Marina Gorbis's Blog, page 1320

To Stay Focused, Manage Your Emotions

A leader’s most precious resource is not their time. It’s their focused attention. Time merely passes, while focused attention makes things happen. When we’re able to gather and direct our attention toward a particular task or interaction, we can have a significant impact in a minimal amount of time. But when we’re unable to bring our attention to bear on the work at hand, all the time in the world is insufficient. So what are the implications of this for leaders?

Leaders must recognize that it’s essential to work at enhancing their ability to direct their attention and minimize unhelpful distractions, and one of the most important steps in this process is managing emotions. Psychologist Victor Johnston describes emotions as “discriminant hedonic amplifiers,” meaning that they boost various signals in our mental landscape, drawing our attention toward certain issues and events and away from others. In other words, emotions are attention magnets.

Consequently, awareness and regulation of our emotions are central to the productive use of our attention. Here are some practical steps leaders can take.

Build Capacity. We can expand our attentive capacity though a commitment to practices such as meditation, journaling, time in nature, regular physical activity, and good sleep hygiene. All of these activities support our ability to direct our focus, filter out distractions, and manage our emotions, and we can often realize their benefits with a modest investment of time. Recent research indicates that meditating for just a few minutes a day, spending just one hour a week in nature, or jotting down a few reflective notes in the evening has a noticeable impact on well-being. My experience as a coach suggests that these benefits extend to leaders’ effectiveness. The key is a consistent commitment to each daily or weekly practice.

While these activities are often enjoyable in themselves, they aren’t indulgences–they’re investments in our ability to operate at peak effectiveness. High-performing professionals often enjoy success early in their careers by virtue of their ability to forego activities like this–they cut back on sleep or go without exercise for extended periods of time. But while those sacrifices temporarily expand our capacity for throughput, they actually diminish our capacity for focused attention. And while more senior leaders like my clients continue to work hard, what allows them to add value isn’t the extra hours spent working, but rather the quality of their focused attention while they’re at work.

Plug Leaks. Attention is finite, and our ability to focus in the moment is severely limited. Because distractions can fatally undermine effective leadership, it’s critical to avoid “attention leaks.” As I wrote a few months ago, “The functions on our phones and other devices that beep, blink and thrust red numbers in our faces are designed to capture our attention and create a sense of urgency… But how often are any of these interruptions truly urgent? Almost never. Turn them off.”

Another attention-destroying practice is what we’ve come to call “multi-tasking,” an utterly misnamed concept. While insignificant tasks requiring minimal cognitive effort can be performed in parallel, the truly meaningful work through which most leaders add value–one-on-one conversations, facilitation or decision-making in meetings, and creative thought and ideation–require a much more intense level of focus. Multi-tasking in those environments inevitably results in significant inefficiencies as we switch contexts and lose focus before returning to a deeper level of thought.

Create Space. Leaders typically face intense demands on their time (in part because everyone wants their attention), and if they’re not careful they can find themselves booked nonstop for days on end. It’s important to maintain some open space in the calendar, on a weekly or even daily basis, which allows for more creative thinking and helps replenish our stores of attention.

Further Reading







HBR Guide to Getting the Right Work Done

Leadership & Managing People Book

19.95



Add to Cart





Save
Share

This inevitably involves disappointing people, all of whom believe their issue is worthy of the leader’s time, but productive leaders realize that they can’t meet all of these requests and must ignore many of them. Here leaders require help from their senior team, family, and friends, and–perhaps most importantly–their executive assistants. People in these roles are uniquely positioned to help leaders protect open space on their calendars, and they’re uniquely positioned to undermine that process if they don’t understand this responsibility.

One final thought: If you’re a leader sitting in a meeting that’s not worth your focused attention, then you’re serving a theatrical function. Sometimes this makes sense. There’s a place for organizational theater. But more often the whole organization is suffering because your most precious resource is being wasted. Let the people who organized the meeting know that you’ll attend in the future when you’re needed, excuse yourself, and get on with your day. And if it’s your meeting, then you may well be wasting everyone’s time and attention–they may all be there in a theatrical function because they’re deferring to your authority. Have a candid conversation with a trusted ally, and get some feedback on the utility of your meetings.

Thanks to Chris Oestereich for a timely reminder on the importance of open space.

[image error]

Why the Keystone Pipeline Is the Wrong U.S. Energy Debate

The Keystone XL — a proposed addition to a network of pipelines running from the Canadian oil sands to refineries in Texas — has become the political football of the moment. It was the first issue that Sen. Joni Ernst addressed in her response to last week’s State of the Union address, and yesterday the Senate passed a bill forcing its approval. President Obama, however, has said he’ll veto Keystone, and he should.

Putting aside the divisive politics, let’s consider the pipeline on its merits, as an investment choice for the United States. In the short run, with oil at $50 per barrel, Keystone will connect refineries to oil that may be unprofitable to extract. In the long run, as the world turns away from fossil fuels aggressively, the pipeline will be moot — a relic of the past.

Either way it’s a poor investment.

First, the short-run economics. They’re not good. To feed the 90-million-barrel-a-day beast that is the global economy, we need more than just OPEC. The “unconventional” sources of oil, like fracked shale oil from North Dakota and the Canadian oil sands, help fill a large gap left by the production of conventional crude, which has, for years, flatlined at around 70 million barrels per day.

But “unconventional” also means expensive — squeezing oil out of uncooperative mud or tight rock formations is an energy, water and capital-intensive process. Oil sands require up to 3 barrels of water for every barrel of oil produced. And consider the “energy return on investment” — that is, how much useful energy you get for every unit of energy put in. Globally, oil and gas sites attain an average ratio of about 20 to 1, while oil sands efficiency can range down to below 2 to 1.

This resource intensity costs money and time. So at today’s (surprise) $50 per barrel price, most of the oil production sites in the world are facing serious economic challenges. When prices rise again — and they will — oil sands will be more profitable. But even then, these unconventional sources will still face two large and existential challenges: climate change and the fast-improving economics of renewable energy.

A tipping point on global action on climate change is approaching. For years, the likely suspects (environmental non-profits, well-known green leaders like Al Gore, and a handful of progressive business executives) have pushed for cuts in carbon emissions and a change in how we produce and use energy. But now an unlikely group of new voices — from the Pope to bankers and former U.S. Treasury Secretaries Hank Paulson, Robert Rubin and, most recently, Larry Summers — are calling for aggressive policies, such as a tax on carbon. The World Bank has also gathered the signatures of 1,000 multinationals and 70 countries in support of a price on carbon. These voices are not going unheeded: carbon taxes and trading systems are already in operation around the world, from British Columbia to China.

The call for regulations and public pressure on fossil fuels has intensified because the math and physics of climate change tell a clear story: We cannot burn all the reserves of fossil fuels that humanity has already identified … not even a third of them. A new study in Nature magazine overlays this harsh reality with the actual location of reserves. It’s not a pretty picture for oil-dependent regions like Russia and, yes, Canada. To keep the world from warming more than the globally-agreed upon 2 degrees Celsius (3.6 Fahrenheit), the study says, “85% of the 48 billion barrels of reserves” in Canada will have to “remain unburnable.” So why would we build a pipeline to a resource that will most likely go unused?

