Marina Gorbis's Blog, page 1532

Google on Launching an Analytics MOOC and Taking Data-Driven Actions

Analytics. It could be the deepest, darkest mystery in your organization, served up by a few select tech wizards, or it might be the solitary master by which all company decisions begin and end. In all likelihood, it’s somewhere in between.

No matter where you fit on the spectrum of analytics know-how, data-driven decision-making is here to stay. With millions of users, Google Analytics is among the tools well entrenched in paving the road to actionable data. And a business’ choices when it comes to analytics services are many, with one tool rarely being a one-stop solution (for full disclosure, GA is one of several analytics tools HBR uses to parse its online data). So not only do we have to learn how to use analytics technology, we need to become more data fluent and confident in how to go from a collection of insights to action. And we have to do all of this while maintaining an empathetic connection to our users and customers.

For some perspective on this challenge, we talked to Paul Muret, Engineering Vice President for Google, and Babak Pahlavan, Product Management Director for Google Analytics. Muret is known as the “father” of GA, having founded Urchin, which was acquired by Google in 2005 and helped build the analytics tool we know today. Pahlavan is the founder of Clever Sense, a marketing data tool also acquired by Google.

When we talked, Muret and Pahlavan were prepping for the Google Analytics summit happening on Oct. 1, where they are announcing a type of massive online course, or MOOC, that will allow anyone to learn the fundamentals of analytics, among other new initiatives. Below is an edited version of our conversation.

Everyone wants to talk big data right now. How do you define the difference between big data and analytics?

MURET: I think it’s easy to have this “big data” term mean a lot of different things. Some people think about just trying to collect so much information from all kinds of different places. The key difference is making sure the data is useful and accessible by the people in your organization.

We have all these analytics tools — and Google Analytics is a tool that a lot of people are using and they’re getting a lot of data points out of it — but how do you really move to action or to making decisions?

MURET:  I think that it’s easy to just go directly into the tools and technology and lose sight of the big picture. The reality is that companies all over the world are using data to make smarter business decisions and drive creativity and innovation and it’s having a huge impact on their bottom line.

In the last few years, with the amazing advances in technology, especially the growth in communication networks and mobile devices, consumers are in this state of being constantly connected. And this is having a huge impact on every market and creating an opportunity in every vertical where consumer decision making and purchasing decisions are happening, which is not just in your brick and mortars stores anymore.

A decade or less ago, it would be very easy to see our customers and understand them. We could actually see them physically walking into our stores and doing their research, making their decisions, and you could see what they look like and what they’re looking at. There’s so much information you can gain by seeing your customers. It gives you this intuitive understanding of who they are and how to engage with them.

But imagine now moving into the era where that’s all happening online. It’s like running the store with the lights out. And if you can’t see your customers, you’ve risked reducing them down to sort of bits of data, URLs, and Javascript events. You have to learn how to engage with that data. It’s incredibly important now to empower everyone in your organization with data and that goes for the CEO, the CMO on down. We want the service managers, the user experience designers, and the product managers. But that means the data needs to be accessible.

One of the announcements that we’ll make at the Google Analytics Summit is that we’re launching a new analytics academy. This is a rich media, interactive, massive online course that everyone can access to learn more about digital marketing, digital analytics, Google Analytics, and how to put these tools into practice. We’re educating everybody about these techniques and helping answer their questions so they can move forward with making decisions.

So is it a MOOC? Or is it more of a resource tool that people will dip in and out of?

MURET:  It is a MOOC, but there are two modes of it. You can use it in a self-service way as well. There will be a combination of videos and Google Plus Hangouts and online community resources all together with actual certification steps along the way.

The first classes will be taught by our key digital marketing thought leaders and evangelists. In your organization, you might have one or two analysts that are kind of experts on Google Analytics but very quickly, their job becomes trying to sort of quarterback and educate the rest of your organization. There will be some areas that will require that kind of level of sophistication. But a lot of these techniques are incredibly accessible. The data can be used by basically the whole organization.

It sounds like almost everyone working for a company today is going to have to be a data analyst of sorts.

PAHLAVAN:  In this new world, you will have a much better business if your decisions are data driven. In order for it to be data driven, you have to be empowered with tools that are easy to use but also powerful enough that it can actually lead you to proper decisions. With regards to the MOOC side of the story, I would say this is a bit of a radical investment in our side. We’re leveraging a lot of technology and we’ll have our best education leaders and Google experts to teach this course. There’s going to be a lot of collaboration, a lot of discussions. We are expecting thousands of people to sign up.

I don’t think there are many other products out there that they’re putting this much investment insuring that technology can be accessible to other organizations so they can learn how to use them properly.

MURET: I do think that it’s going to be important for organizations to have a certain level of data fluency. If you think about Excel and spreadsheet technology, when it first started, spreadsheets seemed like a really scary thing and people weren’t sure what to do with it. Now today, people can write macros and have 15 spreadsheets doing all these crazy things. But for most cases, you don’t need that. You just need some basic math background and some basic things in order to sort of use spreadsheets in a way that’s really useful.

