Marina Gorbis's Blog, page 1544

Your Workplace Offers Flexibility, But Can You Really Use It?

Two-thirds of working adults surveyed by Harris Interactive for talent-acquisition firm Mom Corps say their companies would be willing to accommodate them if they requested flexible work schedules (for reasons such as taking care of their kids). Yet 47% of respondents feel that asking for flexible options would hurt their chances of advancement. So even though flexibility is gaining popularity as an abstract concept, organizations aren’t doing enough to make employees feel secure in actually using it; that represents a “significant disconnect between employer and employee,” says Mom Corps.

You Are What Your Employees Eat

When I started out in the food service business over four decades ago, corporate food was largely cafeteria-style dreck. But today, food is playing a role far beyond just keeping employees fed and sustained. What once was a distraction has become a great way of integrating work and life. In my work supplying food for some of the most innovative companies, I’ve found that making food – and great food experiences – part of everyday office life can make employees happier and more productive.

In 1987, when I launched Bon Appétit Management Company, I had this idea that employees deserved better than mystery meat. The first phase was simply about quality: Excellent food not only helped recruit and retain employees, but also increased productivity by encouraging employees to stay on campus for meals and not waste time getting to and from a restaurant. Then, once the quality baseline was established, employers started to ask how to help their employees be happier and healthier with food. That’s why, starting around 2000 or so, we suggested our chefs put healthy options front and center. They answered with locally-sourced salad stations, substituting healthier ingredients into traditional comfort foods, and hosting regular events — from cooking demonstrations to monthly nutrition-education tables.

And now, we find ourselves at another turning point. The baseline is delicious and healthy. Now it’s about more than the food — it’s about the food experience. If we’re good at what we do, employees eat with us several times a week or more. And work is no longer where people spend just 40 fixed hours per week, but a space with fluid hours and rhythms dictated more by inspiration and the need to innovate. And in that environment, there’s no reason why you shouldn’t have lunch with your colleagues standing outside in the sun, eating fish tacos from a cool van, or sampling different chutneys in an evocatively lit campus restaurant.

How do you turn lunch into a moment of community, inspiration, or connection? Take Google. At its Mountain View headquarters, we operate 30 different cafés. Every day, Google employees can decide what they feel like eating, and in what kind of setting: from a grilled meatloaf sandwich at an all-barbecue joint, to a seitan “Reuben” from the 100% vegan restaurant. Not long ago we opened what feels like a traditional Indian restaurant, with table service for Googlers and a set three-course menu that changes daily. In the front, dark booths and sheer divider curtains offer intimacy to small teams for meetings; in the back, a Bollywood theme encourages group celebrations. It’s been packed since we opened it; young employees talking over dosas, Android phones face down on the table.

The experiences are useful because they fit the company – and inspire collaboration. “Googlers enjoy unexpected twists and surprises that trigger conversation and reflection. Together we’ve created diverse food environments that are conducive to casual collisions and a sense of community,” says Michiel Bakker, Google’s Director of Global Food Services.

At many corporate campuses, we invite local chefs and food businesses in, and “pop up” surprise treats and healthy snacks regularly. At Oracle, we host a weekly farmers market and offer pastries and confections made to order for special occasions. It’s key to recognize the difference between having a piece of pie for dessert and pre-ordering ginger-pear pies to take home for Thanksgiving. Productivity used to be about keeping employees’ personal lives at bay; now it’s about integrating work life with well, real life.

We’ve been running full-fledged food trucks at Google and elsewhere, including a gourmet grilled-cheese truck that made a weekly stop outside Starbucks’ corporate headquarters in an industrial part of Seattle, among other locations. We’re about introduce what I think is the next stage — Dub Boxes. These are customized VW bus shells that have been kitted out with a grill and a refrigerator, to offer ever-changing, fun menus that like food trucks, will entice people to get up and go outside — but not far — with their colleagues.

Upstairs from the Dub Box now delighting Starbucks and coffee tourists, we worked closely with Arthur Rubinfeld, Starbucks’ chief creative officer and president of global innovation, on a three-part dining concept: a wood-paneled neighborhood bistro open to the public for lunch, a jewel of an employees-only sushi restaurant, and a casual but authentic taqueria. Arthur’s goal was to re-establish a sense of the Starbucks culture among the company’s employees, community, partners, and visitors, and a year later, our food experiences seem to be doing just that.

It’s impossible to feel siloed in environments like these. A different kind of interaction happens than when you file into a cavernous cafeteria and sit down with a tray at a long table. Meanwhile, many companies have accepted that social media is an integral part of how they do business. Employees “lifecast” without thinking twice about it. Those glowing posts and filter-enhanced photos of their lunches can be a very effective marketing campaign for a great place to work.

The benefits that companies are reaping by placing a renewed emphasis on food are too varied and too numerous to ever turn back. Even universities, which compete for students just as much as companies do, are changing the way they think about and serve food. And once those young people — tomorrow’s corporate employees — get accustomed to locally and sustainably sourced meals, presented in innovative ways to keep the experience fresh, they won’t ever again settle for mystery meat and the fluorescent glow of vending machines.

Can Chinese Smartphone Darling Xiaomi Compete in Western Markets?

In the week before Apple’s release of its latest generation of iPhones, a lesser-known Chinese upstart, Xiaomi, had a launch party for its new Mi3 phones. Led by its Steve Jobs-inspired CEO Lei Jun, the company has experienced breakneck speed since its first smartphone launch in October 2011. With a business model of at-cost hardware and software up-selling, it recently raised its 2013 sales targets from 15 million smartphones to 20 million, and is now gazing abroad.

