Good theories are not meant to teach us what to think. Rather, they teach us how to think.

When you see numerical data, remember that it was created by people: individuals or groups of people who decide which elements of the phenomena they include in published data and which they overlook and destroy. Hence, data reflects bias.

Clarity on the jobs Deseret News could distinctively solve provided not only a compass for how to shape its solutions and how to compete, but also a filter for what to not do. Take the example of covering the legislative session in Congress. Traditional news organizations would say, “We’re covering the legislature,” and provide broad coverage across all the bills and debates happening in the session. But the jobs-based lens resulted in a different approach: “For our A1 page coverage on the legislative session, there might be thirty bills coming forward. But we would focus on just the five issues that were going to affect your family. Once we had this job related to faith and family defined, it completely shaped the way we searched for, discovered, and covered news. It was about understanding the job of the reader—putting yourself in those shoes.”

An Intuitive Playbook

A leader has to count on employees up and down the company’s ranks to make the right choices in everyday decisions. Those choices will determine a company’s real strategy. As we discussed earlier, the way an organization’s employees work together toward common goals is the basis of its culture. If they work together with a focus on the Job to Be Done, a culture will emerge that reinforces that job and stays deeply connected to it. If that culture has formed around the job, people will autonomously do what they need to do to be successful.

But those instincts aren’t formed overnight. Rather, they are the result of shared learning—of employees working together to solve problems and figuring out what works. As long as the way they have chosen keeps working to solve a problem, the culture will coalesce and become an internal set of rules and guidelines that employees in the company will draw upon in making the choices ahead of them. The advantage of this is that it causes an organization to become self-managing. Managers don’t need to enforce the rules. They understand the “commander’s intent”—a military term that explains why soldiers up and down the ranks know how to make the right choices absent a specific order. They are clear on the commander’s goals and priorities.

Business leaders need to ensure that employees everywhere in the company make the right choices every day without requiring constant supervision. This is nothing new: as far back as ancient Rome, emperors would send an associate off to govern a newly conquered territory thousands of miles away. As the emperors watched the chariot go over the hill—knowing full well they would not see their associate again for years—they needed to know that their understudy’s priorities were consistent with their own and that he would use proven, accepted methods to solve problems.

A clearly defined job spec that everyone understands can serve the same purpose—a focal point for employees to make the right decisions without being told specifically what to do each time. Absent a specific directive, employees know how to balance the tradeoffs that necessarily come with any new initiative. What’s most important? What can’t we compromise on? What’s the ultimate goal? What’s my role in achieving that ultimate goal? Jobs Theory provides you with the right set of lenses to make everyday choices that connect to the jobs you are solving in customers’ lives. Jobs Theory provides a language of integration, whereby marketers, engineers, salespeople, and customer service employees can communicate with each other, rather than talk past one another.

As Mercer’s Jacques Goulet sees it, the concept of a Job to Be Done serves this purpose perfectly “because of its simplicity. It’s a simple expression—one-syllable words. Jobs. To. Be. Done. It’s not overly engineered and overly complicated. But it’s powerful, it’s simple, and it focuses the mind.”

It’s not easy to get these jobs-based goals right—as we’ve discussed, jobs are complex and nuanced and require a deep understanding of the progress a consumer is trying to make. But when you do, the impact on an organization’s productivity can be dramatic, because the resulting clarity enables a much greater share of the organization’s human capital to be deployed with the right balance of autonomy and alignment. Since we know that strategy is formed in the everyday choices employees make about resources, processes, and priorities, clarity about what jobs your customers are hiring you to do provides a kind of intuitive playbook.

Having a jobs-focused organization, the CEOs we interviewed for this book tell us, leads to four categories of clear benefit:

- Enable distributed decision making with clarity of purpose—employees throughout the organization are empowered to make good jobs-focused decisions and to be autonomous and innovative.
- Align resources against what matters most—and free resources from what does not.
- Inspire people and unify your culture in service of what they care about most.
- Measure what matters most—customer progress, employee contributions, and incentives.

