Category Archives: Insights

A Few Lessons I’ve Learned

A young entrepreneur asked me a great question the other day, “What are some things you learned later in your career that you wish you knew earlier in your career?” I didn’t have a great answer at the time, but of course it got me thinking. There are a few key lessons I have focused on these past five years or so that weren’t part of my thinking early in my career. I’m not sure I would have cared for these thoughts back then, but I thought I’d share them.

Be comfortable being uncomfortable.

Most of the great things in life are hard. The circumstances that lead to great accomplishment are often uncomfortable — strange and new, out of your comfort zone, and filled with challenges. Getting your mind programmed to be comfortable in the midst of challenge, conflict and uncertainty brings you great benefit. You won’t shy away from the conflict or uncomfortable conversations often required to influence outcomes. Your mind becomes in control of your body. In physical challenges, your mind usually quits before your body does because it is opting to avoid discomfort. It tells you your body is failing before it actually is. Take control of this and get comfort around the fact that many situations in life are not comfortable, but you can still handle it. Hang in there. Be in control.

Develop an expert point of view earlier than the consensus.

By the time everyone agrees on something, it has already happened. You can’t innovate ahead of the curve unless you see a future that most others don’t yet see. You also have to be right about it, but not every time. You can change your view about the future when you see evidence that it won’t happen the way you thought it would. For me, I first try to become expert on something by going super-deep on the topic, learning everything I can about it, talking to many people about it, and using the technology or product in question as much as I can. Once I do, I usually find that many of the people talking about it aren’t truly experts. In fact, I believe many of the loudest voices are often the most wrong.

I remember in 1996, John Markoff, then the most senior and well-respected technology writer at The New York Times, called Microsoft’s Active Desktop, “the most fundamental change to personal computers since the machines were invented in the 1970’s.” To me, this sounded like not just silly hyperbole, but a fundamental misreading of where things were going on the internet. Given his vaulted position at The Times, many people believed Markoff and accepted his view that Microsoft would dominate the next phase of the internet. As we all now know, Active Desktop was an inconsequential product and a failure, and more than fifteen years later, Microsoft is still struggling to be consequential on the internet.

I work to develop my own point of view about where things are going. I work to validate that by looking for data or evidence. Then, if I feel passionately about it, I try to bet on this outcome. And in many cases, my point of view is different than most others. This gives me confidence that I might be on to something (or just be totally wrong). Consensus scares the heck out of me. Really loud voices tend not to be right. My job, as both an entrepreneur and a venture investor, is to beat the consensus long before it happens, but to be right that it will.

Be fact-based in your observations and beware of confirmation bias.

We live in a world filled with data, so use it to make observations. Don’t live life purely on your gut. I gain confidence in my point of view by seeking out research or data that supports my hypotheses. But I force myself to be open about the data I find, knowing that we have a psychological tendency to seek out data which confirms our preconceptions. In short, be honest with yourself about what you observe and challenge your point of view.

Figure out what you are good at and depend on it.

Are you great at reading people, generally right about their capabilities? Are you an astute observer of markets and trends, usually right about who will win or what will happen? Are you a product savant whose obsessiveness with simplicity produces outstanding experiences? Are you a natural leader, able to convince a room full of people to follow you into an uncertain future? Are you an outstanding sales person, able to convince people to part with their money? Or, are you a total introvert who wants to avoid interaction with people but can architect a massively scaleable web application? Maybe you are a mixture of these things? Knowing what you are good at and building your undertakings around that is a quicker path to success. Yes, you can improve in all areas of weakness, but certainly engineer the game to play to your strengths.

Be self-aware, know your short-comings, and find mentors.

We all suck at plenty of things. The only way to get better and to level-up is to first recognize our own limitations and to work with experts to teach us. Self-aware people recognize their short-comings, are not afraid to talk about them, and seek out experts to teach them how to improve. Asking for help is not an admission of weakness. It’s the path to improvement.

Big companies are slow, do not innovate and are unwilling to self-cannibalize.

When I was younger I thought this might be true but now I have seen it happen over and over and over again. Sure, there are exceptions, but in general, startups can move very quickly and innovate on the home turf of large incumbents. As organizations get bigger, executive pay structures often do not encourage companies to cannibalize their existing business even when they see a new technology coming that may impact them. And power is more fleeting these days then in decades past. Do not be daunted by the presence of large incumbents when you can capitalize on a technology shift and catch giants flat-footed. There are too many examples of this common cycle of disruption working time and again.



Will There Really Be an Uber for Everything?


The Next Uber

This post originally appeared on TechCrunch here.

Though the press has turned on them as of late, seizing on every allegation and misstep, I love using Uber. From the very first time (September 28, 2010 to be exact) I saw the little town car icon crawling across the map coming towards my little green dot I knew taxi cabs, airport car services, and parking lot attendants in downtown SF were going to see a whole lot less of me.   Tens of millions of riders around the globe love this service so much it has become its own verb. And at a $40 billion valuation, it is no wonder that it has become cliché to describe other on demand mobile services (ODMS) as the “Uber for X”. Any offline service that can be reserved, or delivered to you physically, or transmitted to you virtually through your smartphone seems to have a startup or several trying to become the Uber for that particular vertical. A few of these will turn into very large and successful global internet brands, grabbing major market share and even greater market capitalization from the offline rivals they out innovate. Most, however, will succeed on a much more limited scale, making only a small dent in their industry and servicing limited geographic markets.