Lei Jun has hired ex-Googler Hugo Barra to head Xiaomi’s international expansion. Barra has his work cut out for him: Chinese companies have had mixed success so far in competing with top Western brands on several fronts at once. For every success (like Huawei or Lenovo), there have been stumbles (like Jianlibao and or Li-Ning).

Why have Chinese companies struggled to build consumer brands overseas? The answer has been in large part a failure to meet consumers’ social and emotional needs.

What Job Are You Doing?

For Barra and Xiaomi the “jobs-to-be-done” theory, in particular, is relevant. Many internationalizing companies fail because they pick the wrong jobs; addressing this can save both Xiaomi and other companies money and strife.

The “jobs-to-be-done” theory articulates the gap between how producers view and market a product and how customers actually use it. Every time a customer buys a product, they are trying to do a job that brings some value to them – and not necessarily what the product says on the label. In the words of Harvard Business School marketing professor Theodore Levitt, “People don’t want to buy a quarter-inch drill. They want a quarter-inch hole!”

The jobs that customers want to do have functional, social and emotional dimensions. For example, in buying a can of Coke (as opposed to another drink), I might be addressing 3 jobs:

Functional: “Enjoying an affordable drink, or quenching thirst”
Social: “Signaling social status or social inclusion”
Emotional: “Exercising an emotional connection with the Coke brand”

The relative split of the functional, social, and emotional dimensions helps explain how a challenger should best attack the incumbent. For example, consumer brands tend to have more of a social/emotional component to their jobs-to-be-done, while B2B products are heavier on functional needs. This means that consumer brand challengers must pay more attention to the social and emotional needs of their customers (often through heavy marketing expenses), while B2B players can afford to compete mostly on their product’s price and efficacy. It is difficult and time-consuming to fulfill the social and emotional jobs, and consumer brand challengers are often tempted to replicate the incumbents’ strategies. But, in Clay Christensen’s disruption language, this approach puts them on a “sustaining” rather than “disruptive” path. And there the incumbents almost always win.

Li-Ning stumbled because it tried to target low-end customers of Nike, and could not fulfill their social/emotional jobs better than Nike without spending more money. According to the company’s vice-president of digital operations, Craig Heisner, the company struggled after it “went right into a fiercely competitive overseas market going directly against the likes of Nike and Adidas”. Similarly Jianlibao, formerly the number one beverage in China, lost out on a frontal battle along the social/emotional dimension overseas before coming back home to compete with Coca-Cola on functionality (price and taste). Unfortunately, with its lower cost structure, Coca-Cola had the patience to see this sustaining challenge through, and ended up crushing the Chinese brand both domestically and overseas.

The better path for Chinese consumer brands seeking expansion to the West is to focus on consumers not yet in the smartphone market. Instead of targeting current customers of the incumbent (who already have sophisticated social/emotional needs associated to the product), they should target non-consumers with a compelling functional offering and help mold their social/emotional associations. For example, when Honda moved into the US motorcycles market, it found little success in targeting existing American motorcyclists — it was only after it moved to non-motorcyclists that it experienced success in creating a new subcategory. B2B businesses can afford to go directly to the low end (Japan’ steel industry and Korea’s semiconductor industry have achieved success via this route) and compete on functionality, but consumer brands should be more careful unless they have the budget for a long fight. Hence the focus on non-consumers.

Xiaomi’s Challenge

The implications for Xiaomi and Hugo Barra are clear. If Xiaomi chooses to prioritize foreign markets with low penetration of iPhones and high-end smartphones (e.g. India, African markets), the dominant entry strategy is to focus on cultivating the vast pool of non-consumers of high-end smartphones. Xiaomi’s resources should thus be directed towards converting feature-phone users to their phones, or educating a new generation of consumers without phones.

If Xiaomi decides to target markets with high penetration of high-end smartphones (e.g. USA, Western Europe), Barra should take a more patient approach. The first step should be to corner the (relatively small) market of non-smartphone users. The step after that involves seeking out non-consumption instances, e.g. selling Xiaomi software to existing Android users, as an add-on. In doing this, Xiaomi can form a “tribe” of loyal supporters with new emotional and social associations who can provide the platform for a push into the lower segment of the high-end smartphone hardware market. Only with this platform should Xiaomi pursue direct competition for low-end customers of Apple and Samsung. The strategy calls for a measured, careful approach – one that first analyzes the jobs that current non-consumers of high-end smartphones are trying to do (e.g. save money, “simplify my life”) and creates a compelling value proposition for them.

With a valuation of $10 billion after 3 years of existence, Xiaomi certainly has caught the eye of many investors. But as Barra settles into his new role, he might find that getting foreigners comfortable with Xiaomi’s name is the least of the company’s internationalization problems.

An Old-Boys’ MBA Is Not High-Value Management Education

How much value does your MBA provide? The value of your management education derives partly from the skills it helps you develop and partly from the school’s reputation. High-value management education prepares leaders to navigate the most complex challenges organizations face. It forces you to question your assumptions and habitual ways of acting, boosts your self-awareness, and increases your capacity to lead in a way that elevates your organization and the people who work within it above its field of competitors.

Promoting gender equity in the leadership of private and public organizations is one of the most pressing business, economic, and social challenges we face at present.  It’s clear that the loss of talent that occurs when women face career advancement barriers poses a threat to firms’ long-term competitiveness. But while many business leaders have embraced the importance of increasing gender equity and are investing in significant efforts to reduce internal obstacles to progress, it’s surprising to find leaders in management education who are not. Take the dean of a leading global business school, who was chatting with business leaders at a reception. “The proportion of women both on your faculty and among your student body is below average,” one asked, “what are you doing about that?” The dean’s response: “Of course gender is important. But I’d say it’s a second-tier issue for us. Our primary focus is on providing world-class management education.”

