Day 15
Let Patterns Guide and Actions Decide

If you accept the teachings from Mike Tyson, Helmut von Moltke, and Rita McGrath in chapter 3, you accept that the idea that you worked on diligently in week 2 is wrong in some meaningful way. The critical issue, then, is identifying whether there’s at least hope that you could be moving in a productive direction.

So how can you tell whether an idea does in fact have potential? I know how most large companies approach this problem. They break out the spreadsheets. They ask innovators to create models projecting the potential of their idea. The model spits out a number—perhaps a net present value or a return on investment. The higher the number, the greater the chance that management will take the idea forward.

Scott Cook

Courtesy of Intuit

The approach is a reasonable enough way to compare projects with a high degree of certainty. After all, you can believe the assumptions in the analysis on the spreadsheet. But when you are innovating—particularly if you are doing something that hasn’t been done before—the numbers can be deceiving.

Scott Cook is the founder and chairman of Intuit, whose claim to fame is TurboTax, Quicken, and QuickBooks. These programs all bring financial discipline to users. Cook is also the source of perhaps my favorite quote about innovation: “For every one of our failures, we had spreadsheets that looked awesome.”

Don’t ever confuse an awesome spreadsheet with an awesome business. They are two different things.

On the flip side, sometimes a terrible spreadsheet can obscure a good business. Consider the case example of Align.¹ I first met this team in 2004 during a workshop we were doing for Procter & Gamble. The team was developing a probiotic supplement whose daily use could alleviate the symptoms of irritable bowel syndrome. More than 30 million people in the United States alone suffer from this condition. The best that most of the afflicted can do is to modify their lives to account for their condition.

The idea was brimming with disruptive potential. It addressed a pressing problem with no adequate solutions. And it proposed a potentially category-creating way to get the job done. The product had unique intellectual property, and consumers who tried it literally reported that their lives changed.

And, of course, it was about to get shut down.

Why the disconnect? The original market forecast said that the opportunity would be relatively small. Launching a new brand is expensive, and the team hadn’t yet worked out all the technological kinks. Big investment, high risk, small return, is not a recipe for corporate approval.

Yet, the Align team persevered. It turned out the critical factor in the market research was the degree to which customers would take the pill every day (in industry language, compliance). Consumers told researchers that they would probably take the pill occasionally. Of course, since consumers had never experienced the benefit, there was a reasonable chance that their self-reported figure didn’t reflect reality. The team conducted scenario analysis to identify what compliance would have to look like to justify a full-scale launch. Management agreed to follow more of a venture-capital approach, where the company would provide a small amount of seed capital to learn more about these assumptions. The team quietly launched the product over the Internet. It didn’t spend tens of millions in national advertising; rather it conducted targeted activities in a handful of cities. It turned out compliance in the controlled pilot was high enough to warrant expanding distribution to include Web sites like Walgreens.com. Further progress led to a national launch in 2009. The product won a coveted industry award as the most innovative launch in its category.

So, if good spreadsheets can obscure a crummy business, and crummy spreadsheets can obscure a good business, what do you do?

On the basis of his experience, Cook has developed a simple rule of thumb: he guides teams to assess the depth of the customer need and the novelty of their solution. His experience teaches him that getting those two things right typically lays the foundation of successful new businesses. Align certainly passed those two tests! I generally ask five questions of any entrepreneur with an idea:

1. Is there an important problem that customers can’t address because existing solutions are expensive or inconvenient? In the language of this book, is there a high-potential job to be done?
2. Is there a disruptive way to solve the problem in a simpler, more convenient, or more affordable way?
3. Is there a plausible hypothesis about an economically attractive, scalable business model? Answering this question doesn’t require a detailed financial model (which is wrong, anyway), but it does require a sensible story that’s at least conceivable—and a plan to turn that hypothesis into reality. (Day 16’s training describes how to come up with a quick view of an idea’s financial potential.)
4. Does the team have the right stuff to course-correct according to in-market learning? Remember, the odds are high that the first idea isn’t quite right. A team that is dogmatic and keeps trying to prove it is right is the wrong team for many innovation efforts.
5. Can early profitability be a choice? Ultimate success requires a profitable model. The sooner there is a line of sight to profits, the better. You might make a strategic decision to be unprofitable by investing in marketing, sales capability, and so on, but at least you know that the core part of the model works.

