Why Big Teams Suck

In 1957, British naval historian and management satirist Northcote Parkinson painted a cynical picture of a typical committee: It starts with four or five members, quickly grows to nine or ten, and, once it balloons to 20 and beyond, meetings become an utter waste of time – and all the important work is done before and after meetings by four or five most influential members.

As Parkinson would have it, numerous studies now confirm that, when it comes to teams, many hands do not make light work. After devoting nearly 50 years to studying team performance, the late Harvard researcher J. Richard Hackman concluded that four to six members is the team best size for most tasks, that no work team should have more than 10 members, and that performance problems and interpersonal friction increase “exponentially as team size increases.”

These troubles arise because larger teams place often overwhelming “cognitive load” on individual members. Most of us are able to mesh your efforts with and maintain good personal relationships with, say, three or four teammates. But as a group expands further, each member devotes more time to coordination chores (and less time to actually doing the work), more hand-offs between the growing cast of members are required (creating opportunities for miscommunication and mistakes), and because each member must divide his or her attention among a longer list of colleagues, the team’s social glue weakens (and destructive conflict soars). Following my earlier LinkedIn piece, findings about group size are reminiscent of psychologist George Miller’s famous conclusion that seven was a “magical number” because people could only hold “seven, plus or minus two” numbers in short-term memory. Both Hackman and Miller found that, once people start trying to deal with double digits, the cognitive overload takes a toll.

These findings help explain why the average restaurant reservation in the United States is for a party of four. Think of the last time you were at a dinner with a group of 10 or 15 people. It is difficult, perhaps downright impossible, to have a coherent and emotionally satisfying conversation that engages each member of the party all at once. Typically, the group breaks into a series of smaller conversations or a few people do all the talking and the others say little or nothing.

Some organizations learn about the drawbacks of oversized groups the hard way. Retired Marine Captain and former U.S. Senator James H. Webb explained why the “fire team” – the basic combat fighting unit – shrunk from 12 to 4 during War II. Webb wrote in the Marine Corp Gazette that this “12 man mob” was “immensely difficult” for Marine squad leaders to control under the stress and confusion of battle. Coordination problems were rampant and close relationships – where soldiers fight for their buddies – were tougher to maintain in 12-man teams. The U.S, Navy Seals have learned that four is the optimal size for a combat team as well. And, the basic work unit at McKinsey, the consulting firm, is one “engagement manager” and three other members. As Intuit’s CEO Brad Smith puts it, when it comes to teams, “less is often best.” Just like on­line retailing giant Amazon, Intuit insists: “Our development teams can be no larger than the number of people who can be fed by two pizzas,” which helps them “stay nimble and make decisions quickly.”

This lesson applies to small organizations too. Pulse News, makers of a “news aggrega­tor” app, was started in mid-2010. Communication breakdowns and misunderstandings flared-up after it grew slightly, from three to eight people. Founders Akshay Kothari and Ankit Gupta told us that, after they divided those eight among three teams, people produced better software, did it faster, and argued less. When Pulse expanded to about 12 people (working in four teams, all in the same room), each team maintained a bulletin board that captured their current work to help everyone at Pulse follow what they were doing. Every afternoon at about 3:30, each team also gave a short talk to the company about what they working on and where they needed help. Pulse relied on small teams as it grew to 25 employees and 30 million users; it is now part of LinkedIn, which bought Pulse for 90 million dollars in April, 2013.

The lesson is that, if you are on a big team that keeps screwing up, where members don’t care much about each other, and are fighting like crazy, try some subtraction or division. A Harvard Business School study by Melissa Valentine and Amy Edmondson of a large hospital’s emergency department demonstrates how powerful such moves can be. The crowd of 30 or so doctors and nurses who staffed the department at any given time were divided into multiple six person “pods,” each led by a senior doctor or “attending physician.” After the change, information about patients flowed more quickly and accurately and personal relationships improved markedly. Smaller teams reduced confusion and discomfort about who to ask for help and updates.