[...] the organization is so focused on customers’ jobs that it allows itself to operate like a “network of start-ups” in which small teams launch new product pilots with minimal senior-level approval because they are so clearly aligned with jobs.

Intuit’s development teams would extensively survey customers about what new features they’d like to see in Intuit products. And customers had a lot to say. They’d rattle off an expansive wish list. “They’d ask for 150 features,” Cook says. So the team jumped on that feedback. Development teams would spend weeks arguing and debating which of the list of potential new features were most important to provide. Everybody, Cook says, was guided by what he or she thought was right for the customer. But in reality, it offered no guidance at all. “We got into feature chase,” Cook says. “Too often we’d go look at what customers were asking for and build it.” But absent a clear understanding of the job the customers were hiring that product to do, “there was simply no way to differentiate which features were the right ones. It’s like navigating without a compass.”

[...] when the job has a voice in an organization, individual work streams have meaning and employees understand why their work matters. A well-articulated job provides a kind of “commander’s intent,” obviating the need for micromanagement because employees at all levels understand and are motivated by how the work they do fits into a larger process to help customers get their jobs done.

There’s an even more fundamental problem with data. Many people view numerical data as more trustworthy than qualitative data. But where does “objective” data come from? The data used in many research projects comes from companies’ financial statements, for example. Is this objective? H. Thomas Johnson and Robert S. Kaplan showed quite convincingly that the numbers representing revenues, costs, and profits in financial statements are the result of processes of estimation, negotiation, debate, and politics in allocating overhead costs that can produce grossly inaccurate reflections of true cost and profit.

We pick and choose the data that suits us. “Decisions don’t get made. They happen,” observes neuromarketing expert, Gerald Zaltman, a longtime colleague at Harvard Business School who has spent years studying how managers represent their ideas and apply their ideas and knowledge. Among the common mistakes he’s identified? “The tendency to treat facts as insights and leap directly from data to action,” Zaltman recently wrote in the Journal of Advertising Research. “It is common when research is used to prove points rather than as fuel for imaginative insight.”

Your sales, marketing, and R&D teams are all in the same room with the business-unit head, discussing where to focus innovation resources. The sales team is sure it knows what customers want because it’s constantly talking to its customers about their most pressing needs. The marketing team has reams of ideas for leveraging the existing brand, perhaps by offering new versions, new flavors, new colors, or special offers. The R&D team is excited about new features and benefits it’s working on, driven by cool new technologies or applications. And the head of the business is relentlessly focused on getting things into the market that have a shot at helping the P&L by the end of the year. Needless to say, each team comes armed with carefully constructed supporting data that offers a model of reality through the lens of its functional responsibilities, performance metrics, and financial incentives. All the teams are working with a kind of confirmation bias—seeing only the information that tends to support their point of view. None of these perspectives is wrong, but the point is that none is truly objective. And more important, not one of the models reflects the customers' job.

So often, companies are blindsided by a competitor’s innovation or what turns out to be a missed opportunity. “Why didn’t we see that coming??” The truth is, you had no chance of seeing it because you weren’t looking for it. In the words of Sherlock Holmes, “There is nothing more deceptive than the obvious fact.”

Psychologists have explained that when we hold conflicting ideas or beliefs in our minds, this “dissonance” produces reactions of stress and anxiety that we naturally seek to minimize and avoid. Uncomfortable truths are just that—uncomfortable. As data comes in, it’s not that we lose objectivity—we never had it to begin with. I can’t help but think of every parent-teacher conference I ever attended—my wife and I would always leave the room with totally different perspectives on what we just heard. I heard, I’m sure, the things that confirmed my expectations. My wife, I suspect, heard something closer to what the teacher actually said. We make the data and the messages conform to what we believe.

