Articles of Interest

<div class="artwork-narrow"><div class="credit"></div> </div> <p>As business buzzwords go, “collaborate” and its derivatives are surely modern favorites. Applying for a job? Emphasize your collaboration skills. Courting customers? Promise a collaborative relationship. Wooing new hires or investors? Talk up your collaborative culture</p>

Any business works better when its employees, teams, divisions, and leaders share ideas and resources to pursue a common goal.

Four new books offer advice

You’ll find the most interesting case studies—of organizations getting collaboration right and of those felled by the lack of it—in <span class="mediatitle">The Silo Effect,</span> by Gillian Tett, an editor at the <span class="mediatitle">Financial Times</span>

Tett shows us how Sony missed the digital music revolution because its competing divisions couldn’t agree on products, platforms, or strategy;

how UBS, the venerable Swiss bank, lost billions through lack of coordination between its New York and London credit derivative desks and its three risk departments (credit, market, and operational), which left everyone clueless about the enterprisewide threat

nd how tribalism among the world’s leading economists blinded them to the causes of the most recent global financial crisis.

Tett explains how Facebook uses a hierarchy-free orientation program, frequent job rotations, and regular “hackathons” to encourage cooperation among project groups

how the Cleveland Clinic reorganized its medical staff into teams that focus on ailments rather than their own skills to improve patient outcomes

how data crunchers infiltrated bureaucratic police departments to reduce crime rates in New York and Chicago.

Many readers will have heard those stories before, but the detail is impressive. And the lessons Tett offers at the end of the book are spot on:

Keep organizational boundaries flexible and fluid

use technology to disrupt them

share data and let different interpretations of it be heard

reimagine corporate taxonomies and experiment with new ones

tie compensation to collaboration

These are high-level, top-down recommendations. But she also has a few tips for any manager eager to fight silos from the bottom up

Think like an anthropologist—with curiosity, healthy cynicism, and an appreciation for how things relate to one another so that you’re able to recognize when systems no longer make sense

In <span class="mediatitle">Friend &amp; Foe,</span> Wharton professors Adam Galinsky and Maurice Schweitzer (see <a href="/2015/09/the-organizational-apology">“The Organizational Apology,”</a> in the September 2015 issue) present reams of cool research showing why, although humans are inherently social animals, we’re also wired to vie with one another when resources are scarce and conditions are dynamic or uncertain.

The most pertinent lesson for would-be collaborators: Build trust by showing warmth and competence, appreciating others’ perspectives, and revealing vulnerability.

In <span class="mediatitle">Collaborative Intelligence,</span> consultants Dawna Markova and Angie McArthur drill down into personal skill building.

They encourage leaders to understand their own and others’ “mind patterns” (six in all, based on one’s preference for visual, auditory, or kinesthetic information processing) and “thinking talents” (35, ranging from “adapting” to “wanting to win”).

The authors then describe how to use inquiry and mindset shifts to ensure that everyone is contributing to a successful shared future.

Appreciate the value in intellectual diversity, and approach every work partnership wondering, “What can we make possible together?”

Longtime management writer and consultant Ken Blanchard also believes that <span class="mediatitle">Collaboration Begins with You.</span>

to shift his and others’ hearts (intent), heads (thought), and hands (action) toward collaboration.

must build on differences;

He comes to see that leaders

talk openly about collaboration

craft a clear purpose,<span class="diigoHighlightCommentLocator"></span> values, and goals

nurture safety and trust;

empower themselves and others to spread it

Companies don’t fail at collaboration because not enough people will cooperate with one another. They fail when people work too closely in certain teams, functions, or departments without any regard for the rest of the organization.

Coaching for collaborative thinking and behavior <em>might</em> help them break through those boundaries.

But policy changes—such as the incentives and restructuring put in place at the Cleveland Clinic or the nudging mechanisms seen in Facebook’s orientations, rotations, and use of its own social network to forge surprising connections—are much more effective.

