Work Metrics Quotes

Maybe niceness is the wrong metric, I said. Of course it's really about power, Bobbi agreed. But it's harder to work out who has the power, so instead we rely on 'niceness' as a kind of stand-in. I mean this is an issue in public discourse. We end up asking like, is Israel 'nicer' than Palestine.

We think, mistakenly, that success is the result of the amount of time we put in at work, instead of the quality of time we put in.

Lovers' reading of each other's bodies (of that concentrate of mind and body which lovers use to go to bed together) differs from the reading of written pages in that it is not linear. It starts at any point, skips, repeat itself, goes backward, insists, ramifies in simultaneous and divergent messages, converges again, has moments of irritation, turns the page, finds its place, gets lost. A direction can be recognized in it, a route to an end, since it tends toward a climax, and with this end in view it arranges rhythmic phases, metrical scansions, recurrence of motives. But is the climax really the end? Or is the race toward that end opposed by another drive which works in the opposite direction, swimming against moments, recovering time?

My advice was to start a policy of making reversible decisions before anyone left the meeting or the office. In a startup, it doesn’t matter if you’re 100 percent right 100 percent of the time. What matters is having forward momentum and a tight fact-based data/metrics feedback loop to help you quickly recognize and reverse any incorrect decisions. That’s why startups are agile. By the time a big company gets the committee to organize the subcommittee to pick a meeting date, your startup could have made 20 decisions, reversed five of them and implemented the fifteen that worked.

Some people have the luxury of asking themselves whether a job fulfills their career hopes and ambitions. I’ve got my own metric to gauge the fabulosity of a job: Does that job require me to keep my boss informed of the inner workings of my gastrointestinal system, or am I allowed to go to the bathroom at will?

If you don’t collect any metrics, you’re flying blind. If you collect and focus on too many, they may be obstructing your field of view.

it is very telling what we don’t hear in eulogies. We almost never hear things like: “The crowning achievement of his life was when he made senior vice president.” Or: “He increased market share for his company multiple times during his tenure.” Or: “She never stopped working. She ate lunch at her desk. Every day.” Or: “He never made it to his kid’s Little League games because he always had to go over those figures one more time.” Or: “While she didn’t have any real friends, she had six hundred Facebook friends, and she dealt with every email in her in-box every night.” Or: “His PowerPoint slides were always meticulously prepared.” Our eulogies are always about the other stuff: what we gave, how we connected, how much we meant to our family and friends, small kindnesses, lifelong passions, and the things that made us laugh.

The Six Steps to Success: 1) Define Success 2) Devise a Plan 3) Execute and Overcome Adversity 4) Measure Results with Key Metrics 5) Revise the Plan 6) Work Hard

When we are all mind, things can get rigid. When we are all heart, things can get chaotic. Both lead to stress. But when they work together, the heart leading through empathy, the mind guiding us with focus and attention, we become a harmonious human being.

The history professor Nelson Lichtenstein told me, “What you can’t measure, you can’t reward,” and that may be why executives are so focused on work hours. For decades, the corporate world has been consumed with metrics. Managers love tangible measures by which they can determine success or failure. Work hours is one of the easiest ways to measure employee performance, but total hours worked is a meaningless statistic.

We have only minimal control over the rewards for our work and effort—other people’s validation, recognition, rewards. So what are we going to do? Not be kind, not work hard, not produce, because there is a chance it wouldn’t be reciprocated? C’mon. Think of all the activists who will find that they can only advance their cause so far. The leaders who are assassinated before their work is done. The inventors whose ideas languish “ahead of their time.” According to society’s main metrics, these people were not rewarded for their work. Should they have not done it? Yet in ego, every one of us has considered doing precisely that. If that is your attitude, how do you intend to endure tough times? What if you’re ahead of the times? What if the market favors some bogus trend? What if your boss or your clients don’t understand? It’s far better when doing good work is sufficient. In other words, the less attached we are to outcomes the better. When fulfilling our own standards is what fills us with pride and self-respect. When the effort—not the results, good or bad—is enough. With ego, this is not nearly sufficient. No, we need to be recognized. We need to be compensated. Especially problematic is the fact that, often, we get that. We are praised, we are paid, and we start to assume that the two things always go together. The “expectation hangover” inevitably ensues.

We can’t even be sure how to tell when the immune system’s not working right, let alone why not, because we don’t have good metrics of what a healthy human immune system looks like. Despite billions spent on immune stimulants in supermarkets and drugstores last year, we don’t know what—if anything—those really do, or what “immune stimulant” even means.{564}

Money is just like the metric system: you work more, you earn more and there’s always an extra zero to be added. It’s only a zero, though.

When companies do not understand their customers’ or users’ problems well, they cannot possibly define value for them. Instead of doing the work to learn this information about customers, they create a proxy that is easy to measure. “Value” becomes the quantity of features that are delivered, and, as a result, the number of features shipped becomes the primary metric of success.

The Principle of Least Resistance, protected from scrutiny by the metric black hole, supports work cultures that save us from the short-term discomfort of concentration and planning, at the expense of long-term satisfaction and the production of real value.

I often see teams that maniacally focus on their metrics around customer acquisition and retention. This usually works well for customer acquisition, but not so well for retention. Why? For many products, metrics often describe the customer acquisition goal in enough detail to provide sufficient management guidance. In contrast, the metrics for customer retention do not provide enough color to be a complete management tool. As a result, many young companies overemphasize retention metrics and do not spend enough time going deep enough on the actual user experience. This generally results in a frantic numbers chase that does not end in a great product.

Communicate the plan clearly and have clear metrics conveying whether you are progressing according to it.

Establish clear metrics to make certain that you are following your plan.

c. Establish clear metrics to make certain that you are following your plan. Ideally, someone other than you should be objectively measuring and reporting on your progress.

Use evaluation tools such as performance surveys, metrics, and formal reviews to document all aspects of a person’s performance.It’s

Jeter’s work ethic, kneaded into the dough and manifesting itself in the leavening of his metric loaf, has already nourished the dossier with which his contracts are negotiated.

start with the most important questions and imagine the metrics that will answer them. Remember that any single metric can mislead; you need enough evidence to establish patterns.

You need to know which aspects of your business are too risky and then work to improve the metric that represents that risk.