Like many people, perhaps this dean is suffering from gender fatigue: he doesn’t have a full picture of the gender barriers that still exist and consequently is tired of hearing so much about gender.  Because he fails to perceive how significant the gender equity problem is—as well as the fact that he is implicated in it—the conversation feels like a distraction to him. But in fact, it is impossible to provide a world-class management education in a learning environment that disproportionately serves one half of the population and draws on a limited set of perspectives.  In such an environment, the quality of analysis and decision making is diminished.

It’s true that well-meaning but under-resourced diversity initiatives, especially those without firm backing from organizations’ chief executives, can generate more frustration than enlightenment. But business schools that fail to recognize and advocate for the critical role of gender-balanced leadership in business performance simply reinforce the status quo.

Wanting more insight into the thinking behind the dean’s comment, I contacted a colleague who has served on the school’s faculty for many years and inquired about the gender climate there. “It’s poor,” he reported. “Our few women professors receive lower ratings on teaching evaluations than the men do. We know that there is a gender effect in these ratings. And we recruit, retain and promote women at a lower rate than men.” He explained that the proportion of women on the faculty mirrors the low proportion among the school’s lucrative executive program participants.  The bottom line is that the school serves up management educators that its clients find most pleasing, even though by so doing it may undermine the quality and value of its programs.

But wait: doesn’t the fact that this school’s female professors receive lower ratings mean that the school is simply rewarding merit by advancing more male than female faculty? No, we cannot conclude this. Research on selection and performance appraisal confirms that people tend to rate others who are demographically similar to them as more qualified. This common form of bias is as prevalent among management students and executive participants as among any other group.

Jodi Kantor’s recent New York Times story on Harvard Business School’s multipronged initiative to promote a gender-equitable climate offers additional insight. Close examination of the HBS culture revealed that, among other problems, classroom discussions were often dominated by a relatively small number of confrontational male students who browbeat female faculty and students in ways that they were not equipped to deal with effectively. Students saw female professors as less able than their male colleagues to manage this classroom dynamic. The effects were damaging for female students as well: because classroom participation counts for half of students’ grades, their academic performance suffered. In addition, it seems that some professors simply overlooked the contributions female students were making in the classroom, unwitting victims of their own biases. In turn, women students rarely achieved the highest honors at HBS.  Rather than accepting the classroom dynamic and toughening up the women to handle it better, HBS invested itself in the infinitely more complex and important effort of changing the gender climate. In addition to building in careful observation and measurement of male and female students’ participation and providing coaching for women faculty and students, the school promoted extensive dialogue about gender issues.

Fostering gender equity in business schools is difficult work that requires high-level commitment, resources and creativity.  Despite the discomfort and eye-rolling that purposeful culture change creates, however, the HBS case study shows that focused commitment can yield impressive results. In addition to significant increases in female professors’ teaching effectiveness and female students’ academic performance, interviews with more than 70 students, faculty and administrators revealed that HBS had become a markedly better place for women in many ways.

Business schools have a major role to play in fostering the development of gender-balanced business leadership. Developing managers who appreciate the value of gender balance in leadership and are sensitive to the many dynamics that undermine it is a foundational strategy in the effort to make progress. While we applaud the excellent executive women’s leadership development programs that many schools offer, we caution that “fixing the women” will not fix the larger problem. As long as business schools fail to commit to the pursuit of gender equity in our core management programs, our contribution to building the sophisticated leadership competencies businesses need to thrive will be constrained.

To ensure that the management education you invested in retains—and hopefully increases—its value, you should be concerned about how well your school is doing on fostering gender equity. The same thing holds true if you’re in the market for management education: if you care both about the quality of your experience during your studies and the value of your education after completion, it makes sense to investigate the extent to which the schools you are considering are committed to and performing well on gender inclusion.  Here are some questions to ask.

In what ways does the school model a gender-inclusive management style and organizational culture? What initiatives have you implemented, and what have the results been?
What percentage of the school’s board of trustees are women?
What percentage of the school’s faculty overall and, in particular, full permanent professors are women? How many female professors will I have in my program?
What percentage of students in the program are women?
What do current students and recent graduates have to say regarding the school’s gender climate inside and outside of the classroom?

Clearly, most business schools lack the resources of HBS. And under-resourced gender equity initiatives that lack real commitment from the top of the organization don’t have a great track record. But one thing is clear: it’s time for those who lead business schools to admit to themselves and others that if they aren’t actively working for real gender equity in their classrooms, they are playing into the system of second-generation bias that continues to bedevil businesses today. To produce high-value management education that is needed to drive successful businesses, we need more educational leaders who are visionary on gender inclusion and fewer who are holdouts from the old boys’ club.

Value-Based Health Care Is Inevitable and That’s Good

Vaccines. Anesthesia. Penicillin. Bypass surgery. Decoding the human genome. Unquestionably, all are life-saving medical breakthroughs. But one breakthrough that will change the face of medicine is being slowed by criticism, misunderstanding, and a reluctance to do things differently.

That breakthrough is value-based care, the goal of which is to lower health care costs and improve quality and outcomes. It will eventually affect every patient across the United States. Not everyone, however, is onboard yet, because part of the value-based equation is that hospitals will be paid less to deliver better care. That’s quite a challenge, but one that Cleveland Clinic is embracing as an opportunity to do better. Others must, too.

How the Health Care World Will Change

We all know that U.S. health care is too expensive, too inefficient, and the quality is too varied. The goal of value-based care is to fix that.

A major component of the Affordable Care Act is to change the way hospitals are paid, moving away from a reimbursement model that rewards procedures to one that rewards quality and outcomes. No longer will health care be about how many patients you can see, how many tests and procedures you can order, or how much you can charge for these things. Instead, it will be about costs and patient outcomes: quicker recoveries, fewer readmissions, lower infection rates, and fewer medical errors, to name a few. In other words, it will be about value. And that is good.

