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Note: This was originally posted to Wikinomics.com on May 28, 2009.  See here for the original post.

Given how emotional people get about their micro-blogging, I thought I’d include a disclaimer on this post: The views contained in this post are mine, and do not necessarily reflect those of the entire Wikinomics team. While we often disagree on topics of Twitter, I think we can all agree that there are there are opportunities for improvement across the Twitterverse.

The Wikinomics team has many posts discussing the real potential of Twitter for business value. This is how I predominantly use the tool: As an efficient way to find new stories relevant to my research, as well as discover interesting or amusing content, and occasionally peek into the personal lives of interesting people. A good signal-to-noise ratio is critical for this type of usage.

I use Tweet Deck to help filter my updates, but it still becomes a challenge because filtering is by individual, not content. That means if I add someone to my “Main Feed,” I have to somewhat trust that they will act responsibly. What do I mean by responsible? The other day I opened Twitter and notice 39 tweets in a row from the same person, most of which were links. Literally 39! That’s irresponsible. It’s also not a way to get noticed on Twitter, but rather ignored.

Responsible Twitter users abide by four simple rules:

1. You learn something new everyday 2. Twitter is not chat 3. Don’t be a needy jerk 4. Ignore rules 1 to 3 if you are in marketing

RULE #1: You learn something new every day There are two key parts of this rule: 1) “Learn” – Share a new discovery, something novel or interesting you learned today. There are a lot of people I’d like to hear from more often, but who rarely post (I’m somewhat guilty of this myself). Everyone has something they can contribute to Twitter. At the same time, it sets the bar slightly higher than posting a stream of consciousness. 2) “Something” – not everything. How much is too much? Think top-10, max. I gave Denis a hard time about this a couple of weeks ago.

twitter-10_small

In truth, Denis was actually at a conference tweeting insights from various presentations. It’s an exception to the rule that I haven’t figured out how to deal with yet, so I took him back. He hasn’t betrayed my trust since ; )

RULE #2: Twitter is NOT chat There is a reason that the inventors of Twitter had the good sense to include a Direct Message function. No one wants their feed spammed with out-of-context snippets of conversation like, “Sorry I missed you @mybuddy, next time for sure.” This is a very simple, yet often forgotten rule.

RULE #3: Don’t be a “needy jerk” If you missed it, Vanessa Grigoriadis has a fantastic article in New York Magazine about Facebook. In it, she talks about the declining usefulness of Facebook updates:

“This was the beginning of the end. Suddenly, Facebook began to irk me—the way friends always posted about procrastinating, being stuck in traffic, needing a nap or a vacation, or seemed to formulate their updates in declarative yet vague form, like ‘Michelle is upset’ or ‘Roya is pouting,’ thus coming off like a needy jerk and making us take time out of our day to plead with them to answer the burning question: ‘Why are you pouting?’”

I couldn’t have put it better. There is a lot of this on Twitter and it’s exceedingly unproductive. Worse; it’s noise that obfuscates the valuable signals we’re all trying to get at.

RULE #4: Ignore rules 1-3 if you are in marketing The future of Twitter – especially in marketing – may well be bigger than my “rules.” I talked to a company Crimson Hexagon this week that makes a business out of mining user opinions online (including from Twitter) for market research. In fact, marketers love the stream of consciousness because to them it’s data, and valuable data at that: “Post all you want about what you had for lunch, just be sure to mention the brand of mustard you used and how it made you feel…” (Note; Rule #4 should have excused Denis from his misstep on Rule #1, since he is our program manager for our Marketing 2.0 program.)

Marketers also don’t want to use Direct Message. If you answer a customer question publicly, it not only makes you look good in terms of being responsive, it also potentially saves you from having to answer the same question multiple times, as well as helps boost brand mentions. For more on how to think about your brand on Twitter, see: A potential framework for how different brands are using Twitter.

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So, I actually forgot that I wrote this way back in 2009!  It’s a really weird feeling when you search for something on Google and it takes you to something you wrote, but actually forgot you wrote… See here for the original article (including many insightful comments): http://www.wikinomics.com/blog/index.php/2009/06/15/diminishing-returns-of-collaboration/

While generally a believer in how collaboration can lead to better insights and greater efficiency, I continually see examples of where it is neither effective, nor terribly efficient – and in the worst cases totally counter-productive. I work in a highly collaborative environment and study many others, and my experiences have led me to two areas where problems typically emerge:

  1. At an individual level people suffer from cognitive overload. As people get busy and collaborate across a multitude of projects, the brain gets distracted, and the quality of the output suffers. In short, one person can only do so much.
  2. At a project level where you run into a situation of ‘too many cooks spoiling the broth.’ In short, only so many people can do one thing.