In both cases, Cook and I are relying on patterns. That’s not to say these are the only patterns or the best ones for different contexts. But the general guidance holds—if you are trying to figure out if your idea, approach, or plan has merit, go back and look at history. Look at what you or other people tried. What worked or what didn’t? For example, if you are trying to determine if you have enough savings to go back and get a doctoral degree, and your projections say you are going to write your thesis 50 percent faster than anyone in history, at least ask the question, “What does history teach us?”²

Let patterns guide … but let actions decide. The truth is that even something that fits a pattern perfectly can fail. Look up to Mike Tyson’s face on the Mouth Rushmore of Innovation to remember that you are going to be punched in the face. Something is undoubtedly wrong about your idea. And you have to figure out what is wrong. The only way you know whether you have a good idea is when someone pays money for your product or service, when the amount that someone pays supports a profitable business model, when you actually start to achieve the results you had hoped for, and so on.

That doesn’t mean you have to place a big bet or wait a long time to qualify an idea. Your goal is to learn as much as you can as quickly as you can by running focused experiments. Hungry for more? Keep reading! The other tips this week will provide further thoughts on this topic.

HOW-TO TIPS

1. Identify three of the most innovative moments in your life. What connects them?
2. Talk to a friend about a great idea that was killed because the numbers didn’t work.
3. Compare the financial projections of your company’s last five major innovations to the actual results.
4. See how well two successes and two failures answer the preceding list of five questions that I ask entrepreneurs. Do you see anything missing from this list?

Day 16
Calculate Your Idea’s Four P’s

Any marketer can quickly rattle off the so-called four P’s of marketing (product, price, place, and promotion). Innovators should also be able to quickly recite the four P’s (population, penetration, price, and purchase frequency) that capture their idea’s potential.³

Let’s rewind for a second. In mid-2010, I was sitting in a meeting where an innovation team was painstakingly working through a meticulously crafted spreadsheet detailing the growth potential of its idea. Executives trying to look smart lobbed in gotcha questions about specific assumptions. Much discussion ensued.

The team had asked me to observe, but not speak, during the meeting. I sat quietly and took some notes. After the meeting was done, I talked to the innovation team leader.

“That was a really good review,” she said. “The executives were really involved, and we have deeper buy-in to our plan.”

I had a different perspective. “I don’t think a single executive could tell you the essence of the idea, or what makes it compelling,” I said. “You survived the meeting, but you aren’t really any closer to convincing executives that they should invest in this idea.”

Before the meeting even took place, the team should have had insight into how big their opportunity had to be to matter to executives. People might say that size doesn’t matter, but believe me, size matters an awful lot, particularly inside a large company. Then, the meeting should have focused on two specific questions:

1. Which calculation—simple enough to fit on the back of a napkin—would cross the agreed-upon size threshold?
2. What evidence did the team have that suggested the calculation was plausible?

The four P’s of innovation help to answer these questions—and provide a great way to do a quick “sanity check” of any idea’s financial potential.

For example, a few years ago, I was working with a team at a consumer health-care company. The team members knew that their idea had to have the potential to cross $100 million in annual gross revenue to get support from leadership.

We knew that the population of severe sufferers for this particular condition was about 10 million people. The product the team was thinking about introducing would cost $20 per package. The team’s best guess was that the average consumer would purchase five packages a year.

So that’s $1 billion if the team penetrated the entire market. That meant that getting 1 million people—10 percent of the market—would allow the team to cross the magic $100 million mark. That’s the four P’s in action. Getting to $100 million in revenue required penetrating 10 percent of a 10 million population who purchased the product five times a year at a price of $20 per purchase.

Two pieces of advice. First, try to be as precise as you can about your target population. It’s easy to fall into the trap of defining the market so broadly that any threshold is achievable (“If we just got $1 from everyone in India …”). Create as small a market as possible, notably, the people who would constitute your dream customers. Second, don’t assert a penetration rate—solve for it after you’ve estimated the population, pricing, and purchase frequency.

This deceptively simple calculation neatly captures many of the elements of an idea’s business model. Does the idea target a niche or a mass population? Is it an occasional or frequent purchase? What channel would support the target price point? What kind of post-sales service would be necessary, given the purchase frequency?

Once you calculate the four P’s (and of course, if you add in a fifth—profit margin—you can look at profits instead of revenue), the focus shifts to the second question above: finding systematic ways to determine whether the assumptions behind the calculation have any hope of being true.