One nurse said, before the pods, “You had to walk across the ED all timid” and get up bit of courage and say to the doctor “Uh, excuse me?” With the pods, “Now they are in the trenches with us.” It was also easier to discern which “podmates” were responsible for particular chores and deserved credit or blame when things went well or badly.
Another nurse added:

“Now there is much more of a sense of ownership of each other. I’ll say, “My pod isn’t running well. Where is my doctor?” And he’ll be accountable to me. And the doctors will say, “Where are my nurses, who do I have today?’” People rarely, if ever, claimed each other in this way before the pods were implemented even if they were working together on many shared cases. A resident would have used more detached language like, “Who is this patient’s nurse?” – ignoring that the nurse had any relationship to him – rather than, “Where are my nurses?”

The pods also created big efficiency gains. Valentine and Edmondson analyzed data on 160,000 patients served by the Department during the six months before the pods were created and the year after. After the pods, patient throughput time plummeted by about 40%, from about eight hours (8.34) to five hours (5.29) per patient –without increased staffing levels. This drop not only reflects more efficient use of staff; think of the patients’ experience: Five hours at the hospital sucks a lot less than eight.

The upshot? As my co-author Huggy Rao and I found in our research, scaling is a problem of both more and less. Many hands do not always make for light work, especially when it comes to team size. The first question I ask when a team reports they are locked in dysfunctional conflict, suffering from indifference, making bad decisions, or missing deadlines -- or all of the above -- is “how big is it?” If the answer is more than then five or six members, especially more than than ten, some savvy subtraction or division can create striking improvements. As Valentine and Edmondson's research shows: Leaders become more effective. Efficiency improves. Interpersonal friction wanes. And strangers become friends.

Robert Sutton is a Stanford Professor and co-author (with Huggy Rao) of Scaling Up Excellence: Getting to More without Settling for Less. This piece is an edited excerpt from that book. 
Posted by:Bob Sutton

Leadership Lessons from Tug-of-War

 

“What am I creating?” is a critical leadership question you must ask yourself every day. Personally, it aligns your choices and actions. Organizationally, it orients your team’s choices—it creates alignment. The reason for organizations is to harness the collective power of the group.

WE can accomplish more than I, and our collective efforts are most impressive when they surge forward in unison. Alignment produces a multiplier effect that demonstrates that the whole IS greater than the sum of the parts. Teamwork, however, can also be challenging and frustrating as we subjugate our needs and impulses and emphasize consideration of others and emotional intelligence. On the downside, teamwork can rob us of our spontaneous expression and blur our coveted individuality. On the upside, teamwork can provide a platform from which we can accomplish meaningful and breathtaking achievements.

Teams generate power when everyone is focused on the same horizon.

When each member answers, “What am I creating?” in the same way, amplification occurs. By collectively focusing on the same objective, they harness the power of alignment.

Tug-of-war is a practical example of the power of alignment. I grew up playing this game a lot. The game cost nothing, was easy to set up, and was intensely competitive. With a heeled shoe we’d scratch a line in the dirt, then we’d split our group in two. Each group took hold of opposing ends of a strong rope, and on command we’d begin to pull. I remember the effort that we expended as we pulled the rope in order to draw the opposing team toward us and over the midway line. The biggest and heaviest team member was typically the “anchor” planted at the end of the rope. As the resident “big boy” I spent my tug-of-war career as the anchor. From here I had a clear view of my team as well as the opposing team. What I learned watching both teams is that the size, weight, and strength of the team were not the most important predictors of who would win the game.

By collectively focusing on the same objective, they harness the power of alignment.

Alignment was the winning factor. Teams whose members pulled together at the same achieved cumulative force. When our backs, feet, and waists were lined up and pointing in the same direction, we became unified. The combined force of an aligned team magnified our individual contributions exponentially. I remember many sunny days anchored at the end of the line, and hoping the opposing team would look disjointed, that their guys would be out of sync, pulling the rope at different angles. When even one person pulled at a different angle, the entire team lost their cumulative force and, rather than win, they struggled.

Organizations, too, are pulling against competition in an ongoing contest for market share, resources, and talent. This constant tension is a tug-of-war with consumers and competitors. Each organizational function is a hand on the collective rope. Aligning the functions is not a mere philosophical abstraction; it is a dictate of mechanics and physics. Team members pull the rope at the operational level. When R&D, for example, pulls the rope North and production pulls the rope West, the organization falters.