Too many of us leave our lives—and, in fact, our souls—behind when we go to work.

The Principle of Least Resistance, protected from scrutiny by the metric black hole, supports work cultures that save us from the short-term discomfort of concentration and planning, at the expense of long-term satisfaction and the production of real value. By doing so, this principle drives us toward shallow work in an economy that increasingly rewards depth.

Build great metrics. Metrics show how the machine is working by providing numbers and setting off alert lights in a dashboard. Metrics are an objective means of assessment and they tend to have a favorable impact on productivity.

Falling consumer prices is what enriches people (deflation of asset prices can ruin them, but that is because they are using asset prices to get them the wherewithal to purchase consumer items). And, once again, notice that the true metric of prosperity is time. If Cornelius Vanderbilt or Henry Ford not only moves you faster to where you want to go, but requires you to work fewer hours to earn the ticket price, then he has enriched you by granting you a dollop of free time.

Trying to force people to conform their work to preestablished numerical goals tends to stifle innovation and creativity—valuable qualities in most settings. And it almost inevitably leads to a valuation of short-term goals over long-term purposes.

Under this framework, it’s a kid’s job to stay eligible for the labor market (not in jail, not insane, and not dead—which is more work for some than others), and any work product beyond that adds to their résumé. If more human capital automatically led to a higher standard of living, this model could be the foundation for an American meritocracy. But Millennials’ extra work hasn’t earned them the promised higher standard of living. By every metric, this generation is the most educated in American history, yet Millennials are worse off economically than their parents, grandparents, and even great-grandparents. Every authority from moms to presidents told Millennials to accumulate as much human capital as we could, and we did, but the market hasn’t held up its side of the bargain.

When you're the only person who could have created a work of art, the competition and standard metrics by which things are measured become irrelevant because nothing can replace you. The factors that distinguish you are so personal than nobody can replicate them.

However, simplicity is a virtue when developing metrics for your platform business. Overcomplex metrics make management less effective by introducing noise, discouraging frequent analysis, and distracting from the handful of data points that are most significant.

It’s not easy to feel good about yourself when you are constantly being told you’re rubbish and/or part of the problem. That’s often the situation for people working in the public sector, whether these be nurses, civil servants or teachers. The static metrics used to measure the contribution of the public sector, and the influence of Public Choice theory on making governments more ‘efficient’, has convinced many civil-sector workers they are second-best. It’s enough to depress any bureaucrat and induce him or her to get up, leave and join the private sector, where there is often more money to be made. So public actors are forced to emulate private ones, with their almost exclusive interest in projects with fast paybacks. After all, price determines value. You, the civil servant, won’t dare to propose that your agency could take charge, bring a helpful long-term perspective to a problem, consider all sides of an issue (not just profitability), spend the necessary funds (borrow if required) and – whisper it softly – add public value. You leave the big ideas to the private sector which you are told to simply ‘facilitate’ and enable. And when Apple or whichever private company makes billions of dollars for shareholders and many millions for top executives, you probably won’t think that these gains actually come largely from leveraging the work done by others – whether these be government agencies, not-for-profit institutions, or achievements fought for by civil society organizations including trade unions that have been critical for fighting for workers’ training programmes.

Use evaluation tools such as performance surveys, metrics, and formal reviews to document all aspects of a person’s performance.It’s hard to have an objective, open-minded, emotion-free conversation about performance if there is no data to discuss. It’s also hard to track progress.

I invite you to open your mind to new possibilities. Let’s fake it till we make it. Let’s create visions of an aspirational future. You don’t have to quit your job. But think about what might change your trajectory by half a degree. It could be that when you come home every night your first words are “I’m home! How can I help?” Try doing that. You may have a shitty job. You don’t like it. You do it for the money, even if the money isn’t great. Try to look at your work in a different way. Find something about your life that’s great. Follow that thread. Volunteer. Even if you’re in the worst possible situation, there’s hope. Challenge yourself. Set your own bar. Redefine your success metrics. Create opportunities for yourself. Reassess your situation. We are all marching together. We’re headed toward something big, and it’s going to be good.

The falseness of the seventeenth century became a large measure of the truth by the nineteenth. Money made the man, or at least went a long way toward doing so; and death became the occasion for a final accounting, a stocktaking of worldly success. Of course, there were other metrics: virtue, martyrdom, political standing, fraternal ties. But it took money to publicize them. The funeral became more and more a standardized commodity whose cost could be matched with exquisite precision to the class and degree of 'respectability' of the deceased. When one bought a funeral, one bought a more or less splendid parade, each additional bauble, each horse, each feather or set of nails adding to the base price. Bit by bit, finery accumulated, and by looking at the account books of an undertaker who specialized in pauper funerals, we can begin to see the bounds of decency in death.

In real life, the value capture process is sometimes deliberately managed by elites to manipulate and control others with game design-like tactics. Gig economy platforms like Uber and Lyft use "badges" and rating systems to manage the decision-making environment of their driver employees. Even outside of work, social media features such as likes, shares, and retweets play the role of points in games. Over time, these simple metrics threaten to distort or take the place of values (say, the wish to meaningfully contribute to discussion or to take pride in the quality of one's work) that might otherwise have inflected our behavior on these platforms.

… a better objective for support units would be the following: to effectively fulfill their administrative duties with as small an impact as possible on the specialists’ main work obligations. If taken seriously this metric might mean a given support unit needs to make its own work less efficient to better serve the organization.

Each country's money supply was not a metric to be determined by central planning committees stocked with Ph.D. holders, but the natural working of the market system. People held as much money as they pleased and spent as much as they desired on local or foreign production, and the actual money supply was not even easily measurable.

Being labeled a failure with a work that was successful by most other metrics can make moving forward that much more difficult to navigate. This is why it’s grounding to protect your personal understanding of success. And to make each new work, no matter where you stand on the ladder of public perception, like you have nothing to lose.

We should finally note a more radical challenge to the concept of Platonic utility that arises from nascent work in the reinforcement learning field under the rubric of intrinsic motivation. One idea is that the "true" evolutionarily appropriate metric for behavior is the extremely sparse one of propagating ones genes. What we think of as a Platonic utility over immediate rewards such as food or water, would merely be a surrogate that helps overcome the otherwise insurmountable credit assignment path associated with procreation. In these terms, even the Platonic utility is the same sort of heuristic expedient as the Pavlovian controller itself, with evolutionary optimality molding approximate economic rationality to its own ends. It as a sober thought that understanding values may be less important as a way of unearthing the foundations of choice that we might have expected.