If you put the two of these together, the worst-case scenario is that in an individual could join a project as the Nth person who ‘spoils the broth,’ while the time they dedicate towards doing so distracts them from their other work – which, continuing the cooking metaphor, leads them to burn the toast as well.

The problem is, it’s very difficult to apply a scientific approach to measure exactly how many people per project, and conversely how many projects per person is optimal. The most well-known study around this is Dunbar’s Number, which sets “a theoretical cognitive limit to the number of people with whom one can maintain stable social relationships” at 150. In terms of collaborative overhead, Dunbar speculates that “as much as 42% of the group’s time would have to be devoted to social grooming.” Now that might be acceptable for the hunter-gatherer societies described in Dunbar’s anthropological study, but I would imagine this amount of “grooming” time would be extremely unproductive in an enterprise context.

In his book Collaboration, released this month, Morten Hansen, a professor at the University of California, Berkeley and INSEAD, identifies two costs related to enterprise collaboration. The first is the opportunity cost collaborating (i.e. the opportunities individuals could have been pursuing had they not been collaborating), the second is the cost associated with fostering co-operation. In both cases, as the number of projects or the number of individuals grow, so too does the potential for diminishing returns.

At the project level, I feel as though most people have general understanding that there is a certain point at which there are simply too many stakeholders and collaboration breaks down.

project-efficiency

However, at an individual level, I think we are less cognizant of – or less willing to admit – our own limitations. I’ve seen many cases where an enthusiastic and eager collaborator was clearly overburdened and well past the point of optimal effectiveness. Incidentally, my personal hypothesis is that this point of optimal effectiveness is a fairly small number of projects per person. My main “proof” for this is anecdotal, but I notice that the busier one is, the more likely they are to quickly skim a topic and provide feedback in short (sometimes valuable) chip-shots without contributing to a better in-depth understanding of the topic space. Worse, in some instances perceived value comes from dissenting, so instead of constructive feedback, you get wildly varying opinions with no one working towards a coherent solution.

individual-effectiveness

On the subject of cognitive overload, a recent Deloitte report notes, “Even a Sunday newspaper contains more information than the average 17th century citizen encountered in a lifetime. Add to that the stress of decision-making amidst uncertainty, corporate change, and a tidal wave of tasks. Never before in history have workers been asked to absorb and make sense of so many data points.” One more sensational study even suggests that information overload is more damaging to the brain than smoking pot. I think we can certainly make an argument that where collaboration is most likely to break down is at the individual level.

This brings up another point: What about the virtues of solitude? Are we losing our capacity for individual decision-making? Moreover, who’s actually doing the deep thinking needed to solve complex problems? We talk about the multitasking Net Gen brain that is not actually doing multiple things at once, but rather switching more efficiently. Does constant switching allow for deep analytic thought?

So what is the solution? Overall, I’m wondering if there’s a Dunbar Number for the optimal number of simultaneous projects per person (small and large). How is this number affected when you take into account broader ecosystem participation and places where quick feedback from multiple participants is actually desired over in-depth participation?

As a start, I think collaborative technologies can help by streamlining different types of feedback. So, for example, a project can have 1,000 collaborators if they are providing feedback via a prediction market. Conversely, if only three people are collaborating on a document, perhaps a wiki is most effective.

One possible model for managing cognitive overload is letting individuals self govern – i.e. everyone decide where they can add the most value. Of course, this also raises many issues, including: people, especially in high-performance cultures, tend to overextend themselves; people tend to pick project that interest them, but that may not add the most value to the organization; and people tend to be social and so will gravitate towards the same projects, thus contributing to project inefficiency.

In order for this to work, you would have to architect a system that would allow people to allocate their own time in a structured way (similar to the Freiburg budget example). I’m envisioning a system where resources are finite but can dynamically allocated; where employees are guided by decisioning logic that identifies the projects that provide the most value to the organization; and where limits are set that prevent projects from being staffed by too many people and that stop people from taking on too many projects.