My own framework for trying to determine which markets and which companies will be truly transformational is basic in concept. Start with a service where the greatest percentage of customers are most painfully unhappy with the existing providers. Fortunately for entrepreneurs and investors (but unfortunate for our daily lives as consumers), many service sectors suffer major challenges around availability, quality, transparency, and pricing. Not all problems are equally painful, however. Most people don’t consider the logistics around getting a massage or attending a yoga class nearly the same level of pain and frustration as home renovation or trying to sell their old car privately. There is also the question of how often one needs such a service, with frequently used services having the advantage of being more likely to become sticky habits versus one-off trials that may be forgotten over time. We are much more motivated to find solutions for frequently encountered pain than occasional pain. Next, ask yourself how can an on demand mobile service leverage smartphone technology, network effects, economies of scale, rich data, crowdsourcing, and the other tools found in a tech entrepreneur’s arsenal to build a service that truly delights customers and “bends the curve” in terms of customer experience. This is obviously the really hard part. Great service is hard to consistently deliver in general, but there are those services that are innately more challenging, such as home or auto repair, where the nature of the service is to diagnose and fix idiosyncratic physical problems that catch consumers by surprise leading to an initial state of frustration and financial worry. While aspirational to think that an ODMS can fix even the most broken service sector, often the symptoms of pain in the hardest industries may need to be treated progressively over time. Thus, it is the total distance travelled between the typical incumbent service level and the redefined ODMS service level, rather than the start or end point on an absolute scale, which creates the opportunity to create a truly great business.

How can on demand mobile services create delight versus their offline incumbents?

Immediacy and Reliability—the main point of most ODMS is to use the smartphone to be your remote control for life so that when you push the button for your ODMS stuff needs to happen, as fast and consistently as possible. Uber leverages local network effects between drivers and riders, and invests heavily in data science and AI simulations to insure that rider wait times are as short as possible and drivers are as busy as possible so they can earn the most money. Without short wait times Uber would not be nearly the magical experience we all love. Another example of instant fulfillment is Doctor on Demand*, a service providing immediate smartphone video visits with a board-certified physician so that you don’t have to wait for days or weeks to get an appointment to see your doctor or head to an after-hours clinic or emergency room for routine medical needs. Clearly you wouldn’t use Doctor on Demand if you have severe chest pain or are bleeding profusely, but there are a huge variety of use cases for which you don’t need to be in the same room as your doctor and the convenience of an immediate appointment, at one third the cost (on average) compared to an in-office visit, is so compelling that employers are offering DoD as a benefit to their employees.

For the majority of services that can’t be delivered virtually like Doctor on Demand, the act of rolling out city by city is expensive and time consuming, often requiring an investment in “boots on the ground” to recruit and train workers, market to new users, and assure quality in new cities. If you are truly bending the curve with a revolutionary service breakthrough you can attain a superior growth rate which attracts the capital to enable a nationwide and even global expansion strategy like in the case of Uber or Airbnb. For many ODMS that are only incrementally improving upon the traditional service model, geographic expansion will likely have to come more slowly and may ultimately max out at the major US cities or even just a region or two. This is not necessarily a bad thing as many enduring businesses can be built as the most technologically advanced player in a region. Personally we still enjoy PurpleTie’s drycleaning home delivery services, which started as a 1999 VC backed effort to go big with an online nationwide dry cleaning service but failed and got acquired by bootstrapped CleanSleeves (who apparently liked the PurpleTie name better.) Fifteen years later operates only in the Bay Area between San Mateo and San Jose and seems to have a healthy business. Perhaps the new generation of ODMS startups providing dry cleaning and laundry deliver services will go substantially further than did CleanSleeves, and if so it will be because they figured out how to create more customer delight than just mobile app order placement and efficient delivery. My wife is quite eager to give a try, but whether or not she would stay loyal to them versus the next cheaper version will depend on how well they turn a relatively commoditized service category into a truly differentiated experience.

Quality—Service businesses are so hard to build because they rely on people to deliver service and interact with customers as much or more than they rely on computer code. Managing people, especially a workforce of independent contractors rather than full time employees, is a lot more variable than executing software routines and so recruiting, selecting, training, and managing workers is a core element of any ODMS. Background checks, license verification, detailed applications and face to face interviews are all part of the selection process. Most services rely on their customers to rate service providers and tend to ruthlessly cull those drivers/doctors/plumbers/etc that fall below a rating threshold, often a fairly high bar. Doctor on Demand checks the lighting, sound, and appearance of every doctor before every virtual shift. Some services even provide a satisfaction guarantee on the completed job, such as Red Beacon’s* $500 offer. Service quality can often be a matter of individual taste. For example, in the home cleaning category services like Homejoy may delight 9 out of 10 customers but it will be an endless uphill battle to please the pickiest consumers when it comes to something as subjective as a clean home.   Quality is not just the absence of problems, but also those unexpected touches which delight. Good Eggs, for example, would unexpectedly throw in a free gourmet treat or two when we first started the service. The freebies stopped once they hooked us as repeat customers but the amazing quality, friendly service, and personal touches like handwritten notes have made us loyal. There are simply no shortcuts when it comes to delivering consistently great services levels and ultimately quality can make or break a business regardless of whether they have the best looking mobile app.

Price—Tech enabled services are often far more efficient than traditional businesses at acquiring customers and aggregating demand through digital channels, viral marketing, and highly visible brands. This often enables cutting out layers of middlemen in the value chain. Additionally ODMS can rely on large regional facilities on cheaper real estate for physical goods processing versus sub-scale storefronts and expensive Main Street locations of their offline peers. Passing a good portion of these savings on to consumers is perhaps the smartest way to generate trial, grow quickly and hook customers on your service. BloomThat is a flower and gift delivery service that does a wonderful job of curating their selection and providing same day delivery, but their pricing advantage vs 1-800-FLOWERS is so significant that they have dramatically grown the frequency of gift giving among their customers far beyond the traditional Mother’s Day and Valentines Day holiday spikes. Some of the smartest pricing plans still include premium and ultra-premium levels, such as Uber Black or Uber Lux, for the truly price insensitive segment, but the mass market almost always appreciates a good value, especially when being asked to try a brand new service through a new medium. In the long run, however, one hopes that there is enough technology leverage, economy of scale, and disintermediation in your ODMS to be the good margin, low cost provider in your industry, not just the company most willing to subsidize losses indefinitely.