As Galinsky and Schweitzer note, the more cohesive and successful teams become, the less likely they are to cooperate with other teams, even within their own companies.

So, yes, let’s encourage people to get better at collaboration, even train them in it. But let’s also design organizations that make it energizing and fun, not forced.

<p>In 1904, the great sociologist <a href="http://en.wikipedia.org/wiki/Max_Weber">Max Weber</a> visited the United States. &nbsp;As <a href="http://moisesnaim.com/">Moises Naim</a> describes in <a href="http://www.amazon.com/The-End-Power-Boardrooms-Battlefields/dp/0465031560"><em>The End of Power</em></a>, travelling around the vast country for three months, he believed that it represented “the last time in the long-lasting history of mankind that so favourable conditions for a free and grand development will exist.”</p> <p>Yet while Weber saw vast potential and boundless opportunities, he also noticed problems. &nbsp;The massive productive capacity that the industrial revolution had brought about was spinning out of control. &nbsp;Weber saw that traditional and charismatic leadership would have to give way to a more bureaucratic and rational model.</p>

1. If it can fit on an org chart, it’s not a network.

Before Weber’s bureaucracies became predominant, most enterprises were fairly organic. &nbsp;People shared the work, helped out where they could and all pitched in to get the job done. &nbsp;At the end of the day, they went home and then came back the next morning, ready to tackle a new job, which was often different than the day before.

Yet the increase in scale that the industrial revolution brought about resulted in a difference in the kind of work that was to done. &nbsp;Jobs would be broken down into small, specific tasks and be governed by a system of hierarchy, authority and responsibility. &nbsp;This required a more formal form of organization in which roles and responsibilities were clearly defined.

As business became more complex, these rigid structures grew increasingly untenable and so management theorists began to look for another way—<a href="http://en.wikipedia.org/wiki/Matrix_management">matrixed organizations</a>. &nbsp;In addition to the hard lines of responsibility and authority, dotted lines were used to denote cross-functional authorities and responsibilities.

Yet before long, it became clear that <a href="/1978/05/problems-of-matrix-organizations">matrixed organizations also had problems</a>. &nbsp;Despite the often mind-numbing complexity of matrixed organization charts, they still could not match the complexity of the marketplace. &nbsp;So matrices, in a sense, led to the worst of both worlds, a cumbersome organizational structure and the inability to adapt to fast changing contexts.

The truth is that networks are informal structures. &nbsp;If it can fit on a traditional org chart, it’s not a network.

2. Silos themselves aren’t the issue.

The term “network” is often misconstrued. &nbsp;In management circles, it is often used to mean an organic, unfathomable, amorphous structure, but really a network is just any system of nodes connected by links. &nbsp;So, in that sense, any organizational structure is a network, even a formal org chart.

<a href="http://en.wikipedia.org/wiki/Clustering_coefficient">clustering</a>

For functional purposes, networks have two salient characteristics:

Clustering refers to the degree to which a network is made up of tightly knit groups

path length

path lengths is a measure of distance—the average number of links separating any two nodes in the network.

We often hear about the need to “break down silos” to create a networked organization, but this too is a misnomer. &nbsp;Silos are functional groups and they need a high degree of clustering to work effectively and efficiently. &nbsp;The real problem in most organizations is that path lengths are too great and information travels too slowly, resulting in a failure to adapt.

The most efficient networks are <a href="http://www.digitaltonto.com/2010/the-story-of-networks/">small-world networks</a>, which have the almost magical combination of high clustering and short path lengths.

So silos aren’t the issue—high clustering promotes effective collaboration—the trick is to connect the silos together effectively.

3. Small-world networks form naturally, if they’re allowed to.

The idea that clusters of close-knit teams can somehow increase the flow of information on their own, simply through shorter social distances, seems unlikely. &nbsp;Yet actually, small-world networks often form naturally, without design or complex organizational engineering.