There are some basic concepts that people need to be able to understand so that they’re not misinterpreting things. There will be some areas certainly when it comes to analyzing data that are subtle, that will require experts; but for the most part, we think this data can be made incredibly accessible to a very broad set of people in an organization.

PAHLAVAN: It used to be that it was all about the website that you had. But now the consumers are on phones 24/7 and their tablets. So if we don’t get in there right now and help companies to have access to great tools, but also know how to use them properly, people are not going to go to tap into these data-driven opportunities.

We feel like it’s our responsibility to A, make simple but powerful products; and B, try to support and educate people to have data fluency. On top of it, people want to use these things. They’re saying: “Teach us the best way of using this.”

There’s still this question of taking action. What types of decisions should you be looking for?

MURET:  There are two types of ways to take action here. The first type I like to call aggregate actions and the second one I think about as automation.

The first one, aggregate actions, are sets of data over time. So a simple example would be if you have two landing pages. Let’s say you’ve got or two offers. I have offer A and offer B and you test them both and say, “Hey, offer A is working better than offer B.” Then you make a decision and you go with offer A and you remove offer B from your content. That’s a process that’s very straightforward and it’s basically an aggregate decision.

But there’s another way of using the data and that’s to take the data itself and put it back into these systems in a real-time way. That’s because the reality isn’t inside these aggregate numbers. You’ll have pockets of users that respond to different kinds of messages. There’s often an opportunity inside one of these areas to be more specific and provide more tailored information directly to specific users. And that needs to be done in a more automated way.

It’s not something that you as the analyst — I’m sure you’d love to be able to make those decisions one by one — but that’s too hard to do. Maybe it turns out that people coming from the southern United States love offer B and that seems to work better there. We need to be able to make that decision in milliseconds. There’s often a way of putting data back into action in an automated fashion to drive a more automated marketing platform.

OK, but if our customers are becoming bits and bytes, how are leaders and decision makers still going to build empathy for those customers?

MURET: I think it’s a challenge for all organizations going forward to figure this out. But one of the key ways is going to be through the data that we’re talking about. It’s interesting when people say, “OK, I’ve got a bunch of data. Give me insights.” That’s not really building that empathy you’re talking about. But once you’re trying to optimize and analyze a specific part of your business, then it’s through that process that you gain insights into what is working under the hood. I’ve just learned, wow, the way people are actually doing this is much different than what we thought. And that starts to build that empathy back together.

PAHLAVAN: It’s a very good question, the notion of empathy. Are we creating a situation in which the business leaders and business as a whole, are they going to be more empathetic to their customers and focus on their needs versus going to just look at them as more like aggregate formats and say, group them into high level buckets? We look at it from a perspective of can we provide you with tools with a more granular set of users and figure out what is it that they need? What is it that they’re interested in? What are their demographics? Can you put the right set of products or content in front of the right set of users or not?

MURET:  We want to give a very practical approach so that it drives returns almost immediately. But then as part of that process, when you’re going through those steps, we are effectively helping your organization put back together that picture of the customer. And that’s where the empathy hopefully is going to start to build back together so that your organization can make creative jumps in thinking.

Editor’s Note: The headline on this post was updated after it was published.

Bridging the Gap Between IT and Your Business

For the past several years we have watched with increasing dismay at the increasing chasm between information technology (IT) groups and their business counterparts. From where we sit, both sides have legitimate beefs: IT complains that, despite the increasing penetration of technology into every nook and cranny of the business, it doesn’t have a seat at the table and no one understands how difficult their jobs are given the constraints under which they operate. The business complains that IT doesn’t understand the business, consistently overpromises and under-delivers, and slows innovation. CEOs, following the advice in Nicolas Carr’s famous HBR article, “IT Doesn’t Matter,” perceive little strategic opportunity in IT and devote as little time as possible to the issues. Finally, the usual calls for IT to get closer to the business only exacerbate the situation. Neither side fully appreciates how difficult this is. And half-hearted efforts are akin to putting in just enough energy to jump halfway across the stream.

Frankly, we are sick and tired of the bickering, especially since the most important point gets lost — the failure to derive the full advantage of information technologies does enormous disservice to companies. Further, the pace of technological change and the demands to do more with the data grow exponentially and will continue to do so for the foreseeable future. The problem, strategic or not, must be resolved. Smart leaders will ignore the posturing and work to close the gaps.

While we have no “silver bullet” solution, we do offer three steps that can help.

Quit making the same mistakes over and over again. It seems to us that, in far too many companies, IT doesn’t have a fair chance. We see the same mistakes — some subtle, most not so much — over and over. IT is asked to do things, such as improve data quality, which it simply cannot do. People are not given adequate opportunity to provide input, nor educated on the new process and applications they are expected to use, and they blame IT for imposing something on them they do not like. IT is asked to the table far too late to advise on the difficulties of consolidating systems after a merger, then faulted when the task takes longer and costs more. Or business silos blame IT because “systems don’t talk,” when the root issue is that siloed departments don’t like working together.