Leaders are engaged in a constant tug-of-war, with not just one, but multiple ropes being pulled by multiple teams in multiple directions. As so many factors push and pull leaders’ attention and energy, it is focus—”What am I creating?”—that shapes the most effective decisions. Clarity of choice and decisions arise when you can definitively answer, “What am I creating?” as a person, as a leader, and as a team. This focus is your vision and your commitment to the future, and it illuminates a path of decisions, relationships, and behaviors that pave your unique path to success.

Image credit- berkut2011 / 123RF Stock Photo

Eric Kaufmann (1 Posts)Eric Kaufmann brings a unique mix of professional and personal experience to his work of developing executive wisdom and guiding leaders to better decisions and achievement of superior results. Kaufmann, who was born in Israel and lived and worked in South Africa for three years, has two decades of experience in sales and management at Lanier/3M and Corning Clinical Laboratories. In 1999, he began a new chapter of his professional life, launching a consulting business in which he works with individuals and teams in senior management of Fortune 1,000 companies, primarily in the life science and technology sectors. Along with his real-world business experience, Kaufmann brings a range of other skills and perspectives to his roles as executive coach, keynote speaker and management consultant. Kaufmann’s first book, “Leadership as a Hero’s Journey,” explores the four traits shared by successful, passionate and creative business leaders. The book describes how they navigate through uncertainty and anxiety in order to improve the lives and livelihoods of those around them, and is due out in early 2013. When working with CEOs and senior managers, Kaufmann assists them in clarifying their corporate goals and vision; assessing the strengths and weaknesses of their management team; and identifying and eliminating obstacles to collaboration, trust, and productivity. Ultimately, his contribution leads to better decision-making and greater team engagement, resulting in faster and stronger market penetration, improved profitability and employee retention.

5 Principles of Convergence: How To Work Better At The Intersection Of Tech, Creativity, And Media

Convergence is both buzzword and marketing reality. Razorfish CEO Bob Lord outlines 5 ways creative companies can adapt to a converging world and create better brand experiences. 

The word convergence has been picking up steam in the marketing world. It may even be the “big data” term of 2013. Yet, the word means different things to different people. At Razorfish, we use convergence to describe the coming together of three irresistible forces--media, technology, and creativity--to create experiences that enrich the consumer’s relationship with the brand.

Convergence is a constant process, not an end point. Technology, creativity, and media are constantly evolving, and so is the converged company. It is a never-ending challenge to adapt a customer experience that, in our digital age, will always be in flux. Too often, businesses are far behind consumers in embracing technological change, a problem that has everything to do with how the organization is set up. My new book, coauthored with Razorfish Global CTO Ray Velez, Converge: Transforming Business at the Intersection of Marketing and Technology, describes in detail how enterprises and teams must adapt for an age of disruption.

Here are five key principles: 

Put the Customer at the Center.

Being ready for convergence isn’t about building an innovations lab, spending marketing budget on Facebook and Twitter ads or about hiring a social media “guru” to respond to online complaints. It’s about embracing a customer-centric mind-set and making your entire organization responsive to the customer journey. This isn’t as easy as it sounds, especially for larger, well-established companies where scale has mandated the creation of a complicated organizational chart.

Strategies need to be based on data from actual consumer activity, not abstract gut feeling. That data should dictate not only what experiences you serve consumers but where, when, and how. Brand communications must engage the consumer in social platforms and ecosystems and open APIs. And the retail experience must be made omni-channel, giving shoppers the same experience whether they’re in-store, online, or on the phone. 

Think of Your Brand as a Service and Experience.
You’re no longer in the business of selling stuff; you’re filling consumers’ needs. As a marketer, you’re creating new products and apps and always-on ecosystems, not just a series of campaigns based around a calendar of product launches. Nike is the classic example, with its ecosystem of fitness apparel, gadgets like FuelBand and services like Nike+ that immerse the user in the company’s innovation and create an end-to-end fitness solution. Special K, one of our clients, is still in the cereal game and it sells a ton of it. But it’s also in the health, fitness, and weight-loss games. It took its Special K challenge and turned it into a digital weight-loss platform.

