How to Hit the Enterprise 2.0 Bullseye

My colleague Clay Christensen stresses that managers are voracious consumers of theory. In other words, they value ways to think about their world, and mental tools that will let them make decisions and predictions with a level of confidence higher than they get from experience and intuition alone.

I’ve been reminded of Clay’s insight because I’ve recently had some success using a longstanding theory to explain to executives the value of social networking software (SNS) like Facebook. As I wrote earlier, the sociologist Mark Granovetter’s theory of the ‘strength of weak ties‘ provides a great way to conceptualize the value of  SNS.  These technologies increase a knowledge workers’ number of weak ties (and hence access to non-redundant information and bridges to other networks), and also provide an easy and convenient way to exploit these ties from within the tool itself.

But the intersection of ties and Enterprise 2.0 technologies goes much farther than this. In fact, ties provide a great base for understanding the benefits provided by many E2.0 technologies, and for understanding when each one should be deployed. Thinking in terms of ties, in other words, let managers select from among the grabbag of available technologies and also anticipate the benefits they’ll get after successful deployment.

Consider the prototypical knowledge worker inside a large, geographically distributed organization (all of what follows also applies for smaller and more centralized organizations, but probably to a lesser extent). She has a relatively small group of close collaborators; these are people with whom she has strong professional ties. Beyond this group, there’s also a set that includes people she with worked on a project with in the past, coworkers who she interacts with  periodically, colleagues she knows via an introduction, and the many other varieties of ‘professional acquaintance.’ In Granovetter’s language, she has weak ties to these people.

Beyond this group there’s a still-larger set of fellow employees who could be valuable to our prototypical knowledge worker if only she knew about them. These are people who could keep her from re-inventing the wheel, answer one of her pressing questions, point her to exactly the right resource, tell her about a really good vendor, consultant, or other external partner, let her know that they were working on a similar problem and had made some encouraging progress, or do any of the other scores of good things that come from a well-functioning tie. By the same token, if our focal worker is a person of good will, there are many other people in the company she could help if her existence, work experiences, and abilities were more widely known.

Of course, there’s also a large group in the organization who are just not going to be of much use to our prototypical worker, and vice versa. These people will not form ties. They’re simply co-workers, not actual or potential colleagues. It seems at first glance as if it wouldn’t be valuable to use any type of technology to bring these people together. This, however, is too hasty a conclusion, as I’ll discuss.

The bullseye figure below is an extremely simple and not-to-scale representation of the relative size of these groups, from the perspective of our focal knowledge worker. The small core of people with whom she has strong ties is at the center, surrounded by her larger group of weakly-tied colleagues. Potential ties are in the next ring, and co-workers —  people with whom valuable ties do not and will not exist —  make up the outermost ring. My intuition is that for most knowledge workers the four circles in the figure are nested accurately  —  that the number of potential ties, for example, is greater than the number of weak ties —  even if their relative sizes are way off.

bullseye graph of ties

What does all this have to do with the emergent social software platforms of Enterprise 2.0? Well, there are several such platforms, each of which is valuable in a different way. Wikis, a blogosphere, social networking software, and prediction markets all facilitate Enterprise 2.0 as I’ve defined it, but they’re clearly not identical technologies, or even closely similar ones.

But how are they different? Do they to dissimilar things for companies, and to them? And when is each the ‘right answer?’ Answers to these questions arise from the realization that a knowledge worker will want to use a different E2.0 technology at each ring in the bullseye.

A wiki is the classic Enterprise 2.0 technology for a core of strongly tied knowledge workers who are collaborating on a deliverable. They can use it to generate documents, to debate their contents and structure, track project status, link to other resources, etc. Google Docs and Spreadsheets, Zoho, and other online office productivity suites are similar to wikis in that they allow egalitarian editing of documents, spreadsheets, and presentations by all group members; they’re just not currently as extensible as a full wiki.

Evidence suggests that wikis let strongly-tied collaborators get their work done better, faster, and with more agility than was previous possible. With a wiki, what’s emergent is the document itself, with ‘document’ defined broadly.

As I wrote earlier, enterprise social networking software lets our prototypical knowledge worker stay in touch with a large network of colleagues, allowing her to keep up to date with that they’re doing, working on, and producing. It also lets her tell this network what she’s up to.

This might sound like an only marginally useful exercise, but it can in fact be quite powerful because it’s a quick and easy way to form connections and make associations that might not ever occur otherwise. I saw this firsthand a couple days ago when one of my Facebook friends told his network via his status message that he was going to accompany a foreign head of state to a high-level meeting on technology issues. Because I was only weakly tied to this person I had no idea that he was that well connected or interested in public policy. But as a result of his Facebook update, which took him about ten seconds to type and me one second to read, I now know who to reach out to should I ever want to dive into European IT issues, or desire an invitation to the Elysee Palace ;). SNS lets its users build bridges to new human networks, and to let non-redundant information emerge.