For example, our consumer health-care team looked at analogous product introductions and saw that 10 percent was not an unreasonable penetration estimate. Its market research supported a $20 price point. The simple approach built collective confidence in the team’s idea.

The deep thinking that goes into creating complicated spreadsheets for ideas can be very useful. But it also can be a way to mistake motion for progress. Make sure you can answer the simple questions before you worry about the complicated ones.

HOW-TO TIPS

1. Estimate the four P’s for a product you used today.
2. Calculate the four P’s for your company’s flagship offering.

Day 17
Reverse-Engineer Success

The hard part isn’t imagining success. It is achieving it.

This was the thought that went through my head as I looked at the one-page summary I had put together. It was February 2010. Earlier that month, I had begun to sketch out the idea called “Innosight Labs,” where we would offer business-building services to large corporations.

My colleagues generally expressed enthusiasm about the concept and supported taking it forward. They asked me what they thought would be a hard question: “What could this look like in five years?”

Answering that question was actually pretty easy. In a few years, the business would be monumentally successful and we’d be having all sorts of impact with all sorts of interesting companies. The idea fit day 15’s pattern, and day 16’s four P’s calculation looked solid. So, the real question was—what next? What could I do as an intrapreneur (like an entrepreneur but inside a company) to start bridging the massive gulf between an idea detailed in a PowerPoint slide and an impossible-to-disagree-with vision?

It’s easy to fall into two traps at this stage. One is to get paralyzed and to keep looking at—and iterating—your PowerPoint slides. Remember—patterns guide, actions decide. Shuffling slide decks wouldn’t teach me much. And this wasn’t like an image where if you stared long enough, a 3-D picture would emerge.⁴

The other trap is to go to the other extreme and start to run fast in a million directions. That approach clouds learning and makes it difficult to make meaningful progress on an idea.

Some people play certain songs to get inspiration. Me? I turn to the intellectual stylings of McGrath and Cook.

As mentioned in chapter 2, innovation master Rita McGrath (and her esteemed colleague Ian MacMillan) has a very useful way to break apart an idea. It essentially starts with defining success. What outcome would make you happy? Then reverse-engineer that outcome to identify things that would have to be true for success to be attainable. Remember day 14’s training (“bring it together”), and look at the idea from multiple perspectives. The goal is to generate a list of assumptions—stated and unstated factors that lie behind success. McGrath and MacMillan provide a wide range of tools to help with this discovery-driven planning process, from conceptual frameworks to spreadsheet templates.

Of course, the result of this kind of exercise can be overwhelming. You can have dozens, if not hundreds, of assumptions underpinning success. It’s easy again to freeze. Enter Scott Cook.

When my colleagues and I were talking to Cook as part of Innosight’s work with Procter & Gamble (Cook is on P&G’s board), he told us, “For any disruptive team at any one time, there are only maybe two questions they should be focused on. Once they get those two answered or those two hypotheses proven or disproven or altered, then there might be only one or two more in the next stage.”

Identifying the two questions that a team should focus on is a mix of art and science. When I am working on an idea, I focus on the five-element checklist detailed in day 15’s training (an important problem, a disruptive solution, a viable economic model, the right team, and a clear path to profitability). Then I hold conversations with smart people and use a bit of intuition and judgment to identify deal killers, assumptions that, if proven false, would force me to radically rethink my idea. Near-term activities then focus on learning as much about those deal killers as quickly as possible.

For Innosight Labs, two key questions emerged:

1. Was there demand for the service? If the answer was no, it wasn’t worth investing.
2. Could we integrate business-building services into our current offering? If the answer was no, we would have to create a standalone company to offer the service, which we did not want to do.

There were a bunch of other questions to answer (what would we have to build versus borrow? how should the business be led? and so on), but if we could address these two questions in the next ninety days, we would have a good sense of how to take the opportunity forward.

So what did we do? We found a lead client, where we delivered high impact through integrated services. It was a useful proof of concept. But, six months later, we couldn’t find a viable second client. We decided that there were sufficient specialist providers offering compelling solutions, so decided to focus on our consulting and venture capital businesses and leave business building to the business builders.

This technique—imagining success, working backward to understand what would have to be true for success to be plausible, and pinpointing the most critical issues (the deal killers)—is a generally useful approach. We used a variant of it when we were deciding in 2008 whether to shift our Strategy & Innovation publication from a printed newsletter to an online model.

