Category Archives: Web 2.0

Creating collaboration

group by Arenamontanus

How John Chambers Learned to Collaborate at Cisco
[Via HarvardBusiness.org]

In 2001, as the dot.com boom turned to bust, CEO John Chambers of Cisco saw a massive $460 billion of Cisco’s overall stock market value evaporate before his eyes. Game over? Not really. At that moment, Chambers started a reinvention of the company — from a “cowboy” mentality where people worked in silos to a collaborative approach. It has paid off so far. Revenues are up 90% since 2002, while profit margins are up to 20.8% from 16.3%. And Chambers earned the #4 spot on our best-performing CEO ranking, published last month by Harvard Business Review. Not bad.

Chambers created the following 5 pillars to drive collaboration, an approach we can all learn from. These amount to what I call disciplined collaboration in my book Collaboration: focus on business value, tear down barriers, and create a new organization architecture. (Full disclosure: last autumn I met with the top 50 leadership team at Cisco to discuss collaboration; the information here is all from public sources, however).

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The five pillars are these:

1. Change leadership style.

2. Change incentives.

3. Change the structure.

4. Change how you work.

5. Use new social media tools.

These are all hallmarks of systems thinking. No more top-down thinking. Make people want to collaborate. The structure needs to map human social networks. Bring multiple points of view to examine the problem.

But it also uses things like constraints and goals to keep on track. It uses diffused leadership rather than central but makes sure there are ways to give the successful groups their rewards.

It also includes selecting for people who want this sort of structure. Luckily, the ones who thrive here are exactly the types who will produce success.

Read about the development of the Mac to get an idea of what these people are like. And also see what happened when a typical hierarchical manager was put in charge. Order and proper respect for authority was more important than success.

Apple made a mistake by putting these people into a silo type of management structure after the Mac came out. Many of the developers of the Mac were gone in less than 18 months, including the founder of the company, Steve Jobs.

The structure that Cisco built for collaboration can produce wonderful things. But its requirements need to be understood and supported by management in order to succeed.

Disruption rather than deviancy

path by notsogoodphotography

Why every team needs a deviant.
[Via Creativity Central]

Most of us in the creativity brainstorming world are professional deviants.

We don’t typically use the term deviant, preferring the less harsh term gadfly. Or in a politically correct world, idea catalyst.

But deviant is good enough for J. Richard Hackman, the Edgar Pierce Professor of Social and Organizational Psychology at Harvard University and leading expert on teams. Hackman has spent his career exploring and questioning — the wisdom of teams.

In a recent interview with Diane Coutu called “Why Teams Don’t Work” he talks about why every team needs a deviant.

Coutu: “If teams need to stay together to achieve the best performance, how do you prevent them from becoming complacent?”

Hackman: “This is where what I call the deviant comes in. Every team needs a deviant, someone who can help the team by challenging the tendency to want too much homogeneity, which can stifle creativity and learning.

Deviants are the ones who stand back and say, “Well wait a minute, why are we even doing this at all?” What if we looked at the thing backwards or turned it inside out?” That’s when people say, “Oh, no, no, no, that’s ridiculous” and so the discussion about what’s ridiculous comes up…the deviant opens up more ideas and that gives you a lot more originality.

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I view these types more as disruptors than deviants. They look at things differently, bring in novel ideas from outside the group and generally disrupt the ‘easy flow’ of a strong team. They look to stretch or beak some of the constraints that we use, in order to make sure we really need them.They are often disliked by the rest of the group and will simply shut up if not provided even a little support.

And that is what most teams do, shut them up. Shunning is usually the main approach. The disruptors then quickly understand and stop disrupting. The inability to support any disruption, often because it may seem almost insubordinate, leads to the failure of many teams.

But, even a little support will go a long way. Some useful facilitation of disruptors, allowing their ideas to be brought out and examined, can have a huge effect on the general creativity of the group. Good managers need to realize this because, as has been shown in many studies, the people that act as useful filters for this sort of disruptive information, the ones that help the community adopt these disruptive ideas, are often the ones that are viewed as thought leaders in the organization and on the track to greater things.

Unfortunately, at the moment, few organizations properly recognize the disruptor. Maybe that will change.



The difference between the creative and the commonplace

tufte by BruceTurner

Edward Tufte Presidential Appointment
[Via Daring Fireball]

President Obama has appointed Edward Tufte to the Recovery Independent Advisory Panel, “whose job is to track and explain $787 billion in recovery stimulus funds”. Outstanding.