Facebook currently lets members ask their network a question, then collects their answers on one globally-visible page. I imagine that successful enterprise Facebook equivalents will have much more advanced tools to allow members to actively exploit their networks by asking them for assistance, pumping them for information, etc. I also imagine that they’ll let users post answers to their most frequently-asked questions, then simply point seekers to this resource. The facts that Facebook has opened its platform to outside applications, and that a consortium of social media providers anchored by Google and MySpace has just announced a common specification for developers, will no doubt hasten the arrival of robust enterprise SNS.

And what about all the people in the third ring of the circle in the figure —  the potentially valuable colleagues who our knowledge worker just hasn’t met yet? Wikis and SNS in their current configurations don’t help her learn of the existence of such people, but an internal corporate blogosphere could. Imagine a large company in which most workgroups (divisions, labs, departments, project teams, etc.) blogged, as did many individuals. No one would have time to read all the resulting blogs, of course, and most employees would probably read few of them regularly. But I imagine lots of people would set up searches for words, phrases, or topics of interest (as is possible with Bloglines, Google blog search, and other tools), then check in frequently to see what recent posts show up in their search results. This is the main way that I keep up with the latest writing on “Enterprise 2.0.” Even articles in print publications get discussed almost immediately in the blogosphere, so I learn about them, too.

I’ve seen a few surveys indicating that blogs are currently one of the least popular E2.0 technologies among CIOs and other decision makers, probably because the business value of internal blogging isn’t always clear. Maintaining a blog can seem like shouting into a void, and we all certainly have better things to do than that. The benefit of blogs becomes much more clear when they’re seen as tools to convert potential ties, strong or weak, into actual ones. Prior to the Web 2.0 era I don’t believe that good technologies existed to help with this conversion, and the overall toolkit for making employees aware of potentially valuable ties — including newsletters, ‘science fairs,’ seminar series, etc. —  was pretty small. A lively internal blogosphere that includes good search and notification mechanisms represents a significant addition to this toolkit, and can allow productive ties and teams to emerge over time.

The outermost ring of the bullseye seems like the least amenable to technology —  how can the new crop of digital tools productively interconnect people who really don’t have anything to say to contribute to each other? Prediction markets do exactly this. Prediction markets are very much like stock markets. They contain securities, each of which has a price. People used the market to trade with each other by buying and selling these securities. Because traders have differing beliefs about what the securities are worth, and because events occur over time that altered these beliefs, the prices of securities also vary over time.

In a stock market like the New York Stock Exchange the securities being traded are shares in companies, the price of which reflects beliefs about the value of the company. In a corporate prediction market, in contrast, the securities being traded are related to future events such as “How many units of this product will we sell next quarter?” “What will our market share be at the end of the quarter?” “Will our competitor release their product on time?” “Will we release our product on time?” Such markets can be designed so that security prices are the same as the estimated probability that the event will occur, according to the markets’ traders.

Prediction markets provide benefits to the traders in the form of ego boosts and monetary rewards (if a company decides to reward successful trading that way), and they bring substantial benefits to sponsoring companies by providing accurate and decisive answers to important questions. As James Surowiecki wrote in The Wisdom of Crowds, “Corporate strategy is all about collecting information from many different sources, evaluating the probabilities of potential outcomes, and making decisions in the face of an uncertain future.  These are tasks for which [prediction] markets are tailor-made.”

The participants in a prediction market don’t have to have any dealings with each other beyond their trades, and often don’t even know who they’re trading with. So these markets aren’t tools to help human networks coalesce; they’re just ways to have answers emerge from the self-interested, profit-maximizing activities of a population of traders.

The table below summarizes the potential benefits, candidate technologies, and type of emergence at each ring of the bullseye (in other words, for each type of tie). Like the bullseye figure itself, it is a drastic simplification of a large and complex set of phenomena. In particular, the entries in the three rightmost columns of the table aren’t meant to be mutually exclusive or collectively exhaustive. They simply highlight some important differences at each of the four levels.

Tie Strength Potential Benefits Technology Example What is Emergent?
Strong Collaboration, Productivity, Agility Wiki Document
Weak Innovation, Non-redundant information, Network bridging Social Networking Software Information
Potential Efficient search, Tie formation Blogosphere Team
None Collective Intelligence Prediction Market Answer

I’m hearing from a lot of people that late 2007 is much like late 1997, when technology specialists were getting asked by senior executives “What is the Internet, exactly, why is it a big deal, and what’s our Internet strategy?” The question now is “What’s Web 2.0 / Enterprise 2.0 / social media, exactly, why is it a big deal, and what’s our W2.0 / E2.0 / social media strategy?” The table, bullseye figure, and arguments presented here can help frame discussions around these questions by encouraging decision makers to first focus on what ring(s) of the bullseye they’re most interested in targeting. Lots of subsequent decisions and actitivies flow from the answer to this question, and from applying a bit of well-established theory (the theory of strong and weak ties) to technology considerations.