When a company makes big investments in developing relationships with customers, natural incentives arise to find ways to sell more products to existing customers. The marginal cost of selling more products to existing customers is very small—and the profit is oh so alluring. We call this “surface growth.” Companies see products all around them made by other companies and decide to copy or acquire them. But in doing so, companies often end up trying to create many products for many customers—and lose focus on the job that brought them success in the first place.

[...] consider how doctors often treat symptoms, rather than getting to the cause of the problem. High blood pressure, for example, is a symptom of several different diseases. But most drugs for people who struggle with high blood pressure focus on getting those numbers down, rather than curing what’s causing them in the first place.

As data about operations broadcasts itself loudly and clearly, it’s all too easy—especially as the filtering layers of an organization increase—for managers to start managing the numbers instead of the job.

But what feels like progress can prove to be poison if it leads managers to mistake the model of reality that active data offers for the real world.5 Data is always an abstraction of reality based on underlying assumptions as to how to categorize the unstructured phenomena of the real world. Too often, managers conveniently set this knowledge aside: data is man-made.

The railroads were in trouble, Levitt wrote back in 1960, “because they assumed themselves to be in the railroad business rather than in the transportation business.”

People don’t want to buy a quarter-inch drill. They want a quarter-inch hole.

Processes are powerful. By their very nature, processes are set so that employees perform tasks in a consistent way, time after time. They are meant not to change. When processes are organized around the customer’s Job to Be Done—optimized to facilitate the progress and deliver the experiences that customers seek—processes are the source of competitive advantage.

Stack fallacy applies outside of the technology sphere, too. For instance, it might be easy for you to have a vegetable garden. You know what herbs and vegetables you like—and all you have to do is to learn how to grow them and use them in your own cooking. On the other hand, your understanding of growing and using herbs does not prepare you to open and run a restaurant. In fact, eight out of ten restaurants fail within five years. Knowledge of production, Sharma says, is not the same thing as knowing what customers are looking for.

Ford’s core mistake—of focusing on the product spec rather than the job spec—gets repeated all the time. In fact, the misstep is so common in the high-tech world, that Anshu Sharma of Storm Ventures has earned justifiable recognition for calling attention to the problem, which he has dubbed “stack fallacy.” Stack fallacy highlights the tendency of engineers to overweight the value of their own technology and underweight the downstream applications of that technology to solve customer problems and enable desired progress.

[...] peace of mind is an essential, not a luxury upgrade.

Amazon has imported what are essentially subroutines into its operating processes, too, and their power and efficiency are very apparent. This is a huge advance over the traditional practice of “sharing best practices” across regions. Instead, the use of subroutines poses the question of “Are we likely to need to repeat this process (or subroutine) in other activities?” This creates a very dynamic view of an organization as a collection of processes wherein each process is a string of subroutines—some custom and some modular imports—that align perfectly with a customer’s Job to Be Done.

Jobs are not flexible—they have existed for years and years, even centuries. But how we solve for jobs varies over time. The important thing is to be attached to the job, but not the way we solve it today. Processes must flex over time when a better understanding of customer jobs calls for a revised orientation.

What gets measured, gets done.

Creating the right metrics is hard. But so important.

Jobs Theory changes not only what you optimize your processes to do, but also how you measure their success. It shifts the critical performance criteria from internal financial-performance metrics to externally relevant customer-benefit metrics.

If a company has strong processes in place, managers have flexibility about which employees they put on which assignments—because the process will work regardless of who performs it.

W. Edwards Deming, father of the quality movement, may have put it best: “If you can’t describe what you are doing as a process, then you don’t know what you are doing.

Achieving a purpose brand is the cherry on the top of the jobs cake. Purpose brand, when done well, provides the ultimate competitive advantage. Look no further. Don’t even bother shopping for anything else. Just hire me and your job will be done.

When competitors successfully enter markets that seem closed and commoditized, they do it by aligning with an important job that none of the established players has prioritized.

The “struggle” is costly—you’re already spending time and energy to find a solution and so, even when a premium price comes along, your internal calculus makes that look small compared with what you’ve already been spending, not only financially, but also in personal resources.