None of these examples are new or different. Worse, too often we find people on both sides fully cognizant that they’re heading for a train wreck, and then hopping onboard anyway. It is time to put a stop to this. Both sides must acknowledge the mistakes of the past, resolve not to repeat them, and develop the courage to speak up.

Find common ground on medium-term issues. The motivation for our second step is the simple observation that organizations develop trust when they know what to expect from each other. We propose business and IT work in that direction by bringing a few tough technological trade-offs front and center, with the goal of finding some middle ground. These may include the COO’s demand for high systems reliability vs. the product manager’s desires to bring new capabilities online quickly; the CFO’s desire that systems standardize processes to keep costs low vs. the CMO’s demands that these same systems be flexible to promote innovation; or the apparent attractiveness of the cloud to CEOs vs. legal counsel’s concerns about data protection.

To find that middle ground, both should describe the trade-offs from their perspectives, illuminating important subtleties along the way. There will be plenty of differences, but the secret here is to find areas of agreement. It’s not so hard. We recall one case where six big issues came up — and 27 areas of agreement. At least for a time, forget about the six, select a few of the 27, and get to work on them. Good things happen. And in time the business becomes a better consumer of IT and IT a better provider of business services.

Finally, companies should ask, “How do we expect IT to help us compete?” Today, this topic simply doesn’t come up often enough, leading to a one-size-fits-all approach to managing IT, often as a cost center. That’s fine for most functions and processes in most companies, where middle-of-the-pack IT is good enough.

But all companies have areas where middle-of-the-pack IT is not good enough. Companies must invest in these parts of IT for the long term. Importantly, the critical investment is less in any particular technology and more in building organizational capabilities. For while few information technologies qualify as strategic — after all, they will be woefully out-of-date in three to five years — developing the ability to keep pace with the technology curve in these areas must be viewed as strategic.

Seen sequentially, step one clears the emotional clutter that poisons the relationship, step two enables IT to achieve “trusted supplier” status, and step three helps build a true business partnership in the areas that need it most. But we’re less interested in the order. Like it or not, we live in a tech world, from Apple to Hadoop to Zip files. You can’t ignore the fact that technology touches every facet of our lives. Better to get everything you can, leveraging every byte and every ounce of knowledge IT can bring.

Economies of Unscale: Why Business Has Never Been Easier for the Little Guy

The American worker just can’t seem to get a break. Automation is wiping out whole job categories, from cashiers to machine-builders, while pressures from globalization, trade, and new Internet-driven business models have disrupted industries and displaced hundreds of thousands of workers.  And the prescribed solution — education — is becoming increasingly unaffordable for most Americans.

But the tide is about to turn.  A series of breakthrough technologies and new business models are destroying the old rule that bigger is better.  By exploiting the vast (but cheap) audience afforded by the Internet, and taking advantage of a host of modular services, small becomes the new big.  The global business environment is decomposing into smaller yet more profitable markets, so businesses can no longer rely on scaling up to compete, but must instead embrace a new economies of unscale.

Unscaling has emerged over decades. FedEx offered overnight delivery services in the 1970s, letting anyone ship a product anywhere, fast, at a modest cost.  Around the same time, Chinese companies like Foxconn were developing less expensive approaches to manufacturing, and opening those facilities up to product designers across the globe.  These two changes alone allow a lone innovator in Austin to build a world class product in China and ship it to Berlin — and that’s a revolution for someone with a good idea.

Two decades later, Amazon and eBay launched online marketplaces that allowed small businesses to sell their goods to global consumers, creating enormous marketing power even for the little guy.  However, like an orchestra missing several of its musicians, these platforms did not offer the complete ensemble needed for small businesses to compete effectively.

That has now changed. New platforms abound: Facebook and Twitter for social marketing, YouTube for video distribution, and iPhone and Android for mobile. Payment processing was once a legal and financial nightmare, but today companies like Stripe and Square have made it simple for anyone.

Using such tools, companies that embrace economies of unscale compete with far larger competitors. Warby Parker offers prescription eyeglasses over the Internet at $99 a pair in dozens of attractive styles.  They leverage a whole range of services — from the logistics of parcel carriers like UPS to customer analytics software and social media marketing — to build a new business with extremely high customer satisfaction rates.  With only a couple dozen employees, they have taken on the world’s largest manufacturer and seller of glasses, Luxottica, which last year had a market cap greater than $13 billion.

Airbnb empowers homeowners to rent out their extra bedrooms to visitors from around the world through the Internet.  The company buys services like payment processing, mobile interfaces, and social media to create its own marketplace, and today it competes with some of the largest hotel chains in the world.  In just five years, the company now has 300,000 listings and 4 million renters.

Such unscaling is transforming the non-profit sector.  Khan Academy, which offers thousands of lessons on almost any educational topic, employs YouTube for video distribution, uses new social collaboration tools, and uses advanced analytics to understand how students learn and refine its offerings accordingly. Khan receives millions of unique viewers every month and is transforming the way we think of education.

