Marina Gorbis's Blog, page 1536

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




We Need a New Approach to Solve the Innovation Talent Gap
Recognize Intrapreneurs Before They Leave
The Right Innovation Mindset Can Take You from Idea to Impact
When You’re Innovating, Resist Looking for Solutions

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

How to Make a Job Sharing Situation Work

Job sharing — splitting a full-time position into two part-time jobs — is an increasingly popular flexible work arrangement. But is it really possible to share a job with another person? How can you make what looks good on paper work in reality?

What the Experts Say

“There are a wide variety of reasons to choose a job sharing arrangement — it might be to take care of a dependent, to work another job, or to advance one’s education,” says Stew Friedman, a professor of management at the Wharton School and author of Total Leadership: Be a Better Leader, Have a Richer Life. Lotte Bailyn, a professor of management at MIT’s Sloan School of Management and co-author of Beyond Work-Family Balance: Advancing Gender Equity and Workplace Performance, agrees, noting that people often pursue a job share because they want less stress in their lives. Whatever your reason, it’s up to you (and your partner) to make the situation work. Joan Williams, a law professor and the founding director of the Center for WorkLife Law at the University of California’s Hastings College of the Law, believes that any job can be shared if done intelligently and thoughtfully. Here’s how:

Choose the right partner

If you have a say in the matter, be sure to select someone with whom you can easily communicate, collaborate, and disagree. These arrangements often require difficult conversations about prioritizing work, office politics, and personal matters so you want to be sure you pick someone compatible. But don’t seek out your perfect clone either. These situations work best­ for you — and for the company ­— says Bailyn, if the job sharers have complementary skills, experience, and perspectives.

Decide how to divide up the work

“There are a number of ways to slice any given job,” says Williams. “It’s important to conceptualize all different parts and divide them up in the most effective way.” Some people split the work by each taking responsibility for certain tasks. This is called the “islands model” or a “job split.” Others share the same workload and simply divide up the days (usually with a bit of overlap). This is called the “twins model” and is often the simpler of the two. The model you choose will depend on the nature of the job and what preferences and skills each of you bring to it.

Communicate, communicate, communicate

“For job-sharing to work well, both parties must zealously convey and seek information from the other,” says Friedman. “Think ‘mind meld.’” Ideally this communication should happen face-to-face, says Bailyn, but many job sharers use other ways to connect, including email, phone, and Skype. Use this time to agree on work priorities, discuss any issues that have come up, pass off work if necessary, and check in about how things are going generally. “You can’t leave anything unspoken. It has to be very explicit,” says Williams.

Secure your supervisor’s support

If you proposed the arrangement, make sure your boss is onboard. “It’s possible to be successful in an organization that doesn’t generally support job sharing but not if your manager is against it,” says Williams. “If your supervisor doesn’t support it, it’s probably not going to work.” Ask your boss for feedback regularly. Be vigilant about communicating with her about the arrangement. When Friedman was a senior executive at Ford Motor Company, a pair of his direct reports shared a job. “What made it work so well was their willingness to go the extra mile to keep me and others informed about how they were coordinating their work; this gave all those involved a sense of confidence and trust that this was a good deal not just for the job-sharers but for our company,” he says.

Manage expectations and perceptions

Indeed, it’s not only your boss who needs to be informed. Anyone you work with—colleagues, clients, vendors—needs to know how to reach each of you and who they can expect to respond when. Some job sharers will share an email account and phone number. Others automatically cc their other half when responding to any email. The key is to make sure it’s a seamless experience for everyone around you. “All those who interact with you should experience a unity of understanding and purpose,” says Friedman. And any time you talk about the arrangement, focus on how it benefits the organization. “The main thrust of communications with co-workers and clients should focus on the benefits to others, especially the ‘two heads are better than one’ argument,” says Friedman. “Others want to know how this set-up will be good for them, not for you.”

Battle the bias

Bailyn says that one of the biggest barriers to making these situations successful is the attitude of others. In fact, some people perceive any flexible arrangement as a sign that you aren’t committed. Williams has observed this stigma in her research at the Center for WorkLife Law. “In most organizations this is seen as an ‘odd duck’ arrangement,” she says. The best way to challenge this bias is to excel at the work. “Make it very clear that you’re meeting the norms the organization has for people who are dedicated to the job,” says Williams.