The American dream, here it is: In America (and this is not just confined to America of course), if you work hard, play by the rules, you will succeed. Work hard, play by the rules, you will succeed. That’s part of the dream. Typically, it also includes a metric for what constitutes success. It almost invariably takes a commodified form, success. Since that’s the kind of reward a capitalist system can and must deliver. For example, a recurrent formulation is a home of one’s own.

Everyone at the company had access to the whole Facebook code base and was allowed to make changes to the product without much oversight. All they needed to prove was that their edit caused a boost, however small, for some important metric, like time spent on the app. That allowed engineers and designers to work a lot faster, because there was less arguing about why or whether they should build something. Everyone knew that their next raise would hinge on whether they affected growth and sharing. They weren’t held accountable for much else.

Part of what makes real-time scheduling so complex and interesting is that it is fundamentally a negotiation between two principles that aren’t fully compatible. These two principles are called responsiveness and throughput: how quickly you can respond to things, and how much you can get done overall. Anyone who’s ever worked in an office environment can readily appreciate the tension between these two metrics. It’s part of the reason there are people whose job it is to answer the phone: they are responsive so that others may have throughput.

On the pathless path, the goal is not to find a job, make money, build a business, or achieve any other metric. It’s to actively and consciously search for the work that you want to keep doing. This is one of the most important secrets of the pathless path. With this approach, it doesn’t make sense to chase any financial opportunity if you can’t be sure that you will like the work. What does make sense is experimenting with different kinds of work, and once you find something worth doing, working backward to build a life around being able to keep doing it.

The customer is also at the center of how we analyze and manage performance metrics. Our emphasis is on what we call controllable input metrics, rather than output metrics. Controllable input metrics (e.g., reducing internal costs so you can affordably lower product prices, adding new items for sale on the website, or reducing standard delivery time) measure the set of activities that, if done well, will yield the desired results, or output metrics (such as monthly revenue and stock price). We detail these metrics as well as how to discover and track them in chapter six.

Using velocity as a productivity metric has several flaws. First, velocity is a relative and team-dependent measure, not an absolute one. Teams usually have significantly different contexts which render their velocities incommensurable. Second, when velocity is used as a productivity measure, teams inevitably work to game their velocity. They inflate their estimates and focus on completing as many stories as possible at the expense of collaboration with other teams (which might decrease their velocity and increase the other team’s velocity, making them look bad). Not only does this destroy the utility of velocity for its intended purpose, it also inhibits collaboration between teams.

The economic crisis and subsequent bailout exacerbated inequality by every metric and did not lead to significant reform of the financial sector. Bailed-out banks continued to foreclose on the homes of working-class families while refusing to make new loans to creditworthy borrowers. Under an Ivy League–educated African American president, African American family wealth had collapsed. In fact, it is common knowledge that African American and Latino homeowners were hit hardest by the 2008 financial crisis: by 2018, an African American family owned $5.00 in assets for every $100.00 owned by white families.6 Obama’s identity politics did not translate into economic policies that benefited minorities and working-class people.

My goal is not to fail fast. My goal is to succeed over the long run. They are not the same thing.” “To do original work: It’s not necessary to know something nobody else knows. It is necessary to believe something few other people believe.” “Andy Grove had the answer: For every metric, there should be another ‘paired’ metric that addresses adverse consequences of the first metric.” “Show me an incumbent bigco failing to adapt to change, I’ll show you top execs paid huge cash compensation for quarterly and annual goals.” “Every billionaire suffers from the same problem. Nobody around them ever says, ‘Hey, that stupid idea you just had is really stupid.’” “‘Far more money has been lost by investors trying to anticipate corrections, than has been lost in corrections themselves.’—Peter Lynch

Einstein’s “mathematical strategy,” on the other hand, focused on using generic mathematical knowledge about the metric tensor to find a gravitational field equation that was generally (or at least broadly) covariant. The process worked both ways: Einstein would examine equations that were abstracted from his physical requirements to check their covariance properties, and he would examine equations that sprang from elegant mathematical formulations to see if they met the requirements of his physics. “On page after page of the notebook, he approached the problem from either side, here writing expressions suggested by the physical requirements of the Newtonian limit and energy-momentum conservation, there writing expressions naturally suggested by the generally covariant quantities supplied by the mathematics of Ricci and Levi-Civita,” says John Norton.

Not long after I began thinking about what might help the American working class get ahead, a team of economists, including Raj Chetty, published a groundbreaking study on opportunity in America. Unsurprisingly, they found that a poor kid’s chances of rising through the ranks of America’s meritocracy were lower than most of us wanted. By their metrics, a lot of European countries seemed better than America at the American Dream. More important, they discovered that opportunity was not spread evenly over the whole country. In places like Utah, Oklahoma, and Massachusetts, the American Dream was doing just fine—as good or better than any other place in the world. It was in the South, the Rust Belt, and Appalachia where poor kids really struggled. Their findings surprised a lot of people, but not me. And not anyone who’d spent any time in these areas. In

what. Content strategy asks these questions of stakeholders and clients: Why are we doing this? What are we hoping to accomplish, change, or encourage? How will we measure the success of this initiative and the content in it? What measurements of success or metrics do we need to monitor to know if we are successful? How will we ensure the web remains a priority? What do we need to change in resources, staffing, and budgets to maintain the value of communication within and from the organization? What are we trying to communicate? What's the hierarchy of that messaging? This isn't Sophie's Choice, but when you start prioritizing features on a homepage and allocating budget to your list of features and content needs, get ready to make some tough calls. What content types best meet the needs of our target audience and their changing, multiple contexts? What content types best fit the skills of our

These include: the Bar Raiser hiring process that ensures that the company continues to acquire top talent; a bias for separable teams run by leaders with a singular focus that optimizes for speed of delivery and innovation; the use of written narratives instead of slide decks to ensure that deep understanding of complex issues drives well-informed decisions; a relentless focus on input metrics to ensure that teams work on activities that propel the business. And finally there is the product development process that gives this book its name: working backwards from the desired customer experience. Many of the business problems that Amazon faces are no different from those faced by every other company, small or large. The difference is how Amazon keeps coming up with uniquely Amazonian solutions to those problems. Taken together, these elements combine to form a way of thinking, managing, and working that we refer to as being Amazonian, a term that we coined for the purposes of this book. Both of us, Colin and Bill, were “in the room,” and—along with other senior leaders—we shaped and refined what it means to be Amazonian. We both worked extensively with Jeff and were actively involved in creating a number of Amazon’s most enduring successes (not to mention some of its notable flops) in what was the most invigorating professional experience of our lives.