In a recent interview about his company’s enterprise collaboration software, Jive Software’s CEO Tony Zingale made a point of saying, “It’s not Facebook for the enterprise, stupid.” Zingale is understandably defensive: many business leaders find it easy to trivialize or ignore Facebook—after all’s it’s just a social network, a community, a club, a waste of time. Most people can get along just fine without it and, despite being recently valued at $50 billion, the company’s current revenue model is still tied to old-school advertising via (somewhat customized) banner ads. Most people would argue that Facebook’s main value proposition for users is voyeurism and the engorgement of ego. In fact, when I told my wife I would be launching into a research project about Facebook, she likened my interest in the site to narcissistic self-gratification. But, Zingale and my wife (sorry hun) are both wrong on this one. With its vast network of connections and hundreds of millions of gigabytes worth of personal information, Facebook has invented a new kind of business. Instead of selling you a product, with Facebook you are the product.

I’m not about to claim that Facebook is “enterprise-grade” software, but there’s a reason why founder Mark Zuckerburg is not only Time Magazine’s Person of the Year, but also the world’s youngest billionaire. At the very least, enterprises should be taking notes. With an estimated 2010 revenue of 1.6 billion, close to 600 million users (approximately 8% of the world’s population), and a keen understanding of both digital identity and the value of open communication, Facebook has fundamentally changed the way people interact and planted the seeds for some extraordinary business models that will disrupt the way companies operate.

In fact, I respectfully challenge Zingale and would like to suggest that Facebook for the enterprise is exactly what we need. Or, more precisely, enterprises and software vendors should look for ways to replicate design lessons from Facebook in their organizations and products. Facebook has been successful because it instantiated (and subsequently mastered) the social graph, built networks of weak ties and strengthened strong ties, customized information management at the user level, filled gaps in elements of customer relationship management, and used personal profiles as platforms for connectivity to third-party sites. While this might sound like jargon to the typical user that derives value from Facebook, please bear with me as I explain why this is important.

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If you’re a Twitter user, perhaps you’ve already heard of paper.li. If not, I recommend checking it out and creating your own custom “newspaper” based on links shared by your Twitter network. The tool suggests that while the traditional role of journalists as sole curators of news information might no longer be valid, the newspaper as a format can still be quite compelling (not to mention the business model of advertising-funded content aggregation).

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According to the Facebook blog (as of April 2010), the average Facebook user “Likes” nine pieces of content very month. With over half a billion users worldwide, that translates to more than 4.5 billion Likes per month and 54 billion Likes per year on everything from news articles, to jeans, to movies, and even real-live activities and events. Each of these Likes is tied to a real person for whom Facebook has detailed identity information. Although it hasn’t yet been monetized, this data and the analytics applied to it, could become the basis for Facebook’s core revenue model. On Facebook, you are the product.

For every Like that is made, Facebook is able to correspond a product affiliation to demographic information such as sex, age, geography, and education, as well as social graph data about relationships and influence within a group. With Places, Facebook can even correlate product activity to mobile location data. If mobile payments ever take off, they could get actual sales data as well.

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It happened ever so sneakily –just as we were celebrating the demise of old media companies and rejoicing in the new freedom of the web, it’s gone. While we were busy thinking the internet revolution would be about free downloads, peer-to-peer content, and enterprising grassroots innovations for all, “The Man” once again seized control. Wired’s recent article, “The Web Is Dead. Long Live the Internet,” by Chris Anderson and Michael Wolff, sparked my interest and brought to light the idea that maybe the “free web” as we know it was a mere adjustment period during which old empires died and new ones were being created. As the article notes, new vertically-integrated media oligopolies like Google, Apple, Facebook, and others are taking control:

“The control the Web took from the vertically integrated, top-down media world can, with a little rethinking of the nature and the use of the Internet, be taken back.”

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The following was originally posted on Wikinomics.com on June 18, 2010.

Actually, the title of this post should really be, “The Net Gen: Too connected to wireless devices, social media, and ‘always-on’ technologies for parenting,” but “plugged-in” just sounded better. In fact, fewer of us are actually physically plugged-in these days, with smart phones replacing computers as the device of choice for digital accessibility as well as ‘interrupt-ability.’ We’ve researched the effect this has on the Net Generation as both customers and employees, but as this generation gets older (the oldest Net Geners are now 32), it’s also worth discussing how it will affects them as parents. We know that many Net Geners are waiting longer to have kids, but for those that have taken the plunge, how does the experience of ‘growing up digital’ translate into parenting behaviours and attitudes towards technology in the home?

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