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This is pretty cool. Tufte is one of my favorite people, not only for his highly original books on data presentation but also for his sheer force of personality. He is one of the most entertaining, enlightening speakers I have ever heard.

I attended one of his workshops in Seattle probably close to 20 years ago. There was an interchange that has stuck with me ever since, because it so succinctly illustrates the divide between truly original, innovative change and the typical corporate response.

Tufte was discussing the different interfaces between the Mac OS and Windows. After going through a lot of the pluses he saw in the Mac and a lot of the minuses in Windows, he stated that the Mac looked like it had been created by one or a small group of people with a single purpose, a single view of how the information should be presented, while Windows looked like it had been done by a committee.

He then said that all the best presentations were this way – a single point of view forcefully pushed onto everyone. Someone in the audience then asked but what happens if your single point of view turns out to be wrong, to not work.

Tufte replied, simply, “You should be fired.” You could almost audibly hear the intake of everyone’s breath. That is exactly what they feared and why they would always want to retreat into committee decisions – they can’t be fired if the committee made the decision. FUD is what drives most people.

The creative, the innovative do not really fear failure, often because they are adaptable enough to ‘route around the damage’ quickly enough. They do not usually doubt the mission they are on and are certainly not uncertain about the effects. Read about the development of the Mac. They were going to change the world, no doubt about it. While you can see that there really was a focus of vision, there are also lots of ‘failures’ that had to be fixed. The key was to fail quickly, leaving time to find success.

And permitting committed individuals to find their own way to success rather than rely on committees to fix them.

Committees very seldom fail quickly, since failure is the thing they fear the most. They would rather succeed carefully than perhaps fail spectacularly. And they very seldom produce revolutionary change.

Single viewpoint, change the world, rapidly overcome obstacles, adaptable. All characteristics of successful change. They do not fear spectacular failure because the fruits of success will be so sweet.


Getting at data

Four Ways of Looking at Twitter
[Via HarvardBusiness.org]

Data visualization is cool. It’s also becoming ever more useful, as the vibrant online community of data visualizers (programmers, designers, artists, and statisticians — sometimes all in one person) grows and the tools to execute their visions improve.

Jeff Clark is part of this community. He, like many data visualization enthusiasts, fell into it after being inspired by pioneer Martin Wattenberg‘s landmark treemap that visualized the stock market.

Clark’s latest work shows much promise. He’s built four engines that visualize that giant pile of data known as Twitter. All four basically search words used in tweets, then look for relationships to other words or to other Tweeters. They function in almost real time.

“Twitter is an obvious data source for lots of text information,” says Clark. “It’s actually proven to be a great playground for testing out data visualization ideas.” Clark readily admits not all the visualizations are the product of his design genius. It’s his programming skills that allow him to build engines that drive the visualizations. “I spend a fair amount of time looking at what’s out there. I’ll take what someone did visually and use a different data source. Twitter Spectrum was based on things people search for on Google. Chris Harrison did interesting work that looks really great and I thought, I can do something like that that’s based on live data. So I brought it to Twitter.”

His tools are definitely early stages, but even now, it’s easy to imagine where they could be taken.

Take TwitterVenn. You enter three search terms and the app returns a venn diagram showing frequency of use of each term and frequency of overlap of the terms in a single tweet. As a bonus, it shows a small word map of the most common terms related to each search term; tweets per day for each term by itself and each combination of terms; and a recent tweet. I entered “apple, google, microsoft.” Here’s what a got:

twittervenn.jpg

Right away I see Apple tweets are dominating, not surprisingly. But notice the high frequency of unexpected words like “win” “free” and “capacitive” used with the term “apple.” That suggests marketing (spam?) of apple products via Twitter, i.e. “Win a free iPad…”.

I was shocked at the relative infrequency of “google” tweets. In fact there were on average more tweets that included both “microsoft” and “google” than ones that just mentioned “google.”

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Social media sites provide a way to not only map human networks but also to get a good idea of what the conversations are about. Here we can see not only how many tweets are discussing apple, microsoft and goggle but the combinations of each.

Now, the really interesting question is how ti really get at the data, how to examine it in order to discover really amazing things. This post examines ways to visually present the data.

Visuals – those will be some of the key revolutionary approaches that allow us to take complex data and put it into terms we can understand. These are some nice begining points.