To create and maintain this ecosystem, you’ll be investing in marketing operations, not just working media, and bringing in more designers and developers. In the past, marketing ops were largely limited to the maintenance of an internal marketing team and hiring and firing agencies that produced the creative work. People were accountable for spending the dollars, not how effectively they were spent. In a converged world, it will be about those activities, and also about investing in people and systems to ensure that the marketing spending is optimized. 

Reject Silos.
Media, technology, and creativity are no longer discrete problems. Let’s take the most fundamental example of this: the creation of an ad. A few years back, a new ad campaign was simply a creative challenge that was solved by coming up with a new flight of TV spots. These days, a new ad will likely involve some technological and media challenges. Are you tapping into the API of a hot new social media platform? How are you getting your brilliant campaign in front of a demographic that’s no longer watching TV?

The traditional, silo-based organization is ill-equipped to answer these questions. So what you need to achieve is better collaboration between marketing and IT. To get there, your C-suite might have senior roles like chief digital officer and chief marketing technologists, filled by experts in both functions catalyzing innovation throughout the organization and fostering collaboration. Or you might try bottom-up solutions like internal account management. In this structure, marketing folks have counterparts in IT and vice versa. 

Act Like a Startup.
There’s a set of common misconceptions about how established enterprises should learn from startups. It’s not about moving into flashy new digs or setting up Ping-Pong tables or having free sushi for lunch.

Like customer-centricity, the startup mentality requires much deeper and more meaningful change. It requires uprooting many old assumptions and habits, especially those around tech infrastructure, and doing things the way a newer, leaner company might.

Acting like a startup in this sense means the following:

--Your enterprise deploys--or at least experiments with--cheap, fast, and flexible tools like cloud computing, social media platforms, and open APIs.

--You employ product managers who are accountable for particular aspects of the consumer experience, just like Facebook has tasked someone with oversight of the newsfeed. As one of our clients describes it, product managers have to understand the customer and constantly prioritize and re-prioritize what’s best for the customer.

--You employ Agile methodology and rapid prototyping.
And look, no Ping-Pong.

Embrace Diversity
Every organization needs specialists and experts, but in the place of environments where everyone fills one role and thinks about nothing besides that role, there needs to be cross-fertilization, a coming together of various fields, disciplines, personalities, and cultures.

In practice, it’s important to get a wide variety of expertise and perspectives around the table—marketing and technology, of course, but also HR, legal, and finance. We call this building a big boat, and it’s vital to building a convergence-ready organization.

But there’s more to it than just getting all the right people around the table. You also have to incentivize collaboration, getting multiple functions to rally around a shared set of objectives and a shared method of measuring process--that’s a big change and it has to be tracked cleanly and carefully. This entails getting your systems to feed a dashboard that tracks a manageable set of metrics. Then you have to get the team to check in regularly, or at least pay attention to the readouts they’re receiving.

Adapting your organization for convergence is never over. It’s a constant cycle of testing, learning, building, and destroying. All the more reason you should start now. The winners of this era will be the companies whose main focus is constantly improving on the customer journey. If you follow your customer, you can’t go wrong.

By:  Bob Lord, Global CEO of Razorfish.

How Technology Is Changing The Way Organizations Learn

 (Photo credit: Wikipedia)

People used to be valued for knowing a trade. Then came the industrial revolution and those skills became devalued.  Machines took over physical labor and most people either did simple, repetitive tasks or managed those who did.

By the late 20th century, a knowledge economy began to take hold.  Workers became valued not for their labor, but for specialized knowledge, much of which was inscrutable to their superiors.

 Successful enterprises became learning organizations.

Now, we are entering a new industrial revolution and machines are starting to take over cognitive tasks as well.  Therefore, much like in the first industrial revolution, the role of humans is again being rapidly redefined.  Organizations will have to change the way that they learn and managers’ primary task will be to design the curricula. 