We knew that publishing a high-priced bimonthly printed newsletter that had holes in the margins for readers to place it in a three-ring binder just wasn’t right. We needed something simpler and more widely available. But we worried that subscribers who paid relatively steep prices for the newsletter might rebel if we shifted to freely distributed online publication. We were prepared to offer them goods and services to compensate them, but didn’t want to part with the most precious commodity in a young company—cash!

So we reversed the problem. We identified the maximum amount we were willing to lose in the transition. We calculated the rate at which subscribers would have to demand refunds before we hit that threshold. We simultaneously looked for comparable figures from other publications that had made similar shifts. The simple exercise increased our confidence that any downside risk was manageable, so we proceeded with the shift.⁵

The approach has crept into my personal life as well. When we had made the decision to move to Singapore, my wife and I sat down and said, “What would constitute a great first week in Singapore?” We then worked backward to identify the critical activities that would make the transition as seamless as possible. We had certain assumptions about long-lead-time items, so we addressed them early (lining up movers, developing a perspective on schools for our son, selling our cars) so that we could avoid the last-minute scramble.⁶ Using day 9’s training, we drew on diverse sets of inputs, such as online guides about living in Singapore and first-person perspectives from other expats. We didn’t get everything right, but reverse-engineering success certainly helped us.

If you ever feel frozen, try to break apart the problem and seek simple, actionable steps to start a journey that can make the impossible possible. Remember, too, that this isn’t a onetime exercise. You should constantly be assessing what you know and don’t know, to make sure you are focused on the most important things.

HOW-TO TIPS

1. Look at something you did that didn’t work out. What assumption did you make that proved false?
2. Talk to a friend who is thinking about starting a business. Work with him or her to identify the two most critical questions to answer. Do the same thing on something you are working on.
3. Go to TechCrunch.com, and read a story about a hot start-up. Write down two questions you would be worried about if you were the CEO.

Day 18
Test Critical Assumptions

The plan looked great on paper (plans have a way of doing this). Our team at Innosight was going to create a new business to attack the “missing middle” in the Indian men’s grooming market.⁷ A single visit to India showed me the promise of this opportunity. If you wanted a shave or haircut, you could go to a high-end salon at a six-star hotel and have a truly world-class experience. Or, you could get incredibly affordable service from the barber whose “salon” was a single chair that sat alongside the road. His instruments at least looked not-too-unhygienic. But if you wanted something in between—a solid experience at a reasonable price—you were pretty much out of luck.

Razor Rave’s market research vehicle

Photo by Vijay Raju

We called our idea Razor Rave. The plan involved an innovative retail store format that essentially put a single barber chair inside a small pod. Sound familiar? The idea was borrowed liberally from QB House, the simple haircut solution described in day 10’s training. The pod’s small footprint provided low overheads and high degrees of flexibility. We would use world-class products and envisioned tie-ups with the Gillettes and L’Oréals of the world.

Remember, research is valuable, but research has its limits. You can only truly know whether you are right or wrong through action. Good innovators are always on the lookout for ways to run tests—informed, of course, by their research—that can turn assumptions into knowledge.

So would consumers be interested in Razor Rave? There was only one way to find out. We rented a truck and created a salon on wheels by putting a barber’s chair on the back of the truck. We drove the truck around the streets of Bangalore for a couple of weeks. High levels of consumer interest told us that the market was ready for to pay price premiums over the roadside barber or local low-end salons. Total cost of learning? About $3,000. We were off!

Then, we discovered what we ended up dubbing the “hero barber” problem. We had launched a few pods on the streets of Bangalore to try to figure out if we really could make the business model work. We quickly found that having a good barber was absolutely critical to draw enough customers to even dream of hitting our financial forecasts. A good barber already had a loyal group of customers who would go out of their way to frequent the Razor Rave pod. These barbers were able to take new customers who wandered in, intrigued by the pod’s format, and turn them into repeat customers.

The hair cutters were, in fact, too good. You see, the single-chair format clearly made the barber a hero. Once the barber figured out how critical he was to the success of the business model, the demands started coming. We were left with the unappealing choice of increasing the barber’s wages to the point where our economic model began to fall apart, or suffer high attrition. We couldn’t find an obvious way out of this quandary without completely redoing the business model, so we decided that it was closing time for Razor Rave.