Whether providers like it or not, health care is evolving from a proficiency-based art to a data-driven science, from freelance physicians to hospital-employed physicians, from one-size-fits-all community hospitals to vast hospital networks organized around centers of excellence. Each step in this process leads to another.

When hospitals employ physicians on an annual salary as we do at Cleveland Clinic, a doctor is paid the same no matter how many patients he sees, how many procedures he performs, or how many tests he orders. One-year contracts hold our doctors accountable, with yearly performance reviews that include each doctor’s quality metrics, clinical outcomes, and research. And having all your doctors on the same team makes it easier to coordinate patient care among different groups of specialists.

As more independent physicians begin to be hired by hospitals, the opportunity for large group practices and hospital consolidation grows. As consolidation expands, data and transparency become increasingly important, as a way to ensure that caregivers across the system are providing comparable care.

All of this, of course, leads back to quality, which requires an effort to achieve standardization, reduce variation, and eliminate unpleasant surprises. It’s analyzing processes, measuring outcomes, and changing practices until you get it right.

To remain viable in today’s rapidly evolving environment, health care systems must reduce costs while continuing to improve quality and outcomes.

The Cleveland Clinic’s Journey

In the October issue of Harvard Business Review, Michael Porter and Tom Lee cite six components of high-value care-delivery systems: integrated practice units; cost and outcomes measurement; bundled payments; integrated care delivery across facilities; expanded services across geography; and an information technology platform to enable those processes.

As they note, Cleveland Clinic is one of two medical centers worldwide that has implemented all six, beginning with integrated practice units, which we call “institutes.” A patient-focused institute combines medical and surgical departments for specific diseases or body systems. All of our institutes are required to publish outcomes and measure costs. With bundled payments, we combine all the services provided before, during, and after a complex procedure like joint replacement, into a single charge. We have integrated care through shared protocols and the electronic medical record at all of our 75 care-delivery sites. And our expansion across Northeast Ohio into Florida, Nevada, and overseas allows broad geographic access to our services.

What makes Cleveland Clinic different stretches back to our founding 92 years ago as a physician-led group practice that runs a hospital – not a hospital that employs doctors. This distinction is important. Decisions from the CEO on down are made by physicians based on what is best for the patient.

Mining Data

As a leader in the electronic medical records, we have a wealth of data that can tell us what’s working and what’s not. For instance, we were able to comb through data of heart-surgery patients to find that those who received blood transfusions during surgery had higher complication rates and lower long-term survival rates. This finding – mined from our own data – changed the way we do things; we now have strict guidelines in place to limit transfusions.

We’ve made similar strides in many other clinical areas, using data to drive quality. By collecting data on provider performance and making that data transparent, central-line infections have decreased by more than 40%, while urinary-tract infections have dropped 50%.

Data can help identify variations in clinical practice, utilization rates, and performance against internal and external benchmarks, leading to improved quality and a sustained change in culture. Last year, we established a values-based care team, which seeks to eliminate unnecessary practice variation by developing evidence-based care paths across diseases and to improve comprehensive care coordination so that patients move seamlessly through the system, reducing unnecessary hospitalizations and ER visits.

Lowering Costs Without Compromising Quality

American health care is on an unsustainable path. Health care spending topped $2 trillion in 2011. The Centers for Medicare and Medicaid Services predicts that without major change, it will account for more than 20% of GDP by 2021, up from 5.2% percent in 1960. What that means is that if we continue on our current path, $1 in every $5 spent in the U.S. economy will go toward health care.

We can choose a different path, though. At Cleveland Clinic, we’ve been engaged in an ongoing effort to trim costs across the entire system. Through a concerted focus on our supply chain, we use rigorous value-based purchasing protocols, market intelligence, and business analytics to examine every purchase from the standpoint of value, utility, and outcomes. Over the past two years, this has resulted in cost savings of more than $150 million.

Our electronic medical records are also programmed with a “hard stop” function to reduce unnecessary duplicate tests. This led to a 13% reduction in blood-gas determinations, generated $10,000 in monthly savings for laboratory tests, and resulted in savings of $117,000 in just the first month for genetic testing.

A key part of the cost solution is to educate all caregivers, including doctors, about what items cost. Earlier this year, we created a Cost Repositioning Task Force to work with all caregivers across the entire Cleveland Clinic system to assess everything we do and everything we spend. Now, as part of the purchasing process, dozens of doctors gather to discuss the merits of certain products: Which ones provide the best outcomes for patients? How many are needed? How much does it cost?

Traditionally, knowing the cost of a stitch or a catheter or a bone screw — or any of the thousands of other supplies used during surgeries — hasn’t been part of doctors’ medical consciousness. To remedy that, we’ve taped price lists to supply cabinets in some ORs. In others, posters remind everyone to choose supplies carefully, stressing this message: “Without compromising quality, consider cost-effective alternatives.”

As health care reform kicks into high gear, providers are facing a difficult challenge: being paid less to produce better outcomes. We must view this as an opportunity, not a burden. After all, the providers who make the transition early will be rewarded with more satisfied patients, lower expenses, and pride in a job well done.

Follow the Leading Health Care Innovation insight center on Twitter @HBRhealth. E-mail us at healtheditors@hbr.org, and sign up to receive updates here.

