Infovark

Dion Hinchcliffe has a really important post about the impending maturity of the Enterprise 2.0 market, in the wake of Forrester’s prediction that the Enterprise 2.0 space will be a $4.6 billion industry within 5 years.

He contends that a hallmark of the new enterprise solutions is that they are emergent — that they aren’t handed down from on high through the traditional IT/management channels — that instead they are introduced by people in an effort to solve their problems.

“In other words, we seem to be coming from a push-based era of command-and-control management and are heading into an era where more and more work is being conducted using a decentralized pull-based model that’s more scalable, efficient, and leads to increasingly innovative outcomes.”

We’ve spoken about this at length before, because we see emergence as a crucial property for any system that’s going to be able to deal with the kinds of unpredictable situations that occur for modern knowledge workers.

Dennis Howlett, also over at ZDNet calls Forrester out on their Enterprise 2.0 definition:

A set of technologies and applications that enable efficient interaction among people, content, and data in support of collectively fostering new businesses, technology offerings, and social structures.

Forrester’s definition is indeed pretty vague. But then, no analyst is ever going to be precise. (Vagueness means never having to admit you were wrong.)

Dennis also suggests that Forrester have missed a key part of the problem. Forrester expects the major vendors to roll up all of these new “2.0″ features into their collaboration offerings. By doing so, Dennis feels that Forrester greatly inflates the size of the E2.0 market. He’s right; the true E2.0 market is much smaller, and the big enterprise vendors just don’t understand it.

The major vendors sell to CIOs and IT departments through traditional channels. They aim at the top of the corporate pyramid. Their systems enforce repeatable processes and follow established metrics. Their value is derived from imposing order on chaos.

Emergent systems, on the other hand, thrive on chaos. They address the “Barely Repeatable Processes” that happen within organizations. Emergent systems are decentralized, self-organizing and organic — the antithesis of the top-down, rules-based engineering approach taken by most enterprise software. To build an emergent system — an ecosystem — you target the bottom of the pyramid, building it up one user, one connected node, at a time. The value of an emergent system is derived from its flexibility, adaptability, and responsiveness.

Emergence isn’t another feature to add to the enterprise technology stack. Emergence isn’t a feature at all — it’s an approach to solving a problem .

Sam Lawrence just posted an article about Twitter and social computing. Sam notes that people are learning interesting information and getting questions answered by tapping their public social network. Inside the enterprise, however, most of us are stuck using legacy tools that aren’t as effective. Couldn’t Twitter — or something like it — help companies communicate internally?

We certainly think so. As we noted in small cloud theory, there’s no reason why the same tools that work on the Internet couldn’t work on the corporate intranet. In some ways, it should be easier to network within a company than outside it. After all, as Sam points out, folks in an organization have — by definition — shared goals and common interests. So in a sense your social network is already built for you.

Twitter’s intuitive minimalism, like Google search, means that it’s easy to learn and understand. Compared to most of the other software used at work, it’s a breeze to use. No training required. No change management. And right now, it costs nothing to support. From an enterprise IT perspective, you couldn’t ask for a better deal.

The only barrier to Twitter adoption within the organization is the fact that not everyone has adopted it yet. Which means that progressive E2.0 types still need to use traditional channels, like email, to communicate with folks that haven’t begun using it yet. Which means the IT folks still need to provision email to every employee. It’s self-reinforcing; Email’s killer feature is ubiquity. And email is ubiquitous because everyone has it.

And it’s not entirely clear whether Twitter could succeed as a ubiquitous tool. Twitter is a really noisy communications channel. (Hence its name.) The last thing most knowledge workers need is another distracting communications mechanism. Email is bad enough. Hugh MacLeod just permanently disappeared from our twitter stream, because he figured he had better things to do.

Part of what makes Twitter work today is the fact that it’s an opt-in social medium. You sign yourself up. You choose whom to follow. If the IT folks signed you up for an account and automatically subscribed you to all 500 coworkers, would its utility collapse? Not everyone is @scobelizer.