These new economies of unscale will be good for job growth, because they open up thousands of new market niches for exploitation.  By buying specialized services, in customized form and at modest cost, companies can create unique products, find buyers from across the world, and secure profits.  It doesn’t matter if a designer wants to build polka dot bird feeders — there is a hyper-niche market they can tap, using platforms like Etsy to sell it across the world.  To succeed though, we first have to unlearn what we have been taught about business: We have to think in an unscaled mindset, where the emphasis is on a greater number of specialized products sold to customers who know exactly what they need.  How we train our students for this world will be critical to securing their future employment.

It has been a tough few years for workers in the United States.  But in a world with economies of unscale, we are empowered to take advantage of an extensive array of new, amazing services to build sustainable companies.  The coming world is a world of fragmented niches, many with immense profit potential, as we start to discover products that better meet the needs of this varied world. Finally, the American worker is about to get a break.

Four Tips for Better Strategic Planning

No great strategy was born without careful thought. That’s why the process of planning a strategy itself is an important vehicle for setting priorities, making investment decisions, and laying out growth plans. But for many companies, the activity has devolved into either an overexplained budget or just bad amateur theater – lots of costumes in the form of analysis, charts, and presentations – but with very little meaningful substance that can be translated into action. As a result, many strategic plans end up as shelf decorations or hard-to-find files in crowded hard drives.

Since this is the season when many companies are engaged in strategic planning, it’s just the right time to break bad habits. Here are four steps that you can take to make better use of the hard work that goes into planning a strategy:

Insist on experiments to test the assumptions you’ve made. Strategic plans necessarily involve hypotheses that certain outcomes (increased revenue, improved margins, higher ROI) will result from a given set of initiatives. But too often those assumptions are supported by secondary research, educated guesses, or assumptions rather than field tests. As a result, managers are uncomfortable actually moving into action or committing resources, preferring to stay with the business they know rather than possibilities that may or may not pan out. To overcome this inertia, ask managers to include specific, short-term experiments, whose results will communicate what works and what does not. In one company, the senior manager called these “scouting missions” and made sure that each of his managers was responsible for at least one every quarter.

Banish fuzzy language. Strategic plans are often filled with empty phrases such as “Leverage our World Class Operating Capabilities” or head-scratching aspirations like “Reshape Our Pricing and Trade Strategy to Effectively Drive Demand While Maintaining Market Access.” Language like this can signal that a team doesn’t have a clear idea of what they need to succeed. To counter this dynamic, the CEO of a large financial services firm banned her organization from using a list of words and phrases such as “leverage” “synergy,” “disintermediation,” and “robust” (to pick a few of the most overused terms).

Escape from template tyranny. Templates are often a standard fixture of strategic planning. Ideally they force teams to consider important topics – competitive analysis, shifts in external markets, performance gaps that need to be closed – and more easily compare data from different divisions. But the rigid use of templates can lead a team to be more focused on corporate requirements than on doing the hard thinking about how they plan to grow their business. And when teams have to complete the same templates each year, the result can be stale ideas, rote responses, and plans that don’t fully capture – or worse, obscure – the key issues and opportunities that a business needs to address. Avoiding this problem may be as simple as eliminating sections of the planning template that no longer make sense; or it may mean more radically changing the requirements. For example, a large food manufacturer reenergized the process by shifting from a 3 year planning template requiring many different and overlapping pieces of information to a shorter, more open-ended format that gave teams greater latitude to develop their growth plans in the form of a narrative.

Ask provocative questions. In theory, strategic planning should foster intense debates and discussions; but when the process is rigidly structured, and the documents are dense with data, the dialogue can be stilted or constrained. To overcome this, it’s important to ask tough questions when the plans are presented – and to do this in a way that can lead to unscripted answers that will enrich the thinking and increase everyone’s level of confidence in moving forward. A few that we’ve heard include: “What are the top 2 or 3 things that must go right for this strategy to work?” “If we pursue this strategy, what are we deciding not to do?” and “What specific capabilities will we need to develop in order for this plan to succeed?”

The strategic planning process is an important part of most organizations’ operating rhythm. The leadership challenge, however, is to make sure that it’s more than just a corporate exercise – or bad theater.

This piece’s coauthor, Logan Chandler, is a partner with Schaffer Consulting and the co-author of the HBR article Off-Sites That Work .

Don’t Blame the Apple and Exonerate the Tree

JP Morgan Chase is reportedly being pressed to pay more than $11 billion in fines and restitution to settle federal and state probes into mortgage-lending practices during the housing boom. That comes after a nearly $1 billion deal just a few days ago to end civil investigations into several matters including the bank’s multi-billion-dollar “London Whale” trading loss. Then there are the two former bank employees that authorities have been trying to arrest (one successfully) for their roles in the London Whale events.