Give it time

Once you’ve settled on an arrangement that you, your partner, and your boss think will work, try it out. Set a pilot period and experiment with how you split the work and communicate. Then tweak as necessary. “It’s good to give the process a bit of time to work out the kinks and get people used to it. After some experience, most people react positively,” says Bailyn. No matter how long you’ve been sharing a job, it’s a good idea to continually reassess and make adjustments based on what’s working for each of you, your boss, and the organization.

Principles to Remember

Do:

When selecting a partner, choose someone you can easily communicate, collaborate, and disagree with
Ask your boss for feedback regularly — be vigilant about communicating with her about the arrangement
Make sure it’s a seamless experience for your co-workers and anyone outside your organization

Don’t:

Leave anything unspoken — talk to your partner regularly
Assume everyone will be fine with the arrangement — combat bias by excelling at your shared work
Set the details in stone — it’s better to experiment and make adjustments as necessary

Case study #1: Experiment with the arrangement to find what works

Gretchen Anderson had been working as a consultant to the Katzenbach Center at Booz & Company for a few months when the opportunity to take on the role of center director came up. Gretchen knew one of the center’s leaders, Jon Katzenbach — she’d worked at a firm he’d previously founded— and was excited about the opportunity to work with him again. But she was a new mother, and only wanted to work 50% time. Fortunately, another consultant who had been with the firm for almost eight years, Carolin Oelschlegel, was also interested in the position. She was based in London and had recently started working 80% time for lifestyle reasons — “there are so many things I wanted to do outside of work and I wanted the time to do them,” she says.

Gretchen and Carolin spoke once by phone and each had a strong sense that they would work well with the other so agreed to put their collective hat in the ring (each dedicating 50% to the role). Such job-share arrangements are not common at Booz & Company, but the leaders at the Katzenbach Center were eager to make it happen.

Initially, they thought they could split the work by region: Gretchen could cover North America and Carolin would take Europe. But they soon realized that this division felt artificial and ineffective. Next, they tried working on the same projects, passing them back and forth, but that didn’t feel efficient either. Eventually, they decided to carve out two buckets of work: immediate requests from client teams, which required a response within 24-48 hours, and longer term projects.

Immediate requests are now resolved by whoever is available and online at the time. For the longer-term projects, they collectively designate a lead who can bounce the work back to her partner as necessary, relying on the other’s feedback and re-allocating when demands shift or projects end. They manage this hybrid between the “twins” and “islands” model by staying in constant contact: “We’re in touch by email every day, even on Gretchen’s off days and we always know where the other is,” says Carolin.

While they were initially diligent about keeping those around them apprised of how they divided the work, their bosses and co-workers now trust them to sort it out. “How we divide our work is neither of interest nor of concern,” says Gretchen. “They seem to trust that things will happen — and to let us sort it out on our own.”

There have been unexpected benefits to sharing the job as well. For example, since their time is limited, they both push each other to focus on the most important priorities. “We have two peoples’ judgment call on what really needs to get done,” Gretchen says.

Case study #2: Put respect first

Several years back, Ryan Frischmann decided he wanted to get into software development so he applied for a job as a lead developer at a small start-up in Rochester. During his interview, he learned that the role would be shared with a current employee who had been diagnosed with terminal cancer. The idea was that they would do the same job until his co-worker got too sick to work or passed away.

Ryan recognized that this was a unique situation but he was willing to give it a try. “I thought it would be a great learning experience personally and professionally,” he says. The arrangement allowed his colleague the flexibility he needed to continue working and gave Ryan the opportunity to learn from a more experienced colleague.

The two men shared the same role and responsibilities — Ryan worked full time at the office while his colleague worked from home when he was able to.

Ryan believes that the most important element in making their relationship work was respect. “I made sure he made the final decision on anything new in the development pipeline,” he says. “My colleague had built the software from scratch. He felt it was an accomplishment and so did I.” Ryan also worked to gain his co-worker’s trust. “I had to demonstrate to him that I understood his coding and methods. When he was sicker, he told me and the others that he was leaving his software in capable hands. This meant a lot to me.”

The job share lasted for nine months before Ryan’s co-worker died, and Ryan has carried on in the role. He says the experience has inspired him. “My partner had a lot of pride in his work and completed some of his best work when he was very sick. I never anticipated the effect it would have on me personally.”