The reason why we are willing to pay premium prices for a product that nails the job is because the full cost of a product that fails to do the job—wasted time, frustration, spending money on poor solutions, and so on—is significant to us.

No detail was too small to consider for its experiential value.

I have found that creating the right set of experiences around a clearly defined job—and then organizing the company around delivering those experiences (which we’ll discuss in the next chapter)—almost inoculates you against disruption. Disruptive competitors almost never come with a better sense of the job. They don’t see beyond the product.

In recent years Toys“R”Us, Walmart, and even Disney have all tried to challenge American Girl’s success with similar dolls (Journey Girls, My Life, and Princess & Me)—at a fraction of the price—but to date, no one has made a dent. American Girl is able to command a premium price because it’s not really selling dolls. It’s selling an experience.

One of the fundamental mistakes that many marketers make is to collect a handful of data points from a huge sample of respondents when what they really need—and this interview illustrates—is a huge number of data points from a smaller sample size. Great innovation insights have more to do with depth than breadth.

The original goal involves establishing a timeline of all the triggers that actually led to the eventual decision.

What are they really trying to accomplish and why isn’t what they’re doing now working? What is causing their desire for something new? One simple way to think about these questions is through storyboarding. Talk to consumers as if you’re capturing their struggle in order to storyboard it later. Pixar has this down to a science: as you piece together your customers’ struggle, you can literally sketch out their story:

Once upon a time . . .
Every day . . .
One day . . .
Because of that, we did this . . .
Because of this, we did that . . .
Finally I did . . .

You’re building their story, because through that you can begin to understand how the competing forces and context of the job play out for them.

Customers are always reluctant to fire something until they are sure they have something better, even if they’re firing simply living with an imperfect solution.

[...] the job has to have sufficient magnitude to cause people to change their behavior—“I’m struggling and I want a better solution than I can currently find”—but the pull of the new has to be much greater than the sum of the inertia of the old and the anxieties about the new.

ING Direct went to the extraordinary lengths of opening “cafés” in locations across the United States and Canada to relieve customers’ anxiety about a virtual bank. You can drop into one of the cafés, but you can’t actually perform any traditional teller-based cash transactions. You can talk to a staff member or use the ATM, but the café’s primary purpose is to reassure consumers that it’s a “real” bank—and build the brand with its presence. The fact that SNHU is a not-for-profit—with a genuine campus—reduces online students’ anxiety that it’s some kind of fly-by-night focused on fleecing every possible dollar from unwitting students. Overcoming customer anxieties is a very big deal.

Companies don’t think about this enough. What has to get fired for my product to get hired? They think about making their product more and more appealing, but not what it will be replacing.

The most commonly tracked is what we call the “Big Hire”—the moment you buy the product. But there’s an equally important moment that doesn’t show up in most sales data: when you actually “consume” it.

You can’t do design requirements in a conference room. You have to get out in the wild and live it.

If you are to create products and services that customers want to pull into their lives, you have to drill deep and look wide, identifying not only the functional, but also the social and emotional dimensions of the progress your customers are trying to make.

5. Unusual Uses

You can learn a lot by observing how your customers use your products, especially when they use them in a way that is different from what your company has envisioned.

4. Look for What People Don’t Want to Do

I think I have as many jobs of not wanting to do something as ones that I want positively to do. I call them “negative jobs.” In my experience, negative jobs are often the best innovation opportunities.

Whenever you see a compensating behavior, pay very close attention, because it’s likely a clue that there is an innovation opportunity waiting to be seized—one on which customers would place a high value. But you won’t even see these anomalies—compensating behavior and cobbled-together workarounds—if you’re not fully immersed in the context of their struggle.

We call this “nonconsumption,” when consumers can’t find any solution that actually satisfies their job and they opt to do nothing instead.

Understanding the unresolved jobs in your own life can provide fertile territory for innovation. Just look in the mirror—your life is very articulate. If it matters to you, it’s likely to matter to others.

