomes The Plan. Some of this is due to habit—planning is what big companies do, and business initiatives can’t typically proceed without detailed business plans and reams of confirming spreadsheets.

Our research revealed the need for less planning and more testing. Rather than prematurely building out the new business, keep prototyping to explore key questions, such as whether the technology will work, whether the product concept will meet customer needs and whether customers will prefer it over the competitive alternatives.

Rule 8. Remember the Devil’s Advocate. Setting up the right process for demos, prototypes and scaling is crucial but only half the battle. The other half is making sure you ask the tough questions during the process and remain open to hearing uncomfortable answers. Devil’s advocates are individuals or groups whose role is to stress test critical assumptions, key forecastsand other make-or-break aspects of a potential killer app. The goal is not to interject an abject naysayer into the decision-making process but rather to drive at the answer that best serves the long-term success of the organization. Nor is the goal to relegate the task of critical thinking to the devil’s advocate. Instead, the devil’s advocate process serves as a safety net, and, because everyone knows that tough questions are forthcoming, they’ll be more likely to confront them.

Done right, a devil’s advocate frames the most important questions that need to be answered before moving to the next stage of commitment. The advocate also guides the process along, making sure that the right amount of uncertainty is reduced at each step and that the possibility of a graceful exit is always preserved.

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Following these eight rules won’t guarantee killer-app-level innovation. Business is a contact sport. Some companies win. Some companies lose. That won’t change.

What following these rules will do, however, is help you overcome the biggest barriers to innovation and turn size into an advantage. You’ll do a far better job of sensing what’s really going on in your market and of putting yourself at the forefront of the powerful trends that are transforming our economy.

Phone’s New Trick: Cheap Car Insurance

In the last decade, pilots and trials of telematics have eked out only single-digit adoption rates for usage-based insurance (UBI) among drivers, but the opportunity is now here for a breakthrough. All that is required is a smartphone.

To date, buying insurance based on actual, verified miles driven has involved installing expensive and privacy-invading tracking systems, mated to a vehicle port with a “dongle thingy,” or ghosting a cell phone’s reception turn for turn. These systems are complete overkill for verifying odometer readings.

Instead, consumers who want to get low rates because they drive few miles can verify their actual readings on a timely basis by simply periodically taking pictures of their odometers with their smartphones. An app could verify the date and ensure that the photo is of the car that is being insured.

Using a smartphone app for UBI would require insurers to leave behind their traditional approach and be much more responsive to drivers. At the moment, those insurers that offer low-mileage programs tend to just have one cutoff – for those who drive less than 7,500 miles a year – and offer them only something approaching a 10% discount off the rates for those who drive the average distance of roughly 12,000 miles a year. Yet someone who drives 5,000 miles a year should, based on industry data, get a discount of 30%. Given the sophistication of smartphone apps, drivers would expect rates to be set for actual miles driven, not just based on whether they stayed below that 7,500 cutoff. Someone who drives 3,473 miles in a year could pay just for that number.

An app could also be used to win business. The interface will help the consumer not only remember to take the picture of the odometer but could alert them when carriers in their state offer better rates for those customers who drive less. (In many states, miles are not now used in rating.)

Consumers who drive less are set to benefit hugely from telematics. All they need is the right app – and the savings on insurance could even pay the phone bill for some.

Usage-based insurance for the mass market is here.

3 Reasons Why Big Firms Should (and Can) Out-Innovate Start-Ups

The chief innovation officer of a Fortune 1000 company relocated to a Silicon Valley outpost far from her New York corporate headquarters. She now spends most of her time holding court with venture capitalists and entrepreneurs about stakes in hot start-ups. It is never clear who is courting whom in those meetings, though the general attitude in the Valley is that there is more dumb money than good start-ups. Her goal is not to maximize financial returns on her investments—even a 200% return would not be material to her corporation’s financials. Instead, she is essentially outsourcing her company’s innovation strategy to start-ups.

Do these stories sound familiar?

Like too many of their peers, these smart and savvy veterans were stymied in their efforts to get their companies to innovate. They resigned themselves to a conventional wisdom that has taken root in recent decades: that start-ups are destined to out-innovate big, established businesses. Consider, such pessimists contend, that 227 of the companies on the Fortune 500 list just 10 years ago are no longer on the list.