They all succeed at changing both their mindset (the meaning-making system that shapes thoughts and feelings) and their behavior; rather than changing only mindset or behavior, and hoping the other will eventually follow. • They all become keen and focused observers of their own thoughts, emotions, and behaviors, and they learn to use these as information. They see the agenda that is driving them, not just the agenda they are driving. • Changes to their mindsets are always in the direction of seeing and feeling more possibilities: Spaces people had previously thought they could not or should not enter (because they were out of reach or too dangerous) are now fully accessible. • They take focused risks and build a new set of muscles and metrics around assumptions based on actual, rather than imagined, data about the consequences of their new actions. Their anxiety around the initial adaptive challenge is reduced, if not eliminated, while their experiences of pleasure significantly increase. • They experience increased mastery, more options, wider control, and greater degrees of freedom. They make progress on, or even accomplish, their column 1 commitment, and, more often than not, their accomplishments extend considerably beyond the initial aspiration. Because they have developed new mental capabilities—not just a new solution to a single problem—they can bring these capabilities to other challenges and other venues, in their work and in their personal lives.

Then came a series of wondrous discoveries, beginning in 1924, by Edwin Hubble, a colorful and engaging astronomer working with the 100-inch reflector telescope at the Mount Wilson Observatory in the mountains above Pasadena, California. The first was that the blur known as the Andromeda nebula was actually another galaxy, about the size of our own, close to a million light years away (we now know it’s more than twice that far). Soon he was able to find at least two dozen even more distant galaxies (we now believe that there are more than 100 billion of them). Hubble then made an even more amazing discovery. By measuring the red shift of the stars’ spectra (which is the light wave counterpart to the Doppler effect for sound waves), he realized that the galaxies were moving away from us. There were at least two possible explanations for the fact that distant stars in all directions seemed to be flying away from us: (1) because we are the center of the universe, something that since the time of Copernicus only our teenage children believe; (2) because the entire metric of the universe was expanding, which meant that everything was stretching out in all directions so that all galaxies were getting farther away from one another. It became clear that the second explanation was the case when Hubble confirmed that, in general, the galaxies were moving away from us at a speed that was proportional to their distance from us. Those twice as far moved away twice as fast, and those three times as far moved away three times as fast.

Why did you come to the United States? Perhaps no one knows the real answer. I know that migrants, when they are still on their way here, learn the Immigrant’s Prayer. A friend who had been aboard La Bestia for a few days, working on a documentary, read it to me once. I didn’t learn the entire thing, but I remember these lines: “Partir es morir un poco / Llegar nunca es llegar”—“To leave is to die a little / To arrive is never to arrive.” I’ve had to ask so many children: Why did you come? Sometimes I ask myself the same question. I don’t have an answer yet. Before coming to the United States, I knew what others know: that the cruelty of its borders was only a thin crust, and that on the other side a possible life was waiting. I understood, some time after, that once you stay here long enough, you begin to remember the place where you originally came from the way a backyard might look from a high window in the deep of winter: a skeleton of the world, a tract of abandonment, objects dead and obsolete. And once you’re here, you’re ready to give everything, or almost everything, to stay and play a part in the great theater of belonging. In the United States, to stay is an end in itself and not a means: to stay is the founding myth of this society. To stay in the United States, you will unlearn the universal metric system so you can buy a pound and a half of cooked ham, accept that thirty-two degrees, and not zero, is where the line falls that divides cold and freezing. You might even begin to celebrate the pilgrims who removed the alien Indians, and the veterans who maybe killed other aliens, and the day of a president who will eventually declare a war on all the other so-called aliens. No matter the cost. No matter the cost of the rent, and milk, and cigarettes. The humiliations, the daily battles. You will give everything. You will convince yourself that it is only a matter of time before you can be yourself again, in America, despite the added layers of its otherness already so well adhered to your skin. But perhaps you will never want to be your former self again. There are too many things that ground you to this new life. Why did you come here? I asked one little girl once. Because I wanted to arrive.

Was this luck, or was it more than that? Proving skill is difficult in venture investing because, as we have seen, it hinges on subjective judgment calls rather than objective or quantifiable metrics. If a distressed-debt hedge fund hires analysts and lawyers to scrutinize a bankrupt firm, it can learn precisely which bond is backed by which piece of collateral, and it can foresee how the bankruptcy judge is likely to rule; its profits are not lucky. Likewise, if an algorithmic hedge fund hires astrophysicists to look for patterns in markets, it may discover statistical signals that are reliably profitable. But when Perkins backed Tandem and Genentech, or when Valentine backed Atari, they could not muster the same certainty. They were investing in human founders with human combinations of brilliance and weakness. They were dealing with products and manufacturing processes that were untested and complex; they faced competitors whose behaviors could not be forecast; they were investing over long horizons. In consequence, quantifiable risks were multiplied by unquantifiable uncertainties; there were known unknowns and unknown unknowns; the bracing unpredictability of life could not be masked by neat financial models. Of course, in this environment, luck played its part. Kleiner Perkins lost money on six of the fourteen investments in its first fund. Its methods were not as fail-safe as Tandem’s computers. But Perkins and Valentine were not merely lucky. Just as Arthur Rock embraced methods and attitudes that put him ahead of ARD and the Small Business Investment Companies in the 1960s, so the leading figures of the 1970s had an edge over their competitors. Perkins and Valentine had been managers at leading Valley companies; they knew how to be hands-on; and their contributions to the success of their portfolio companies were obvious. It was Perkins who brought in the early consultants to eliminate the white-hot risks at Tandem, and Perkins who pressed Swanson to contract Genentech’s research out to existing laboratories. Similarly, it was Valentine who drove Atari to focus on Home Pong and to ally itself with Sears, and Valentine who arranged for Warner Communications to buy the company. Early risk elimination plus stage-by-stage financing worked wonders for all three companies. Skeptical observers have sometimes asked whether venture capitalists create innovation or whether they merely show up for it. In the case of Don Valentine and Tom Perkins, there was not much passive showing up. By force of character and intellect, they stamped their will on their portfolio companies.