When Big Companies Support Start-ups, Both Make More Money

In the technology world, we’ve seen the tremendous impact that eBay has made in helping small e-commerce businesses get off the ground. Many of them started off selling merchandise from their apartments or homes, and some evolved to become power sellers. Today there are hundreds of thousands of people around the world making their living selling merchandise on eBay. In its turn, eBay has made commissions from every single transaction that has occurred on its platforms.

Now imagine if eBay went beyond providing a technology platform and entered the field of business incubation in a meaningful way, It’s an idea that could have a huge impact. Sellers making $3,000 a month could be coached to get to $15,000 a month. Those making $25,000 a month could perhaps get to $100,000 a month.

Consider, also, Apple and Google. Apple’s iOS and Google’s Android have fueled a global bonanza in app development. Millions of apps have proliferated the world. Some of these generate decent revenues. Most stagnate. But if these two companies took business incubation seriously, and instead of just offering technical guidance on building apps, also offered business guidance, the impact on global GDP would be tremendous.

In the start-up world, there’s a big focus on business incubators such as YCombinator–perhaps too much focus. As we think about the forces that could help more businesses grow into substantial economic engines, it’s important to look at the role that big companies can play, too. Some of them are already providing important platforms that can help small companies get off the ground. But over time, I see the potential for big companies to do much more.

I routinely meet companies that are growing smartly by leveraging platforms provided by big companies. In 2007, I met Kirk Krappe, CEO of a small startup called Apptus. Kirk and his two cofounders Neehar Giri and Nathan Krishnan had earlier done a venture-funded startup called Nextance. Nextance was an enterprise software company providing contract management software. It raised $60 million in venture capital, and eventually failed. The team then decided to take their domain knowledge and start Apptus as a cloud-based contract management software company.

This time round, they decided to take no venture capital. They chose to build the company on Salesforce.com’s Force.com platform, which kept development costs low. The team was able to bootstrap the company, and within a couple of years, shot to $5 million in revenue. Recently, they have received a large influx of funding of $37 million from a group of investors including Salesforce.com.

The beauty of this model is that Salesforce.com has made available a cloud platform-as-a-service upon which entrepreneurs can rapidly and cost-effectively build businesses. The eco-system works really well, and Salesforce.com takes a percentage of the revenues for products built on their platform.

Today, thousands of developers are building on Salesforce.com’s multiple cloud platforms. They all pay royalties to the corporation. Thus, if Salesforce.com were to enter the field of business incubation, helping these companies grow their businesses, the economic benefit would be staggering.

And Salesforce.com itself would also benefit from the increased royalties that would increase their revenues and profits.

The best thing about the corporate incubation model is that it is a win-win for both the corporation and the small business, and it doesn’t have to worry about the startups being fundable by VCs.

Microsoft’s BizSpark program supports 72,000 small businesses building on their various platforms. Oracle’s partner network has a million companies. These massive eco-systems are gold mines of entrepreneurial potential.

As usual, over 99% of these eco-system partners are not venture fundable. But many of them can become $1 million, $5 million, or $20 million a year businesses.

Brian Knight, CEO of Pragmatic Works is one such entrepreneur. Brian has navigated the Microsoft eco-system, and built a $12 million dollar company around the SQL Server platform.

Even on a less mature platform such as SAP’s HANA – a big data analytics platform – entrepreneurs are building significant businesses. Chris Carter, CEO of Approyo, is a great example. Even though SAP only has a couple of thousand entrepreneurs developing on HANA at this point, Chris has already achieved close to a million dollars in revenue developing on it.

Imagine how many Brian Knights, Chris Carters and Kirk Krappes are out there!

If only we could plug the knowledge gaps in these millions of entrepreneurs, and help expand the middle of the pyramid, Capitalism 2.0 would be within reach.

It is, in fact, within reach. Especially, if the corporations wake up and play a bigger part.

We Need a New Approach to Solve the Innovation Talent Gap

My brother-in-law, Joel Murphy, and his brother Erik run a family business  called Murphy & Associates in Seattle. It’s an IT and business consulting staffing business that: (a) recruits top programmers and program managers; (b) identifies key projects at large tech companies; and (c) makes a match. The service allows large companies to rapidly staff up and down. Top talent can work part of the year for full-year pay without ever having to search for a job or worry about paperwork. The key to its success is how well Murphy & Associates evaluates talent. They go beyond the resume and interview and instead focus on key projects employees worked on, using their industry expertise and deep network to discern whether the projects were truly successful, and then they cross-check the impact of the person.

What if this model existed on a larger scale to help staff innovation and growth strategy initiatives for big business?