Based on personal experience with hundreds of large company innovation successes and failures, and research into thousands more, however, I have found that this conventional wisdom just isn’t true. Or, at least, it need not be. Yes, small and agile beats big and slow, but big and agile beats anyone—and that combination is more possible than ever.

There are three reasons why innovators at large companies should be optimistic about their ability to beat start-ups.

1. Start-ups aren’t all they’re cracked up to be.

Yes, Silicon Valley has the cachet, but Harvard Business School research shows that the failure rate for start-ups runs as high as 95%. Start-ups, as a group, succeed largely because there are so many of them, not because of any special insight.

What’s more, the National Bureau of Economic Research (NBER) found that entrepreneurs are saddled with most of the risk while financiers capture most of the rewards. Entrepreneurs invest their time, reputations and accumulated expertise for modest salaries and long hours in the hope of gaining huge rewards at “exit,” when the start-up goes public or is acquired. NBER researchers found, however, that start-ups rarely pay off for the entrepreneurs who slave away at them. Of companies that reached an exit (after a median time of 49 months from first venture funding), 68% resulted in no meaningful wealth going into the pockets of the entrepreneurs. These numbers add up to pretty long odds for corporate innovators looking to find greener pastures as an entrepreneur.

The story is not much better for strategic investors chasing start-ups through venture capitalists. Numerous studies, including a 2012 study by the Ewing Marion Kauffman Foundation and a more recent one by Cambridge Associates, show that venture capital has delivered poor returns for more than a decade. VC returns haven’t significantly outperformed the public market since the late 1990s, and, since 1997, less cash has been returned to investors than has been invested in venture capital. Risk and reward have not correlated.

Vinod Khosla, a billionaire venture capitalist and cofounder of Sun Microsystems, tweeted a revealing line from an executive at one of his companies in 2012: “Entrepreneurs really are lousy at predicting the future… VCs are just as bad.”

2. Scale is more valuable than ever.

In the context of today’s immense technology-enabled opportunities, large companies have growth platforms that would take start-ups years to build. Incumbents have products with which to leverage new capabilities such as mobile devices, pervasive networks, the cloud, cameras and sensors. Social media can amplify brand power and customer relationships. Large companies also sit on mountains of market and customer data and are therefore in the best position to extract knowledge from big data.

The possibilities are startling. And tapping into them isn’t optional. A perfect storm of six technological innovations—combining mobile devices, social media, cameras, sensors, the cloud and what we call emergent knowledge—means that more than $36 trillion of stock-market value is up for what some venture capitalists are calling “reimagination” in the near future. That $36 trillion is the total market valuation of public companies in the 10 industries that will be most vulnerable to change over the next few years: financials (including insurance), consumer staples, information technology, energy, consumer goods, health care, industrials, materials, telecom and utilities. Incumbent companies will either do the reimagining and lay claim to the markets of the future or they’ll be reimagined out of existence.

3. The roadmap for leveraging scale while avoiding innovation landmines is clearer than ever.

Since the start of the Internet boom some two decades ago, so many companies have looked to information technology to innovate that there’s now a track record showing what works and what doesn’t. The problems that have stifled innovation in large companies are now known and can be avoided. These problems are not inherent to bigness. 273 companies that were on the Fortune 500 list 10 years ago are still thriving and remain on the list. Compare that 55% success rate against the 90%-plus failure rate of start-ups.

Large companies can out-innovate both existing and start-up competitors by undertaking a systematic innovation process of thinking big, starting small and learning fast. I outlined this roadmap for how to—and how not to—innovate in a recent LinkedIn post. It is also thoroughly annotated in my books Billion Dollar Lessons: What You Can Learn From The Most Inexcusable Business Failures of the Last 25 Years and The New Killer Apps: How Large Companies Can Out-Innovate Start-Ups (both written with Paul Carroll).

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I am not arguing that there is no place for entrepreneurship or start-ups. Start-ups as a group will continue to be an economic engine driving innovation, jobs and wealth. But any individual start-up, or even a small portfolio of start-ups, is far from a better bet for corporate veterans seeking better jobs or more successful innovation.

Rather than jumping from the frying pan into the fire, corporate innovators should consider staying put and focus on tearing down the barriers stifling their company’s innovation efforts. Yes, small and agile start-ups look very attractive when viewed from the confines of a big and slow bureaucracy. Big and agile is an even more attractive position.

Do you agree? I’d love to get your thoughts!