An interesting juxtaposition

data by blprnt_van

Reaching Agreement On The Public Domain For Science
[Via Common Knowledge]

Photo outside the Panton Arms pub in Cambridge, UK, licensed to the public under Creative Commons Attribution-ShareAlike by jwyg (Jonathan Gray).

Today marked the public announcement of a set of principles on how to treat data, from a legal context, in the sciences. Called the Panton Principles, they were negotiated over the summer between myself, Rufus Pollock, Cameron Neylon, and Peter Murray-Rust. If you’re too busy to read them directly, here’s the gist: publicly funded science data should be in the public domain, full stop.

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and this

BBC News – Science damaged by climate row says NAS chief Cicerone
[Via BBC News | Science/Nature]

Leading scientists say that the recent controversies surrounding climate research have damaged the image of science as a whole.

President of the US National Academy of Sciences, Ralph Cicerone, said scandals including the “climategate” e-mail row had eroded public trust in scientists.

[snip]

He said that this crisis of public confidence should be a wake-up call for researchers, and that the world had now “entered an era in which people expected more transparency”.

“People expect us to do things more in the public light and we just have to get used to that,” he said. “Just as science itself improves and self-corrects, I think our processes have to improve and self-correct.”

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It is important for Federally funded research to be in the public domain. But, Universities, who hope to license the results of this research, and corporations, who will not as likely commercialize a product if they can not lock up the IP, Both of these considerations must be accounted for if we want to translate basic research into therapies or products for people.

So, as the Principles seem to indicate, most of this open data should happen AFTER publication, so this would give the proper organizations to make sure they have any IP issues dealt with.

But what about unpublished data? What about old lab notebooks? The problem supposedly seen now has nothing to do with data that was published. It has to do with emails between scientists. Is this relevant data that should be made public for any government funded research?

Who determines which data are relevant or not?

And what about a researcher’s time? More time in front of the public, more time filling out FOIs, more time not doing research in the first place.

The scientific world is headed this way but how will researcher’s adjust? There will have to be much better training of effectively communicating science to a much wider audience than most scientists are now comfortable with.


Filters lead us to wisdom

filters by aslakr
[2b2k] Clay Shirky, info overload, and when filters increase the size of what’s filtered
[Via Joho the Blog]

Clay Shirky’s masterful talk at the Web 2.0 Expo in NYC last September — “It’s not information overload. It’s filter failure” — makes crucial points and makes them beautifully. [Clay explains in greater detail in this two part CJR interview: 1 2]

So I’ve been writing about information overload in the context of our traditional strategy for knowing. Clay traces information overload to the 15th century, but others have taken it back earlier than that, and there’s even a quotation from Seneca (4 BCE) that can be pressed into service: “What is the point of having countless books and libraries whose titles the owner could scarcely read through in his whole lifetime? That mass of books burdens the student without instructing…” I’m sure Clay would agree that if we take “information overload” as meaning the sense that there’s too much for any one individual to know, we can push the date back even further.

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David Weinberger has been one of my touchstones ever since I read The Cluetrain Manifesto. I cried when I read that book because it so simply rendered what I had achingly been trying to conceptualize.

Dealing with information glut today leverages an old way of doing things in a new way. It uses synthesis rather than analysis. Analysis gave us the industrial revolution. Breaking the complex down into small understandable bits allowed us to create the assembly line that could put together our greatest creations, such as the Space Shuttle, with more than 2.5 million parts.

Yet a single O-ring can destroy the whole thing.

Synthesis brings together facts, allows us to see them in new ways. But to attack the really complex problems of today, we need to utilize synthesis from a wide range of viewpoints, all providing their own filter. As with the story of the 5 blind men and the elephant, no one person has all the information. But a synthesis of everyone’s information provides a reasonable approximation.

David discusses this view:

A traditional filter in its strongest sense removes materials: It filters out the penny dreadful novels so that they don’t make it onto the shelves of your local library, or it filters out the crazy letters written in crayon so they don’t make it into your local newspaper. Filtering now does not remove materials. Everything is still a few clicks away. The new filtering reduces the number of clicks for some pages, while leaving everything else the same number of clicks away. Granted, that is an overly-optimistic way of putting it: Being the millionth result listed by a Google search makes it many millions of times harder to find that page than the ones that make it onto Google’s front page. Nevertheless, it’s still much much easier to access that millionth-listed page than it is to access a book that didn’t make it through the publishing system’s editorial filters.

It is through synthesis that new technologies allow us to deal with information glut. And this synthesis necessarily involves human social networks. Because humans are exquisitely positioned to filter out noise and find the signal.