Payments—Rolling out of your UberX curbside without having to fumble through your wallet for cash nor waiting for your credit card to be run through a mobile POS is simply addictive. Getting food delivered by services like DoorDash or Seamless without the awkward eye to eye tipping procedure with the pizza guy is very easy to get used to.   Customers simply expect that effortless payment is part of the magic in a service that has been newly redefined as on demand and mobile. The nice part is that this also solves many business model problems around your workers handling cash or credit card numbers, deadbeat customers, and leakage from your workers attempting to cut you out of a side deal they offered your customer after you so nicely made the match between them.   The downside for the ODMS is that for low priced transactions the interchange fees on these credit card payments can be a significant hit to your margin, and on the other end of the spectrum certain high ticket services that require onsite estimates like home renovation may not easily lend themselves to being in the payment flow. Over time, however, we will see the vast majority of ODMS handle payments in the background as part of the consumer experience.

So, will there be an Uber for every service industry? There will be some for sure, but not many in terms of a global, dominant, hugely valuable iconic brands.   Some industries are just not important and/or frequent enough to our daily lives, or unpleasant enough as they exist today, whereas other industries face service challenges so fundamentally hard to solve that it will be a long while before we see an ODMS truly solve them. Just like with the B2B Marketplace craze of the late 1990s we will see massive experimentation across an enormous swath of the consumer services sector. We will also see traditional offline service businesses forced to up their game and become more technologically sophisticated. So while there may only be a handful or so of Uber-sized winners, there will be many smaller ODMS who find some degree of success, and the biggest winners of all will be consumers themselves.

*Current or past Venrock investment.


Brian Williams and Abundance vs. Scarcity in Media

The physical world’s native economic basis is scarcity. Value is determined by demand for each item produced. If I make only five gold Ferraris and thousands of people are just dying to have one, the value of those will increase.

In the digital world, we live in a world of abundance. We can make infinite perfect copies of anything produced without significant marginal cost. We can satisfy pretty much all the demand for digital goods, so it’s hard to drive value by limiting quantity.

The same shift is occurring in media. In the legacy media world of newspapers and TV shows, tons of scarcity exists: editors can only fit eight stories on the front page of a newspaper, cable companies only have capacity for a few hundred channels, and TV networks can only offer 24 hours of programming a day. In media governed by scarcity, editors and programmers must make hard decisions about who and what to talk about and hope their audience cares for their choices. In the archaic world of television news, the choice of an “anchor” really mattered. After all, each of the three terrestrial broadcast networks could only have one, and this anchor was going to appear on TV each night for 30 minutes or so. The investment in anointing a single personality around which your network’s entire credibility was built was significant, and made sense.

Consider now the digital media companies of the present day. The most valuable ones are platforms, not programmers. Facebook, Twitter, Pinterest and YouTube, for example, are platforms for expression through the sharing of content produced by, or curated by, their users. All of these are built natively for abundance. They have infinite inventory, can support an infinite number of creators and users, and make no decisions about which content or which personalities are “right” for their audience. The audience decides entirely whom to friend or follow, what to “like”, and what to ignore in their feeds. (Algorithms can help make this process easier.) In this model, platforms are not reliant on a few editors or a few personalities to represent their brand. And they are immune to the inevitable rise and fall of the popularity of people and topics. In fact, they welcome it.

Excitingly, early adopters of these platforms are motivated to figure out the essence of what makes them work. They produce and refine lots of content on them and watch audience engagement until they master the platform. There are now millions of creators who are great at YouTube and Vine, Instagram and Twitter. More of these platforms will emerge, and more creators will blossom. Abundance.

Traditional media, by their selection of what to cover and feature, confer an artificial sense of importance to anything or anyone appearing in their pages or on their programs. I heard an NPR story the other day featuring someone whom the reporter profiled as “a great tweeter.” According to whom? And why this person? It was classic scarcity media — anointing to speak for many. There are millions of great tweeters in the world and featuring one as an example of what Twitter is like is kinda silly. This person’s true relevance on Twitter is indicated by the engagement metrics around their tweets, a topic not discussed in the story.

So how does this relate to Brian Williams? Well, the reason we know about him is because NBC chose, in a scarcity-based media world, to build their entire news brand around him. And now he has significantly tarnished this brand. This will have a real economic affect on NBC as a result. Brands built in the age of scarcity take significant risks when they use celebrities (or any one individual) to act as a proxy for their products. Endorsements bestowed upon athletes carry the same risks — unnecessary in a digital world of abundance. On digital platforms, brands are built by the stories brands tell and the content they share. They rise and fall based on their ability to engage us and capture our attention in the streams. We care about them when they do, and often ignore them when they hire a celebrity spokesperson to speak on their behalf.

The age of abundance in media requires a more democratic approach to programming. In this world, platforms take little risk in the inevitable imperfections of humans. They cherish it. Because when it happens, they are the places where we all go to talk about it.


A Sensible Approach To Net Neutrality by the FCC

Today, FCC Chairman Wheeler announced a sensible approach to ensuring that the internet will remain an open platform. Many folks in the traditional telecom and cable industries have described the use of Title II as a blunt and archaic tool not appropriate for the internet. And others have derided the very notion of internet regulation as anathema to free markets and the internet more broadly.