First Principles vs. Experience
Knowledge, strangely enough, has been a source of fierce debate for over two thousand years, beginning with a disagreement between Plato and his most famous student, Aristotle.

Plato believed in ideal forms.  To him, true knowledge consisted of familiarity with those forms and virtue (which, in a modern terms would have been closer to ability than to morality) was a matter of actualizing those forms in everyday life.  Plato would have felt comfortable as a factory manager whose workers carried out instructions to the tee.

Aristotle, on the other hand, believed in empirical knowledge, which you gain from experience.  In contrast to Plato, we can imagine Aristotle as a Six Sigma black belt, constantly analyzing data in order to come up with a better way of doing things.

Both methods, the indoctrination of principles and the collection of data have played a role in learning organizations.  The difference now is that much of the learning is being taken over by machines.

How Machines Are Learning To Take Over
Not so long ago, we depended on human knowledge for many things, such as setting up travel itineraries, trading financial instruments and buying media that are highly automated today.  As we progress, new areas, such as making medical diagnoses, legal discovery and even creative output are becoming mediated by computers.

Perhaps not surprisingly, the algorithms blend Platonic and Aristotelian approaches just like humans do.  Initially, their thinking is driven by time honored principles supplied by human experts (sometimes called “God parameters”).  Then, as more information comes in, the computer begins to learn from its own mistakes, getting better and better at its task.

This process continues at accelerating speeds.  Much like the rise of the knowledge economy empowered knowledge workers, because they had expertise that their bosses didn’t, computers are now coming up with answers that knowledge workers themselves can’t understand.  That will prove incredibly disruptive in the years to come.

It also presents a particularly thorny problem: How can organizations empower employees whose skills are being outsourced to the cloud? 

Consequences of An Algorithmic Age
Just as the first industrial revolution transformed business and society, this new algorithmic age will bring not just efficiency, but significant, cultural changes.  While the future is unclear, some of the shifts are already becoming apparent:

Bayesian Strategy:  The knowledge economy coincided with the rising influence of business strategists.  Highly trained executives would analyze business conditions and devise intricate plans for the future.  Managerial performance, therefore, was widely evaluated as a function of their ability to “execute the plan.”

However, good strategy is becoming less visionary and more Bayesian. Strategic plans will play a similar role to “God parameters” that will be honed through an evolutionary process of simulation and feedback.  Strategists, to a great extent, will become hackers rather than planners.

Brands as Open API’s:  One little noted consequence of the knowledge economy is the rise of intangible value, which often far exceeds tangible assets in corporations.  Brands, therefore, became tightly controlled assets that were nurtured and protected.

That’s beginning to change as brands are becoming platforms for collaboration rather than assets to be leveraged.  Marketers who used to jealously guard their brands are now aggressively courting outside developers with Application Programming Interfaces (API’s) and Software Development Kits (SDK’s).  Our economy is increasingly becoming a semantic economy.

Firms ranging from Microsoft to Nike to The New York Times have also created accelerator programs, where young companies get financial, managerial and technical support to come up with new innovations (and potentially, enhance the business of their benefactors).

The Human Touch:  While much of the discussion about the rising tide of technology focuses on cognitive skills, Richard Florida argues that social skills will be just as important.  Many of the fastest growing professions are those which emphasize personal contact.

As computers take over more of the work, the role of humans will increasingly focus on caring for other humans.

Flying By Wire
Pilots don’t fly planes anymore, not really.  Whereas they used to have direct control over the aircraft, now they fly by wire.  Today, their instruments connect not to the airplane’s mechanism, but to computers which carry out their commands, modulated by the collective intelligence gained from millions of similar flights.

In essense, pilots perform three roles: they direct intent (where to go, how fast, when to change course), manage knowledge and (rarely) take over during emergencies.  Professionals in other industries will have to learn to perform their jobs in a similar way.

The function of organizations in the industrial age was to direct work.  The function of organizations in the algorithmic age will be to focus passion and purpose.

Managers, rather than focusing on building skills to recognize patterns and take action, will need to focus on designing the curricula, to direct which patterns computers should focus on learning and to what ends their actions should serve.

 

  The Education Of An Algorithm Greg Satell Contributor