This story demonstrates an important principle. When you are doing something new, you often don’t know the most important assumptions you are making until you put the whole system together. Understanding the subtlety of the hero barber problem—we needed to “hero” the barber to make the business work, but the second we made the barber a hero, the business didn’t work—required what academics would call an integrated experiment. As my colleagues Matt Eyring and Clark Gilbert noted in a 2010 Harvard Business Review article, “These are designed to test how various elements—the actual business model and operations—work together. In essence, they involve launching the business, or some part of it, in miniature.”

It sounds a bit daunting, but it doesn’t have to be. A detailed spreadsheet that estimates the income statement, balance sheet, and cash flows for a new idea is a form of an integrated experiment, because it shows how the entire business functions. Simple models or simulations can also help to identify what might happen when parts of a system come together. An integrated experiment doesn’t have to produce huge results. The point is to learn about the “unknown unknowns”—or the things you didn’t know you didn’t know.

Integrated experiments contrast with targeted experiments, where you isolate a specific variable and test it. Targeted experiments work well when there is a clear, identified risk that can be tested directly.

For example, a couple of years ago, we were helping a team at Turner Broadcasting System, Inc. (whose cable channels include CNN, TBS, TNT, and the Cartoon Network). The team had an idea for an interesting advertising model. Studies showed that advertisements that had some kind of contextual meaning resonated with consumers. For example, when you search for something on Google, the connection of advertisements to specific search terms makes the ads more memorable. The team wondered whether it couldn’t bring a similar model to television. To illustrate the idea, the project leader showed people a scene in a popular movie with a high-speed car chase. The action stopped, and the first commercial was for BMW’s latest car. Memorable, isn’t it?

One of the critical questions was whether Turner Broadcasting’s programming had enough identifiable points of context to support a widespread program. The team designed a clever test. It gave a group of summer interns two weeks and asked them to identify points of context that might be of interest to a select group of advertisers in a handful of movies and television shows to which Turner Broadcasting had rights. Not only did the interns find plenty of points of context, but the results of this focused experiment ended up forming a vital part of the pitch Turner Broadcasting made to advertisers for the offering it dubbed TVinContext.

Thomas Edison appeared on the Mount Rushmore of Innovation for his quip “Genius is 1 percent inspiration and 99 percent perspiration.” If you (or those summer interns) aren’t sweating, you aren’t innovating. Whenever you have an idea, try to think about the quickest way to learn about critical assumptions—or to find out the critical assumption you didn’t realize you were making.

HOW-TO TIPS

1. List the five biggest assumptions behind your idea; design and execute ways to learn more about those assumptions without spending any money.
2. Identify a way to learn more about an idea in sixty minutes or less. Execute it! See my blog at http://blogs.hbr.org/anthony/2011/03/60_minutes_to_a_more_innovativ.html for some ideas.
3. Think about a recent life change. What advice would you give yourself before the change? What could you have done to learn more about “unknown unknowns”?

Day 19
Bring Ideas to Life

Testing sounds a bit academic, but it shouldn’t be. Look carefully at the examples in the previous pages. Align sold its product to consumers online. Razor Rave ran tests to see if it could get people to come inside the shaving truck. Turner Broadcasting pitched its ideas to advertisers. Selling—and developing the right collateral to support the sales process—is a critical skill for any innovator.

In fact, a good innovator is always in sales mode. In the course of a day, an innovator could have to accomplish many typical sales tasks:

• Convince customers to buy something they have never bought before.
• Get skeptical senior management to invest in doing something different.
• Pry money out of the hands of tight-fisted venture capitalists.
• Urge friends or coworkers to join an underfunded business that statistics suggest is going to fail.
• Cajole a reticent department to free up a resource.
• Push a team to continue forward when bad news inevitably strikes.

Selling is a great way to test an idea’s most critical assumptions. And it is very hard to sell something without bringing the idea to life in some way. Just try to get people excited about a dense PowerPoint presentation populated with facts and figures. It’s next to impossible. For example, figure 7-1 shows screenshots from a pitch for an idea we developed for a consumer electronics company. Do you think this kind of pitch resonated more than PowerPoint slides?

Start instead by developing a simple way to capture the essence of your idea. Remember the Hollywood pitch described in Chapter 1? The approach crystallizes an idea into an anchor analogy (what is it similar to) and a twist (what makes it unique). I’ve found that ideas that lack a good Hollywood pitch are often hard to communicate to customers and stakeholders. While a good Hollywood pitch doesn’t mean the idea is any good, it at least means that people can quickly understand it.