Most of us who have lived on the internet since its early days feel strongly and personally protective of its level playing field. In order to protect this openness, it became necessary for the FCC to step in. And once that moment came (prompted by some previous court decisions), the FCC had a choice on how best to maintain the openness and freedom to innovate so important to both our society and our economy. When presented with this choice, it became clear to me and many of us who build internet companies that classifying the last-mile internet as a utility rather than an information service was the best way to maintain the essentially openness of the internet. That is why I supported the use of Title II (with the appropriate forbearance of non-relevant regulations) in this case. I am pleased that Chairman Wheeler and his staff listened carefully to the millions of comments which poured in — most in support of these important protections. And I am also thankful President Obama and his staff took such keen interest in this issue and shared their point of view with the public.

We don’t want ISPs and cable companies being kingmakers on the internet. We want the users — all of us —to get to try every product or service no matter who provides our last-mile internet connection and to vote with our attention and our money as to who wins and loses. The FCC’s new rules will require ISPs to stay out of the way and not to allow or demand companies pay them for faster traffic. This is a great development for the internet as we know it and love it.

While it’s true that any regulation can bring unintended consequences, the other choices of either (a) doing nothing or (b) continuing to use Section 706 as a means to enforce these protections both, upon closer inspection, are worse options that will likely lead to an uneven internet.


Our Latest Investment – Beckon

Marketing professionals have more data at their fingertips now than at any other point in history. They have more channels to manage, more places to look, more administrative dashboards to monitor, and more decisions to make.

What Current Digital Marketing Looks Like

You have to:

  • Keep up with Facebook insights and the latest algorithm changes to know which post to sponsor or what graphic might receive the most engagement.
  • Check out Twitter analytics to see which hashtag received the most attention and what tweet received the most retweets and engagement.
  • Sign into Google analytics and your website dashboard every single day in an effort to understand who visits your site and what they do when they arrive.

And this is just the tip of the iceberg.

Marketers need to know who their potential customers are and what they are most likely to engage with. In today’s world of big data, you have several of choices. You can spend more time than you have looking at the data and formulating a plan for each channel your company uses, outsource this work to an agency, or to utilize a new option known as predictive analytics.

Predictive Analytics Will Transform Marketing

Dashboards like Beckon, a marketing software company that lets marketing professionals put the power of their data into their own hands and take appropriate action faster than ever before, will transform the marketing world. Beckon uses channel performance data, machine learning, and a myriad of business specific data points that can help marketers determine what, when, and where your content will receive the most engagement. The days of using anecdotal or generic data that may not apply to your brand or your followers are over.

Beckon is a dashboard and platform that collects data such as clicks, impressions, likes, and other engagement data and rationalizes that information into trends that can be used to make quick and concise marketing decisions that generate revenue and encourage customer retention. Beckon takes “the mess” out of all the data available to marketers and makes it easier to understand and easier to act on.

With predictive intelligence from Beckon assessing big data that is currently scattered across multiple channels, you’ll be able to give your followers, audiences, and potential customers what they want, when they want it. By doing this, you’ll increase engagement, build your brand, convert more leads, and increase revenue all while spending less time figuring out the data.

CMO’s and other marketing professionals continue to have an increasing number of channels to manage and a growing amount of data to filter through. Predictive intelligence solutions like Beckon will help solve this issue for marketers, and we are excited to be a part of the journey!


Why Beckon Beckoned to Me: The Arrival of Marketing Performance Management

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In today’s online and mobile world customers are educating themselves about products and services long before any flesh and blood sales persons utters a word. Consumers can easily find their own way to detailed product information, user reviews, professional reviews, demonstration videos, user generated unboxing videos, sales rankings, price comparisons, social media sentiment, buying guides, and more. For this reason, marketing is more important than ever and the Chief Marketing Officer has never been more powerful nor controlled more budget, for both media and technology.

At the same time, however, the job of a marketing leader has never been harder or more stressful. The digital landscape has become so vast and dynamic that the marketer must master an endless parade of new channels. Just as they were getting used to Facebook, Twitter, and Instagram, along comes Pinterest and SnapChat, and undoubtedly the next hot channel is just around the corner. With an expanding universe of marketing channels comes an ever increasing volume of data. With all this data available, CMOs are expected to quantify their results with the precision of a CFO. While each new channel begets a host of new adtech and marketing tools to help the CMO manage campaigns, measure performance, and optimize results, each of these solutions produces data and reports in their own unique format.

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It has gotten to the point that when the CEO asks “how is our marketing doing?” it strikes fear in the heart of the CMO. This perfectly benign question usually kicks off an all-night exercise of cutting and pasting data and charts from various marketing execution systems into a lengthy presentation to answer the CEO’s question. When PowerPoint (now in its 28th year) is the tool of choice for marketers to aggregate and translate performance data from their various systems you know the situation is dire. Making matters even worse is the fact that many large brands can’t even access their own campaign data as it is held hostage by their various marketing agencies. Not only does the client get charged a markup by the agency for report requests, but it’s the classic case of the “fox guarding the henhouse” to ask an agency to report on their own performance.

Several years ago, a former marketing leader from a Venrock portfolio company did a stint as an Entrepreneur-In-Residence in our offices. She identified this lack of a single “CMO dashboard” integrating data from various point solutions as a problem she had experienced firsthand. Essentially she wanted a “System of Record” for marketing. After several months of researching potential technical solutions she concluded that, despite the crying need for such a product, building one would be too difficult. She gave up frustrated and joined another best of breed marketing tool company. This unsolved problem stuck in my head.