Bailey,” I say, my voice carrying easily across the marble floor. “Wait.” She turns back and rolls her eyes, clearly annoyed to see me coming her way. She quickly wipes at her cheeks then holds up her hand to wave me off. “I’m off the clock. I don’t want to talk to you right now. If you want to chew me out for what happened back there, you’ll have to do it on Monday. I’m going home.” “How?” Her pretty brown eyes, full of tears, narrow up at me in confusion. “How what?” “How are you getting home? Did you park on the street or something?” Her brows relax as she realizes I’m not about to scold her. “Oh.” She turns to the window. “I’m going to catch the bus.” The bus? “The stop is just down the street a little bit.” “Don’t you have a car?” She steels her spine. “No. I don’t.” I’ll have to look into what we’re paying her—surely she should have no problem affording a car to get her to and from work. “Okay, well then what about an Uber or something?” Her tone doesn’t lighten as she replies, “I usually take the bus. It’s fine.” I look for an umbrella and frown when I see her hands are empty. “You’re going to get drenched and it’s freezing out there.” She laughs and starts to step back. “It’s not your concern. Don’t worry about me.” Yes, well unfortunately, I do worry about her. For the last three weeks, all I’ve done is worry about her. Cooper is to blame. He fuels my annoyance on a daily basis, updating me about their texts and bragging to me about how their relationship is developing. Relationship—I find that laughable. They haven’t gone on a date. They haven’t even spoken on the phone. If the metric for a “relationship” lies solely in the number of text messages exchanged then as of this week, I’m in a relationship with my tailor, my UberEats delivery guy, and my housekeeper. I’ve got my hands fucking full. “Well I’m not going to let you wait out at the bus stop in this weather. C’mon, I’ll drive you.” Her soft feminine laugh echoes around the lobby. “Thank you, but I’d rather walk.” What she really means is, Thank you, but I’d rather die. “It’s really not a request. You’re no good to me if you have to call in sick on Monday because you caught pneumonia.” Her gaze sheens with a new layer of hatred. “You of all people know you don’t catch pneumonia just from being cold and wet.” She tries to step around me, but I catch her backpack and tug it off her shoulder. I can’t put it on because she has the shoulder straps set to fit a toddler, so I hold it in my hand and start walking. She can either follow me or not. I tell myself I don’t care either way. “Dr. Russell—” she says behind me, her feet lightly tap-tap-tapping on the marble as she hurries to keep up. “You’re clocked out, aren’t you? Call me Matt.” “Doctor,” she says pointedly. “Please give me my backpack before I call security.” I laugh because really, she’s hilarious. No one has ever threatened to call security on me before. “It’s Matt, and if you’re going to call security, make sure you ask for Tommy. He’s younger and stands a decent chance of catching me before I hightail it out of here with your pink JanSport backpack. What do you have in here anyway?” It weighs nothing. “My lunchbox. A water bottle. Some empty Tupperware.” Tupperware. I glance behind me to check on her. She’s fast-walking as she trails behind me. Am I really that much taller than her? “Did you bring more banana bread?” She nods and nearly breaks out in a jog. “Patricia didn’t get any last time and I felt bad.” “I didn’t get any last time either,” I point out. She snorts. “Yeah well, I don’t feel bad about that.” I face forward again so she can’t see my smile.

The five letters of the SOLID acronym stand for: Single Responsibility Principle: a class should have one and only one responsibility; that is, only one reason to change. The Lack of Cohesion Of Methods metric indicates the antipattern of too large a class. Open/Closed Principle: a class should be open for extension, but closed against modification. The Case Statement design smell suggests a violation. Liskov Substitution Principle: a method designed to work on an object of type T should also work on an object of any subtype of T. That is, all of T’s subtypes should preserve T’s “contract.” The refused bequest design smell often indicates a violation. Dependency Injection Principle: if two classes depend on each other but their implementations may change, it would be better for them to both depend on a separate abstract interface which is “injected” between them. Demeter Principle: a method can call other methods in its own class, and methods on the classes of its own instance variables; everything else is taboo. A design smell that indicates a violation is inappropriate intimacy.

One true measure of progress in Afghanistan is the relationship between the government and the people. The more the villagers support the government, the better the war is going. And this is relatively simple to measure. The best metric is how many people visit the district center every week. The presence of many elders indicated the government was doing well, because the people weren’t afraid to work with government staff.

We can prove that the Great Pyramid's base area (with a metric side of 440*0.5236) expresses a solar year through dividing it by the number of days per year, i.e. 365. As a result it delivers to us an area with a square side of 12 rendering such a square as a unit of measurement relevant to our model as John Michell anticipates throughout his work.

Interestingly, I see this same problem play out in many consumer Internet startups. I often see teams that maniacally focus on their metrics around customer acquisition and retention. This usually works well for customer acquisition, but not so well for retention. Why? For many products, metrics often describe the customer acquisition goal in enough detail to provide sufficient management guidance. In contrast, the metrics for customer retention do not provide enough color to be a complete management tool. As a result, many young companies overemphasize retention metrics and do not spend enough time going deep enough on the actual user experience. This generally results in a frantic numbers chase that does not end in a great product. It’s important to supplement a great product vision with a strong discipline around the metrics, but if you substitute metrics for product vision, you will not get what you want.

If there are no metrics in place, how can you know how well the value stream is performing, let alone if it is getting better or worse?