People like to see and touch things. Beyond Hollywood pitches, we’ve used the following to help bring ideas to life in our efforts:

• Ninety-second videos
• Mock magazine advertisements describing the envisioned product or service with a semiclever tagline (believe it or not, thinking of a tagline helps to bring great clarity around an idea)
• MacGyver-type prototypes (a prototype held together by real or virtual duct tape)⁸
• Storyboards that present a multiframe visual (like a cartoon) depicting how a customer would experience a product or service
• Skits depicting television advertisements
• Semifunctional Web sites created using free services like Wix.com
• A newspaper article five years in the future profiling the transformational impact of an idea

These suggestions may look a bit intimidating, but they are surprisingly accessible. For example, my ten-year-old niece created a pretty slick video using a freely accessible tool. The goal isn’t to produce something that looks like it was done by a professional. Rather, the goal is to ensure that you have really considered the essence of your idea and to help yourself to communicate it more clearly than a detailed PowerPoint slide ever could. As an added bonus, every person I have seen follow one of these approaches has learned more about his or her own idea. After all, you also have to sell to yourself whatever it is that you are making or doing!

The other trick is to have other people do the pitching for you. This could involve having a customer come to an important meeting to describe how he or she feels about your idea, or showing a video testimonial. Even the most analytically minded people react strongly to hearing a real person give a personal reaction to an idea.

If you do feel compelled to do PowerPoint, at least follow Guy Kawasaki’s 10/20/30 rule—ten PowerPoint slides, designed to be discussed in twenty minutes, with no smaller than 30-point font. But with the tools at our disposal today, a PowerPoint presentation should really be a last resort. Do your homework, of course, but don’t bore people to death with it.

HOW-TO TIPS

1. Watch an online video of someone you consider an excellent salesperson. Write down the three things this person does to accentuate a pitch.
2. Write down a one-sentence slogan that you would put on a magazine advertisement for your idea.
3. Spend five minutes pitching a concept from a chapter in this book to a friend.
4. Watch a TED video, and analyze why TED speakers are so effective at selling an idea—at changing their listener’s view between the beginning and the end of a talk.

Day 20
Embrace Everyday Experimentation

Coming up with and executing the kinds of activities described in the past few days’ training might feel a bit daunting. It doesn’t have to be if you make experimentation part of your everyday routine.

Many iconic innovators are portrayed as highly experimental. Innovation master Thomas Edison was famous for being a fiddler and a tinkerer. British entrepreneur and Virgin Group chairman Sir Richard Branson never met anything he wouldn’t try at least once. Experimentation is a very healthy thing. Not only does it get you to try different things, but it also prepares you for those sudden shifts that increasingly seem to characterize our lives.

Sometimes the notion of experimentation scares people, because it sounds like the sort of thing that requires specialized equipment, knowledge, and funding. It doesn’t. Some of the best experiments can take place in your head. Just as chess players quickly visualize several moves ahead when determining their move, innovators conduct thought experiments to figure out an idea’s potential. Mark Johnson shares a great example of a thought experiment in Seizing the White Space. He describes how the chemical company Dow Corning was thinking about rolling out a new low-cost Web site to distribute its products (day 24 discusses this idea in more depth). Historically, Dow Corning relied on its salaried sales force to sell products to customers. The innovation team did a thought experiment to project what would happen if Dow Corning launched its Web site within the mainstream organization. Johnson explains the result: “The new model got crushed. It was too foreign to Dow Corning’s current modes of working. The way forward became clear. The new venture would need to be free from the core business model if it was going to thrive.”

One of the best ways to get good at experimentation is to find ways to embed it into every day activities. Here’s a personal example.

I was in a hotel.⁹ I woke up and started looking around for the coffee maker. After all, for years my day had started with a hot cup. Like all habits, this one didn’t take much thought. It was just what I did in the morning. It was an easy habit to maintain because seemingly every hotel has a small coffee maker in it.

Except that this hotel room, for whatever reason, had no coffee. I had a few things to do, so I couldn’t go downstairs and grab a cup of coffee. It wasn’t that big a deal, because surely, there would be coffee at the meeting I was attending. But there was none in sight. I figured I was set up for a disastrous day, but I actually found myself functioning better in the morning when there was a longer gap between waking up and having coffee.