The second, more long-term threat to the fuels of the past is arriving in the form of cheap renewables. Technically speaking, in the U.S., renewable energy does not replace oil (since oil has almost no role making electricity), but a shift to clean energy reduces demand for gas and coal — and a cleaner grid makes much more attractive the hybrid and electric fleets that do reduce oil demand. Cheaper renewables matter and they’re already here. Renewable energy is winning: in the U.S., half of the new energy generating capacity being put on the grid comes from renewable sources. In total, the world spent $310 billion on clean energy last year.

Investors and energy utilities on both sides of the Atlantic are waking up to these radically changing economics. Barclays bank downgraded all U.S. electric utilities, saying they were not a great investment as solar prices fall. The leading utilities are trying to pivot their businesses in a big way. In the U.S., NRG announced aggressive goals, including cutting carbon 90% by 2050. German utility E.On went further and spun off its fossil-fuel burning assets to concentrate on renewables.

While companies are recognizing that tackling climate change is getting much cheaper, in the political maelstrom around Keystone, Washington is ignoring the ample evidence. The supporters of the pipeline have touted the economic benefits of thousands of construction jobs. The critics have pointed out that those are temporary positions and only 35 jobs will remain after a few years. Both estimates are probably right — that’s what infrastructure investments look like. So those job counts are beside the point. Many other infrastructure choices we could make would create jobs — roads, bridges, schools, or a new energy grid.

So the real question is, what kind of infrastructure do we want to build? Do we approach every project as a one-off way to create some temporary jobs, or do we have a strategy in place that improves our long-term competitiveness? Imagine if we were thinking today of building our education infrastructure by investing in blackboards and slide rules. Instead, many school districts, including my son’s, are wisely handing out Chromebooks and iPads to every child.

Similarly, why would we invest in yesterday’s energy technologies when we have smarter options? Our investment choices should make our country more resilient, healthy, and prosperous. By that logic, the pipeline is a bad investment choice. That’s just simple arithmetic and economics. Given the challenging future facing unconventional, expensive fossil fuels, the Keystone XL is literally a pipeline to nowhere.

[image error]

How to Really Listen to Your Employees

Let’s face it: strong leaders tend to be characterized by their strong opinions, decisive action, and take-no-prisoners attitude. These are important traits, but it’s equally important for managers to stand down and listen up. Yet many leaders struggle to do this, in part because they’ve become more accustomed to speaking than listening. So, how can you develop this muscle? What are the barriers to good listening and how do you overcome them?

What the Experts Say

“As a leader, you need to have a strong voice and you need to know when it’s time to listen,” says Amy Jen Su, co-owner of Paravis Partners, an executive training and coaching firm. “A real conversation is a two-way dialogue; it requires both parts.” Christine Riordan, a leadership coach and president-elect of Adelphi University, agrees: “To be able to motivate and inspire others, you need to learn how to listen in both individual meetings and at the group level.”  Fortunately, there are concrete ways to improve this important skill. Both Su and Riordan agree that the key is to start with the right mindset.

Make it a priority

First, you need the will. “You have to put it at the top of your list and acknowledge it’s a skill that’s important in your role as a leader. It has to be an active decision,” says Riordan. And to get over a need to talk or interject, adapt a mindset that will allow you to hear what’s being shared. If you believe you have all the answers, you simply have no reason to listen to others. Some of Su’s strongest clients build their listening skills by focusing on co-creation. “They recognize their own intellect, but they also recognize that their colleagues are equally smart and have something of value to say.”

Know thyself

It’s important to understand what’s holding you back. Are you a naturally good listener or do you have a more assertive personality? “There are personality traits that lend themselves to more empathic listening,” explains Riordan. “If you’re extroverted and conversational, you’re usually the one doing most of the talking.” Su had a client who was strong, passionate, and innovative. The downside to these fiery traits was that he was, as his subordinates and teammates described him, a “bull in a china shop” when it came to listening. To make matters worse, he was totally unaware of it.  To break him of this bad habit, Su instructed him to use a “listening stick.” He started at home with his wife (who was thrilled at the prospect of his transformation into a better listener). Every time he wanted to talk during dinner, he had to wait for his wife to pass the listening stick. This physical cue finally helped him improve.

When assessing your own habits, also take your upbringing into account. “Some of us may have had early experiences in life where we were taught to be listeners instead of speakers, deferring to others. Some of us were taught that it was weak to listen, that we need to speak up,” says Su. Without first recognizing the influence of your early years, it’s difficult to change.

Further Reading




The Discipline of Listening

Communication Article

Ram Charan

How to master this essential leadership skill.




Save
Share

Get rid of distractions

When your attention is elsewhere during a conversation, you risk sending a message that the speaker and their message are unimportant. “We assume being on our iPhone or tablet isn’t a big deal, but when you speak to the people who work for those leaders, it has a really negative impact,” explains Su. And realistically, splitting your attention in such a way prevents you from getting the full picture; after all, you can’t pick up on facial expressions if your gaze is down at your phone. Demonstrate that you are listening by silencing phones, darkening your desktop monitor, and putting away anything that has the potential to distract you from the conversation at hand.

Look for nonverbal cues

Communication is much more than the words spoken. As Riordan says, “It’s not just content, it’s context, too.” People communicate in a myriad of ways and many of them are nonverbal. “In a conversation, people might say one thing but their face and body are saying the opposite.” Don’t let these cues pass by unaddressed. Acknowledge the information you’re receiving with questions like, “You seem excited about this, can you tell me more?” or “I get the sense that this upsets you, is there anything you need to share?”

Control your reactions

But don’t just focus on their body language. Control yours too. There are times this is challenging, either because we disagree strongly or because the news is upsetting. Riordan has seen leaders overreact to information, typically by snapping or very vocally disagreeing with the bearer before the message has been fully delivered–particularly when the news is bad. Regardless of the information you receive, it’s just as important to maintain control over your body language as it is to notice theirs. Practice sitting still and maintaining silence. Riordan advises us to avoid the rush to react or contradict.

Validate and verify

Leaders who are effective listeners validate and ask clarifying questions. “They don’t make assumptions. They drill down into the content of the conversation and verify what they’ve heard,” explains Riordan. They typically ask questions like, “Here’s what I thought you said, is that correct?” To be clear, Riordan stresses that you don’t have to agree with what’s being said. You can acknowledge and even express gratitude for the information, regardless of how you feel about it. Always close the talk with a summary of points heard and next steps.

Principles to Remember

Do:

Take an honest look at both your good and bad habits
Clear out all distractions that might draw your attention away from the person in front of you
Ask clarifying questions and repeat back what you heard

Don’t

Assume you know all of the answers — allow for the possibility that others have valuable information to share
Overlook nonverbal cues — they often reveal what a person is really thinking
React emotionally to what is being said — acknowledge the information even if you don’t agree

Case Study #1: Create an environment conducive to listening

In 2004, Mike Colwell was promoted to manage a team of five directors, all of whom he’d worked with previously. He made it a priority to bring them together in one cohesive unit. One by one, they would each come in for a meeting with him to discuss the usual day-to-day news, and any other issues his managers wanted to bring to his attention. But it wasn’t long before he noticed things just weren’t flowing smoothly.