As Sheryl Sandberg told me, “I found that when I cut my office hours dramatically once I had kids, I was not just working less, but I was more productive. Having children forced me to treat every minute of my time as precious—

Edmund Phelps, a Nobel Prize winning economist, claims in his book Mass Flourishing: How Grassroots Innovation Created Jobs, Challenge, and Change that one of the virtues of capitalism is its ability to provide “the experience of mental stimulation, the challenge of new problems to solve, the chance to try the new, and the excitement of venturing into the unknown.”9 That is indeed a possibility under capitalism. But those subject to performance metrics are forced to focus their efforts on limited goals, imposed by others, who may not understand the work that they do. For the workers under scrutiny, mental stimulation is dulled, they decide neither the problems to be solved nor how to solve them, and there is no excitement of venturing into the unknown because the unknown is beyond the measureable. In short, the entrepreneurial element of human nature—which extends beyond the owners of enterprises—may be stifled by metric fixation.10

What do citizens expect of government agencies entrusted with crime control, risk control, or other harm reduction duties? The public does not expect that governments will be able to prevent all crimes or contain all harms. But they do expect government agencies to provide the best protection possible, and at a reasonable price, by being:           Vigilant, so they can spot emerging threats early, pick up on precursors and warning signs, use their imaginations to work out what could happen, use their intelligence systems to discover what others are planning, and do all this before much harm is done.           Nimble, flexible enough to organize themselves quickly and appropriately around each emerging crime pattern rather than being locked into routines and processes designed for traditional issues.           Skillful, masters of the entire intervention tool kit, experienced (as craftsmen) in picking the best tools for each task, and adept at inventing new approaches when existing methods turn out to be irrelevant or insufficient to suppress an emerging threat.8 Real success in crime control—spotting emerging crime problems early and suppressing them before they do much harm—would not produce substantial year-to-year reductions in crime figures, because genuine and substantial reductions are available only when crime problems have first grown out of control. Neither would best practices produce enormous numbers of arrests, coercive interventions, or any other specific activity, because skill demands economy in the use of force and financial resources and rests on artful and well-tailored responses rather than extensive and costly campaigns. Ironically, therefore, the two classes of metrics that still seem to wield the most influence in many departments—crime reduction and enforcement productivity—would utterly fail to reflect the very best performance in crime control. Further, we must take seriously the fact that other important duties of the police will never be captured through crime statistics or in measures of enforcement output. As NYPD Assistant Commissioner Ronald J. Wilhelmy wrote in a November 2013 internal NYPD strategy document:

To calculate the GDP, numerous data points have to be linked together and hundreds of wholly subjective choices made regarding what to count and what to ignore. In spite of this methodology, the GDP is never presented as anything less than hard science, whose fractional vacillations can make the difference between reelection and political annihilation. Yet this apparent precision is an illusion. The GDP is not a clearly defined object just waiting around to be “measured.” To measure GDP is to seek to measure an idea. A great idea, admittedly. There’s no denying that GDP came in very handy during wartime, when the enemy was at the gates and a country’s very existence hinged on production, on churning out as many tanks, planes, bombs, and grenades as possible. During wartime, it’s perfectly reasonable to borrow from the future. During wartime, it makes sense to pollute the environment and go into debt. It can even be preferable to neglect your family, put your children to work on a production line, sacrifice your free time, and forget everything that makes life worth living. Indeed, during wartime, there’s no metric quite as useful as the GDP.

As discussed in Chapter 2, data gathered from A/B tests by Ronny Kohavi, who directed Amazon’s Data Mining and Personalization group before joining Microsoft as General Manager of its Experimentation Platform, reveal that 60%–90% of ideas do not improve the metric they were intended to improve. Thus if we’re not running experiments to test the value of new ideas before completely developing them, the chances are that about 2/3 of the work we are doing is of either zero or negative value to our customers — and certainly of negative value to our organization, since this work costs us in three ways. In addition to the cost of developing the features, there is an opportunity cost associated with more valuable work we could have done instead, and the cost of the new complexity they add to our systems (which manifests itself as the cost of maintaining the code, a drag on the rate at which we can develop new functionality, and often, reduced operational stability and performance).

We recommend companies with new business models be patient for growth (to allow the market opportunity to unfold) but impatient for profit (as an early validation that the model works). A profitable business is the best early indication of a viable model. What Rules, Norms, and Metrics Are Standing in Your Way? In

If your metric for the value “success by worldly standards” is “Buy a house and a nice car,” and you spend twenty years working your ass off to achieve it, once it’s achieved the metric has nothing left to give you. Then say hello to your midlife crisis, because the problem that drove you your entire adult life was just taken away from you.

The best way to achieve alignment is to sequentially move through a series of structured discussions that clarify the organization’s strategy, defining precisely what differentiating capabilities are required, then to examine all the systems of choices that develop that capability: work processes; structure and governance; information and metrics; people and rewards; continuous improvement; and culture and leadership (fig. 1.5). These are the conversations entailed in organization alignment. They can—and should—be quick and to the point. But these critical conversations should not be skipped.

According to one Egyptian account, the formation of the world was the realization of a concept first developed within the mind of the Creator. Leibniz had a similar idea. He imagined God as a kind of super computer, calculating every possible world and scoring them all according to some divine scale or metric. Once the Creator had analyzed all possible worlds in his mind (all potentialities), he made actual the world that had scored highest and was thus the best of all possible worlds. If you think this world is bad, you should see the alternatives!

We get paid much more to keep someone on dialysis than to keep them off of it. If we don’t achieve dialysis metrics—like avoiding dialysis catheters or providing a certain dose of dialysis—known to best result in long-term benefits, we are financially penalized. But create a fistula in a little old lady that usually requires interventions to make it work and keep it working and make her stay on the dialysis machine as long as it takes for the numbers to look right, then essentially get a bonus. If we see an in-center hemodialysis patient four times in a month, we stand to make 50 percent more money than if we only saw her once. And the nephrologist really only has to see the patient once each month—if a physician assistant sees the patient the other times, we still get paid. We would have to document a comprehensive medical history and examination over the better part of an hour with a patient returning to clinic twice to see the same money—and good luck trying to justify why that was clinically necessary to do. The second, third, and fourth in-center hemodialysis patient visits can be more like drive-bys—a simple documentation that we (or the physician assistant) “saw” the patient, with no notation of time required. Private insurance companies and the Medicare ESRD program pay top dollar for dialysis care, not clinic visits. It’s profitable to build another dialysis center, but we haven’t figured out how to build comprehensive outpatient palliative care services.