A few years later I met Beckon. The team at Beckon have been marketers, built marketing point tools, worked in agencies, and have built, installed and used systems of record in other enterprise functional domains such as finance and sales. Having seen the problems facing modern marketers firsthand they have taken a novel approach to building a system which can pull in data from over 100 different marketing point tools. While some of this data is available via well supported APIs, much of the data comes in via spreadsheet imports and email parsing (think TripIt.)   The next thing Beckon does is normalize the data so that marketers can compare different campaigns across different channels with one common taxonomy. They allow the marketing team to add metadata such as geographies or regions, product names or categories, customer segments, agencies, objectives, and so on, in order to put the marketing results in appropriate context. They allow for What If analysis, planning, and time series tracking. Beckons creates beautiful visualizations and answers to plain English questions that don’t require analysts skilled in SQL queries. And because this is not a BI tool, but rather an application built “by marketers, for marketers”, it is loaded with best practices for omni-channel marketing performance management right out of the box with no IT Department involvement.

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Over the past year some of the best brands in the world have adopted Beckon. Coke, Microsoft, GAP, and BSkyB are among the clients using Beckon to manage their omnichannel marketing. The real sweet spot for Beckon are mass marketers and indirect sellers who spend across at least five different channels. While I have written about my keen interest in predictive and intelligent software, the truth is that relevant, advanced modeling is only possible if the data sets the models are built on are comprehensive, normalized and continuously updated. Finance, for example, measures its performance according to GAAP (Generally Accepted Accounting Principles), a consistent, agreed-upon methodology shared within and across companies. As a result, we can understand a company’s financial performance quarter to quarter and compare performance to other companies in a standardized way. Marketers have never had a similar system. That’s what Beckon finally brings to marketing – a strong, united data foundation upon which all kinds of consistent, robust marketing analyses can flow – benchmarking, planned versus actuals, test and control, lift over baseline calculations, econometric (mix) models and more. Beckon gives marketers self-serve access to many of these analyses within its application and can also flow its standardized, merged and continuously updated data sets to advanced analytics teams and tools.

Marketing can finally have its own system of record the way sales has Salesforce, manufacturing has SAP, Finance has Oracle, and HR has Workday. Beckon is Marketing Performance Management. Finally the CMO does not have to hide when the CEO calls (or beckons) them to their office.

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A Courageous First Step

This article was first published in The Health Care Blog.  It is co-authored by Bob Kocher and Farzad Mostashari.

Earlier today, Health and Human Services (HHS) Secretary Sylvia Mathews Burwell announced that HHS is doubling down on the historic shift taking place across the health care industry towards value-based care, and is setting a target of having 50 percent of Medicare payments under value-based care arrangements by 2018.

 This would mean that in less than three years, around a quarter of a trillion dollars of health care spending would be made to providers who are being compensated not for ordering more tests and more procedures, but for delivering better outcomes – keeping patients healthier, keeping them out of the hospital, and keeping their chronic conditions in check.

This shift will address a central problem of the US health care system, one that lawmakers and policy experts on all sides of the issue agree is a key contributor to runaway medical inflation.

The logic is straightforward: by simply paying for the volume of services delivered, every provider has a strong incentive to do more — more tests, more procedures, more surgeries. And under this system, there is no financial incentive to maintain a comprehensive overview of patient care – to succeed by keeping the patient healthy, and health care costs down.

In making this announcement, Secretary Burwell took a step that many within HHS had been advocating quietly for years, and which many outside it have advocated more loudly.

Skeptics may ask: what does this accomplish? And why announce it now, when health care costs are already rising at the slowest rate in decades?

As someone who has served on the frontlines of the policy and the practice of this transformation, the answer is clear: because dispelling disbelief and uncertainty about this shift “from volume to value” among decision-makers in the health care industry will be key to sustaining progress.

Part of the reason for the spending slowdown is the fear among some health care executives that their “build-it-and-they-will-come” fee-for-service model may not last. According to the Federal Reserve Bank of St. Louis, health care construction, on a continuous upwards trajectory for years, dropped sharply in 2009, and even as the rest of the construction industry rebounded, dropped again in 2013. The ubiquitous cranes building new hospital wings and proton beam pavilions have paused ever so slightly as uncertainty reigns.

But imagine if this announcement by the world’s largest payor is joined by private sector leaders, signaling urgency and determination. The skeptics and the straddlers will have a definitive answer, and it will accelerate the transformation already underway. Innovation in how healthcare is delivered can succeed only if there is a sustained commitment to change to go along with the technological advances in data and analytics that have revolutionized other sectors.

This is doubly important. There are still too many organizations deeply embedded in today’s payment models, who have chosen to wait and see if this value-based care movement is a passing fad.

Many have dipped a timid toe, or hedged their bets with low-regret moves like buying up practices and forming organizations that are Accountable Care Organizations (ACOs) in name only. These actions consolidate a health system’s referral base, but administrators have no intention of reducing costs, which are their revenues. Put differently, these “ACO squatters” say there are embracing new payment models, but remain stuck in the mentality of the do-more, get-paid-more system.

Unfortunately, this strategy is already too widespread, and likely to grow as long as large organizations are allowed to continue in “one-sided” (upside only) shared savings models, as recently proposed by CMS. It’s also a major reason why so few hospital-sponsored ACOs have actually achieved savings bonuses. Defensive moves by hospital systems provide a veneer of action, while consolidating regulator-blessed market dominance that can raise local prices without improving quality at all.

Without a doubt, the goal announced today by HHS will motivate widespread, real change across both the public and private health care sphere. But in order to achieve the spirit of the transformation – and not simply check the box of meeting numerical goals – I would suggest an additional metric to accompany the headline number.