“I had five very strong leaders, but they all communicated differently and seemed to be giving me different information depending on whether they thought it was important or not,” says Mike. Worse yet, it seemed that they weren’t bringing small issues to his attention before they became big problems.

After some consideration, Mike realized there were two elements that contributed to the problem. First, he wasn’t creating an environment that was conducive to listening. When his managers came in, the various electronics on his desk created distractions and interruptions. His monitor was constantly alerting him to new messages or emails. “I realized I had to eliminate the distractions so I removed everything from my desktop, including my phone, and turned off my monitor,” says Colwell. “The dark monitor became a reminder for me; every time my eyes wandered to it, it was a cue to pay attention.”

Next, Mike decided to follow a specific agenda for each individual meeting. Every time they came in, his directors knew they would be expected to discuss all nine key elements of the business. Mike also told them that he didn’t want to do the talking; he wanted them to take the floor and give him the information freely. Not only did Mike’s tactics give his team the satisfaction of feeling heard and understood; the quality of information he received improved drastically.

Case Study #2: Don’t let personality traits get in the way

In 2006, Cameron Herold was proud of where his company, 1-800-GOT-JUNK?, was headed.  The company, which was started in 1989, had $60 million in revenue and employed over 200 people at its head office. This was a promising position for the growing venture, but dissension soon broke out on the leadership team over how to grow. Their VP of Finance kept warning them not to spend in a few key ways. “He cautioned us about our growth, but we never really listened,” says Cameron, who was the COO at the time.

The problem? “Our VP was quiet. Almost meek,” he says. He was an introvert, and his manner of speaking was subservient. In contrast, Cameron and the CEO were both dominant and expressive. “Because he wasn’t right in our face about it, pushing us, we let his words go in one ear and out the other.” As a result, the VP’s warnings went unheeded and the company expanded too fast and ran out of cash. They faced significant financial trouble, which made it harder to weather the economic downturn in 2009.

Luckily the company survived, and Cameron was able to change his ways. The experience taught him to spot the disappointment in someone’s face when they speak yet don’t feel heard. “It’s important to look for it, to know if I’ve been truly listening to them or simply placating them,” he says. “And as a leadership team, we learned that we had to listen and pay attention to everyone, regardless of their communication style.”

[image error]

The Decline of the Rural American Hospital and How to Reverse It

There are two kinds of health-care innovation: more-for-more and more-for-less.

The American health-care system exemplifies the first kind, offering more and more value at higher and higher costs. If you have the money and can travel, the U.S. is the place to take advantage of the latest innovations such as proton-beam cancer-radiation therapy, for which the equipment and facilities cost about $1 billion.

Despite these high-cost innovations (American consumers spend more on health care than their counterparts anywhere else), U.S. life expectancy ranks 34th in the world, and infant mortality ranks 27th. It’s no wonder that patients, politicians, third-party payers, hospitals, and providers are calling for health-care models and technologies that deliver more for less.

In contrast, India is widely recognized for the second kind. Providers such as Aravind Eye Hospital, Narayana Health, and Apollo Hospitals offer high-quality outcomes at a tenth of U.S. prices to vast numbers of patients who would otherwise have no access to care. The driving forces for this, of course, are India’s economy, its scarcity of providers, and its large population of poor consumers; the U.S. just has not been desperate enough to foster Indian-style health-care innovation.

There are, however, isolated pockets of extreme need in rural U.S. communities, where conditions are ripe for more-for-less innovation. These communities are facing a health-care crisis because economic and regulatory pressures are pushing providers to cluster in urban centers. The consequences are dire. Last year, 13 rural hospitals closed, and a tidal wave of closures is expected over the next few years. These hospitals are caught in a vicious cycle: Rural patients with serious health problems are traveling to cities to seek care from medical specialists, causing revenue declines at rural hospitals and clinics, which respond by downsizing and offering fewer services, causing more patients to seek care in major urban centers.

To help break this cycle, some rural hospitals and clinics are adopting an innovation that allows them to access specialists virtually, for a lot less money. Consulting with specialists via video conferencing may not sound like a dramatic innovation, in comparison with proton-beam radiation therapy, but it is! It redistributes access and makes use of resources in new ways. Virtual consultations, supported by sophisticated diagnostic instruments, high-resolution imaging, and data security, are at the heart of a reconceptualization of rural hospitals (and eventually urban clinics and hospitals as well) because they provide access to higher-quality care at much lower costs. Our research — we’ve interviewed executives and care providers at numerous health-care organizations and written a case study on telemedicine — suggests that telemedicine promises to upend health-care markets where supply and demand are out of balance.

Adam (his name and other details have been changed for privacy), a long-term HIV patient in rural Arizona, illustrates the effect. Prior to the implementation of a virtual-consultation program serving his local clinic in Kingman, he had two unattractive options: see his local provider, who wasn’t an HIV specialist, or travel more than two hours to Flagstaff on one of the HIV clinic days offered in a facility there. Neither was compelling enough for him to seek treatment. He didn’t have reliable transportation, and he was uncomfortable sitting in a waiting room on HIV day, because doing so would publicly announce his health status. Consequently, Adam became one of the thousands of rural patients who have given up on the health-care system.

Then North Country HealthCare developed a telemedicine program that allowed him to visit his local clinic and connect virtually with an experienced HIV specialist in Flagstaff. The telemedicine station at his clinic, supported by an onsite technician, allows the specialist to check blood pressure, view skin lesions, check for mouth sores, conduct an ear exam, watch a live ultrasound exam if needed, and talk with Adam about his personal health practices. The specialist, a nurse practitioner, has been able to triple the number of patients she sees because telemedicine reduces the time she spends driving to satellite clinics. She strengthens her patient relationships through in-person visits every few months, but these are now supported by more frequent meetings and telemedicine exams.

Telemedicine is a win-win for Adam and the local clinic. Adam saves time and money because he doesn’t have to travel to Flagstaff, and the Kingman clinic keeps Adam as a patient (and the revenue he brings in). Most important: Adam, who had opted out of the system, is now receiving the care he would have missed.

This story is not unique. Because of its telemedicine partnerships, a 25-bed hospital in La Grande, Oregon (population 13,000), has virtual access to 19 specialties, including pulmonology, cardiology, dermatology, rheumatology, neurology, and oncology. The same is true for close to 300,000 rural veterans who tap into the extensive telemedicine network maintained by the VA. Mayo Clinic in Arizona, applying a hub-and-spokes telemedicine model to provide neurological consulting for emergency treatment of stroke patients at 16 rural hospitals in four states, has reduced the need for air and ground ambulance transfers and significantly improved patient outcomes.

Administrators at rural hospitals and clinics are discovering that virtual consultations have an enormous influence on their facilities’ reputations. Knowing they can access specialists without making long drives to urban centers, rural patients regain confidence in the ability of their local hospitals to offer high-quality, specialized care. This enhances the hospitals’ ability to retain patients (and revenue), curtailing what for many has been a death spiral. After Lincoln Hospital in Davenport, Washington, started its telemedicine program, admissions grew by 25% and transfers to urban hospitals decreased by 21%, and the increased patient load produced well over $1 million in additional annual revenue for the hospital.

