Connecting the dots is what we call the problem of finding various bits of the answer from various people who may not have been aware of the question to begin with. I described this more deeply in a previous post on the intelligence community’s connect the dots problem:
Imagine 10,000 people on 17 teams, working on 100,000 jigsaw puzzles. Now imagine that some of the pieces have been randomly distributed among the other players. Nobody knows how many pieces are in each puzzle. And some pieces may be missing entirely, or fit into multiple puzzles simultaneously. Each person has a limited number of puzzles that they are aware of, and some may be working on the same puzzle without realizing it.
They need a system that will make it possible for people to know what pieces the others have, for the pieces themselves to find the holes they might fit into, and – here’s the odd one – the holes can describe themselves to the pieces. This one needs one with some blue in it, or a fairly oval shaped connector.
Why do we need to connect dots?
Problem solving – I’m working on a problem. Say its how to satisfy a customer’s tricky technology issue. Say its figuring out how to keep explosive underwear off of airplains, or how a particular frog species might predict global warming effects, or how a certain bacteria may solve the worlds energy crisis, or competing against another technology company in a market sector. These can be extremely difficult problems. They all depend on being able to form a complete picture from a diverse set of information, understanding the implications of that picture and being able to act on that insight.
So. Suppose I’m looking for a cure for cancer. Some other person in my company (or not) is studying the effects of pseudonameotryxlate on diabetes. She notes that this drug seems to limit hair growth, but she’s not certain why. I notice that one of the key processes in this cancer progression is the same process that is involved in hair follicle generation. How am I going to know about the study on diabetes?
What if I had a system that would tell me about things that had to do with hair. What if I had a general awareness of surprising outcomes that people chatted about?
What if I were trying to form a strategy to compete against a certain vendor. And one of the sales reps got a comment from a prospect about that vendor that told us something we didn’t know.
What if I’m on a services team, struggling with some exotic server configuration that I’d never seen before – but someone in my org has….
So what are the components that would be of value to us here (so, so, so – why do I write this way?).
First – you need a system which will capture small bits of knowledge, not just formal documents or even wikis. Fortunately, social media tools are (can be) nicely designed to facilitate and capture question and answer, comments, remarks and corrections. In a good system, these will be indexed and retrievable.
Second – you need a system that promotes some level of ambient awareness – twitter/yammer type capability is very helpful here, as you see a (somewhat self filtering) stream of activity go by that you never really have to deal with, but you’ll notice when something critical pops up.
Third, you need a really, really good search tool. This search should not only identify content, in the form of docs, comments, Q&A and wikis, but should also identify people who may have generated that content, and communities, projects or networks where that activity is taking place.
Fourth- you need to let technology work for you in the form of recommendations based on semantic and statistical analysis. Both the – “these concepts are similar and therefore you might want to check this other one out” idea, and the amazon recommends concept “people who read or write about x also find y interesting”.
In this way you are maximizing the flow and availability of information in your organization, and allowing it to be filtered by a) yourself b) your network and c) technology – which is a winning trifeceta. With you, your network and your technology working in complementary fashion to find information most valuable to you, you have maximized your chances of finding what you need to know and which you may not know to ask about.
A social collaboration system should have each of these components, leveraging the productivity focus of collaboration into a refined ability to connect the dots.