It could have been a random occurrence tied to the specifics of the circumstance, so I began to experiment more consciously. One day, I’d wake up, work for a bit, have a cup of coffee with breakfast, then shower. The next day, I would wake up, immediately have a shower, have breakfast, go to work, and have a cup later in the morning. These weren’t perfectly controlled experiments, but I did begin to notice that I tended to function best when there was some kind of space between waking up and ingesting caffeine.

Think about all the small experiments you could run in a day. Change how you commute to work. Alter the order of the things you do in the day. Eat five small meals instead of three large ones. Don’t shave one morning. The avenues for experimentation explode in the office. Shut your messaging app of choice off until 10 a.m. Start the day by logging into Facebook instead of e-mail (or e-mail instead of Facebook if you are under thirty-five). Commit to being the last person to speak in a meeting. Introduce your comments first.

Karl Ronn, the former P&G leader who described the importance of being close to context in research in day 6’s training, also believes in being close to context in experimentation: “Always try the experiments yourself. If you want someone to do it, you have to at least imagine trying it yourself and find out what surprised or confused you. This is the empathy that is needed.”

Once you start to think about experimentation, it is hard to stop. You will begin to see dozens of daily tasks for which experimentation might show you a better way.

Think back to high school science class to get the most out of experimentation. Document your hypothesis. “If I make a left on Beacon Street, I will shave four minutes off my commute.” “I can avoid the 3 p.m. energy lull if I have fruit at 2 p.m.” “I will finish editing that report if I turn off e-mail for an hour.” Then, of course, check the results with what you hypothesized.

Experimentation need not be expensive or time-consuming. One of the most common questions from people inside companies is, “What do I do if I can’t get my management to give me a larger budget or more staff?” Of course, you can beg, plead, or pout. Or you can prove it. Find some kind of way to scrape together low-or no-cost experiments that address management’s most critical assumptions. Show management what you learned without resources. It makes quite a compelling argument for what you could do with a bit more resources.

HOW-TO TIPS

1. Identify three everyday routines that could be grounds for experimentation.
2. Look at a looming life decision. Identify two options. Ask what would have to be true for you to choose option two. Identify an experiment that could give you more information.
3. Take an idea that you have. Identify three costless ways to learn more about the idea’s potential.

Day 21
Savor Surprises

This week’s training has been all about assessing and testing an idea. Of course, you aren’t doing this for fun. You are trying to gain confidence that you are moving in the right direction—or get critical learning that helps you change your idea in ways that increase the odds of success (this is what innovation master Steve Blank would call pivoting).

Remember that innovation is an iterative process. You might go back to day 14 and reframe your plan. Or you might hop back to day 3 to rethink the job you identified as needing to be done. Or perhaps you will turn to day 17 and identify two new questions to answer. Before you do any of these things, you need to make sure you have learned the right things from your tests.

Unfortunately, extracting that learning isn’t easy, largely because of a factor that psychologists call confirmation bias. In everyday terms, it means that people see what they want to see. If you have a belief, you see the things that conform to that belief, and you ignore the things that don’t. Confirmation bias explains why two people can look at the same data and see completely different things.

One of the great examples of confirmation bias at work comes from a 1954 study by Albert Hartorf and Hadley Cantril. The researchers showed students from Dartmouth and Princeton a filmstrip of a controversial football game between the two teams. Perhaps not surprisingly, the two groups saw the game very differently. Princeton viewers thought that the Dartmouth squad had committed more than twice as many violations as had Princeton’s team. Dartmouth students thought the two teams had committed an equal number of violations. Neutral observers thought Dartmouth had committed more fouls, but nowhere near the number that Princeton students reported. As the great philosopher Paul Simon said, “Still a man hears what he wants to hear and disregards the rest.”¹⁰

Innovators who are testing their ideas need to be very aware of confirmation bias. Think about the old parable about the two shoe salespeople who go to a market where the locals don’t wear shoes. One seller sends a note to the head office: “No one wears shoes here; returning home.” The other salesperson sends a note saying: “The market is wide open! Please send more shoes.”

Where you stand indeed depends on where you sit.

I saw an example of confirmation bias up close while working with a leading consumer packaged-goods brand. We’ll disguise the story by calling the company Gargantuan, Inc., and pretend that the company makes a delicious breakfast cereal. The company had long prided itself on its technical expertise. While competitors mostly fought battles of marketing, Gargantuan had legions of scientists working on improving the measurable quality of its product. Over the years, Gargantuan increased the space between it and its leading competitors and obtained dominant market share. Its cereal was crunchier than its leading competitor, Simpleton, by 30 percent; had 20 percent more nutrients; and tasted 15 percent better. Obtaining this quality required that consumers use a low-cost bowl affixed to their kitchen counter that worked seamlessly with Gargantuan’s cereal to produce the end benefit. Since everyone eats in the kitchen and the bowl was simple and inexpensive, no one complained about this solution.