A few barriers stand in the way of widespread implementation of telemedicine: In most states, virtual consultations can be reimbursed only for rural patients, which means telemedicine isn’t available for the urban poor. And U.S. patient-privacy laws require sophisticated data encryption that rules out some of the simpler applications used in other countries — in Australia, or example, a doctor can be reimbursed for a consultation over Skype.

In addition, some of the providers we interviewed complained about problems with the technology. In Phantom Ranch, a remote location in the bottom of the Grand Canyon, paramedics feel that fiddling around to get the right satellite link is low priority when they are attending to time-sensitive emergencies.

Perhaps the most important barrier is acceptance. Not all primary care physicians see a need for the kind of additional expert help telemedicine can provide. Patients, too, are sometimes resistant: Indian Health Services, one of the largest users of telemedicine in the United States, has had difficulties getting older individuals in the Navajo nation, for example, to use the service because of religious concerns regarding the taking of photographs.

Despite these barriers, the innovation will spread as it matures. We expect that many of the telemedicine services that patients in rural America find invaluable will soon be demanded by urbanites. Who wants to drive an hour across town to see a specialist in a large medical center? Why not have a virtual visit in your local clinic — or, better yet, from your own home?

[image error]

Google Glass Failed Because It Just Wasn’t Cool

It was hailed as the greatest product since the iPod … the wheel … the car. Instead, it turned out to be more like New Coke or the Segway. So what went wrong with Google Glass?

It’s not that Google Glass looked absurd — people wear silly fashions every day. It’s not that it was overpriced — people collect luxury watches and handbags every day, too. Google Glass’s failure was a story of a visionary product utterly failing to be cool.

Cool is not trivial. As Apple, Warby Parker, Net a Porter, and Shinola all know: Cool is perhaps the crucial factor in the success of new products. Cool isn’t something that is easily calculated by data-driven corporobots or profit-maximizing algorithms. Cool is not an equation. It’s mysterious, ineffable. An art, not a science. Which makes it hard for an engineering behemoth like Google to master. Cool cannot be engineered.

And yet that’s precisely what Google tried to do. It put Google Glass on models during Fashion Week, in advertorials in fashion magazines, in the hands of fashion “influencers.” Why? To engineer hype, excitement, adulation … to manufacture “buzz.” Aha! Textbook digital strategy! Genius! How could it fail?!

Actually: how could it succeed? All of that desperate maneuvering served to reinforce the obvious: that Google Glass was so uncool, the only thing Google could do was try to force it to be cool. It’s like the sad guy at the bar who shows up one day in a Ferrari and a shiny $3,000 suit … all of which only makes him less attractive. In short, Google made a fatal error of post-modern marketing: it attempted to buy cool through the not-so-subtle techniques of influence, persuasion, and manufactured buzz. But if you have to buy cool, it’s probably a reliable signal that you’re totally, hopelessly uncool. Every organization, or leader, in history that has tried to buy their way to cool has learned the hard way: cool has to be earned.

So how does one earn cool? At its most fundamental, cool is about liberation. Jazz liberates music from the suffocating formalism of classicism. Disco liberates people to stop standing around and looking awkwardly at one another and get down until the sun comes up. Great books are cool – and often banned – because they liberate people from established ideas and norms. Biker jackets are cool, not because they represent two-wheeled transport, but because they represent freedom from the tedium of spreadsheets and minivans (which in turn are just representations of other things). Things stop being cool once they stop liberating; think of a revelatory Jimi Hendrix guitar solo juxtaposed with any run-of-the-mill shred-fest by some ’80s hair band. It’s so important, I’ll say it again: Cool liberates. What, exactly, did Google Glass liberate people to do – spend more time on Facebook?

Back up for a moment. What makes rock stars so enviable? It isn’t just the money, fame, and hangers-on. Even bankers have those (and no one wants to be a banker … not even bankers). Nope. What makes rock stars so enviable, and what we really mean when we describe someone as a “rock star,” is that they don’t give a damn — about the drudgery of bosses, bills, backbiting, invoices, accounts receivable, performance reports, deadlines, conference call and all the hellish paraphernalia of a prosperous post-modern life. (I’m willing to bet that the Ramones didn’t give a damn about conference calls.) In short, rock stars are freer than the rest of us, in a fundamental way: they’re free to pursue their their passion and not to waste their lives on what doesn’t matter. They’re free to be individuals.

But Google Glass did not liberate people. It didn’t make them freer. It didn’t help them become individuals. Why did people roll their eyes at (or even punch) people wearing Google Glass? Not just because it looked ridiculous. Because it promised to be just another way to rob people of their individuality. It threatened them with yet another demand for mind-numbing conformity. Better not speak out! Better not express yourself! Maybe the Glasshole’s recording you!

Patching into another three hours of meetings in your self-driving car on your augmented reality headset so you can spend even more time getting yelled at by your boss? That’s not freedom. That’s repression. Self-chosen. Which, of course, is the most pernicious kind.

There’s a now-old joke: Google Glass lets you step outside … to check the weather. But that joke contains a profound truth. Google Glass simply reinforced the status quo.

The painful truth is that there wasn’t enough rebellion in Google Glass. Google might have thought there was. But me, you, and probably even the guy in the $3,000 suit at the bar knew: it wasn’t revolutionary, socially, economically, culturally revolutionary … it was just more of the same suffocating, shoulder-shrugging, yawn-inducing conformity. And nothing conformist is ever, ever cool.

Let me put it this way. The average American has a veritable gadget cornucopia at his fingertips. But he’s poorer, more unhappy, more anxious, and less mobile than he was 30 short years ago. In short, technology hasn’t liberated people. It might just be thwarting them, in significant ways, from the lives they should be living.

And that’s why we love things that are cool. Because they give us a tiny taste of liberation. A small caress of freedom. A little jab of individuality. All that’s always in stuff that’s cool. That’s why it doesn’t just titillate and amuse us … but thrills, excites, and exhilarates us. What is truly cool challenges us. To imagine the world as it should be. And then make our lives the levers of those worlds.

Here’s the lesson: If you want to make something cool, you’re going to have to make people the rock stars of their own lives.

[image error]

Accomplish More by Committing to Less

Believing that more is always more is a dangerous assumption.

There’s a cost to complexity. Every time you commit to something new, you not only commit to doing the work itself, but also remembering to do the work, dealing with the administrative overhead, and to getting it all done in the time constraints involved.

The unfortunate result of taking on everything that comes your way is that you end up spend more of your time managing the work and less time investing in truly immersing yourself in what’s most important and satisfying. Many people in large organizations spend a huge amount of their time going to meetings to talk about doing work, writing e-mails to communicate about work, and worrying about how they’re going to get work done — yet rarely making meaningful progress on a weekly basis. They see saying “yes” to everything and having a constantly growing to-do list as at best a marker of success, and at worst something that can’t be avoided anyway.

But the people creating the most value for their organizations take a different approach. They start with having radical clarity on the meaningful work that will create results. Then when something new comes up, they stop and evaluate the new item versus what they already know is most important before saying “yes.” Sizing up new opportunities — from a simple request for a meeting to a large request for a project — isn’t about being insubordinate or unhelpful. Instead, it’s about recognizing new activities for what they are: a request for time resources that if not managed properly could pose a serious risk to the stellar execution of the most significant priorities.