There’s another familiar lesson in this graph: output metrics—the data we graphed above—are far poorer indicators of trend causes than input metrics. It turned out in this case that the cause of our decelerating growth was a reduction in the rate of acquiring new customers—but nothing in these graphs gives any clue to that cause. With a sizable existing business, if you only pay attention to the output metric “revenue,” you typically won’t see the effects of new customer deceleration for quite some time. However, if you look at input metrics instead—things like “new customers,” “new customer revenue,” and “existing customer revenue”—you will detect the signal much earlier, and with a much clearer call to action.

Defining the basics of the culture, articulating leadership principles, regularizing essential practices—Bar Raiser hiring, teams with single-threaded leaders, written narratives, Working Backwards, focusing on input metrics—all these things have proved to be essential to us in other endeavors. Indeed, we can’t imagine doing business without them.

They’re evidence of a holistic misconceptualization of DEI, in which trainings and metrics ultimately function as a panacea for white guilt instead of a blueprint for enduring cultural change. So long as companies continue to approach diversity within this framework, they’ll continue to waste time, money, and employee patience. The shift to remote and flexible work won’t solve the problem entirely—not even close. But it can begin to disassemble structures that have long felt immovable and start to build new, unexpected, more inclusive ones in their place. —

In an effort to help decode these buyer actions, researchers from consumer intelligence firm Motista found specific “emotional motivators” that provide a critical indicator of customers’ potential affinity to a company.2 In fact, these emotional motivators, a proxy for value, were more compelling than any other metric in terms of driving key buying sentiments such as brand awareness and customer satisfaction. While hundreds of emotional motivators were found to drive consumer behavior, the study found ten that drove significant levels of customer value across all of the categories studied. I am inspired by a desire to: Brands can leverage this motivator by helping customers: Stand out from the crowd Project a unique social identity; be seen as special Have confidence in the future Perceive the future as better than the past; have a positive mental picture of what’s to come Enjoy a sense of well-being Feel that life measures up to expectations and that balance has been achieved; seek a stress-free state without conflicts or threats Feel a sense of freedom Act independently, without obligations or restrictions Feel a sense of thrill Experience visceral, overwhelming pleasure and excitement; participate in exciting, fun events Feel a sense of belonging Have an affiliation with people they relate to or aspire to be like; feel part of a group Protect the environment Sustain the belief that the environment is sacred; take action to improve their surroundings Be the person I want to be Fulfill a desire for ongoing self-improvement; live up to their ideal self-image Feel secure Believe that what they have today will be there tomorrow; pursue goals and dreams without worry Succeed in life Feel that they lead meaningful lives; find worth that goes beyond financial or socioeconomic measures

Leaders operate at all levels, stay connected to the details, audit frequently, and are skeptical when metrics and anecdotes differ. No task is beneath them.

At many companies, when the senior leadership meets, they tend to focus more on big-picture, high-level strategy issues than on execution. At Amazon, it’s the opposite. Amazon leaders toil over the execution details and regularly embody the Dive Deep leadership principle, which states: “Leaders operate at all levels, stay connected to the details, audit frequently, and are skeptical when metrics and anecdotes differ. No task is beneath them.

Because they have zero price, these services are virtually invisible in the official statistics. They add value to the economy, but not dollars to GDP. And because our productivity data are, in turn, based on GDP metrics, the burgeoning availability of free goods does not move the productivity dial. There’s little doubt, however, that they have real value. When a girl clicks on a YouTube video instead of going to the movies, she’s saying that she gets more net value from YouTube than traditional cinema. When her brother downloads a free gaming app on his iPad instead of buying a new video game, he’s making a similar statement.

To work less and make more, all you need to do is move the needle on one metric: Effective Hourly Rate (EHR). Here’s how to calculate your EHR: Take the amount of revenue you make in a month and subtract your costs. What you have left is your monthly profit. (If you have a job, then your wage is your profit.) Divide your profit by the number of hours you worked in the month to get it. The number you have now is your EHR. Let’s say you make $20,000 a month in revenue, and your fixed and variable costs come to $15,000. That means your profit will be $5,000. If you work 250 hours a month to achieve that profit then: $5,000/250 = EHR $20/hour

the Analyze stage is all about developing a comprehensive understanding of what drives your metrics. Until you know all the external factors that impact the process, it will be difficult to implement positive changes.

normally and performance is not degrading over time. As your fundamental understanding of what drives the business improves, it’s common for the WBR to become an exception-based meeting rather than a regular one for discussing each and every metric.

It is worth noting here that, at Amazon, even the most senior executives review the full WBR deck of metrics, including all the inputs and outputs. Metrics—as well as anecdotes about the customer experience—are the area where the leadership principle Dive Deep is most clearly demonstrated by senior leaders. They carefully examine the trends and changes in the metrics; audit incidents, failures, and customer anecdotes; and consider whether the input metrics should be updated in some way to improve the outputs.

The WBR is an important embodiment of how metrics are put into action at Amazon, but it isn’t the only one. Metrics dashboards and reports are established by every engineering, operations, and business unit at the company. In many cases metrics are monitored in real time, and each critical technical and operational service receives an “alarm” to ensure that failures and outages are identified instantly. In other cases, teams rely on dashboards that are updated hourly or daily for their metrics.

The customer is also at the center of how we analyze and manage performance metrics. Our emphasis is on what we call controllable input metrics, rather than output metrics. Controllable input metrics (e.g., reducing internal costs so you can affordably lower product prices, adding new items for sale on the website, or reducing standard delivery time) measure the set of activities that, if done well, will yield the desired results, or output metrics (such as monthly revenue and stock price).

OP2 aligns each group with the goals of the company. Everybody knows their overall objectives, including targets for revenue, cost, and performance. The metrics are agreed upon and will be supplied as part of every team’s deliverables. OP2 makes it crystal clear what each group has committed to do, how they intend to achieve those goals, and what resources they need to get the work done. Some variances are inevitable, but any change to OP2 requires formal S-Team approval.

Pronovost himself accounts for its success by the fact that the project worked through clinical communities, working toward common professional goals and treating central line–induced infections as a solvable social problem.