Leading Health Care Innovation

From the Editors of Harvard Business Review and the New England Journal of Medicine




Leading Health Care Innovation: Editor’s Welcome
Redefining the Patient Experience With Collaborative Care
A Better Way to Encourage Price Shopping for Health Care
Military Leadership Lessons for Training Doctors
Why Health Care Is Stuck — and How to Fix It

Nate Silver on Finding a Mentor, Teaching Yourself Statistics, and Not Settling in Your Career

Perhaps no one has done more for the cause of data-driven decision-making in the minds of the public than Nate Silver. His book, The Signal and the Noise, explains the power of statistical modeling to improve our predictions about everything from the weather to sports to the stock market. Data science is the hottest field to be in right now, and Silver is its poster child.

But for most people, the gulf between recognizing the importance of data and actually beginning to analyze it is massive. How do those without extensive training in statistics equip themselves with the skills necessary to thrive (or even just survive) in our age of “big data”?

Last month I had the chance to put that question to Silver, and his answers may surprise you. Far from counseling that everyone must major in statistics, in the edited conversation below he advises students and executives alike to roll up their sleeves — no matter their statistical literacy — and get their hands dirty with data.

HBR: If I’m an average professional or an executive, I’ve read your book, I know this stuff matters and I also know it’s complicated and I can only expect so much. Is there such a thing as kind of a level of statistical literacy that I need to get to? What kind of education do I have to go back and make sure that I have?

Silver:  I think the best training is almost always going to be hands on training. In some ways the book is fairly abstract, partly because you’re trying to look at a lot of different fields. You’re trying not to make crazy generalizations across too many spheres.

But my experience is all working with baseball data, or learning game theory because you want to be better at poker, right? Or [you] want to build better election models because you’re curious and you think the current products out there aren’t as strong as they could be.  So, getting your hands dirty with the data set is, I think, far and away better than spending too much time doing reading and so forth.

HBR: What about if I’ve read your book and I’m just starting college or a little younger and I’m trying to think actually maybe this statistician/data scientist role is something that I’m interested in? What do I study? How much education do I need? What’s that base for plugging into some of these jobs?

Silver:  Again, I think the applied experience is a lot more important than the academic experience. It probably can’t hurt to take a stats class in college.

But it really is something that requires a lot of different parts of your brain. I mean the thing that’s toughest to teach is the intuition for what are big questions to ask. That intellectual curiosity. That bullshit detector for lack of a better term, where you see a data set and you have at least a first approach on how much signal there is there. That can help to make you a lot more efficient.

That stuff is kind of hard to teach through book learning. So it’s by experience. I would be an advocate if you’re going to have an education, then have it be a pretty diverse education so you’re flexing lots of different muscles.

You can learn the technical skills later on, and you’ll be more motivated to learn more of the technical skills when you have some problem you’re trying to solve or some financial incentive to do so. So, I think not specializing too early is important.

HBR:  Say you’re at the point where you started playing around with some data. You’re interested, you’re motivated, and now it’s time to actually learn some of those skills just like you talked about. Am I just going and picking up a textbook? Am I trying an online course?

Silver: I mean my path has been kind of sui generis in some ways, right? Probably an online course could work, but I think actually when people are self-taught with occasional guidance, with occasional pushes here and there, that could work well.

An ideal situation is when you’re studying on your own and maybe you have some type of mentor who you talk to now and then. You should be alert that you’re going to make some dumb mistakes at first. And some will take a one-time correction. Others will take a lifetime to learn. But yes, people who are motivated on their own, I think, are always going to do better than people who are fed a diet of things.

HBR: Say an organization brings in a bunch of ‘stat heads’ to use your terminology. Do you silo them in their own department that serves the rest of the company? Or is it important to make sure that every team has someone who has the analytic toolkit to pair with expertise?

Silver: I think you want to integrate it as much as possible. That means that they’re going to have some business skills, too, right? And learn that presenting their work is important. But you need it to be integrated into the fabric of the organization.

You’ve seen this shift in baseball teams, for example, where it used to be that you’d hire an analyst to check that box and have them compartmentalize. That doesn’t accomplish much at all.

HBR: You’ve had obviously some very public experience with the fact that even when the data is good and the model is good, people can push back a lot for various reasons, legitimate and otherwise. Any advice for once you’re in that position, you have a seat at the table, but the other people around the table are really just not buying what you’re selling?

Silver: If you can’t present your ideas to at least a modestly larger audience, then it’s not going to do you very much good. Einstein supposedly said that I don’t trust any physics theory that can’t be explained to a 10-year-old. A lot of times the intuitions behind things aren’t really all that complicated. In Moneyball that on-base percentage is better than batting average looks like ‘OK, well, the goal is to score runs. The first step in scoring runs is getting on base, so let’s have a statistic that measures getting on base instead of just one type of getting on base.’ Not that hard a battle to fight.

Now, if you feel like you’re expressing yourself and getting the gist of something and you’re still not being listened to, then maybe it’s time to change careers. It is the case [that] people who have analytic talent are very much in demand right now across a lot of fields so people can afford to be picky to an extent.

Don’t take a job where you feel bored. If it’s challenging, you feel like you’re growing, you have good internal debates, that’s fine. Some friction can be healthy. But if you feel like you’re not being listened to, then you’re going just want to slit your wrists after too much longer. It’s time to move on.

HBR: What about, from the perspective of an organization or a business, knowing those areas where data is really going to be the key to making good predictions and good decisions versus those areas where it isn’t? Speaking to a lot of start-ups and tech companies, you hear ‘Data can’t tell us anything. The future is so different than the past and we really can’t rely on it at all, so it’s really an intuition game.’

Silver: A lot of times when data isn’t very reliable, intuition isn’t very reliable either. The problem is people see it as an either/or, when it sometimes is both or neither, as well. The question should be how good is a model relative to our spitball, gut-feel approach. And also how much do we know about this problem. There are some issues where you just don’t have a good answer and you have to hedge your risks as a business and not pretend that you’re more certain than you really are.