I’ve discussed the DIKW model. Data simply exists. Information happens when humans interact with the data. Transformation of information, both tacit and explicit, produces knowledge, which is the ability to make a decision, to take an action. Often that action is to start the cycle again, generating more data and so on.

This can be quite analytical in approach as we try to understand something. But the final link in the cycle, wisdom, is the ability to make the RIGHT decision. This necessarily require synthesis.

New technologies allow us to deal with much more data than before, generate more information and produce more knowledge. However, without synthetic approaches that bring together a wide range of human knowledge, we will not gain the wisdom we need.

Luckily, the same technologies that produce so much data also provide us with the tools to leverage our interaction with knowledge. If we create useful social structures, ones that properly synthesize the knowledge, that employ human social networks that act as great filters, then we can more rapidly compete the DIKW cycle and take the correct actions.




Why knowledge management failed

knowledge by Parksy1964
A Better Way to Manage Knowledge:
[Via HarvardBusiness.org]

We give a lot of talks and presentations about the ways and places companies and their employees learn the fastest. We call these learning environments creation spaces — places where individuals and teams interact and collaborate within a broader learning ecology so that performance accelerates.

During these discussions, it’s inevitable that somebody raises their hand. “Wait a minute,” they say, “isn’t this just knowledge management all over again?”

It’s an understandable concern. Knowledge management, after all, was probably the hottest topic in management in the 1990s. “If only our company knew what our company knows” was the mantra in those days. With knowledge becoming the most important factor of production, surely competitive success awaited those companies that could effectively manage what their employees knew.

But we all know by now that despite massive investments and a lot of highly motivated people knowledge management in some instances didn’t yield all the benefits it could have. The best KM systems succeeded at capturing and institutionalizing the knowledge of the firm. But for the most part the repositories and directories remained fragmentary and the resources didn’t get used. The folks with the knowledge were often reluctant to put what they knew into the database. The folks seeking the knowledge often had trouble finding what they needed.

Moreover, in their quest to capture what the firm already knows, most knowledge managers lost sight of the fact that the real value is in creating new knowledge, rather than simply “managing” existing knowledge. In this fast moving world, what we know — our “stocks” of knowledge — depreciate faster than they used to. So we've got to keep creating new knowledge in order to keep pace.

Most of us, as individuals, know this. That’s why we’re not keen to spend time entering our latest document into a knowledge management system. We know we’re better off engaging in the interactions and collaborations that create new knowledge about how to get things done.

In these circumstances, the last thing the world needs is another knowledge management scheme focusing on capturing knowledge that already exists. What we need are new approaches to creating knowledge, ones that take advantage of the new digital infrastructure’s ability to lower the interaction costs among us all — ones that mobilize big, diverse groups of participants to innovate and create new value.

We’ve found in our research into environments like World of Warcraft (WoW) that new knowledge comes into being when people who share passions for a given endeavor interact and collaborate around difficult performance challenges. Most long-time gamers, for instance, figured it would be months before anybody made it all the way through the many difficult performance “levels” involved in The Burning Crusade, the World of Warcraft extension released in 2007. But a French player named Gullerbone did so little more than 28 hours after the extension was released. His accomplishment made headlines in the gamer world.

Gullerbone succeeded by taking advantage of the tools and resources available to him (and his “guild” of teammates) in the vast creation space that has emerged within and around World of Warcraft. Creation spaces emerge from a careful recipe of participants, interactions, and environments blended by insightful designers. And they succeed where knowledge management fails.

Why? Because these creation spaces, heavily relying on shared network platforms, provide tools and forums for knowledge creation while at the same time capturing the discussion, analysis, and actions in ways that make it easier to share across a broader range of participants. Soon after Gullerbone and his guild figured out how to get through the new performance levels of the Burning Crusade, the details about how they did it soon became widely available in the social media “knowledge economy” surrounding the game — videos, blogs, wikis, etc.

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Knowledge management is really a misnomer.

What most companies called knowledge management was actually information management. It was just a way for them to capture tacit information held by the employees and make it explicit. That is something companies are very good at but not how knowledge is created.

It is through the interconversion of tacit and explicit information that creates knowledge, which is the ability to take an action.

Employees see little value to their workflow by providing information to the company without any really effective enhancement to the workflow. People want knowledge in exchange for their information. Knowledge management tools were great at collecting information but very poor at yielding knowledge. They did not permit the easy interconversion of tacit and expiicit information, nor facilitate its exchange with others in the community. These are requirements for any sort of real knowledge creation.

