There is a well-know phenomenon that affects users adoption of tools that rely on their contribution, something that Jakob Nielsen called Participation Inequality. This theory says that, in online communities, a tiny fraction of the users are responsible for a disproportionately large amount of content and activity. This is often also called the 90-9-1 theory (90% observe, 9% engage (comments) and 1% produce content). Although the phenomenon was initially studied on general social networks and communities, we are now seeing the same behaviour inside organizations. It’s not uncommon to have a few people produce the majority of the internal wiki articles or being the most active (by far!) in the company’s microblogging tool.
What is strange in this behavior is that it doesn’t reflect the real participation distribution in the organizations. We all agree that no organization would work if it had only 1% of their people producing something, so this disconnection between real work and its reflection on the enterprise social tools is something we should reflect upon. Certainly community managers play a significant role on trying to contradict the 90-9-1 rule, but the real question remains – how can we match user participation with the actual work they’ve been doing?
For example, one of the major features that enterprise social tools provide is the ability to know who are the experts in the company. Some tools are able to provide that directly, using searchable profile directories while others take a more indirect path where you ask for experts in a chat room or skim through the microblogging history trying to figure it out who has the largest amount of activity around a certain topic. Now, if the participation is unequal, the expert-finding process will become rather ineffective (and even misleading). The person with the largest activity in the microblogging tool may not be the real expert you’re trying to find. The same happens when only a fraction of the people updated their profile (and keeps it up-to-date). Maybe the real expert belongs to the 90% who only observe, which I reckon is a rather polite way of saying that he (the expert) simply doesn’t care. He just wants to have his work done, the best possible way, because that’s his job – having work done, not “socializing” in the company’s chat room. I’m not dismissing the importance of those tools, it’s just the way it actually happens.
So, one of our goals, as designers of social enterprise tools, should be to fight the 90-9-1 rule, bridging the gap between actual work and social activity. It’s clear that work is comprised of activities, and that most of those activities should be social directing to better, more efficient and effective results overall. So, what needs to be done (and this is the path we’re taking with Spreadd), is to connect these social tools to the work people are actually doing instead of telling them to do the connection themselves. And this must be done in a seamless way, where there is no difference between the real activity and the “captured” activity. Their profile? Once you start capturing their real work, you will have an always up-to-date profile for everyone in the company. Not 1%, not 9%, the whole 100%. Suddenly, it becomes much easier to find the real experts in the company. Isn’t it great?
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