Then, in the mid-1990s, Simpleton introduced a very different solution. It put its cereal in a bar that allowed consumers to eat it on the go. Simpleton intentionally sacrificed quality in pursuit of convenience. Gargantuan’s scientists found that the gap in crunchiness, nutrients, and taste increased to 40, 30, and 25 percent, respectively.

Those findings came from a carefully constructed piece of research Gargantuan commissioned to understand Simpleton’s new solution. The large company also asked consumers which solution they preferred. The answer? A majority of consumers stated that they preferred Simpleton’s solution.

This puzzled the scientists. “But consumers report that we are better along every measurable dimension,” the scientists said. “How could they prefer Simpleton?”

Of course, one explanation (the right one) was that while Gargantuan rated better along those traditional dimensions, more and more consumers sought convenience. But that’s not the way the industry traditionally worked. So the Gargantuan scientists concluded that they must have asked the question the wrong way. They rewrote the survey, running a series of pretests to make sure that survey takers understood the intent of each question. They didn’t change the essence of any of the questions; they didn’t start working on a competitive response to Simpleton’s fast-growing offering. They ran the survey, and waited for the result to come back.

The results didn’t change a bit. Consumers still reported that Gargantuan’s offering was better; they still reported preferring Simpleton’s offering. Punishingly, the six months Gargantuan spent fine-tuning its research instrument gave Simpleton time to introduce a new and improved version of its convenience-based product, putting Gargantuan even further behind.

Scott Cook (three mentions in week 3!) guides people to savor surprises. That is, instead of looking for data that fits your hypothesis, specifically study the data you didn’t expect to get. Scientists would call this studying the anomalies, and it is in those anomalies where the great insight often lies. After all, if an experiment showed you what you expected, you didn’t need to run the experiment.

How do you avoid confirmation bias and more successfully savor surprises? Consider these three tricks. First, don’t separate researchers and decision makers. If there is separation, researchers will feel an overwhelming need to summarize their market research in easy-to-digest sound bites. That means throwing away outliers and anomalies. If decision makers experience the raw data, they can spot signals that third-party researchers might miss. When we are working with companies to pilot new businesses, we insist on conducting any consumer-facing work ourselves so that we can pounce on these signals and make adjustments as we learn new information.

The second trick is to frame things as a reverse of what you are truly expecting. I tell teams that their initial hypothesis when investigating whether to advise clients to invest in a new-growth business should always be “We should not invest in this new-growth business.” That means they carefully study the results that fit that hypothesis, and, of course, carefully study the “outliers” as well.

Finally, involve people who don’t have “skin in the game” in the discussion. Thought leaders who describe the wisdom of crowds note that groups outperform experts because while individuals suffer from confirmation bias, a group does not (individual biases essentially cancel out, except, of course, when manias, bubbles, and herd behavior take over). Even the injection of one outside voice can help you savor surprises.

You are probably wondering what happened to Gargantuan, right? Well, the company got its act together. After losing significant market share for a couple of years, it introduced a product that successfully stopped Simpleton in its tracks. And it started work on an innovative product that would eliminate the need for breakfast altogether.¹¹

HOW-TO TIPS

1. Identify a contrarian friend who can help you avoid confirmation bias.
2. Read detailed qualitative comments from a recent market research report.
3. Look at outlying data that was discarded from a management presentation to identify gems worth savoring.

Week 3 Wrap-Up

The focus of week 3 was assessing and testing your innovative idea. You hopefully answered four questions this week:

1. How confident am I about my idea’s potential?
2. What are the most critical assumptions?
3. How can I design experiments to learn about those assumptions?
4. What do the experiment’s results suggest about my idea’s potential?

More broadly, remember three phrases.

1. Deal killers: Assumptions that, if proven false, mean your current strategy is not viable.
2. Discovery-driven planning: An approach that involves imagining success, determining what would need to be true for success to be achievable, and executing tests around critical assumptions.
3. Test and learn: No matter how smart you are, your first plan is sure to be wrong—test and learn to figure out how.