In fact, in their <a href="http://www.nature.com/nature/journal/v393/n6684/full/393440a0.html">initial paper</a> describing the phenomenon, <a href="http://en.wikipedia.org/wiki/Duncan_J._Watts">Duncan Watts</a> and <a href="http://www.stevenstrogatz.com/">Steven Strogatz</a> found the neural network of a roundworm, the power grid of the western United States, and the working relationships of film actors all followed the small-world network pattern. &nbsp;It takes effort to design a traditional organization, but small-world networks form naturally.

traditional organizations actively discourage connectivity. &nbsp;They favor strict operational alignment within specific functional areas while doing little to foster links between them.

4. Networked doesn’t mean flat.

The latest management craze is flat, <a href="http://www.digitaltonto.com/2012/the-leaderless-organization/">leaderless organizations</a>. &nbsp;Much has been made about <a href="/2015/05/making-sense-of-zappos-war-on-managers">Zappos’ recent efforts with holacracy</a>, but as Tim Kastelle recently <a href="http://timkastelle.org/blog/2015/05/zappos-just-pulled-off-the-boldest-change-management-move-ever/">explained</a>, the jury is still out whether the effort—and those like it—will be ultimately successful.

&nbsp;My own feeling is that flat structures will work for some cultures, but not others.

The important thing is that an organization does not have to be flat to be networked.

<p>In his new book, <a href="http://www.amazon.com/Team-Teams-Rules-Engagement-Complex/dp/1591847486/"><em>Team of Teams</em></a>, General <a href="http://mcchrystalgroup.com/our-team/">Stanley McChrystal</a> explains how he drastically reinvented how his forces operated, but didn’t changed the formal structure. &nbsp;The changes mainly had to do with informal structure, communication and forging a shared purpose.</p> <p>General McChrystal’s Special Forces command was still hierarchical and clustered into small operating groups. &nbsp;What changed is how they were interconnected. &nbsp;Rather than a collection of units, they became a <a href="http://www.digitaltonto.com/2014/the-synchronized-organization/">synchronized organization</a> that acted as one.</p>

So what really needs to change is not how we describe our organizations, but the <a href="http://www.digitaltonto.com/2014/the-new-role-of-leaders/">role of leaders</a> within them. &nbsp;Whereas before, it was the role of managers to direct work, in a connected age we need to instil <a href="http://www.digitaltonto.com/2010/the-passion-economy/">passion and purpose</a> around a <a href="http://www.digitaltonto.com/2014/how-your-mission-drives-your-strategy/">shared mission</a>. &nbsp;The networking, if encouraged and not inhibited, will take care of itself.

The author of this article has found that many organizations fall close to one of five natural “configurations,” each a combination of certain elements of structure and situation.

When managers and organizational designers try to mix and match the elements of different ones, they may emerge with a misfit that, like an ill-cut piece of clothing, won’t wear very well.

The key to organizational design, then, is consistency and coherence.

he's predicted that in 15 years' time, computers are going to trump people. That they will be smarter than we are. Not just better at doing sums than us and knowing what the best route is to Basildon. They already do that. But that they will be able to understand what we say, learn from experience, crack jokes, tell stories, flirt. Ray Kurzweil believes that, by 2029, computers will be able to do all the things that humans do. Only better.

Ray Kurzweil who believes that we can live for ever and that computers will gain what looks like a lot like consciousness in a little over a decade is now Google's director of engineering.

Google has bought almost every machine-learning and robotics company it can find, or at least, rates. It made headlines two months ago, when it bought <a href="http://www.theguardian.com/technology/2013/dec/29/google-robotics-us-military-boston-dynamics" title="" data-link-name="in body link" class=" u-underline" data-component="in-body-link">Boston Dynamics</a>, the firm that produces spectacular, terrifyingly life-like military robots, for an "undisclosed" but undoubtedly massive sum. It spent $3.2bn (£1.9bn) on smart thermostat maker <a href="http://www.theguardian.com/technology/2014/jan/13/google-nest-labs-3bn-bid-smart-home-devices-market" title="" data-link-name="in body link" class=" u-underline" data-component="in-body-link">Nest Labs</a>. And this month, it bought the secretive and cutting-edge British artificial intelligence startup DeepMind for £242m.