Our new care pathways were effective because they were led by physicians, enabled by real-time data-based feedback, and primarily focused on improving the quality of patient care,” which “fundamentally motivated our physicians to change their behavior.” Crucial too was the fact that “the men and women who actually work in the service lines themselves chose which care processes to change. Involving them directly in decision making secured their buy-in and made success more likely.” What we can learn from the Geisinger example is the importance of having providers develop and monitor performance measures. The fact that the measures were in keeping with their own professional sense of mission was crucial.

Our third-quarter financial results released on October 21, 2004, showed that sales had grown by 29 percent year over year. Free cash flow had increased by 76 percent. Many corporations would look at such growth figures with envy, but a closer look at our financials at the time revealed a more concerning picture. Throughout 2004, Amazon sales had continued to grow, but the rate of growth decreased from the prior year, across all lines of business. The output metric of sales revenue was not growing as fast as we wanted.

The Amazon Deliver Results leadership principle states, “Leaders focus on the key inputs for their business and deliver them with the right quality and in a timely fashion. Despite setbacks, they rise to the occasion and never settle.” Shipping speed is a key input metric for Amazon. So, if you are customer obsessed, then you’re also obsessed with measuring and improving the shipping experience for customers.

The oasis of success essentially conditions us to over-strive for external metrics and detaches us from our inner knowing. This often leaves us disconnected and drained.

share price is what Amazon calls an “output metric.” The CEO, and companies in general, have very little ability to directly control output metrics. What’s really important is to focus on the “controllable input metrics,” the activities you directly control, which ultimately affect output metrics such as share price.

When the retail, operations, and finance teams began to construct the initial Amazon WBR, they turned to a well-known Six Sigma process improvement method called DMAIC, an acronym for Define-Measure-Analyze-Improve-Control.1 Should you decide to implement a Weekly Business Review for your business, we recommend following the DMAIC steps as well. The order of the steps matters. Progressing through this metrics life cycle in this order can prevent a lot of frustration and rework, allowing you to achieve your goals faster.

Donald Wheeler, in his book Understanding Variation, explains: Before you can improve any system … you must understand how the inputs affect the outputs of the system. You must be able to change the inputs (and possibly the system) in order to achieve the desired results. This will require a sustained effort, constancy of purpose, and an environment where continual improvement is the operating philosophy.2 Amazon takes this philosophy to heart, focusing most of its effort on leading indicators (we call these “controllable input metrics”) rather than lagging indicators (“output metrics”).

Input metrics measure things that, done right, bring about the desired results in your output metrics.

We can’t tell you how many times we’ve heard people say, when talking about a recently launched Amazon initiative, “You can do that at Amazon because you don’t care about profits.” That simply isn’t true. Profits are just as important to Amazon as to any other major company. Other output metrics like weekly revenue, total customers, Prime subscribers, and (over the long term) stock price—or more accurately, free cash flow per share—matter very much to Amazon. Early detractors mistook Amazon’s emphasis on input metrics for a lack of interest in profits and pronounced the company doomed, only to be stunned by its growth over the ensuing years.

What happens inside the WBR is critical execution not normally visible outside the company. A well-run WBR meeting is defined by intense customer focus, deep dives into complex challenges, and insistence on high standards and operational excellence. One may wonder, at what level is it appropriate for executives to shift focus to output metrics? After all, companies and their senior executives are routinely judged by output metrics like revenue and profit. Jeff knows this well, in part based on his time spent working at a Wall Street investment firm. The simple answer is that the focus does not shift at any level of management. Yes, executives know their output metrics backward and forward. But if they don’t continue to focus on inputs, they lose control over and visibility into the tools that generate output results.

Prince of Wales still lies, her huge 44,000-ton bulk turned upside down by the violence of the enemy, nearly 40 fathoms deep off the Malaysian coast. Here, in all its concentrated, solemn vastness, an official war grave, is a solid, enduring relic of Britain’s final days as a great industrial, economic and naval power. At 745 feet long and 105 feet wide, she contains centuries of shipbuilding and fighting experience, now dead, scattered, disbanded, forgotten or lost, thousands of tons of steel from blast furnaces, mills and forges long demolished, made with coal from mines long ago closed and sealed, and dug and smelted and hammered by an industrial working class now vanished. Every intricate part of her was made according to the traditional measurements of England, feet, inches, pounds and hundredweight. These are now abandoned in favour of the metric system which was used by our enemies in that war and which would have been imposed upon us had we been defeated. But in this matter, as in so many others, we have made a conquest of ourselves. Somewhere in her barnacled ruins is the cabin where Churchill slept, the cinema where he watched That Hamilton Woman with tears in his eyes, the bridge from which he waved so cheerfully, and perhaps the rotted fragments of the hymn book from which he so lustily sang ‘For Those in Peril on the Sea’ and ‘Onward, Christian Soldiers!’, beside his ally and supposed friend, the president of the United States.

idea that Washington would work better if there were TV cameras monitoring every conversation gets it exactly wrong…. The lack of opportunities for honest dialogue and creative give-and-take lies at the root of today’s dysfunction.

Degradation of work. Compelling the people in an organization to focus their efforts on the narrow range of what gets measured leads to a degradation of the experience of work. Edmund Phelps, a Nobel Prize winning economist, claims in his book Mass Flourishing: How Grassroots Innovation Created Jobs, Challenge, and Change that one of the virtues of capitalism is its ability to provide “the experience of mental stimulation, the challenge of new problems to solve, the chance to try the new, and the excitement of venturing into the unknown.”9 That is indeed a possibility under capitalism. But those subject to performance metrics are forced to focus their efforts on limited goals, imposed by others, who may not understand the work that they do. For the workers under scrutiny, mental stimulation is dulled, they decide neither the problems to be solved nor how to solve them, and there is no excitement of venturing into the unknown because the unknown is beyond the measureable. In short, the entrepreneurial element of human nature—which extends beyond the owners of enterprises—may be stifled by metric fixation.10 One result is to motivate those with greater initiative and enterprise to move out of mainstream, large-scale organizations where the culture of accountable performance prevails. Teachers move out of public schools to private schools and charter schools. Engineers move out of large corporations to boutique firms. Enterprising government employees become consultants. There is a healthy element in this. But surely the large-scale organizations of our society are the poorer for driving out those most likely to innovate and initiate. The more that work becomes a matter of filling in the boxes by which performance is to be measured and rewarded, the more it will repel those who think outside the box.