I don’t mean just to pick on JP Morgan—although its legal troubles have been the ones dominating headlines lately. My former employer Goldman Sachs paid a $550 million fine to the Securities and Exchange Commission in 2010 to settle claims that it misled investors in a collateralized debt obligation (CDO) built around subprime mortgages, and in August former Goldman trader Fabrice Tourre was found liable for fraud by a federal jury in New York for his role in designing and marketing that very CDO. And of course there have been fines and court verdicts involving lots of other institutions, and surely will be many more to come.

The punishments in these cases are usually meted out either to a few, usually not very high-ranking, individuals or to the entire corporation, meaning its shareholders. What they fail to get at is what’s in between—the organizational structure and the culture that brought on the problems in the first place.

When there is a loss or failure, the tendency is to blame one thing or a few people, when typically there are complex organizational reasons. The desire is for a clear cause-and-effect relationship, and often a villain. We should, however, also be asking what set of conditions, constraints, pressures, and expectations affected the culture and organization to allow or produce the bad behavior. These may be difficult to discover because the picture may be blurry or the analysis may be messy. But addressing them is essential if we actually want to change behavior.

After two decades in the financial sector, I returned to school to get a Ph.D. in sociology focusing on organizations, and to teach at Columbia Business School. One thing I have learned is that the organization and its external environment matter. If you get rid of the few people supposedly responsible for a misdeed, when new ones take over the behavior often still continues. We need to look beyond the individuals, striving to understand the larger organizational and social context at play. And I think we are missing it.

While I was working on my new book about Goldman Sachs’ changing culture, I interviewed a retired Goldman partner who questioned why when one person or a few people do something bad that costs shareholders and possibly puts the public at risk, that one person or small group gets fired (maybe with some clawbacks of compensation) but the managing directors of the entire firm don’t have their compensation significantly affected? In JP Morgan’s case, the company’s board docked the pay of CEO Jamie Dimon by more than half, to $11.5 million from $23 million, after the London Whale loss (even as they cut his pay, the board praised Dimon for responding “forcefully” to the trading loss, presiding over an overhaul of the bank’s risk management, and getting rid of the responsible executives).

That’s something, but the bulk of the loss was of course borne by shareholders. And what happened to the compensation of a typical JP Morgan managing director? According to people that I interviewed, not much (other than losses on their JP Morgan stock holdings, which in most cases represent only a fraction of their overall net worth). Why? The main reason, I was told, is that that JP Morgan must pay competitively or lose top talented people. The second reason I was told is that most managing directors had nothing directly to do with the losses.

But they were important parts of an organization that messed up. One banker that I interviewed suggested that if JP Morgan managing directors collectively had to pay a large portion of settlements or losses related to the misbehavior out of their bonus pool, perhaps they as a group would take stronger internal actions to prevent such behavior, reward those who acted responsibly and consistently with stated values, and kick out those who did not. Maybe they would hold their leaders to higher standards and question each other’s activities.

This in fact is how things generally worked at Goldman Sachs and other Wall Street firms back when they were partnerships instead of publicly traded corporations. Each managing director was financially interdependent with every other. Typically, each received a fixed percentage of the overall annual bonus pool and was personally liable for other managing directors’ actions. At Goldman there was the added restriction that partners could not pull out their capital until after they retired. The organizational regulation created by this structure was key to managing risk, and we should be thinking about ways to bring it back.

I am not suggesting the banks return to being private partnerships. But they should move away from today’s norm of discretionary annual bonuses for managing directors to, at least for a select group of top employees (at Goldman the elected “partner-managing directors” represent around 1.5-2% of total employees), a shared bonus pool with fixed percentages that would pay a large portion of settlements or losses related to misbehavior and have greater restrictions on selling stock. Managing directors would share in the firm’s successes, but also feel it when others incurred losses or when the firm got hit with fines. Giving bankers reason to hold each other accountable would cause them to pay much more attention to asking questions and managing risk and misbehavior. Restricting stock sales could push their thinking and actions in a more long-term direction.

The difficulty with these suggestions is that, as mentioned above, banks must pay competitively or lose top talented people. Some people I interviewed said that some talented managing directors now decline joining operating or risk management committees or being designated as “Material Risk Takers” because of the accompanying liability and restrictions on their ability to sell stock. If a bank tried to force them to bear such risks and restrictions, they might leave for a more freewheeling competitor. But this seems to be where regulators could play a positive role. Instead of putting all their efforts into punishing individuals or extracting big company-wide settlements funded primarily by shareholders, they should be focusing more on organizational dynamics and external pressures, and pushing the industry back toward a system in which a transparent group of leaders of the organization are held accountable (and hold each other accountable) for the actions of the entire firm.

Do Depraved Thoughts Make You More Creative?

In an experiment, Protestants produced better, more creative work when they were induced to feel unacceptable desires and primed with words evoking depravity and damnation, says a team led by Emily Kim of the University of Illinois. For example, those who were exposed to words such as “dirty,” “punish,” and “forbid” and then asked to make a clay sculpture and write a poem were judged to have created better art (2.63 versus 2.30 on a 5-point scale) than those who had seen words such as “clean,” “reward,” and “virtue.” The effect was not seen among Catholics or Jews, the researchers say.

