Its not the same thing – the 3 types of collaboration

A year or so ago, i found myself in a (slightly heated) discussion around what the key enabling factors for collaboration were. Somewhere along the way, I discovered (as often happens when one is debating with ones spouse, or at least my spouse) that we were actually not talking about the same thing.

I was talking about helping teams to work together. He was talking about helping people who may not know one another connect as their expertise becomes relevant to one another. Oh. Well those are very different things, and while some enabling factors are similar, these two activities actually have rather different requirements both culturally, organizationally and technologically.

After working this issue for a while, I’ve labels the three major types of collaboration. This categorization seems to work for most people, and I’d love to hear what you think as well. I believe that it is critically important that we have a shared language to discuss and describe these different concepts if we are to make any progress toward enabling them in organizations. We cannot become sophisticated and make progress here if we cannot define the terms. So here is my take on this, and I look forward to your refining input.

Collaboration refers to a cluster of 3 types of activity – they are often interdependent and linked, but they are distinct in what they can achieve, and what is required to enable them.

1 Creative Collaboration.

Creative collaboration is collaboration that’s intended to create something. It is goal-oriented, and has a defined team (though stakeholders may come and go) that is responsible for delivering that product. Examples here are a product team, a legal team, a team responsible for an RFP, or a marketing launch, or developing a product, or a corporate acquisition.

The objective for this type of collaboration is to be able to achieve what an individual can not, either because its too much work for a single individual, or, as is more common, it requires a multitude of skills or perspectives to achieve.

The outcome that we’re concerned with is a factor of the team’s productivity. We want the outcome to happen as quickly, cheaply and with the highest possible quality, and collaboration has been shown to improve each of these dimensions. [citations]

What we need to do to encourage such collaboration is make it easy for teams to form, communicate, get organized, contribute, aggregate and iterate on work. I talk about this in depth in a recent post “Is Collaboration enough for Productivity.” Technology helps enormously here by providing shared workspaces, a variety of communications tools (wikis, document management, discussion forums, instant messages, etc), which, if you’re lucky enough to have well designed software, accelerates the rate at which people can get work done, and removes barriers like geographical and organizational distance.

The key cultural requirements for success for such teams are (and forgive me if you’ve heard this before) 1) a shared sense of mission 2) mutual respect 3) trust 4) a commitment to continual improvement. I’ve discussed these elements elsewhere on this blog, so I’ll spare you the details right now.

2. Connective Collaboration – its not the wisdom of crowds, its the aggregated wisdom of individuals.

This refers to connecting with a broader community – the organization as a whole, or even more broadly than than. You may not know most of the people in this community. The goal of this type of collaboration is to connect dots – find expertise and resources as you need them. Discover unexpected relevance, connections or insights, and maximize the chances that information, resources and expertise find the places that they’re meaningful or critical. (I’ve written about this in several places too – “Intel clear on ROI of Social Media” and “ Is collaboration enough to connect-the-dots?”). While there are examples of this type of requirement everywhere – science, healthcare, art, strategy, problem solving of nearly every kind – the most notable examples these days are from the intelligence community – is it possible that the intel community could have identified and connected the dots to warn them of the 9/11 attacks? The Christmas 09 underwear bomber? The answer is – maybe. There’s a lot involved in that problem, and I won’t get into all of it here, but recognizing patterns of droplets of  information and activity in an ocean of activity is not easy. The goal right now is to maximize the odds.

Connective Collaboration requires a broad, loosely connected community that can maintain awareness of activity, and ideally, technology that helps them find, discover or get pinged about relevant information, resources, insight and expertise –  that they may or may not have been aware of – elsewhere in the system. Status and microblogging have proven surprisingly useful here to build ambient awareness of what is going on  in the organization. It is also vital, however, to have communication and work indexed and searchable to be able to find those nuggets of connection. Semantic analysis, and statistics also have much to offer (and far to go) here.

3. Compounding Collaboration – Standing on the shoulders of giants.

The purpose of compounding collaboration is to ensure that whatever our endeavor, we are leveraging, to the greatest extent possible, the work that has been done already. Even if it is only to show us what to avoid. To the extent that we can do this, we can constantly compound and extend our capabilities, productivity and agility. There is nothing that can compete with this sort of dynamic, and it in competitive situations it trumps nearly any other dynamic (think of compound interest on your money – you cant catch up with an early, strong start).

To achieve this, we need to be able to capture work. Work is not only about documents. Work is what happens when you’re creating those documents (or other products) – what resources were used? What questions were asked? Who answered them? How did you overcome obstacles? What were the false starts or poor assumptions? What processes were followed?

The beauty is, that if you’re using technology to support Creative Collaboration, you should be capturing all this, so that the next people coming through can learn from what you achieved – or failed too. (cultural note – you need a culture where its ok to fail, and it is a respected part of the learning, discovery and continual improvement process).

The field of Knowledge Management was devised to support this type of efficiency and collaboration. But the trouble with KM as it was defined in the 1990s , is that knowledge capture and dissemination was separate from the work itself. It is something that must be undertaken and explicitly referred to. The implications of this are many, but it usually means that only the most formal, documented and recognized knowledge is captured. That a vast majority of insight is lost, and that what is captured is only found if someone explicitly thinks of looking there. In other words, because the prior generation of knowledge management techniques were largely divorced from the act of work itself, they were inefficient at both capture and dissemination of knowledge.

The new age of collaborative technologies should fix this, and make knowledge capture and transfer much, much easier.

There are other issues here as well – onboarding and training of new people.

I was recently part of a discussion where people were talking about the twin issues of senior people leaving and junior people coming up to speed. I’m a firm believer that one of the most tried, true and effective methods of transferring large amounts of knowledge is through apprenticeship – (try learning to make a pie crust from a book, vs doing it  with a friend or relative who already knows how). The transparency and team environments that good collaborative technologies can create enable apprenticeship on a broader scale than ever possible – and the beauty is that it goes both ways. The new kid can teach the old fart some new tricks too – without any loss of face on either side. Transparent environments are tricky and imperfect, and extremely sensitive to culture and organization – but they are also the most effective learning environments there are.

So there you have it. Deb’s basic taxonomy of collaboration. Thanks, Ken, for pointing out that I hadn’t pulled this together in a single post before. And thanks in advance to you, for your feedback so that this can be further refined and increasingly useful.