In addition to tracking all dollars paid out under value-based systems (like the “fee for service” revenue generated by hospitals with an ACO contract), HHS should also separately count how much money was actually awarded or taken away as part of value-based contracts. The headline number will give a picture of how many providers are participating in value-based care programs; the second number will give a clearer policy goal of increasing the number of providers that are actually succeeding in these arrangement. This additional objective would discourage the “ACO squatting” described above, and challenge participant providers to embrace not simply the letter of the regulations, but the spirit of the program.

“You can give them a big number and you can give them a date, but don’t give them both.”

That was the sly advice on target setting given by a career bureaucrat to a newly appointed agency head. Bureaucracies protect themselves against embarrassment and deflect scrutiny, especially when they feel attacked, and the leadership of the Department of Health and Human Services (HHS) has felt intense scrutiny since the earliest days of the Obama Administration. In that light, HHS Secretary Sylvia Mathews Burwell’s announcement today of a target for reforming healthcare payments is both astonishing and courageous.


Here Is What Happens When Your Brand Doesn’t Know Its Customers

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How 10 leading health systems pay their doctors

This article was first published in Healthcare: The Journal of Delivery Science and Innovation. It is co-authored by Dhruv Khullar, Robert Kocher, Patrick Conway, and Rahul Rajkumar.

We conducted interviews with senior executives at 10 leading health systems to better understand how organizations use performance-based compensation. Of the organizations interviewed, five pay physicians using productivity-independent salaries, and five use productivity-adjusted salaries. Performance-based pay is more prevalent in primary care than in subspecialties, and the most consistently identified performance domains are quality, service, productivity, and citizenship. Most organizations have less than 10% of total compensation at risk, with payments distributed across three to five domains, each containing several metrics. Approaches with many metrics—and little at-risk compensation for each metric—may offer weak incentive to achieve any particular goal.

Provider organization; Performance-based compensation; Productivity; Incentives; Value-based healthcare delivery; Quality improvement

Large healthcare organizations that seek to create value by managing population health face a Principal-Agent problem, in which one actor (here, the physician—agent) makes decisions on behalf of another person or entity (the organization—principal). Organizations have a particular set of incentives, but it is ultimately frontline physicians—who at times face different incentives—that make clinical decisions. Problems can arise when the two parties׳ goals are in conflict, when they have different tolerances for risk, or when it is difficult for the principal to verify the agent׳s actions. In medicine, these challenges can result in the delivery of too much, too little, or inefficient care, depending on how procedures and services are reimbursed.

In an effort to align the interests of Agent and Principal, many organizations in other industries use performance-based compensation schemes, in which employees are paid based on how they perform on selected metrics that promote the organization׳s overarching goals. According to the human resources consulting group Aon Hewitt, more than 90% of US companies now offer employees performance-based pay, up from 78% in 2005 and only half in the early 1990s.1 Many healthcare organizations have also shown interest in using performance-based compensation to align provider incentives with organizational goals.

To better understand whether and how leading health systems use performance-based compensation, we conducted interviews using a standard questionnaire with senior executives at 10 leading provider organizations. We selected organizations that are either leaders in reputational surveys or that are established innovators in healthcare delivery. All 10 organizations cooperated with our survey. Key findings are presented in Table 1.

Table 1Physicians at these organizations are largely salaried with relatively minor adjustments for performance. Of the 10 organizations interviewed, five pay physicians using productivity-independent salaries, meaning that salaries are determined by a physician׳s specialty and experience and usually pegged to national or regional benchmarks—but not tied to measures of productivity like Relative Value Units (RVUs). Five systems pay physicians using a productivity-adjusted salary, in which salaries are based on a physician׳s recent RVU-productivity.

Our interviews suggest that compensation models vary greatly by medical specialty. Organizations emphasize performance-based pay more in primary care than in subspecialties. Compensation for procedural subspecialties is more closely linked to RVU-productivity, whereas non-procedural subspecialties tend to receive an unadjusted salary. This discrepancy may be due to the relative market power of subspecialists as compared to primary care physicians, which likely strengthens their bargaining position with provider organizations. Moreover, because performance measurement initially emerged in primary care, policymakers have a more robust set of validated quality metrics here than in the subspecialties. A relative dearth of quality metrics serves to maintain status quo volume-based compensation.

Interviewed organizations tie a relatively low percentage of total compensation to performance. At the Cleveland Clinic, Mayo Clinic, and Iora Health, for example, physicians are 100% salaried. At Group Health and Kaiser Permanente (Southern California) more than 90% of total physician compensation is salary. Importantly, even organizations that tie little or no compensation to performance attempt to track and encourage performance on a variety of metrics by conducting internal performance reviews. Furthermore, performance data for individual physicians is transparent in most systems; physicians are able to see their own performance and rank, as well as that of their colleagues.

At most organizations, senior leaders set overarching strategic aims, and then work closely with frontline physicians and department chiefs to develop fair and meaningful performance metrics. Group Health, for example, is undertaking a five-year process in which each year several departments meet with senior leadership to develop metrics to improve quality and efficiency in that specialty. Most organizations use a combination of group and individual metrics to make allocation decisions about compensation. Leaders note that some outcomes can only meaningfully be understood at the system-level (e.g., utilization patterns), while others are more appropriately assessed at the physician-level (e.g., patient satisfaction). Across systems, the most consistent performance domains were quality, service, productivity (generally measured by RVUs), and teamwork or citizenship.

Research has long shown that physicians respond to financial incentives. Productivity in medical groups tends to increase as a larger share of physician compensation is tied to his or her individual production, and this finding has been replicated in a number of specialties and organizational designs.2 and 3 But while studies suggest financial incentives can increase productivity in the traditional sense (number of patient encounters or hours worked), it is unclear if they do so when productivity is redefined as value or quality per unit time. Some have raised concerns about the ability of performance-based compensation to achieve desired outcomes, arguing that it creates unintended consequences such as avoiding high-risk patients, focusing on narrowly-defined metrics at the expense of holistic care, and “crowding out” internal motivation and professionalism.