Health Insurance Exchanges Fulfill Both Liberal and Conservative Goals

The new health insurance market places—the exchanges set up under Obamacare—have become the hot health policy topic.  Will they work or won’t they?  The focus is on the near term.  And no one should doubt that what happens in the next few months is extremely important—as former cabinet officer Wilbur Cohen said, good policy is 1% inspiration and 99% implementation.  Vital though near-term effectiveness is, the exchanges hold a longer-term potential—they can help reshape the organization, delivery, and financing of insurance.  Simply put, we think that the health insurance exchange—supported at various times by both liberals and conservatives—may well fulfill the health reform dreams of both.  To see why, one need only recall what conservatives and liberals want.

Conservatives want people to be free to choose the insurance plan that best matches their preferences.  They want insurers to compete with one another on the basis of price and service.  They are convinced that if people can shop freely for the plans they want and insurers must compete actively for their business, everyone will gain: customers will get coverage that matches their preferences, and insurers will become more cost- and quality-conscious than they now are.  Conservatives also recognize that many people will need financial help in order to afford health insurance, and they have embraced such aid.

Liberals want universal coverage.  While they accept competition, they believe that regulations are also necessary to hold down the growth of health care spending and promote the adoption of improved modes of delivering care.  Liberals believe that market pressures, by themselves, will be too weak to prevent hospitals, doctors, and other providers from sustaining what economists call ‘rent seeking’ activities.  Left to voluntary action, system-wide reforms, such as the adoption of health information technology and new provider payment practices that lower costs and increase quality of care, will proceed with glacial slowness.

The health insurance exchanges have the potential to fulfill the hopes of both conservatives and liberals.  By design, the exchanges will intensify competition by requiring insurers to offer the full range of plans to customers.  By providing software and counseling, the exchanges will help consumers make informed comparisons among these offerings.  The exchanges will initially serve only individuals and employees of companies with no more than 50 employees.  But in 2016 the exchanges will open to companies with 51 to 100 employees.  In 2017, they may open up to still larger businesses and to state and local governments.  If the exchanges do a good job, most businesses may well be glad to rid themselves of administering a vexatious form of compensation that has nothing to do with their main business activities.  If and when that happens, the exchanges will have become the instrument for realizing the conservative dream—free individual choice and tough, head-to-head competition among health insurers.

To do a good job the exchanges have at hand a number of important regulatory powers along lines that liberals have long endorsed.  To prevent information overload, the exchanges can protect consumers from being overwhelmed with plans that have no meaningful difference.  The exchanges can require insurers to offer certain standardized plans so that customers can easily compare price and service. They can set standards for the quality of care paid for by plans, bar plans that do not meet quality or price standards, and selectively contract with those that do. They can post data on the quality of care provided by hospitals, physicians, and others.  They can advertise such information to help consumers make informed choices or, more aggressively, require plans to offer incentives for people to use high-quality, low-cost health care services and providers. Exchanges could also create incentives for insurers to encourage or require providers to apply research findings from analyses of comparative effectiveness.

In addition, the Affordable Care Act has set in motion a large number of pilot programs, experiments, and demonstration projects involving new methods of paying for care and organizing providers. These innovations include bundled payments and accountable care organizations. Not all of these innovations will succeed. But if some do, the exchanges will be in a position to encourage or require their adoption. And if exchanges cover a sizable fraction of the insured population, they will have the clout to change the delivery system.  (For further discussion, see our Perspective article entitled “Only the Beginning – What’s Next at the Health Insurance Exchanges?” in the September 26, 2013 New England Journal of Medicine.)

Many conservatives still decry the ACA.  Many liberals still regret that health reform did not include a public option or was not Medicare for all.  We think that conservatives and liberals alike are failing to see that the ACA holds the seeds of fulfillment for the core objectives each has long sought.

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
Reimagining Primary Care: When Small Is Beautiful
Getting Big Results from a Small Business Unit
How We Revolutionized Our Emergency Department

The Importance of Spatial Thinking Now

In its 375 years, Harvard has only ever eliminated one entire academic program. If you had to guess, what program do you think that was and when was it killed off?

The answer: Harvard eradicated its Geography Department in the 1940s, and many universities followed suit.

The timing couldn’t have been worse, really. Shortly after the elimination of Geography here at Harvard, the discipline underwent a quantitative and computational revolution that eventually produced innovations like Google Maps and global positioning systems, to name just two. Seventy years later we are paying for a prolonged lack of spatial thinking at American universities. There are too few classes that enable learners to improve their spatial reasoning abilities, with maps and visualizations being of course the most central artifacts to such improvements. The problem is simple: not enough people know how to make maps or handle spatial data sets.

In the meantime, spatial thinking, visualization, contemporary cartography, and the other core competencies of geographic education have never been more relevant or necessary. As this forum has made clear, data visualization is an emerging, important discipline, and spatial thinking—geography—is a fundamental skill for good data visualization.