The folks at Twitter have two related challenges to solve before they have a truly enterprise ready system. They’ve got to figure out how to scale the system technically as well as scale the system socially.

As a startup in the social productivity space, we know how hard it is to get the social design right. Twitter’s done a great job of social design so far. We wish them the best of luck.

Darn. While I was writing this post, another 40 tweets came in.

Nate Nash at e2.oh has an interesting blog post about folksonomy, Facebook and metadata extraction. He wonders whether automatic indexing tools might a better way to get accurate productivity information about employees, rather than relying on performance reviews. Nate touches on an idea that Gordon and I have been kicking around for a while.

In psychology, it’s called the self-reporting bias. Most people like to think well of themselves. It’s such a common tendency that people who think badly of themselves are usually thought of as depressed or maladjusted. Having low self-esteem has been blamed for all sorts of social ills.

Our brains are wired to err on the positive side. If you asked people, they’d tell you that they donated more to charity than they actually did, or worked out at the gym more, or engaged in more positive activities and less negative activities than was actually the case. In psychology experiments, you have to plan carefully to eliminate or minimize the self-reporting bias if you want to get at the motivations and causes of people’s behavior.

The classic business-school example of the self-reporting bias is the Nielsen Ratings for television. The early Nielsen Ratings were based solely on surveys, and showed that Americans liked high-minded fare such as Masterpiece Theater. Later, Nielsen incorporated set-top boxes into the surveys, to report the station and the time whenever the television was turned on. Unsurprisingly, given human nature, sports, sitcoms and shows like American Idol began appearing in the top ten.

The self-reporting bias is a core part of what it means to be human. It plagues social software like Facebook and LinkedIn. It shows up in the business world as a tendency to inflate one’s own resume or to indulge in marketing hype. To counteract the self-reporting bias, you’ve got to develop independent measures — or independent measurers. You’ve got to watch what people do and not listen to what they say they do.

(If you’d like to take a good objective look at your own cognitive biases, wikipedia has a fascinating list on the subject.)

Brad Feld at Feld Thoughts posted a slide by Adam Smith relating the Southpark underpants gnomes to pitching venture capitalists. The slides were meant to demonstrate how not to sell an idea to a venture capitalist. I understand the point, but I think if venture capitalists find themselves listening to gnome-like business plans they themselves are partly to blame.

Brad’s posted the clip from the Southpark episode, so I’ll just give a quick recap of the gnomes’ three phase plan:

1. Collect underpants
2. ???
3. Profit!

The hardest part of any startup is figuring out Phase 2. Phase 1 is easy; it’s doing what you do best. For a software company, that means making software. For an author, it’s writing a book. For an artist, it’s creating art. Phase 3 is the goal: Making money, achieving fame, winning awards, etc. Phase 2 is the trick: finding a way to get from doing what you do best to the ultimate goal.

Often, someone starting out has only the talent and the dream. Figuring out how to make the dream a reality is a combination of hard work and dumb luck.

The idea behind venture capital is not simply to give new startups access to seed money. There are plenty of ways to raise funds. You could take out a business loan, put a second mortgage on the house, or hit up friends and family for cash. Part of the reason why startups turn to a venture capitalists is to get the benefit of their experience with other startups. In other words, it’s to get help with Phase 2.

Many of the current Web 2.0 darlings succeeded without any sort of business plan at all. YouTube was losing money hand over fist and had several copyright infringement lawsuits pending when Google rescued them. Google themselves nearly went broke before they hit upon the advertising formula that powers the attention economy. Facebook hasn’t figured out their model yet. Twitter has no means of visible support beyond VC backing. With these examples in mind, it’s hard to blame startup founders for glossing over Phase 2.

Yes, build it and they will come is the call of hopeful idealists everywhere. But boundless optimism is a necessary requirement for an entrepreneur. It goes with the territory. Venture capitalists, of all people, should appreciate that.