And those are just the big deals. It also bought <a href="http://www.botndolly.com/" title="" data-link-name="in body link" class=" u-underline" data-component="in-body-link">Bot &amp; Dolly</a>, <a href="http://www.theguardian.com/technology/2013/dec/04/google-robots-andy-rubin-amazon" title="" data-link-name="in body link" class=" u-underline" data-component="in-body-link">Meka Robotics</a>, Holomni, <a href="http://www.theguardian.com/technology/2014/feb/10/robots-artificialintelligenceai" title="" data-link-name="in body link" class=" u-underline" data-component="in-body-link">Redwood Robotics</a> and Schaft, and another AI startup, DNNresearch. It hired Geoff Hinton, a British computer scientist who's probably the world's leading expert on neural networks.

And it has embarked upon what one DeepMind investor told the technology publication <a href="http://recode.net/" title="" data-link-name="in body link" class=" u-underline" data-component="in-body-link"><em>Re/code</em></a> two weeks ago was "a Manhattan project of AI". If artificial intelligence was really possible, and if anybody could do it, he said, "this will be the team". The future, in ways we can't even begin to imagine, will be Google's.

He's been making predictions about the future for years, ever since he realised that one of the key things about inventing successful new products was inventing them at the right moment, and "so, as an engineer, I collected a lot of data".

In 1990, he predicted that a computer would defeat a world chess champion by 1998. In <a href="http://en.wikipedia.org/wiki/Deep_Blue_versus_Garry_Kasparov" title="" data-link-name="in body link" class=" u-underline" data-component="in-body-link">1997, IBM's Deep Blue defeated Garry Kasparov</a>.

He predicted the explosion of the world wide web at a time it was only being used by a few academics and he predicted dozens and dozens of other things that have largely come true, or that will soon, such as that by the year 2000, robotic leg prostheses would allow paraplegics to walk (the US military is currently trialling an "<em>Iron Man</em>" suit) and "cybernetic chauffeurs" would be able to drive cars (which Google has more or less cracked).

His critics point out that not all his predictions have exactly panned out (no US company has reached a market capitalisation of more than $1&nbsp;trillion; "bioengineered treatments" have yet to cure cancer).

They're based on his belief that technology progresses exponentially (as is also the case in Moore's law, which sees computers' performance doubling every two years). But then you just have to dig out an old mobile phone to understand that. The problem, he says, is that humans don't think about the future that way. "Our intuition is linear."

"My book <a href="http://www.amazon.co.uk/The-Age-Spiritual-Machines-Kurzweil/dp/0140282025" title="" data-link-name="in body link" class=" u-underline" data-component="in-body-link"><em>The Age of Spiritual Machines</em></a> came out in 1999 and that we had a conference of AI experts at Stanford and we took a poll by hand about when you think the Turing test would be passed. The consensus was hundreds of years. And a pretty good contingent thought that it would never be done.

But then he predicts that by 2045 computers will be a billion times more powerful than all of the human brains on Earth. And the characters' creation of an avatar of a dead person based on their writings, in Jonze's film, is an idea that he's been banging on about for years. He's gathered all of his father's writings and ephemera in an archive and believes it will be possible to retro-engineer him at some point in the future.

And it's the Google-scale resources that are beyond anything the world has seen before. Such as the huge data sets that result from 1 billion people using Google ever single day. And the Google knowledge graph, which consists of 800m concepts and the billions of relationships between them. This is already a neural network, a massive, distributed global "brain". Can it learn? Can it think? It's what some of the smartest people on the planet are working on next.

Peter Norvig, Google's research director, said recently that the company employs "less than 50% but certainly more than 5%" of the world's leading experts on machine learning.

And that was before it bought DeepMind which, it should be noted, agreed to the deal with the proviso that Google set up an ethics board to look at the question of what machine learning will actually mean when it's in the hands of what has become the most powerful company on the planet.