A lot of private businesses are very reluctant to deal with uncertainty in their outlook. The manager doesn’t want to seem like he’s not sure what he’s doing. And the consultant or the analyst wants to provide information to make the manager feel more confident. That’s quite problematic because a lot of problems that are on the frontier of business, on the frontier of science, [are] by definition fairly challenging ones that no one else has solved.

That’s where having a more humble attitude about what you can accomplish and what you can’t is important. Just because a model is not going to be very precise or accurate doesn’t mean that therefore you should trust your gut instinct after a couple of whiskeys and assume it’s going to be very much better.

Three Signs That You Should Kill an Innovative Idea

Whether you’re a digital start-up or an institutional entrepreneur, three simple heuristics offer an excellent way to determine whether a fledgling innovation initiative should be put out of its misery (and yours).  Even if the innovation business case appears compelling and its numbers sound, should these three pathologies appear, don’t hesitate or delay: Kill your innovation effort ASAP.

1) No Pleasant Surprises

Almost all innovation efforts have the hiccoughs and bumps in the road. Design schedules invariably slip and that “quick-and-dirty” prototype ends up costing much more than expected. That’s normal. But listen closely for and pay attention to the pleasant surprises:  The coding that takes two weeks to develop and test instead of two months; the material that has more malleability and strength at lower cost; that really smart supplier who makes one of her smarter designers available to collaborate.

The absence of pleasant surprise is not unlike the dog that doesn’t bark: A signal that something that should be happening isn’t. If the innovation idea or proposal really represents a novel value creation opportunity, there’ll be serendipities sprinkled amidst the inevitable unpleasantness. Those “small wins” may not look or feel like much but, almost always, they signal new opportunities for exploitation and advance.

For example, a retailer found that automating how it would send coordinated digital alerts to its suppliers and distribution centers was much easier than expected. Writing, coding and testing business rules turned out to be less risky and expensive than thought. That “pleasant surprise” gave IT, purchasing agents and store managers alike the confidence to create a bigger business conversation around what had once been a purely technical innovation effort.

Pleasant surprises reinforce original enthusiasm. That is fuel. No pleasant surprises means you’ll soon be running on empty.

2) No Deeper Insights

This sounds similar to “No Pleasant Surprises’” but it’s not. Every aspiring innovator has a tacit or explicit hypothesis about their innovation and its desired impact on the organization and/or its customers. Quite naturally, innovation teams bring a confirmation bias—a cognitive decision trap—to those hypotheses. They’re looking for evidence supporting the new product/service path they’re on.

But that’s not good enough. As innovators progress through prototyping iterations and design tests, they need to ask, “Are we getting deeper, richer and more sophisticated insights into our value proposition and how it’s perceived?”  Simply hitting benchmarks and milestones affirming that everything’s copacetic is complacency. That’s dangerous.

If innovators aren’t learning dramatically more about their potential customer’s real needs or the “degrees of freedom” their innovation effort enables, they’re doing compliance, not transformation. Innovators who are really innovating are also really learning. Each iteration and test—with and without customers—should be generating nuggets of data and information that facilitate a deeper understanding of what they’re really doing instead of what they started out doing. Innovation journeys should, quite literally, change how they see their original ideas.

I was sitting in a new product meeting at a South of Market social media start-up that had been grinding away on a clever little Facebook app that wasn’t quite getting as much traction or enthusiasm as they had expected. The product leader asked his team, “So what do we understand about our users now that we really didn’t before…?’

No one had a good answer. No real learning was going on. The product was killed. Good.

3) Greater Prospect/Customer/Client Engagement Inspires Little Emotion

Learning curves are important but so are emotional plateaus. The more your prospects engage with innovation prototypes, the more their feelings should intensify around what you’re trying to do. Ideally, they should come to care as much—or more—about your innovation as you do. But if their feelings don’t change as they engage more with your next iteration or simplified UX, you’re in an emotional kill zone. Indifference is death.

It’s even better if prospects dislike the changes you’re making in your models and prototypes because that means you were doing something they liked. You know you’ve got something when prospects and beta partners want to collaborate and contribute to your value proposition. Their actions speak louder than their words. They choose to be more engaged with your team’s innovation journey. They may not be “passionate” but they care. You can tell. Most importantly, they want the innovation to succeed not because they like you, your team or your company but because they “get” and appreciate the value and values your promised innovation represents.

Don’t confuse emotional engagement with focus group feedback or customer satisfaction scores. You want and need to be attuned to any changes they have in their “affective connection” to your innovation. If measurably greater participation and engagement with your prototypes and simulations fail to move the emotional needles of your prospects, they’re not going to commit to you when the real challenges materialize. Customers don’t have to love or even like your prototypes; but they do need to feel that the more they interact with your innovation, the more they get what it can do for them.

If your innovation fails even one of these tests, you know you have serious problems. But if you’re 0 for 3, you’ve struck out. Stop what you’re doing immediately. Passionate innovation champions are wonderful and essential to success. But their passion inherently means they can’t be dispassionate analysts of their babies. The real issues emerge after the charismatic innovation champion leaves the room.

Does the innovation generate the serendipity, insight and emotional engagement that matters? You know what to do if the answer is, no.

Executing on Innovation

An HBR Insight Center




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Women Wed to High Earners Had the Biggest Increases in Hours Worked

From the late 1970s to the late 1990s, American married women’s weekly working hours rose significantly, but the increases were uneven: The increase in hours was 3 times greater for those married to top earners than for those wed to low earners, say Christian Bredemeier of the University of Dortmund and Falko Juessen of the University of Wuppertal, both in Germany. Women married to high earners worked more hours because they had greater earning potential; women with high earning potential became more likely to marry men with high earning potential because birth control allowed for later marriages, after “wage uncertainty” was resolved, the authors suggest.