It’s simple math. Each additional project divides your time into smaller and smaller pieces so that you have less of it to devote to anything. Whereas if you reduce your number of responsibilities, you have more time to devote to each one. That means on an individual level, you want to strike the ideal balance between the number of projects and the time you need to excel in them. The same principle holds true on a department and company-wide level. Promising fewer new projects, new products, and even new customers gives everyone the capacity to deliver breakthrough results on what remains.

You and Your Team



Getting More Work Done


How to be more productive at work.

The best way to break out of this vicious cycle of over-commitment and underperformance is to very carefully manage what you agree to do. You can actually do more if you take on less. Here are a few steps you can take to prevent overloading your plate:

Create a pause. Whenever possible, avoid agreeing to new commitments on the spot. Instead slow down the decision making process to give yourself the space to make a reasoned choice. First ask clarifying questions. For example, if someone requests that you take on a presentation, say, “That sounds interesting. What did you have in mind?” Confirm the topic, format, and formality, as well, so you can ascertain how much prep work it will require. Then, ask for some time to review your commitments and get back to them with an answer: “I’ll need some time to review my current commitments. Would it be reasonable for me to get back to you tomorrow?” People want to be “reasonable” so they’ll typically say “yes.” If this correspondence happens via e-mail, you may not need to ask for the time to come to an answer — just take it.

Say “no” early and often. If you immediately know that you don’t have the capacity to take on a project, say “no” as soon as possible. The longer you wait, the harder it will be for you to decline the request and the more frustrated the other person will be when they receive your reply. A simple, “This sounds amazing but unfortunately I’m already at capacity right now,” can suffice.

Think through the project. If you want to take on the project, stop to think through what you’d need to do in order to complete it. For a presentation, that might include talking to key stakeholders, doing research, putting together the slide deck, and rehearsing. For a much larger project, the commitment may be more extensive and less clear. Map out what you know and then make rough estimates of the amount of time you think the steps might take.

Review your calendar. Once you’ve thought through the commitment, review your calendar. This allows you to see where you have — or don’t have — open space in your schedule. In the case of the presentation, if you see that your calendar has open time, then you can commit to the project with confidence and block out time for it on your schedule. If your calendar has no time free between now and the day of the event, and the presentation would require prep, you have a few options. The first is to simply decline, based on the fact that you don’t have any available time in your schedule to take on anything new. The second option would be to consider renegotiating your current commitments so that you could take on the new project. Evaluate the new request versus your current projects. Is taking this new project on worth dropping or delaying something else? If you’re not sure, you can ask your manager: “I was asked to do a presentation for XYZ. That would mean that I’ll need to take some time away from project ABC. Would you like me to adjust my priorities in this manner to accommodate the new request, or would you prefer that I not take on the presentation?” Using one of these strategies allows you to take on a reasonable amount of commitments and stay out of time debt.

Adjust your commitments. If you take on something new that will impact other projects, make people aware of what they can or can’t expect from you. They may not prefer that you made another initiative a priority, but if you’re aligned with your boss and your goals, you’re making the right choice. Also, if you let people know what to expect as soon as possible, they’re less likely to be upset. This gives you the opportunity to work with them on creating a new timeline or on delegating work to someone else with more availability.

Once you’re clear on your commitments, get them on the calendar. That way you know you have time and space for the work you’ve just committed to do. With this honesty in your scheduling, you can do the work and do it well. Give yourself hours at a time — even whole days to immerse yourself in excellence. When you’re not trying to eek out 20 or 30 minutes here and there between e-mails and meetings to move forward important initiatives, you can accomplish work of real value — and enjoy the process.

[image error]

An Important Data Lesson from an Inconsequential Football Scandal

As “Deflategate” rattles the National Football League in the run-up to this year’s Super Bowl, data analysts have swooped in, including Warren Sharp, one of many self-styled football analysts who blog about the topic. In a Slate article he analyzes the fumbling rate of the New England Patriots — the team accused of purposefully underinflating footballs to gain an advantage. The headline to his analysis calls the Patriots’ fumble rate compared to the rest of the league “nearly impossible.”

Sharp, you might think, found the smoking gun — a statistic that proves that the Patriots cheated. Only a patient reader who persists to the last paragraph will see that Sharp ultimately admits that New England’s spectacular performance on the metric could be explained in any number of ways, including legitimate ones like perfecting ball security techniques or practicing prevention.

In short, the data say the Patriots are excellent at preventing fumbles. It says nothing about why.

This distinction represents one of big data analysis’ most under-appreciated problems: talking about reverse causation. In reverse causation problems, we know the result and we work backwards to understand the causes.

Reverse causation investigations have the opposite structure from A/B tests, in which we vary known causes, and observe how the variations affect an outcome. If the number of visitors to your website jumped after you changed the image on your Facebook page, you conclude that the new photo is the reason for the traffic surge. (Note: Good A/B test construction can help you see most likely causes; bad A/B test construction creates its own set of problems.).

By contrast, the biggest obstacle to solving reverse causation is the infinite number of possible causes that might influence the known outcome. This is compounded by the fact that we want to assign a cause. So when some data is plucked out of a large set that fits a narrative we may have already constructed, it’s very tempting to simply assign causation when it doesn’t exist.

Most of the time, though, the data offer hints, but no proof. Sharp’s article on the Patriots is one such case. When reading this style of data journalism, pay attention to the structure of the statistical argument. Here is how I summarize Sharp’s:

New England is an outlier in the plays-per-fumbles-lost metric, performing far better than any other team (1.8x above the NFL team average).


Different ways of visualizing and re-formulating the metric yield the same conclusion that New England is the outlier.


There is a “dome effect.” Teams whose home stadiums are indoors typically suffer 10 fewer fumbles than the outdoors teams. New England is a non-dome team that surpasses most dome teams on plays-per-total-fumbles. If dome teams are removed from the analysis, New England is a statistical outlier.


Assuming that the distribution of the metric by team is a bell curve, the chance that New England could have achieved such an extraordinary level of play per fumbles lost is extremely remote.


Therefore, it is “nearly impossible” for any team to possess such an ability to prevent fumbles … unless the team is cheating.

Points 1 to 4 are essentially slightly different reiterations of the known outcome. It is point five in which a connection is established between that outcome and its cause(s). But the causal link is tenuous at best. However suggestive, the data does not prove intent or guilt. It simply describes a statistical phenomenon.

Indeed, digging in on the Patriots data shows that they may not be much of an outlier. In the “dome” analysis, Sharp switched from looking at fumbles lost to total fumbles (which includes recovered fumbles). Other football data analysts have concluded (more than halfway down the page) that fumble recovery is mostly random, so plays per total fumbles is the more useful metric.

Given this new measure, the Patriots are not an outlier, as they’re second to the Atlanta Falcons in fumble performance. Only when Sharp removed all dome teams (the Falcons being one) could he argue that the Patriots were an outlier.