It is through social interactions that information becomes knowledge.t That is how we evolved. Information management systems can be useful but people care about knowledge, as that helps them make a decision. The decision might be as simple as making a change in their workflow to use the new ‘knowledge management’ system.

Now, people will participate when there are direct benefits. Blogs and wikis have great benefits for a worker. An emergent property of this is that the community sees the information and can easily transform it into knowledge. That is because, as opposed to almost every knowledge management system, Web 2.0 technologies map almost one-to-one with human social networks, yet provide benefits unattainable before. One example is being able to carry on a conversation without having to occupy the same place at the same time.

These authors know this:

This focus on knowledge creation shifts the motivations of participants. Knowledge management systems desperately try to persuade participants to invest time and effort to contribute existing knowledge with the vague and long-term promise that they themselves might eventually derive value from the contributions of others. In contrast, creation spaces focus on providing immediate value to participants in terms of helping them tackle difficult performance challenges while at the same time reducing the effort required to capture and disseminate the knowledge created.

Creation spaces have the potential to generate increasing returns — the more participants that join, the faster new knowledge gets created and the more rapidly performance improves. They bring into play network effects in the generation of new knowledge. In contrast, traditional knowledge management systems are inherently diminishing returns propositions. Since existing knowledge is by definition limited, it requires more and more effort to squeeze the next increment of performance improvement as existing knowledge gets more broadly distributed.

Capturing information is easy and was the low hanging fruit that many so-called knowledge management systems used. It failed at creating knowledge mainly because it did not leverage the social aspect in worthwhile ways.

But, providing immediate benefits to the employees, while providing social links for others in the community, permits simple human nature to take over – the need to connect and transform information into knowledge.

The companies that recognize this – that create systems that permit their employees to easily create knowledge using social network paradigms that go back to our primate beginnings – will be the most adaptive to disruptive innovations.

They will succeed where others fail.

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A great primer on the diffusion of innovation

innovation by etcname
I Should Have Majored In Psychology:
[Via Chuck’s Blog]

Way back when, I thought it useful to do two courses of study. I wanted that CS (computer science) degree, but the whole topic, while fascinating, seemed so self-contained.

At the time, I thought adding coursework in economics was the right thing to do. Even way back in the late 1970s (yes, I’m that old), I could see the two interweaving in very interesting ways.

I was wrong. I should have chosen to add in psychology rather than economics.

Because — at the end of the day — I’m finding that success with technology has more to do with how people perceive things rather than the hard facts we all work with every day.

Ever Rolled Out A Big IT Project?

I have. Several times, as a matter of fact. And — each time — I spent an inordinate amount of time lining up approval and support for what I was proposing to do.

The least of my problems was making sure the darn stuff worked as expected. My most daunting challenge was usually changing perceptions with hundreds — sometimes thousands — of people who had a vested stake in the outcome.

If you work in IT, you’ve probably come to the same conclusion — the technology will probably be ready far in advance of people’s willingness to embrace it.

Accelerating Change Creates Value

I’m not just talking about IT here — I’m talking about any leadership role in a large organization. To create unique value, we have to change the way we do things. The faster we can change and adapt, the more value we create for our organization and our stakeholders.

And — more often than not — it’s people’s perceptions that stand between where we are — and where we’d all like to be.

A while back, I was chatting with people who put together MBA coursework. Since I tend to work with freshly minted MBAs here at EMC, they wanted to know what I found missing.

My answer was pretty clear: they need at least some sort of background in behavior psychology if they expected to be successful in any organization.

After all, organizations are nothing more than collections of people.

And If You’re In Marketing

I don’t see how anyone could be successful in any form of marketing these days without a deep and empathetic understanding of the human psyche, and how it manifests itself in your target audience.

Yes, showing ROI and “business value” is essential. But I’d offer that’s just table stakes. There’s so much good technology out there today that there are many ways to solve a given enterprise IT requirement.

Worse, when we as vendors come up with something new and interesting (as is frequently the case at EMC) but is a departure from conventional thinking, it takes an inordinate amount of time to get people comfortable with the new approach.

People will often say things like “well, we need time for the technology to mature”. Fair enough. But more often, I’m thinking it’s less about the technology, and more about time needed to have perceptions change.

One of the most frustrating recent examples for me personally was enterprise flash drives. EMC launched them at the beginning of 2008. They worked absolutely perfectly at the time. But adoption was slow, mostly because it was an entirely new idea.