Twitter, that Old Media Darling

Did you hear? Twitter’s initial public offering is coming. News of this has created a fresh round of pontification across digital media. There are already winners and losers. There are reasons to worry (140 of them, naturally). Its IPO is “unusual.”

The IPO will finally put a market value on Twitter—is it $10 billion? $100 billion?—and many digital types hope and believe it will validate new media.

Then again, what if Twitter isn’t really new media after all? Before you get ecstatic that Wall Street is about to validate new media, listen to one researcher, who has come to the conclusion that Twitter is becoming “a non–evolving, static structure, like TV…It’s just going to become a new way to follow celebrities, corporations, and the like.”

That’s Olivier Toubia, from Columbia Business School, who co-authored research on Twitter called Intrinsic versus Image–Related Motivations in Social Media: Why do People Contribute to Twitter (pdf), which was recently published in Marketing Science. We caught up with Toubia to talk about his research and the evidence that Twitter’s becoming, as he says, “a traditional channel.”

HBR: How do you come to the conclusion that Twitter is becoming much more like old media than continuing to blaze a new media trail?

Toubia: My colleague Andrew Steven from the University of Pittsburgh and I researched how people use Twitter. But we didn’t ask them “Why do you post?” We did an experiment. We created 100 synthetic accounts to increase the number of followers from some subset of 2,500 non-commercial Twitter users. These were very realistic accounts with avatars, and followers, and posts. We literally made people more popular and watched how they responded.

How did they respond?

For users that already have many followers, as they become more popular they become less active. It appears that at some threshhold, they have earned their status as “popular” and they stop working as hard to earn more followers.

This assumes that people’s motivation in posting is to earn followers.

What we know for sure is that non-commercial users don’t have any direct financial incentive to post. We had two hypotheses as to why they do post. One is that they like to share information with world, that they want to reach others. This is an intrinsic motivation. They enjoy the act of contributing. The second hypothesis is that posting is self-promotional, a way to attract followers to be able to earn higher status on the platform. Judging by how people behaved once they achieved popularity—they posted far less content—we believe the second hypothesis is probably the primary motivation. If the primary motivation were to share with the world, most people would not slow down posting just because they were popular. But most people did slow down as they gained followers.

Okay, but how does this make Twitter more like old media TV than new media?

So as Twitter becomes mature, the connections become stable. There are fewer new people and there’s less room for new following. When that happens, posting will not be a way to attract new followers. If the motivation for non-commercial users is to gain followers and they can’t do that, they are not motivated. They can’t get the value out of the platform that they want. If they stick around, the value proposition has to shift away from contributing , to become more popular, and toward consuming content, to be entertained.

What content will they consume?

Content that’s produced by people who still have an incentive to contribute: commercial entities and celebrities. Professional content creators. You end up with commercial users who get value by producing content for non-commercial users who get value by consuming it—just like TV.

So does this mean Twitter is being overvalued as a new media brand as it approaches its IPO?

It’s hard to answer the question. All I can say is that the value from Twitter, whatever it is, will come from traditional channels rather than from conversations between people. It has more value as a traditional media platform than as a platform for conversations which is what we think of it as. I don’t know how much peer-to-peer communication and information sharing factored into the valuation, but it’s clear to me that’s not where the value will be.

Twitter maybe not as disruptive to media as we thought it was?

It’s going to end up much less that revolutionary grassroots source of ideas and will instead converge toward a traditional commercial venture . It will be harder and harder for non-commercial users with interesting things to say to cut through the clutter. It will be harder to get noticed. Also, it’s a bit unrealistic to expect everyone to have value to bring to the platform, so we end up with the professionals producing the content, just like with TV and magazines and so forth.

Do you find this at all sad?

I think it will be sad, yes. The effect when something good gets attention and everyone gets on to it inevitably affects what made it special in the first place. But maybe this just settles into what it will be and the next grassroots social media movement will come along. It’s not the end of social media.

What do you think the executives at Twitter think about this idea that they’re becoming old media?

I think they understand it. You can actually see it in their positioning. I kept two screen grabs of Twitter’s “About Us” page. One is from more than two years ago, and it was all about sharing and the grassroots aspect of spreading ideas around the world, and the fact that it’s “powered by the people”:

Now, they’re saying, you don’t even have to post, just come and be here on our platform. It’s about following and even goes so far as to suggest “you don’t have to tweet to get value from Twitter”:

They have changed their positioning significantly. They’re courting consumers, not producers. They’re trying to monetize eyeballs, which is very much an old media way of doing business.

The Downside of Health Care Job Growth

While the growth of health care costs has slowed over the past few years, lowering costs over the long term will depend on improving health care labor productivity. Over half of the $2.6 trillion spent on health care in the United States in 2010 was wages for health care workers, and labor productivity has historically worsened at a rate of 0.6% per year. Simultaneously, the individual mandate, subsidized coverage, and Medicaid expansion in the Affordable Care Act (ACA), along with an aging population, will drive up the demand for health care. Reducing the rate at which health care costs grow, and the proportion of U. S. gross domestic product and public sector budgets that are consumed by health care over the long term, therefore, will require either increasing labor productivity or substantially lowering workforce salaries. The early signs are worrisome. With health care viewed as a jobs source and jobs being added faster than demand is growing, we appear to be on a path toward more workers and lower salaries, not necessarily more productivity, unless something changes dramatically.