Sharp showed that it is almost impossible for an average team to attain such a low fumble rate, but we have no data that proves the Patriots or any particular team couldn’t achieve it in a legal way. And in fact, the dome analysis suggests there are legitimate methods to perform equally or slightly better than the Patriots did — just look at the Falcons. Unless you want to allege the Falcons also tampered with footballs. (Others have also since refuted this fumbles-prove-malicious-behavior narrative and corrected what seems to be a major flaw in Sharp’s approach: eliminating dome teams from analysis, intead of dome games. When that change is made, the Patriots seem to perform well, but not strangely well; not even the best).

To his credit, Sharp did not argue point five. Nevertheless, many readers and incurious reporters made this causal leap. Sharp helped them along by using a loaded phrase “nearly impossible” to sell the story.

And that’s the reverse causation problem we face. Big data is exposing all kinds of outliers and trends we hadn’t seen before and we’re assigning causes somewhat recklessly, because it makes a good story, or helps confirm our biases. You see this all the time in your Twitter stream: “7 Charts that Explain This.” Or “The One Chart that Tells You Why Something Is Happening.” We’re getting better and better at analyzing and visualizing big data to spot coincidences, outliers and trends. It’s getting easier and easier to convince ourselves of specific narratives without any real data to support them.

Most good statistical analysis will be narratively unsatisfying, loaded down with “we don’t know,” “it depends,” and “the data can’t prove that.”

You can see how this can become a big problem for companies wanting to exploit the big data they’re amassing. If you think about most practical data problems, they often concern reverse causation. The sales of a particular product suddenly plunged; what caused it? The number of measles cases spiked up in a neighborhood; how did it happen? People with a certain brand of phone tend to shop at certain stores; why is that? In cases like these, we know the outcome, and we often don’t know the cause.

The possibility of any number of causes tempts us to retrofit a narrative but we must resist it. The astute analyst is one who figures out how to bring a manageable structure to this work. See this post by statistician Andrew Gelman for further thoughts.

In the mean time, maintain a healthy skepticism the next time someone suggests they’ve found causation in the reverse. Their claims may be overblown.

(Editor’s Note: This article is an edited version of a post that originally appeared on the author’s blog.)

[image error]

Building a Software Start-Up Inside GE

Is your company ready to compete in a world of smart, connected products? For some time now we’ve been living into a smarter world filled with Big Data and analytics, and a more connected one that’s been described as “the internet of things.” In this world, customers expect their suppliers to surround their products with data services and digitally enhanced experiences. This means that many organizations and their leaders are running as fast as they can to quickly build their software capabilities. How can these companies overcome the inevitable leadership, organizational, and cultural challenges involved?

General Electric turns out to be an excellent case in point. It made a massive investment (more than $1 billion) to build a software “Center of Excellence” in San Ramon, California to manage the data explosion created by the increasing intelligence of its industrial machines. CEO Jeff Immelt declared in 2011 that GE needed to become a software and analytics company or risk seeing its hardware products become commodities as information-based competitors took over. As Marco Annunziata, Chief Economist at GE, told me, “We’re no longer selling customers just a jet engine, a locomotive, or a wind turbine; we’re bringing data and actionable solutions along with the hardware to reduce costs and improve performance.” So GE has hired 1,000 software engineers and data scientists to provide enhanced software and analytical skills across GE’s many businesses. GE is now approaching $1 billion in new revenue annually from their expanded software and data activities. Here’s a brief account of how GE quickly scaled up a sizable software start-up within a big, successful conglomerate.

Getting Started

After Jeff Immelt threw down the gauntlet for building a global software center, GE faced significant physical, organizational, and cultural challenges. Who would lead it? Where would it be located? How would it be organized and how would it relate to GE’s existing businesses? How would it integrate into the culture of the larger organization? Would the traditional host organization reject the new software center as an alien entity?

The first step was to hire someone to run it. Bill Ruh was selected in 2011. Key selection criteria included experience in innovative software and service (versus product) development, and an ability to manage a start-up in a very large, complex company. Bill and his team set out to develop a system that could bring all GE machines onto one efficient cloud-connected platform. In a departure from GE’s traditional control systems, the Center was not set up as its own business unit with its own P&L, but rather was funded by a $1 billion investment by Jeff Immelt and became part of GE Global Research.

The next question was where to establish the software center. Though technology would have allowed for a significantly virtual enterprise, it was important to Ruh to have a physical building where people could actually be located together. It was also important to tap into the start-up software culture of Silicon Valley. Together, these constituted radical moves for an industrial company headquartered on the East Coast. San Ramon was selected because it was close to Silicon Valley and had expansion potential. GE started on one floor of a large office building in 2012 and has grown to take over all five floors. The interiors look like Google’s spare, open office plan with concrete floors and airy workspaces (unlike other GE facilities). A design studio is geared for collaboration and innovation work with customers and partners.

Then they needed to decide what kinds of people to hire. Matt Denesuk, Chief Data Scientist, told me, “Who you hire depends on your strategy. We said we were going to build a technology platform in the ‘cloud’ that would provide data plumbing, high-value analytics, and modeling content, so we hired the appropriate skills in software engineering, user experience, and data science. We decided we wouldn’t hire people for some other skills, such as systems integration and change management, and would use partners for that, instead.”

Hiring for Growth

The biggest challenge was growing fast. Melody Ivory, a User Experience Product Manager, told me, “I was about employee number 30 in February 2012. By June of 2012 we were close to 100. By the end of the year we were 500 people. There was an explosion of demand. We were a service organization in a big corporation, so we had ready-made customers. We didn’t have enough people to respond, and we couldn’t scale up fast enough. We were a startup, and like a startup, we grabbed quality people, were hands on, and wore many hats. We grew faster than we thought we would. Yet we still aren’t as large as we need to be to meet the demand from the businesses.”

Jennifer Waldo, Head of Global Human Resources, GE Software Center, was at the epicenter of GE’s recruiting challenge. She told me how difficult it was. “GE didn’t have brand recognition in software. 90% of the people we recruited didn’t know a GE software group existed. And the market for software talent was hot hot hot. There were three competing offers for each user experience expert or data scientist. We were competing with the cool, Silicon Valley tech companies, yet at the same time we needed to find people who would fit in GE’s culture.” To hit the aggressive growth targets (750 by the end of 2013 and 1000 by November 2014) Waldo had to rewrite some GE rules. “We hired a talent acquisition leader from the software industry, someone who really understood technology. And we ‘insourced’ the recruiting activity, hiring recruiters who knew where our target candidates hung out and what appealed to them. We focused on passive candidates, people that weren’t necessarily looking but could be a strong fit for GE. It also required us to amend our compensation practices to be competitive in the technology space.”

I spoke to several GE Software employees, all filled with enthusiasm about their ability to make a difference by combining GE’s industrial domain knowledge with the speed and innovation of a software start-up. In making the appeal to potential candidates, recruiters created a value proposition which emphasized GE’s brand, including GE’s reputation for leadership development; a compelling vision of the “Industrial Internet” as the next big thing; and the opportunity to work on meaningful challenges in fields such as healthcare and energy.”