A recent article by Mostashari et al. argues that primary care physicians should be thought of as CEOs responsible for $10 million in annual revenue and that physicians should be accountable for the overall quality and costs in health systems as senior executives are in other organizations.4 Our study of leading provider organizations, however, suggests that physicians generally have far less compensation at risk than senior executives in other industries.

Most organizations have less than 10% of total compensation at risk, and payments are typically distributed across 3–5 performance domains—each containing several metrics—so that physicians may be responsible for 10–20 metrics during any given measurement period. Approaches with many metrics—and very little compensation at risk for each metric—offer a relatively weak incentive to achieve any particular goal. Some physicians may hit performance targets just by chance, especially if thresholds are low, and even physicians who change nothing could potentially receive as much in payments as those who make significant changes. Furthermore, physicians cannot focus on everything at once and may be uncertain about where to devote their efforts.

This observation should be taken with some caveats. Firstly, even organizations with many performance domains may choose to focus on only two or three metrics in a given measurement period. Secondly, some researchers have found that small incentives can change physician behavior. For example, a recent Massachusetts General Physicians Organization (MGPO) quality-improvement program significantly increased hand hygiene compliance and electronic prescribing using incentives totaling less than 2% of the average physician׳s income.5 Thirdly, many leaders emphasized institutional culture, not financial incentives, as an important driver of quality and performance. Finally, performance-based compensation is certainly not the only method to address the Principle-Agent problem. Non-financial incentives such as public reporting and internal performance reviews and recognition may also be effective.

Despite calls for greater value-based purchasing, physician reimbursement continues to be driven primarily by volume of care delivered. In organizations with performance-based compensation, RVU productivity still dominates quality and service metrics by driving base salary, perhaps reflecting the continued prevalence of a fee-for-service payment environment. This is, however, at odds with new value-based purchasing goals, and may change as payment models continue to evolve. Indeed, several organizations reported that they plan to significantly increase performance-based pay for physicians in the near future.

Several conditions are necessary for organizations to move a greater proportion of payment into performance and away from volume. Researchers must continue to explore validated metrics that meaningfully impact patient outcomes. Organizations should encourage physician buy-in by giving them input into the metrics upon which they will be evaluated. And finally, to foster greater experimentation early on, payers should ensure it is in the financial interest of providers to explore novel reimbursement models and enter risk-based contracts.

There is likely no universally effective physician compensation model suitable for all organizations, and each system will need to incent physicians with its unique culture, goals, patient population, and financial situation in mind. But provider organizations may be missing an opportunity by linking too little compensation to too many metrics. Large changes in physician behavior and healthcare delivery—increasingly important in the post-reform era—may require larger amounts of at-risk compensation. Further research on physician compensation models and their effect on quality outcomes and costs is needed. Payers are moving toward paying provider organizations on quality and costs; but organizations themselves should do more to examine how they can better align financial incentives for frontline providers with those of the larger organization. By exploring payment models with more pay tied to performance, and less to productivity, provider organizations may be able to free physicians of traditional constraints and empower them to be not just aligned agents, but change agents.

The views herein represent the opinions of the authors and not necessarily policy or views of the Department of Health and Human Services, Centers for Medicare & Medicaid Services.

1 Aon Hewitt Salary Increase Survey. 〈〉; 2014.

2 M. Gaynor, M. Pauly
Compensation and productive efficiency in partnerships: evidence from medical groups practice
J Politic Econ, 98 (1990), pp. 544–573

3 D.A. Conrad, A. Sales, S.Y. Liang, et al.
The impact of financial incentives on physician productivity in medical groups
Health Serv Res, 37 (2002), pp. 885–906

4 F. Mostashari, D. Sanghavi, M. McClellan
Health reform and physician-led accountable care: the paradox of primary care physician leadership
J. Am Med Assoc (2014), pp. 1855–1856

5 D.F. Torchiana, D.G. Colton, S.K. Rao, S.K. Lenz, G.S. Meyer, TG. Ferris
Massachusetts General Physicians Organization׳s quality incentive program produces encouraging results
Health Aff, 32 (2013), pp. 1748–1756


Why So Many New Tech Companies Are Getting into Health Care

This article was first published in the Harvard Business Review.

Note: In addition to Bob Kocher, this post is authored by Bryan Roberts, also an investor at venture capital firm, Venrock.

A flood of new health care IT companies has been pouring into the U.S. health care market. The cause of this torrent: the recognition that as market and regulatory forces alter incentives in health care, IT companies will play a powerful role in combating the overemployment and declining productivity that has plagued this industry and in helping providers improve the quality of care.

The dam broke in September 2007, when Athenahealth went public, the price of its shares jumping by 97% on the first day. Since then, the company’s value has risen to $5 billion. Athenahealth proved to entrepreneurs, software engineers, and investors that the health care sector is fertile ground for creating large technology-services companies that use a subscription-based business model to offer software as a service (SaaS).

Despite its size and growth rate, the health care sector was long considered an impenetrable, or at least an unattractive, target for IT innovation — the entrepreneurial equivalent of Siberia. Athenahealth broke the ice by proving that it could sell SaaS efficiently to small physician businesses, get doctors to accept off-premises software, and achieve the ratios of customer-acquisition costs to long-term value that other sectors already enjoy.