When talking about data visualization many begin with the assumption that it’s a new thing, freshly formed in this big data era. Visualization is not new, and it’s much older than the “Napoleon’s March” example cited by Edward Tufte as the best information graphic. For centuries, people have measured and mapped out worldly phenomena. We were collecting and mapping information long before the printing press. Libraries supply us with limitless evidence of visualization masterpieces that predate any automated computation, let alone big data, like Gerardus Mercator’s revolutionary map of the world in 1569:

That’s not to say nothing’s new about this moment in time. What is new is the recent integration of spatial thinking and computing. The current rise of what I prefer to call computational visualization is an obvious and logical extension of human practices that are as old as lines in the sand. But this idea that visualization is new hinders teaching and learning about the act of visualization. Without the proper context, “dataviz” discussions and “data science” curricula neglect the important lessons and huge contributions from the past, contributions that can inform everything from design principles to teaching and learning.

As I look out on the world of data visualization, I see a lot of reinventing of the wheel precisely because so many young, talented visualizers lack geographical training. Those interested in a 21st century career in visualization can definitely learn a lot from 20th century geographers like Jacques Bertin, Terry Slocum, and Cynthia Brewer, and they will identify pre-existing principles, cognate scholarship, and countless masterpieces that are extremely useful guides.

Which brings us back to the sheer lack of geographical training available. Recommitting to a geography curriculum in both our high schools and universities will be crucial to effectively developing a generation of great data visualizers who can tackle our challenges. Quantitative spatial analytics offer vital insights into the world’s most important domains including public health, the environment, the global economy, and warfare.

Without geography—or any teaching that emphasizes spatial thinking—the focus will remain on the data, and that’s a mistake. Yes, data are undeniably important but they are not holy. Data are middlemen. Even the term “data visualization” overemphasizes the role of the middleman, and mischaracterizes the objective of the activity. Nobody wants to see data; nobody learns from that. The best visualizations never celebrate the data; instead they make us learn about worldly phenomena and forget about the data. After all, who looks at the Mona Lisa to think about the paints?

Which Management Style Will China Adopt?

The three nations that, in one way or another, lead the global economy at the moment are the United States, Germany and China. They lead it in very different ways.

For the United States and Germany, strong multinational corporations and technological innovation are the driving factors. In the case of the U.S., innovation is driven by a can-do spirit and a healthy appetite for risk, with established corporations and startups introducing some of the world’s most important and game-changing technologies. In Germany, a commitment to product quality and engineering excellence has been key both for multinationals and small- and medium-sized enterprises (SMEs).

Up to this point, China’s economic development has been focused on cost competitiveness and the adoption of foreign-developed technologies and innovations. Its global impact has been due mainly to its massive scale. The global financial crisis, however, marked the beginning of a new period in China’s economic history. China can no longer rely predominantly on foreign consumption as an engine for growth. It has to develop domestic consumer markets and orient its production towards them.  Furthermore, rising wage costs make it highly unlikely that China can continue to grow by being the factory for many of the world’s simpler products.

To move itself forward and to move up the value chain, China needs to begin developing a management system and, more important, a culture for technological and product innovation. Germany and the U.S. offer the two main — and quite contrasting — models.

The U.S. business community benefits from a long tradition of newcomers taking risks on entirely new product categories and technologies and leapfrogging companies that have lost their competitive edge.  One need only look at the technology industry for a basic idea of how this plays out. Another trait of U.S. firms is that decisions are usually made in a top-down fashion, depending only on one or a few leaders’ approval, which can allow for rapid adaptation and changes in direction.

The advantages of the U.S. approach to managing innovation are quicker market penetration of new products, broad brand recognition in new markets, and attention to customer feedback which can be used to improve future generations of products. The weakness, one could argue, is that product quality may suffer, leaving the door open for other firms (possibly from other nations) to step in.

German corporations have historically been big innovators in terms of technology and product quality.  However, because of cultural resistance to risk and a widespread preference for stability, larger German corporations of late have not been able to capitalize on new ideas to as great a degree as American ones.  Management in German firms is also much more horizontally organized. If a decision is to be made, it must be approved in a time-consuming process by multiple individuals or groups. Even after it’s been decided at the top, the process may be slowed by levels below if there is insufficient buy in. (These traits are less pronounced with Germany’s more nimble SMEs.)

The advantages of the German approach to managing innovation are high product quality and well-thought-out services that accompany those products. The downside is that new products can be late to market, and truly disruptive innovations few. Even when German companies come up with disruptive ideas, they can miss discovering their immense market potential (witness the saga of the German-invented MP3 player). Disruption and rapid scaling-up seem to fit better with the U.S. psyche.  It is important to keep in mind, though, that as far as market and sales potential are concerned, the German approach — while more restrained — can be lucrative and self-sustaining.

What does this mean with regard to China’s future path?  In both the U.S. and Germany, the argument is often made that the freer people are in a society or an economy, the more innovation is likely to result.  Innovation is bound to happen when people are taught from a young age to challenge the norm. However, the democracy-innovation nexus should not be overstated.  Historically speaking, German companies displayed an innovative spirit long before the country was a democracy.  That suggests that democracy is not necessarily a requirement for innovation.