Innovation is less about producing something new and more about enabling something new and important for customers.

But if we fail to understand why customers make the choices they make, we’re just getting better and better at a fundamentally flawed process. Without the right understanding of the causal mechanism at the center of the innovation universe, companies are trying to make sense of the universe revolving around the earth.

[...] perfectly satisfying someone’s job likely requires not just creating a product, but engineering and delivering a whole set of experiences that address the many dimensions of the job and then integrating those experiences into the company’s processes [...]

One thought experiment we’ve found helpful to really grasp a job is to imagine you are filming a minidocumentary of a person struggling to make progress in a specific circumstance.

Understanding jobs is about clustering insights into a coherent picture, rather than segmenting down to finer and finer slices.

What Is a Job?

To summarize, the key features of our definition are:

- A job is the progress that an individual seeks in a given circumstance.
- Successful innovations enable a customer’s desired progress, resolve struggles, and fulfill unmet aspirations. They perform jobs that formerly had only inadequate or nonexistent solutions.
- Jobs are never simply about the functional—they have important social and emotional dimensions, which can be even more powerful than functional ones.
- Because jobs occur in the flow of daily life, the circumstance is central to their definition and becomes the essential unit of innovation work—not customer characteristics, product attributes, new technology, or trends.
- Jobs to Be Done are ongoing and recurring. They’re seldom discrete “events.”

We define a “job” as the progress that a person is trying to make in a particular circumstance.

Toyota developed processes that ensured that every defect was identified and fixed as soon as it was created. As long as Toyota is continually identifying “anomalies” in the manufacturing process, every single defect is seen as an opportunity to make the process better.

Creating the right experiences and then integrating around them to solve a job, is critical for competitive advantage. That’s because while it may be easy for competitors to copy products, it’s difficult for them to copy experiences that are well integrated into your company’s processes.

[...] an innovation transforms an existing market or sector by introducing simplicity, convenience, accessibility, and affordability where complication and high cost have become the status quo—eventually completely redefining the industry.

There is a better question to ask—one that can help us understand the causality underlying a customer’s decision to pull a new product into his or her life. What job did you hire that product to do? The good news is that if you build your foundation on the pursuit of understanding your customers’ jobs, your strategy will no longer need to rely on luck. In fact, you’ll be competing against luck when others are still counting on it. You’ll see the world with new eyes. Different competitors, different priorities, and most important, different results. You can leave hit-or-miss innovation behind.

Jobs Theory, we believe, can move companies beyond hoping that correlation is enough to the causal mechanism of successful innovation.

Innovation may never be a perfect science, but that’s not the point. We have the ability to make innovation a reliable engine for growth, an engine based on a clear understanding of causality, rather than simply casting seeds in the hopes of one day harvesting some fruit.

When you have a job to be done and there isn’t a good solution, “cheaper and crappier” is better than nothing.

As W. Edwards Deming, the father of the quality movement that transformed manufacturing, once said: “If you do not know how to ask the right question, you discover nothing.” After decades of watching great companies fail over and over again, I’ve come to the conclusion that there is, indeed, a better question to ask: What job did you hire that product to do?

If a company doesn’t understand why I might choose to “hire” its product in certain circumstances—and why I might choose something else in others—its data about me or people like me4 is unlikely to help it create any new innovations for me. It’s seductive to believe that we can see important patterns and cross-references in our data sets, but that doesn’t mean one thing actually caused the other. As Nate Silver, author of The Signal and the Noise: Why So Many Predictions Fail—But Some Don’t, points out, “ice cream sales and forest fires are correlated because both occur more often in the summer heat. But there is no causation; you don’t light a patch of the Montana brush on fire when you buy a pint of Häagen-Dazs.”

Companies are spending exponentially more to achieve only modest incremental innovations while completely missing the mark on the breakthrough innovations critical to long-term, sustainable growth. As Yogi Berra famously observed: “We’re lost, but we’re making good time!”