I previously wished for a Shark-Tank for Corporate America to create more efficient capital markets to fund great innovation ideas bogged down by bureaucracy. But  capital isn’t the only problem facing big businesses that want to innovate. Many companies lack the right talent to take on important new projects that could help create the business’s next big category.

Just this year I’ve spoken to more than three CEOs who are excited about huge opportunities for category creation or big innovation, but each is stuck figuring out with how to staff it. Often they tell me that because their innovation is very similar to a previous successful business launch–the analog could range from a technology like Netflix to a consumer product innovation like the Swiffer–they’d love to hire a person who’d been a key player in those projects. I routinely hear comments like: “Who was on that team? Who did what? Finding those people would be awesome!”

In theory that should be easy to do. In practice it’s not, because success has many fathers. The teams that create breakthrough products are large. The projects last a long time, and team members come and go. By the time a product is a clear-cut success, vital team members have moved on. And if a product becomes a breakout hit, you can be sure that many people who were only peripherally involved will claim more than their fair share of success. I remember talking to someone who was a core member of the team that developed a $500 million breakthrough innovation. He recounted meeting numerous strangers who claimed they’d played a key part. He would sometimes respond: “I’m glad to meet you, because I didn’t realize you had such an important role on my project.”

Observing this problem, I’ve begun wondering: What if there was a talent exchange model that wasn’t people and skill centric, but rather project and role centric?

Said differently, I think the existing talent evaluation models should be reversed. Right now the model starts with people, then skills, then accomplishments. Validating the information is getting better (due to innovations such as LinkedIn’s endorsed skills), but most accomplishments are not vetted.

My colleague, Jody Kirchner, and I brainstormed the following: What if LinkedIn, search firms, and VCs flipped the flow. What if, instead of looking at resumes, they began by looking at recent successful products, then identified and validated who was on those teams, including  their roles, responsibilities and personal results. Only at the end would you begin to focus on individual people.

The first step is to build a searchable database of the biggest innovations, successes and toughest problems in business. A good amount of this is available already via HBR, or key lists like Fortune 100’s top fastest growing companies or Nielsen’s Breakthrough Innovation Report. The key is to create searchable details around the situation, complication and resolution. What was the original context before the success? What were the biggest barriers? How did they solve for it? The more detail, the easier it will be for other companies to identify analogs for them to explore.

The second step is to identify the team that drove the results. I think this will be easy, as I’ve discovered that core members of a team have memories like elephants. They remember intricate details, key make or break moments, and especially who was involved and who really contributed (and who did not). The teams could be self-regulated…you can identify yourself as a member of the team, but a good part of the team needs to approve.

The third step is to highlight the specific roles and responsibilities each core member had. Who was the project manager? Who was the technical lead? Who sold the idea into key stakeholders? Did this person add or detract from team chemistry? And importantly, would this project have been as successful without this person?

Finally we need a step that identifies what our CEO, Steve Carlotti, and I like to say are the 3F’s needed to drive truly extraordinary growth—Facts, Faith and Fortitude. Finding the facts is the easy part. Having the faith to believe in something that doesn’t yet exist and the fortitude to persevere are two entirely different things.  Finding a way to verify this, even if by qualitative endorsement by others on the team, is critical to finding the right people.

We believe the data to synthesize this exists –  and existing social media networks can help us validate. The question is: who will get it done? If someone can accomplish this, many companies will benefit.

Executing on Innovation

Special Series



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The Right Innovation Mindset Can Take You from Idea to Impact
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How Your Brand Can Beat Goliath

There was once a running joke at Virgin Mobile when it came to our marketing spend: What Virgin Mobile would spend in one year, AT&T would spend on one episode of “American Idol.”

Many disruptive brands struggle with how to best manage their marketing budgets while they strategize around how to dethrone their incumbent Goliaths. Smaller companies, of course, don’t have the advertising spends to compete with their competitors on traditional vehicles, and they’re far more susceptible to shifts in the competitive landscape. A simple budget cut can render them “dark” during peak months on TV, causing their consideration levels — a key metric for brand directors trying to compete — to dwindle.  Marketing execs then end up “re-launching” their own brands to new audiences on a loop in a struggle to make up for lost time.

This is exhausting and, more importantly, it isn’t working.

If ever a David were to save his strength to fight Goliath, the first step would be to eliminate needless spending on changing campaigns for re-brands, and focus more time on changing the conversation. Literally.

