Highlights
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Hopes for this data trove are higher than ever. “Correlation is enough,”2 then-Wired editor in chief Chris Anderson famously declared in 2008. We can, he implied, solve innovation problems by the sheer brute force of the data deluge. Ever since Michael Lewis chronicled the Oakland A’s unlikely success in Moneyball (who knew on-base percentage was a better indicator of offensive success than batting averages?), organizations have been trying to find the Moneyball equivalent of customer data that will lead to innovation success. Yet few have.
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As Yogi Berra famously observed: “We’re lost, but we’re making good time!”
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Here is the fundamental problem: the masses and masses of data that companies accumulate are not organized in a way that enables them to reliably predict which ideas will succeed. Instead the data is along the lines of “this customer looks like that one,” “this product has similar performance attributes as that one,” and “these people behaved the same way in the past,” or “68 percent of customers say they prefer version A over version B.” None of that data, however, actually tells you why customers make the choices that they do.
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There might be a correlation between some of these characteristics and the propensity of customers to purchase the Times. But those attributes don’t cause me to buy that paper—or any other product.
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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.”
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They’re comfortable with correlation. It allows managers to sleep at night.
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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?
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Harvard Business Review (HBR) article “Marketing Malpractice” that first debuted the Jobs to Be Done theory in the pages of HBR.
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As W. Edwards Deming is also credited with observing, every process is perfectly designed to deliver the results it gets. If we believe that innovation is messy and imperfect and unknowable, we build processes that operationalize those beliefs. And that’s what many companies have done: unwittingly designed innovation processes that perfectly churn out mediocrity.
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Within months, something notable happened: Nothing. After all the marketers’ efforts, there was no change in sales of the chain’s milk shake category.
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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.
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For example, in 1854, when cholera gripped London, the miasma explanation inspired massive, state-sponsored clearing of the air by draining cesspools. A physician of the time, John Snow, was able to isolate the pattern of new cholera cases and to conclude that new cases correlated to proximity to a specific water pump on Broad Street. Disease, he concluded, correlated with that pump—and therefore cholera was not transmitted through miasma, but likely through contaminated water. Snow’s work saved countless lives—and he has subsequently been recognized as one of the most important physicians in history. But while an improvement, Snow’s analysis still didn’t get to the root cause of what actually made those people sick.
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The circumstance is fundamental to defining the job (and finding a solution for it), because the nature of the progress desired will always be strongly influenced by the circumstance.
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For example, a job that occurs in a lot of people’s lives: “I want to have a smile that will make a great first impression in my work and personal life”;
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Our understanding of the Job to Be Done can always get better. Adopting new technologies can improve the way we solve Jobs to Be Done. But what’s important is that you focus on understanding the underlying job, not falling in love with your solution for it.
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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. They’re forced to rely on an array of borrowed best practices, probabilistic tools, and tips and tricks that have worked for other companies, but which can’t guarantee success.
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As you look at innovation through the lenses of the Jobs Theory, what you see is not the customer at the center of the innovation universe, but the customer’s Job to Be Done. It may seem like a small distinction—just a few minutes of arc—but it matters a great deal. In fact, it changes everything.
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The university’s longtime bread-and-butter strategy had relied on appealing to a traditional student body: eighteen-year-olds, fresh out of high school, continuing on a traditional educational path. In essence, “Come to this picturesque New Hampshire campus and you’ll get a solid education for a reasonable price.” The marketing and outreach were generic for everyone, regardless of their circumstances, and the policies and delivery models that served the school were designed to appeal to a “typical” student that really didn’t exist. This one-size-fits-all perspective was reminiscent of the milk shake dilemma—only in this case they were trying to design a one-size-fits-all education for the “average” student.
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Organizations that lack clarity on what the real jobs their customers hire them to do can fall into the trap of providing one-size-fits-all solutions that ultimately satisfy no one.
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We offer here five ways to uncover jobs that might be right in front of you if you know what you’re looking for: seeing jobs in your own life, finding opportunity in nonconsumption, identifying workarounds, zoning in on things we don’t want to do, and spotting unusual uses of products.
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The magic of the Jobs to Be Done lens is that there isn’t any magic required at all. The lens allows you to look at the same things everyone else is looking at—but enables you to see differently.
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Rarely, though, can customers articulate their requirements accurately or completely—their motivations are more complex and their pathways to purchase more elaborate than they can describe.
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What they hire—and equally important, what they fire—tells a story. That story is about the functional, emotional, and social dimensions of their desire for progress—and what prevents them from getting there. The challenge is in becoming part sleuth and part documentary filmmaker—piecing together clues and observations—to reveal the jobs customers are trying to get done.
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Consumers can’t always articulate what they want. And even when they do, their actions may tell a different story. If I asked you if you care about being environmentally friendly, most of us would say yes.
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But if I opened your cupboards, would they tell the same story?
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On the other hand, research has consistently shown that a significant portion of customers are willing to pay more for foods that are labeled “organic,” a word that is so generically used that it’s almost meaningless.
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Companies don’t think about this enough. What has to get fired for my product to get hired?
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Loss aversion—people’s tendency to want to avoid loss—is twice as powerful psychologically as the allure of gains, as demonstrated by Kahneman and Amos Tversky.1
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Note: Loss aversion comes into the habit force
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Remember, the insights that lead to successful new products look more like a story than a statistic. They’re rich and complex. Ultimately, you want to cluster together stories to see if there are similar patterns, rather than break down individual interviews into categories.
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There is no one special method of uncovering Jobs to Be Done and that is precisely the point: there is no black box. You just have to have a “beginner’s mind” as you walk through a consumer’s decision-making process, looking for clues as to the full picture of the struggle.3
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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.
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Processes are invisible from a customer’s standpoint—but the results of those processes are not.
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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.”
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This is what processes aligned with customer jobs do: they shift complexity and nuisances from the customer to the vendor, leaving positive customer experiences and valuable progress in their place.
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Whereas the subjectivity of data from field-based, ethnographic research is glaringly apparent, the subjective bias of numerical data hides behind its superficial precision.
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Data has the same agenda as the person who created it, wittingly or unwittingly.
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But trying to steal revenue from your competitors by taking them on with lower-quality imitations is not a growth plan to count on. That’s why we call it surface growth. You can copy ideas you already see on the shelves but none of this is based on a clear understanding of jobs—and it’s far, far less likely to succeed.
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However, mission statements are usually phrased at such a high level and so generically that employees find it difficult to use them as guides for action, decision making, and innovation.
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Note: Ties into Greg McKeow's idea of Essential Intent. Clay's version is that a Job should be the north star.
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A couple of examples: “I need to have a chocolate milk shake that is in a twelve-ounce disposable container” is not a job. The possible candidates that I could hire to do this are all in the milk shake product category. I could call this a need or a preference—but it isn’t a job. We need to go up another level of abstraction in order to discover the job.
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We can see that this is a Job to Be Done and not a technical specification or requirement. We know this because the alternatives of things to hire to get the job done come from very different categories of products and services.
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I’ve spent twenty years gathering evidence so that you can put your time, energy, and resources into creating products and services that you can predict, in advance, customers will be eager to hire. Leave relying on luck to the other guys.
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