Integrating with the Mother Ship

One challenge, as you might expect, was introducing a software center that disrupted the existing GE’s power structure, which resides in its business units, such as Aviation, Healthcare, Power and Water, and Transportation. I spoke to Ganesh Bell, Chief Digital Officer and General Manager, Software and Analytics, at GE Power and Water, who sits at the intersection between GE’s Software Center of Excellence and one of its biggest business units, to understand how a corporate startup can work effectively with existing units:

“It started with positioning. We created an expanded vision of customer partnerships with big, market-driven outcomes that the company could rally behind. And we took a stand on what the future holds: driving Industrial Internet solutions. If it were just about software, it wouldn’t fly, but this is a much bigger, customer-driven play. Second, we are incubating new software talent and [creating] software DNA. We have separate funding, and we set it up so that the revenue we generate from software-led solutions is recognized in the businesses. Our performance measures are aligned on driving additional revenue in the businesses. And third, we embraced the fast approach to innovation (“FastWorks”), which was already being driven across the company.”

 It’s working. Bell told me that a cross-functional GE team, working with customers like E.ON, used a software product (“PowerUp”), which is driving more output per wind turbine – a 4% improvement at E.ON.

Despite the vision and potential, there have been other bumps along the way. Many software developers at GE were concerned about reliability and security, which led some of them to resist moving some of the capabilities to the “cloud.” Incorporating rapid programming practices (“Agile” and “Extreme Programming”) to bring significant time-to-market and productivity benefits also required new and different skill sets than what were traditionally found within GE. And there were challenges moving people off old technology and onto the new.

The Silicon Valley software ethic of running experiments to fail fast and learn has been a cultural challenge for GE, where failure has been frowned upon. Successful companies like GE tend to protect the business and perpetuate formulas that have worked well in the past. An ingrained industrial mindset keeps things “within the yellow lines,” focused on controlling operations or managing safety. Streamlining a process with Lean Six Sigma fits this mental model: you focus your product development on making things perfect before releasing them to the market. However, the mindset of software development and Silicon Valley is quite different – you can try something and back it out if it doesn’t work. You have a hypothesis, you try it, and learn. It requires systematic leaps of faith, risk-taking, and potential failure as organic parts of the approach.

To overcome the resistance, Ruh and his team started by working with those businesses within GE that could change quickly. When others started to see the rapid transformation of their peer businesses, they couldn’t move fast enough to get on board. In a way, peer pressure created a domino effect across GE. To quote Annunziata:

“We have moved very quickly from a little resistance and skepticism to seeing the value embraced at all levels. We’ve brought a lot of people to San Ramon who have experience outside of GE and who interact in a less structured way, like a startup. To get these two cultures to work together, first we had a strong commitment from the top, from CEO Jeff Immelt. Second, there has been a cooperative attitude from the people in San Ramon, who are bringing new expertise and pushing the businesses, but listening. And the third success factor has been setting the right priorities, especially choosing opportunities that take advantage of the scale of our company, taking innovations from one place to others.”

The software-enabled revolutions we see in our daily lives, such as navigation using Google Maps or taxi service through Uber, are shaking up the industrial world, too. Machines are getting smarter and smarter. Industrial companies that don’t rapidly scale their software and data capabilities to leverage their hardware will be left behind. GE is one example of a big, industrial company showing how you can quickly build software capabilities using an internal start-up model. Going this route may mean breaking some rules, but ultimately, that’s a fair cost to pay in order to survive and grow.

[image error]

3 Questions to Get the Most Out of Your Company’s Data

Our world is sentient. Websites watch where we look. Mobile applications keep track of our response times. Companies learn which buttons we like to press and which we don’t.  With cameras, microphones, and thermometers, the human race is giving inanimate objects everywhere eyes, ears, and skin. And with all this observation, we’ve created a massive new layer of information.

Jonah Peretti, the CEO of Buzzfeed, knows that this layer of information can be used to test, learn, and iterate in rapid cycles. In this world, you can know, with some level of certainty, the way to craft the exact right title for an article — whether it’s investigative journalism or a cat video. “This isn’t possible in print, broadcast, or traditional films, which may be why the media industry is such a dysfunctional place,” Peretti has said. “Executives make huge bets based on gut, it’s hugely expensive to take risks, and most projects fail.”

But what if you could automate your gut decisions? What if machine intuition is better than human intuition? Trends like the pervasiveness of mobile, the near-infinite storage and computer power of the cloud, and new methods of analyzing masses of data are not just important in themselves. They’re important because they’re allowing businesses to develop new business models that better serve customers. Models that revolve around capturing information and putting it to work. In their simplest form, these businesses rely on the information that’s already there to provide automated intuition. In their most complex form, they flip age-old processes upside down to put a new type of information at the center of the business.

Consider entertainment. Buy a DVD, and the creator of the content learns practically nothing about you. That’s why film producers have no choice but to go with their gut. Netflix, on the other hand, sees every button you push, every movie you like, every TV series you finish — and every one you don’t. From its 40 million subscribers, it’s built an incredible understanding of entertainment preferences. This database has given rise to hit show after hit show, from House of Cards to Orange Is the New Black to Marco Polo (which was popular with audiences, if not with critics) According to Netflix’s own calculations, this data-driven original content is much more valuable for them than the content it licenses, because more people spend more time watching it — despite the high production costs of a series like Marco Polo.

Increasingly, we observe that the companies harnessing machine insight to augment or replace human intuition tend to be native to the internet. From Amazon with its pricing algorithms to Nest with its learning thermostats and smart smoke detectors, these companies have been born in an era where it’s natural to digitally track every interaction with a customer.

But companies from the industrial era are also figuring out how to capture digital insights and feed them back into their business to build advantage. General Electric has made machine-generated insight a priority. Over the last few years, the industrial giant has built an enormous software group dedicated to leveraging all the data they can extract from their sensor-laden hardware. The company realized that it would be much cheaper, for instance, to improve the uptime of turbines by sensing upcoming failures and rescheduling maintenance appointments than by investing in ever-more expensive parts that might break less frequently. Because GE is delivering machine uptime via 1’s and 0’s, instead of via improvements in metallurgy, it’s able to deliver that uptime at a far lower cost than its competitors.

Similarly, 30-year-old software company Intuit has invested extensively in putting its online Mint product at the center of its users’ lives. Many people only think of Intuit once a year, when they use its TurboTax software. But Mint, its product for personal budgeting and bill paying, is becoming the beating heart of its users’ daily financial lives. Mint collects users’ financial information in one place, learns their patterns, provides recommendations for better ways to save, offers investment options, and integrates with TurboTax. Mint has allowed Intuit, a tax software company, to slowly add more and more services otherwise provided by banks. The data that it already uses to help streamline your tax submission is invaluable for the algorithms that will ultimately replace the intuition and experience of financial advisors.

Every business can benefit from using digital intuition to compete. The key is determining how to catch the wave. We believe that three questions can help you position your business for success in the era of automated insights:

What’s your customer’s job-to-be-done?
In a perfect world, what information would help you complete that job?
If you had this information, what inside your business would need to change?

What’s your customer’s job-to-be-done?

Customers don’t buy products just for the hell of it. Customers buy products because a job arises in their lives for which they need a solution. The job of “I need to get this document from here to there with perfect certainty” is one that has existed for millennia. In Ancient Rome, the job required Caesar to hire his best charioteer to ride to the front lines of battle. Fifteen years ago, when that job arose, the name of FedEx popped into peoples’ minds. Today, we hire encrypted email services. But the job is the same. Knowing the job-to-be-done that your product is being hired to complete is the only way to be sure that the improvements you’re making are going to deliver the experiences your customers desire.