Social conversation is the only way small brands can get an edge on the big guys.

True brand affinity — or brand “lust” as we like to call it at Virgin — breaks down into three key ingredients: Rational, cultural, and emotional. The Goliaths typically play in the rational space; this is the arena that appeals to the part of the brain looking for a good deal.  The core campaign message is very specific and clear, and it’s usually about value. The problem is, when several competitors share the same rational message about value, the Goliath with the loudest voice (i.e., the highest media spend) wins.

For your brand to break through, you need to appeal on two more nuanced dimensions: cultural and emotional.  You need to create and share a point of view that your prospects find enlightened and unique. And to express that point of view is to speak your mind freely — as a brand — not about what you have on sale, but about something bold that will stir a customer’s interest.

Cultural marketing starts by creating your own topical breaking news about trends your customers care about, making your brand hyper-obsessed about a specific niche or topic. When you tap into something that your audience can relate to, you’re tapping into something cultural.  Lululemon, for example, talks about yoga. Nike talks about fitness.  But sometimes the delineation isn’t always clear.

At Virgin Mobile, we tapped into something more abstract:  the absurd phone etiquette that seemingly preoccupies us all. It wasn’t about showing a happy customer using Instagram;  it was instead about the relatable folklore surrounding a woman who’d rather Instagram a pizza she was eating than respond to her jilted ex’s desperate texts.

This example taps into two cultural and relatable norms – our smartphone-obsessed society and a relationship gone bad. They require more thought and customization than typical marketing messages around the rational, but also result in an ownable voice that Goliath can’t touch.

Emotional marketing is even more nuanced. It requires tapping into, or reacting to, a larger, more shareable moment. And above all else, it requires a mastery of the element of surprise to create something emotional.  If a cultural trend occurs, the response that creates an audience reaction is not to align with it, but to buck it.  That, in turn, makes the moment emotional. And true emotion is what fuels something shareable.

During the wake of the recession in 2009, we at Virgin Mobile faced the awkward decision to potentially cancel our music festival (as others had done, fearing that fans couldn’t afford the ticket).  At the time, swine flu and job layoffs headlined the nightly news. Our goal was to put forth a new energy that would focus on optimism.  We embraced the cultural winds and declared our festival free of charge to the public.  We created a VIP lounge whose admittance was only offered to those who had been laid off (and those guests were pampered accordingly).

“Pink Slip Pinatas” were hung from trees and for a brief moment, young fans could celebrate a day of free music instead of stressing about getting a job. Virgin Mobile FreeFest was born with an announcement that earned nearly 500 million earned impressions and to this day (literally to the day — the 5th annual FreeFest was just held two days ago), the festival raises hundreds of thousands of dollars a year for homeless youth, celebrating good karma and the right to pay it forward. Similarly, that same year, Hyundai offered it’s legendary offer to buy back cars from people who lost their jobs.

Owning a breakthrough moment. A social conversation. These are admittedly scrappy tactics and taken alone, don’t make a cogent, annual marketing strategy. To really master this art on the cheap, you have to create a platform that can leverage traditional vehicles that gain mass reach while complementing them with the “fairy dust” of social storytelling that adds folklore to your brand and forges true emotional connection to reach the consumer.

Another good way of thinking about it is via the lens of a political campaign, which typically involves two forms of marketing: traditional (e.g., TV ads, billboards) and seeded. For example, a political candidate may run an ad that says she favors gun control — a marketing message that speaks to rational.  The campaign’s social storytelling, however, may spread images that remind us of recent shootings to create context around the marketing message. “Haven’t we had enough? Isn’t it time we elect someone who controls our guns?” The social conversation tees up the ad, which is designed to reach as many people as possible with a simple, memorable message.

Here’s the way that works at Virgin Mobile. We would run ads that spread our core message: “For $35 a month, you get unlimited messaging and data and only 300 voice minutes.” Our seeded message on social channels was simply the following: “You don’t need voice minutes. No one talks on the phone anymore. In fact the people you talk to on the phone are people you probably don’t want to talk to (e.g., the cable guy, airlines, etc.).” Both seeded and traditional worked hand in hand. And if budget cuts killed our TV media (and oftentimes, they did), our social conversation was alive and well.

Goliath will always have the luxury of being omni-present in the consumer’s field of vision. But Goliath is not nimble. And to truly win a crowd, you need to pivot to tell the right stories they want to hear at the right time.