Chaos in Collaboration: The Changing Locus of Collaboration (Part 3 of 5)

This is Part 3 of the Chaos in Collaboration series.

Collaborating during the creation phase of the content lifecycle means working together to create great content. It is an explicit activity. You know that you are working together with others because you can either see them directly (they are in the same office), or because they will starting bugging you if you don’t complete what you said you would do or participate in something you said you would participate in.

Collaborating in the latter parts of the content lifecycle, on the other hand, is largely implicit. It means that the normal, everyday actions of people in relation to published content are taken into consideration for the use of other people when they come in the future to browse and access published content. Let’s think about it in terms of searching for a specific keyword within your organization’s document management system. Today when the search is undertaken, you get back a list of documents that include the term, and these are ranked using certain algorithms related to the content itself. Thus the needs of end users are met by machine algorithms.

As an alternative, you do the same search and this time the results come back with additional contextual information based on the use of social algorithms. You can see how many people have already read each of the documents that have been listed. You see an accumulated rating score for each of the documents, based on what earlier readers thought about each one. You see how the document has been classified by other people, and you can quickly click to see a collection of other documents that share the same classification.

It may be that the document that has the highest density of words that matches your query under the machine algorithm is actually the worst the document for answering the question you are asking, and because the actions of your colleagues have been captured and synthesized into something meaningful — the social algorithm — you can see which ones get the highest social rating. This is a form of collaboration, although it is a different form from team collaboration activities. As a user, I am taking the actions of others and using their decisions and reactions to help guide what I’m going to be doing going forward. Which of these documents will I read, and which ones will I not? I take the best information presented to me via the machine algorithm and mix it with the additional context provided by the social algorithm, and I make my choice.

Looking out across the newer “Enterprise 2.0” tools on the market, we note that these are introducing new capabilities to compute this social algorithm — remember, the underlying user actions are happening now just as they used to happen, but now they are being tracked and utilized, and some new constructs are put in front of users to help them shape the social algorithm:

  • Content Rating … as a reader of this content, what do I think of this, and how good do I judge it to be?
  • Tags and Tag Normalization … how do I think about and classify this material, and therefore how does it link to other items of content in the wider organization?
  • Semantic Matching … as a reader who has a set of things that interest me, based on the analysis of other people with similar interests, what other related areas should I be interested in?
  • Expertise Surfacing … as a reader, who do I think is good at what they do in a certain area of the business — who do I trust and who do I look to for words of wisdom — and as a result, who should other people look to? Who are the real experts based on our communal reactions to their work contributions?

Again, all of this post-publishing collaboration is based on implicit actions and cues. As users, we don’t know who specifically will benefit from our rating activities, and we are highly likely to be blind to the impact that our mere reading activity has on implicit social algorithms, but in sum it comes together to make for a more informed organization.

So then the question becomes, based on these new capabilities which extend the locus of collaboration from teams to the organization as a whole, how does an organization go about making it happen?

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