Adoption started to pick up dramatically during 2009. Not because the technology was any better — it was simply that people had gotten more comfortable with the concept.

Since EMC’s business model involves investing a lot in new and disruptive technologies, this inherent psychological barrier to “something new” is often front-and-center in my mind.

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Read the whole thing. This is a great discussion by someone on the ground, detailing ow hard it can be to get people to adapt to new technology.

Different organizations have different rates that innovation diffuses through them. Many do absolutely nothing to facilitate this diffusion in any way. It just happens by essentially ad hoc means.

I’ve written about how change and innovations traverse a community. A better way to facilitate such things is to put disruptive innovators and mediating early-adopters in place to evaluate new technologies. That is what they are really good at and actually enjoy. If they see the value, especially the mediators, they can often speed up the rate the new technology diffuses.

Usually, however, the people in this position are from the middle, the Doers, who really do not like the uncertainty and disruptive effects on their workflow by the introduction of novelty. They are the most hesitant to accept innovation unless informed by the relevant mediators.

But, the organizations that understand human social behavior, that put the right people in the right spots to actually evaluate and evangelize new technologies in a community, will be the ones that succeed. They will not only be able to leverage new technology faster, they will be more resilient and able to deal with failure.

Because, after all, failure is just another change. and organization that deals well with change will have little to fear from failure because it knows that is a faster route to success.

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Things that change and those that do not

How Heartfelt Marketing Delivers:
[Via chrisbrogan.com]

Dave Delaney and the Griffin Tech CESBound Project

Dave Delaney and his company, Griffin, put on quite a great little project with CESBound. They took an old VW bus, after hours, and restored it, and then drove it from Nashville all the way to Las Vegas for CES. Along the way, they made media, met friends, told stories, shot photos, froze a bit, played music, and had a blast.

When they arrived at CES, the thing they kept hearing (and I heard it when I visited the booth, too) was, “Man, it’s so cool that you restored this bus and took it on a huge road trip. That’s so much more genuine than renting a nice car and putting it in the booth.

The side of the van was covered in little Polaroid photos from the road trip. The back of the van was playing some of the CESBound TV episodes. Everyone around the bus, whether they were from Griffin or not, seemed really happy.

Dave and the whole rest of the team (we know Dave because he’s one of us, but there’s also Melanie Pherson and tons of other names that Dave or someone will add when they see this post) really did a lot to make the >Griffin Technology CES story into more than just a company selling iPhone and iPod accessories.

Luchador of Griffin

They made a special site, CESBound.com. They befriended the VW community via some forums, where they were told that, when the bus breaks down, someone will come and help them out, no matter where they are in the country. They did all kinds of gatherings and other on-the-road relationship building on the way to the event.

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This is a nice example of how the creativity of people who have a vested interest in an organization can be harnessed in completely novel ways. New technologies now allow the end users with the most passion to create the materials they need, without having to rely on outside vendors.

Using photos, videos, the web and more Griffin produced something quite novel, something that helped demonstrate their brand as well as show what a ‘fun’ company they are.

But, while these technologies allowed them to produce material cheaper and more directly, the success of this project really still depended on how they connected with other human beings. They needed to create, activate and stimulate human social networks in order for this to be a successful project.

As Chris mentions, they connected with a wide variety of people, including many who would not be at all interested in an electronics convention. They extended the reach of their social networks and produced a project that almost markets itself, with continuing connections as people find their website.

What this tells me is that Griffin listens to its innovative talent instead of ignoring their disruptive actions. This is really necessary for an organization that has to remain nimble and resilient in an industry that changes daily. Being able to leverage its own internal creativity increases the chance that Griffin will continue to be successful.

Being able to use technology to enhance social interactions is a given these days. But having the organization that successfully takes its own creativity and extends it with technology is rare. It requires a set of management tools that are not well codified in many MBA programs.

It seems to me, though, that Griffin is one of those rare companies.

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The key question

Transformation, not technology:
[Via Jon Stahl’s Journal]

It occurred to me yesterday that the real challenge we[1] face is not the question of “how do we apply technology tools to organizations?” but more “how do we help organizations & people transform themselves so that they are more able to harness the power of technology?”

[1] “we” = those of us standing astride the worlds of technology and social change.

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There is really not much more to add to this. I believe this can be accomplished by helping the organizations to diffuse innovations more rapidly. The rest will follow.

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