Using data from the Bureau of Labor Statistics (BLS) and the American Medical Association, my colleagues and I found that from 1990 to 2012, the number of workers in the U.S. health system grew by nearly 75%. Nearly 95% of this growth was in non-doctor workers, and the ratio of doctors to non-doctor workers shifted from 1:14 to 1:16. On the basis of BLS median wages, this equates to $823,000 of labor cost per doctor. Demand and supply are not growing in tandem: from 2002 to 2012, inpatient days per capita decreased by 12% while the workforce in hospitals grew by 11%. This misalignment underlies some of the productivity decline we have observed in health care. Fortunately, we anticipate demand for health care to grow in 2014, so to the extent that jobs are not added, productivity gains are possible. Unfortunately, health care as an industry continues hiring far faster than demand is growing, adding 119,000 new workers in the first half of 2013, for example, with little increase in patient volume.

So, what are all these people doing? Today, for every doctor, only 6 of the 16 non-doctor workers have clinical roles, including registered nurses, allied health professionals, aides, care coordinators, and medical assistants. Surprisingly, 10 of the 16 non-doctor workers are purely administrative and management staff, receptionists and information clerks, and office clerks. The problem with all of the non-doctor labor is that most of it is not primarily associated with delivering better patient outcomes or lowering costs. Despite all this additional labor, the most meaningful difference in quality over the past 10 years is the recent reduction in 30-day hospital readmissions from an average of 19% to 17.8%, which arguably was driven by penalties imposed by the ACA and not by organic improvements in care models. While one could interpret the expansion of non-doctor clinical labor as a source of leverage for doctors, the number of patients doctors are seeing and whose care they are managing hasn’t increased.

This trend is troubling as we enter a phase of transformation in health care. Today, more than 60% of labor is nonclinical and is fragmented across various provider organizations, payer systems, and delivery models. It is highly unlikely that we can reorganize these jobs in a way that meaningfully improves productivity. This difficulty is compounded by regulations that limit the corporate practice of medicine, Stark laws, state nurse and physician assistant scope-of-practice and licensure rules, and billing requirements that physicians physically see patients to receive full reimbursement. Reducing regulatory hurdles represents a substantial opportunity to improve productivity by reducing fragmentation of clinical labor and delegating care to lower-cost qualified providers, but the most immediate goal should be to eliminate many nonclinical jobs through standardizing and simplifying revenue-cycle processes, credentialing, supply chains, regulatory compliance, and information technology systems, which will then allow us to reengineer administrative systems.

On the clinical side, care delivery must be designed so that the 6 clinical workers per doctor substantially contribute to a patient’s care. Today, too much clinical labor is diverted from direct patient care to lower-than-license roles such as payer utilization-management roles, staffing of underutilized diagnostic centers, administrative roles, and uncoordinated care activities. In practice, little of the existing clinical labor is actually organized into patient-care teams, and few have clarity about what outcomes they are specifically working to achieve and who is responsible. Reorganizing clinical labor around direct patient care and creating unambiguous accountability for clinical outcomes together have the potential to substantially alleviate the predicted shortage of clinicians as coverage is expanded and to improve system-level productivity, outcomes, and patient experience.

Lessons can be learned from sectors such as manufacturing. Through a significant revolution, manufacturing was able to transition from direct labor to a more productive, efficient industry, and this happened over a century, from 1855 to 1975. In addition, both production and administrative labor decreased as processes were redesigned to become more reliable, error-free, and efficient. In health care, although, the optimal relationship among doctors, other clinical staff, and administrative labor is uncertain, it is certainly the case that there should not be more administrators than doctors and all other clinical labor combined. Rather, one would expect the ratio of nonproductive to productive labor to decline over time in health care as it has in all other productive sectors of the economy. We can also surmise that the improvement needed will take decades and must be sustained by economic incentives that are aligned with productivity far more strongly than they are today.

To reverse the decline in health care labor productivity, we must transform the system both on the supply and on the demand side. As Ari Hoffman and Ezekiel Emanuel argue in the Journal of the American Medical Association, reengineering is very different from implementing new technologies. For example, new innovative reimbursement models aim to reward providers for lowering health care costs on the supply side. Consider, for example, the sorts of models being tested in Arkansas (where health care providers are given a fixed budget and a set of quality measures to achieve for an entire course of care from diagnosis to recovery) and Pioneer accountable care organizations (where providers are paid a lump sum and given a set of quality goals for year of care for a patient). With these payment models, providers make more money when they invent more cost effective approaches to delivering high-quality care. Simultaneously, more transparency in price and quality data can direct patients to more productive settings, intensifying the incentive for providers to improve on the demand side.

In the interim, workers in the health system will need to worry about their wages as more jobs are added — unless care and costs are substantially reengineered in the systems in which they work. Health care practitioners should take pride in delivering consistent and excellent clinical outcomes with fewer labor hours and lower total costs, just as leaders have in other industries. Moreover, health care leaders should also focus on replicating other sectors of the economy when it comes to reducing nonproductive labor. Finally, health care leaders and practitioners should seek to remove labor that is not directly contributing to better outcomes or delivering a hard return on investment through reductions in the cost of care. It is conceivable that shared services can emerge for processes such as credentialing, compliance, and data management and that, along with ACA-mandated revenue-cycle simplification they can substantially reduce administrative labor. In a health system where costs, out of fiscal necessity, grow more slowly, it is far more desirable to reduce nonproductive administrative labor than to reduce clinician wages.

Follow the Leading Health Care Innovation insight center on Twitter @HBRhealth. E-mail us at healtheditors@hbr.org, and sign up to receive updates here.

Leading Health Care Innovation

From the Editors of Harvard Business Review and the New England Journal of Medicine




Leading Health Care Innovation: Editor’s Welcome
Why Health Care Is Stuck — And How to Fix It
Getting Real About Health Care Value
Understanding the Drivers of Patient Experience
A Better Way to Encourage Price Shopping for Health Care
Redefining the Patient Experience with Collaborative Care