That part of the historic record sounds like potential good news for today’s China. But it is crucial to recall what Germany did have as assets at the time: a strong engineering tradition, a strong adherence to the rule of law as well as a quickly rising focus on intellectual property rights.  On that basis, risk taking and innovation were properly rewarded.  Today’s China, though, does not yet have the engineering and legal traditions Germany has.  It also still lacks on the other key ingredients in the innovation formula.

How about Chinese firms finding inspiration in the U.S. model? The trait that Chinese firms share with U.S. ones is the ability and inclination to bring a new product to market quickly, although generally still at a low level of product sophistication.  Where Chinese firms still have a lot of catching up to do is in making adjustments based on customer feedback after a product hits the market.  Bringing a new product to market rapidly and improving its quality based on empirical evidence from customers is the true value of the U.S. approach.  It stands to reason that Chinese firms will manage to absorb that lesson before long. The continental size of the Chinese market and the increasing sophistication and quality demands of Chinese consumers will likely ensure that.

Still, that does not yet solve Chinese firms’ problems of indigenous innovation.  The big question is whether they can find their own equivalent of the Yankee spirit of going for radical product innovation, or develop something more like the German model of constant innovation to keep one’s products on the cutting edge globally.

All that can be reliably said at this stage is that Chinese leaders recognize the challenge.  They have begun a process of encouraging innovation and are revamping educational structures and priorities.  Some of China’s leading universities have started up programs dedicated to honing the innovation potential of the country’s future managers.

It’s also likely that both the “German” and “American” approaches to management are going to be practiced in China.  The country’s state-owned enterprises, whether partly privatized yet or not, are more “German” in their character.  They have to obtain a lot of buy-in, including from political stakeholders, and thus are likely to follow a more slow-moving, horizontal management approach.  In contrast, privately owned firms in China are bound to follow the more nimble top-down U.S. model.

The ultimate outcome of China’s corporate and innovation journey of course remains highly uncertain. One thing is for sure, though — it will be fascinating to watch.

Implementing Innovation: Segment Your Non-Customers

Some of the most successful and disruptive innovations stem from a company’s ability to tap into demand from non-customers in its market category. The challenge, of course, is to identify why these people aren’t customers already. Once you know why potential customers aren’t buying your product, you can develop innovations to make your product more appealing to them.

Unfortunately, a focus on known customers and share of the existing market is ingrained in the processes and metrics of companies. As a result, they have less systematized data about their noncustomers.   You can improve the odds on succeeding through innovation if you fix this data problem by treating non-customers as a segmentation problem and apply some of the discipline of marketing research.

The key is to segment according to reasons for not buying products in your category.   In my experience, these typically fall into one of six categories:

Economic:  People lack access to cash or credit
Functional:  The product does not help people achieve what they want to achieve
Educational: People don’t know how to use the product or even what it can do
Access: People can’t buy the product because it is not readily available to them
Social: The product doesn’t conform to religious or social norms
Emotional: The product triggers negative emotions.

The global swimwear company Arena used this categorization as a framework for segmenting non-customers. They first hypothesized a list of non-swimmers, then they analyzed the barriers inhibiting the potential demand of each segment, and finally they developed a set of new products that could overcome some of these barriers.

One attractive segment they identified were beginners who went to the pool a few times and then gave up.  The principal problem for this group was functional: they struggled to develop good breathing technique.  Breathing is perhaps the biggest challenge for novice swimmers. Poor breathing creates problems with executing strokes, making it harder to move comfortably in the water.  It is one of the most common reasons that novices give up learning to swim and turn to non-water gym activities.

This insight led Arena to develop a new device, called the Freestyle Breather, a pair of plastic “foils” or “fins” that can be attached to most marketed goggles. The Freestyle Breather has three main functions: it facilitates inhalation by enhancing the bow wave, making it easier to breathe into the air pocket; it secures inhalation by protecting the mouth and nose from splashes and water drops; and it reduces over-rotation of the head and body because swimmers feel less anxiety and risk of breathing water.

Swimming with a Freestyle Breather makes the pool experience so much easier for beginners that it has the potential to convert many novices into regulars at their local pool.  Arena reckons that there’s potential to more than double the global population of regular swimmers.

Another segment Arena identified was Muslim females, who experience social barriers to swimming.  They want to be able to move fluidly in the water but they can only swim when their body is fully covered.  Unfortunately, swimming in traditional cotton bodysuits is uncomfortable both during the swim and after (cotton body suits take a long time to dry off).  After studying groups of Muslim women using the traditional swimsuits, Arena applied its expertise in performance materials to design a line of swimwear that conformed to religious norms, was comfortable in the water, and dried quickly.

Of course, you won’t capture all your potential marketspace through this exercise.  But if Arena’s experience is anything to go by, simply sorting non-customers into the categories described here and analyzing barriers blocking potential demand gets you a very long way.   Companies should be doing more of it.

Executing on Innovation

An HBR Insight Center




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