The key to General Electric’s evolution was the realization that it was no longer a provider of industrial machinery. It was part of an ecosystem that delivered productivity for their customers. Its products were hired along with a plethora of systems integrators, aftermarket services vendors, and other industrial machinery companies, to help businesses do things like fly planes, generate power, and pull oil out of the ground. And any innovation in service of helping their customers operate more efficiently would be welcomed.

This might seem obvious, but it’s often missed. Managers typically focus on how to improve their products and services the way they’ve always been improved. They invest in annual R&D cycles aimed at continuously improving features as opposed to exploring how the ever growing sea of information at their fingertips can be used to help them fulfill the job that arises in their customers lives.

In a perfect world, what information would help you complete that job?

The next question you have to ask is which information would help you complete that job better. What information could provide you with all the insight you need to make the best decisions on behalf of your customers?

In the case of Uber, the company knew from day one that its job was to make it as convenient as possible for customers to get from point A to point B. The key information required was where people were located when they needed a ride. For cab companies everywhere, that’s always been the holy grail of information; unfortunately, none of them had done a particularly good job of capturing it. Instead, cab drivers were forced to rely on intuition and an understanding of the city to head to areas most likely to support fares. But the fact that taxis were already on the street gave them an advantage over car services that need to come to customers from central garages only after they’ve been summoned. Uber used information about both where the cars were and where the customers were to blend both models into one: allowing customers to simply push a button and be connected with an available, nearby, driver.

Many of us already have access to the information we need. It’s stored in our systems, or our customers are willing to offer it to us. Some of us will need to go out and get it — whether through a partnership, public databases, or the development of new offerings. But one way or another, the key is recognizing the job we’ve been hired to do and figuring out what’s the ideal information that would help us complete that job best.

If you had this information, what inside your business would need to change?

The final question is the hardest to answer. Even when we have the ideal information that would let us generate insight and displace our reliance on human intuition, we still need to identify what we would change as a result to capitalize on it.

Typically, this question forces us to think about developing new business models. Certainly, Intuit, Netflix, and General Electric all had to build models that relied less on human experts than they did on algorithms. Such a model typically reduces the need for employees and reduces prices to customers. Often, this is an unpalatable option for executives. But the reality is that the more we can use machine intuition to improve our existing services and lower prices, the more attractive our offerings will be to more customers — in turn further improving our machine-generated insights. Find yourself in a virtuous cycle like this, and the more likely it is that your businesses will flourish. And when businesses flourish and grow, it’s more likely we can support employment and profitability over the long term.

The reality is that we’re in a time of transition. Machine-based intuition is changing the way companies work. The question is: who in your industry will figure it out first?

[image error]

Manage Your Team’s Attention

What’s your scarcest resource at work?

Most people answer, without hesitation, that it’s time. It certainly is finite, but I would argue that time isn’t actually your scarcest resource. After all, everyone has the same amount of time, and yet individual differences in productivity can be enormous.

A better answer might be your attention — your personal capacity to attend to the right things for the right amount of time. As Nobel Laureate Herbert Simon first suggested 40 years ago, when information is plentiful, attention becomes the scarce resource.

So perhaps the biggest challenge we face as individuals at work, and as leaders, is attention management.  This means being thoughtful and disciplined about how we split our time between different activities, and also about how we encourage others to focus on the right things. How?

First, consider yourself as an individual contributor. If attention is your scarcest resource, the first thing you need to do is discipline yourself to avoid interruptions. So if you are working on something that needs real focus — say, writing a report — then switch your phone to silent, and close down Outlook and Facebook. This is obvious stuff, but it’s amazing how often we don’t do it, and how easily we get sidetracked.

Second, and more difficult, is figuring out when to stop gathering information. When I was a doctoral student, the cost of acquiring information was high — I had to go to the library and make my own copies of annual reports or academic papers. Today, such costs have shrunk dramatically, but the net result of easy access to information is that we often keep on collecting information long after we have enough to make a decision or write a report. How can we avoid this “analysis paralysis”? The best approach is to develop your hypothesis or argument early on, so that your search is focused on supporting or refuting that argument. If that doesn’t work, just give yourself a deadline. One rule I use when working with collaborators is to ensure I have something to send over to them by the end of the day: this helps me avoid getting into an open-ended search process.

Third, even though we live in an era of ubiquitous information, we should not be afraid to bring our intuition and emotion to the table. It is tempting to seek evidence to support every argument we make, but the most successful business leaders — from Jack Welch to Steve Jobs to Jeff Bezos — have always sought to combine rational and intuitive thinking. An ounce of real insight is worth a pound of data.

Further Reading




Getting Work Done (20-Minute Manager Series)



Leadership & Managing People Book


12.95



Add to Cart





Save
Share

Finally, when we have plentiful access to information, we also need to find time for reflection. Think of this as a low-tech version of meditation or mindfulness: it simply means creating breaks in the day, perhaps during a commute or while exercising, where you make sense of the stimuli you have been bombarded with, and where your ideas are allowed to gestate. When I am feeling distracted, a half-hour swim is the best way I know for clearing my mind and clarifying my next work priorities.

Now, consider your role as a manager. Remember, your team is as easily distracted as you are. Your team members are also highly sensitive to stimuli and cues that come from above. If you start talking about, say, an impending cost-cutting initiative, you are manipulating your team’s attention, whether you like it or not. Changes to job titles, to the layout of the office, to the agenda of the weekly meeting, to decisions about who gets promoted — all of these are attention “cues” that collectively shape people’s views of what is important, thereby shaping how they behave. (This idea was first developed by Tom Davenport and John Beck in The Attention Economy).

If you recast your role as the manager of your team’s attention, there are a couple of simple pieces of advice to follow. First, keep the message simple and clear. If you emphasize different things each week, people will become confused, and will learn to tune out. But if you come back to the same message time and time again, the effect on your team’s behavior is likely to be substantial. For example, most mining companies start every meeting with a “safety share” (a story about a recent safety-related incident) — it’s a simple, but effective way of keeping safety top-of-mind.

Second, be clear on what the default focus of attention is, so that you can be strategic about how to shift your team away from it. Here’s an example: a global software company was losing out on opportunities in Asia because every decision ended up prioritizing the needs of the European business (its historical home base). The CEO moved himself (temporarily) to Asia; global team meeting times alternated between morning in Europe and afternoon in Asia; the Chair of the meeting alternated between the two locations; the agenda always included region-specific as well as global concerns. By manipulating these relatively symbolic cues, rather than changing the entire reward system or reporting structure, there was a marked shift in behavior towards a greater focus on Asia but without a loss of attention to Europe.

Our key job as managers is to make efficient use of scarce resources. In the industrial era, the scarce resources were capital and labor. In the knowledge era, we have become accustomed to thinking of knowledge and information as the scarce resources we need to harness. But increasingly, information is ubiquitous and knowledge is shared widely across companies. In such a world, the scarce resource is our own and our employees attention. We need to become smarter about how we manage it.

[image error]