I first saw Boston Dynamics' robots in action at a presentation at the <a href="http://www.theguardian.com/technology/2012/apr/29/singularity-university-technology-future-thinkers" title="" data-link-name="in body link" class=" u-underline" data-component="in-body-link">Singularity University</a>, the university that Ray Kurzweil co-founded and that Google helped fund and which is devoted to exploring exponential technologies.

"I don't see any end point here," he said when talking about the use of military robots. "At some point humans aren't going to be fast enough. So what you do is that you make them autonomous. And where does that end? <a href="http://www.theguardian.com/film/movie/88018/terminator" title="" data-link-name="in body link" class=" u-underline" data-component="in-body-link"><em>Terminator</em></a>?"

Language, he believes, is the key to everything. "And my project is ultimately to base search on really understanding what the language means. When you write an article you're not creating an interesting collection of words. You have something to say and Google is devoted to intelligently organising and processing the world's information. The message in your article is information, and the computers are not picking up on that. So we would like to actually have the computers read. We want them to read everything on the web and every page of every book, then be able to engage an intelligent dialogue with the user to be able to answer their questions."

Google will know the answer to your question before you have asked it, he says. It will have read every email you've ever written, every document, every idle thought you've ever tapped into a search-engine box. It will know you better than your intimate partner does. Better, perhaps, than even yourself.

"Computers are on the threshold of reading and understanding the semantic content of a language, but not quite at human levels. But since they can read a million times more material than humans they can make up for that with quantity. So IBM's Watson is a pretty weak reader on each page, but it read the 200m pages of Wikipedia. And basically what I'm doing at Google is to try to go beyond what Watson could do. To do it at Google scale. Which is to say to have the computer read tens of billions of pages. Watson doesn't understand the implications of what it's reading. It's doing a sort of pattern matching. It doesn't understand that if John sold his red Volvo to Mary that involves a transaction or possession and ownership being transferred. It doesn't understand that kind of information and so we are going to actually encode that, really try to teach it to understand the meaning of what these documents are&nbsp;saying."

His relatives escaped the Holocaust "because they used their minds. That's actually the philosophy of my family. The power of human ideas. I remember my grandfather coming back from his first return visit to Europe. I was seven and he told me he'd been given the opportunity to handle – with his own hands – original documents by Leonardo da Vinci. He talked about it in very reverential terms, like these were sacred documents. But they weren't handed down to us by God. They were created by a guy, a person. A single human had been very influential and had changed the world. The message was that human ideas changed the world. And that is the only thing that could change the world."

"Most of whom are accepting the normal cycle of life and accepting they are getting to the end of their productive years. That's not my view. Now that health and medicine is in information technology it is going to expand exponentially. We will see very dramatic changes ahead. According to my model it's only 10-15 years away from where we'll be adding more than a year every year to life expectancy because of progress. It's kind of a tipping point in longevity."

<em>Newsweek</em>, a few years back, <a href="http://www.newsweek.com/ray-kurzweil-wants-be-robot-80265" title="" data-link-name="in body link" class=" u-underline" data-component="in-body-link">quoted an anonymous colleague</a> claiming that, "Ray is going through the single most public midlife crisis that any male has ever gone through."

Although possibly this is what Kurzweil's critics, such as the biologist <a href="http://scienceblogs.com/pharyngula/?s=kurzweil" title="" data-link-name="in body link" class=" u-underline" data-component="in-body-link">PZ Myers</a>, mean when they say that the problem with Kurzweil's theories is that "it's a very bizarre mixture of ideas that are solid and good with ideas that are crazy. It's as if you took a lot of very good food and some dog excrement and blended it all up so that you can't possibly figure out what's good or bad."

Or <a href="http://www.theguardian.com/technology/2013/mar/17/jaron-lanier-digital-pioneer-rebel" title="" data-link-name="in body link" class=" u-underline" data-component="in-body-link">Jaron Lanier</a>, who calls him "a genius" but "a product of a narcissistic age".