As Athenahealth accomplished its goals, several larger forces have dramatically widened the scope of opportunity in the sector:

  • The Great Recession led to a loss of 8.8 million U.S. jobs and big declines in demand throughout the economy (including health care services) — yet health care employment grew by 7.2%. That reality increased awareness that a decline in labor productivity was driving much of the excessive spending in health care.
  • The American Recovery and Reinvestment Act of 2009 included the Health Information Technology for Economic and Clinical Health (HITECH) Act, a $25.9 billion program to give doctors and hospitals incentives to adopt electronic health records. EHR adoption has now grown to nearly 80% of office-based physicians and 60% of hospitals, fueling many successful software start-ups, such as ZocDoc, Health Catalyst, and Practice Fusion.
  • The Affordable Care Act (ACA) requires that an enormous amount of data on cost and quality be made freely available. In addition, digital health applications, mobile phones, and wearable sensors, as well as breakthroughs in genomics, are creating truly big data sets in health care. These data contribute to greater market efficiency, more consumer-oriented products and services, and clinical care that is evidence-based and personalized.
  • The ACA has led to a proliferation of risk-based (rather than fee-for-service) payment models. For example, providers inaccountable care organizations are rewarded for generating annual savings, and providers who use bundled payments get a fixed budget for an end-to-end course of treatment. Effectively responding to these changing economic incentives will increase reliance on software that helps providers manage population risk, understand costs and trends, and engage patients.

These macro-level developments set the stage for other SaaS companies to follow Athenahealth’s lead in enormously improving labor productivity and quality of care.

Within the next decade, software tools will eliminate thousands, perhaps millions, of jobs in hospitals, insurance companies, insurance brokerages, and human resources departments. Not the jobs of people who actually provide care — but those of administrative middlemen, whose dead weight contributes to economic loss. Here are five examples:

  1. Digital insurance markets, combined with ACA-enacted regulatory changes such as guaranteed issue and community rating, make it possible to price and sell health plans to anyone immediately. These developments will decimate the armies of brokers who act as intermediaries between customers and insurance services.
  1. Price transparency, digital insurance products, and tools such as reference pricing make it possible to generate an exact price and instantly collect payment for a health care service. As a result, revenue cycle managers in hospitals and claims adjudicators in insurance companies will be displaced.
  1. The inevitable shift to the cloud will render obsolete the costly, insecure data centers that most doctors and hospitals are now building, staffing, and running.
  1. Adopting self-serve mobile applications will eliminate the forms, faxes, and excess staffing at many call centers, thereby improving satisfaction for everyone in the process.
  1. Centralized clearinghouses that share information across organizations and state lines will eventually replace the byzantine, paper-based process of credentialing doctors, tracking continuing medical education, and keeping licenses up-to-date. That means smaller staffs in hospitals’ medical affairs divisions, health plans, medical boards, and state and local health departments.

Given that wages account for 56% of all health care spending, improvements in labor productivity could generate enormous value. Simply reducing administrative costs could yield an estimated $250 billion in savings per year.

As compelling as the prospective labor efficiencies are, the benefits of SaaS extend beyond direct labor costs. Easier access to data on physician quality, specialization, and adherence to evidence-based care will better match patients with doctors who provide high-quality, efficient services, thereby averting health complications for their patients. Moreover, software can help bring relevant clinical guidelines and personalized risk scores to patients and clinicians as they improve care plans, engage in shared decision making, and avoid duplicative services. Such efficiencies will, in turn, enhance how patients perceive and experience the care they receive. SaaS companies can trumpet all of these advantages, not just the employment savings they yield.

To seize on the new opportunities in the health care sector, SaaS companies can take these steps:

  • Attack economic inefficiencies in order to generate immediate, tangible customer return on investment. Witness howCastlight Health’s transparency tools are generating annual savings for employers and employees. And be clear about the source of the ROI, given that in most cases the revenue comes from another health care stakeholder who may be able to undermine the business.
  • Focus on building in network effects so that improvements made by one user enhance the product’s value for current and future users, just as Athenahealth does when it rapidly disseminates changes in payment rules at one provider to all other providers. Most SaaS businesses in health care IT cannot protect their intellectual property; so it is important to continually augment the value of the product to achieve scale.
  • Use software-enabled service models, rather than pure SaaS. For example, Grand Rounds’ software not only recommends an expert doctor for a patient but also collects, organizes, digitizes, and summarizes the patient’s records — and then books the appointment for the patient. In effect, the software makes it easier for patients to adhere to high-quality, cost-effective care, thereby enhancing the overall ROI for the product.

It took Athenahealth a decade, from 1997 to 2007, to go public on the strength of its SaaS model. It took Castlight Healthonly six years, from 2008 to 2014, to do the same. Now an array of highly valued healthcare SaaS companies, each worth more than $100 million, is emerging. They include Zenefits, Grand Rounds, Doctor on Demand, Omada Health, Health Catalyst, Doximity, and Evolent Health. Indeed, Zenefits is one of the fastest-growing SaaS companies ever, regardless of industry, surpassing $500 million in enterprise value in its first year.

The success of SaaS companies in health care is thanks, in part, to an influx of leaders from other sectors. They bring with them teams of technical talent that deliver consumer and enterprise software faster, better, and more cheaply than many legacy health care IT companies can do. Witness ZocDoc, founded by first-time entrepreneurs from McKinsey; Grand Rounds, founded by Owen Tripp, who cofounded; Zenefits, founded by Parker Conrad, who cofounded SigFig; and Doctor on Demand, founded by Adam Jackson, who cofounded Driverside (just to name a few). This type of cross-pollination is an essential ingredient of innovative change.

The barriers between health care IT companies and IT in other industries are clearly coming down, and we expect the number of sector disruptions and billion-dollar companies to swell. As each innovation wave generates more data, disruption-cycle times will shorten, thereby forcing all players in the health care ecosystem to address inefficiency as they compete on quality and value creation. Those who fail to act will be washed away by the tide that lifts all other boats to greater productivity.