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Sep 16, 2014

I bumped into an interesting gentleman at a recent HR analytics conference: Peter Smit. He’s not an HR guy but he did say something of interest, he said he wanted to measure collaboration.

Collaboration is one of those soft and fluffy “HR things.” We’re all for it. It falls within our domain. We might even provide some training on it, but we’ve not gone much beyond vaguely feeling we should encourage it.

Collaboration got a boost from social communication software like Jive and Yammer which often bill themselves as “collaboration platforms.” This new level of investment in collaboration puts pressure on companies to think more clearly about what collaboration is and how to measure it.

Tapping into “accidental” data

If you ask a consulting firm to measure collaboration in your company they will roll in with a time intensive and costly study, probably doing a good deal of interviewing to write a report and offer recommendations. Another approach to measurement is social network analysis which traditionally relied on manual surveys to collect data.

Smit and his research team at Collabogence are taking the measurement of collaboration a step further.

Smit’s insight is that all the systems in a company that allow people to work together are sources of data on collaboration. For example, web conferencing software may just seem like the an updated version of the conference line on your telephone; however that software is, as a matter of course, tracking who is meeting with whom.

This same accidental collection of data about who talks to whom may appear in an unlikely place like project management software; really any software that includes peer-to-peer communication.

An important aspect of organizational dynamics?

Tapping that accidental data and finding a way to make sense of it is Collabogence’s mission. Once they have good data then the scope of possible analysis gets interesting.

We may be able to create an index of the overall intensity of collaboration, we may be able to categorize individuals by their style of collaboration (e.g. connectors, sharers, hoarders), and we may be able to pinpoint specific weaknesses in our ongoing collaboration.

To take a broad social construct like collaboration and investigate it through the thin strands of metadata will no doubt have shortcomings. However, we may be cracking open a new window into an important aspect of organizational dynamics. In particular, we will have data on how various interventions have intentionally or unintentionally affected collaboration.

Collabogence is in the midst of a research project with the main Canadian HR association: HRPA. We will learn more when they publish the results in early 2015.

What’s interesting?

  • We are collecting useful data without knowing it and that data may sit in surprising places. I wonder what other useful HR data is hidden away in the various applications strung across our enterprise.

What’s really important?

  • HR needs to be ready to engage with this kind of analysis even though it may be well outside our comfort zone. Innovative thinkers are finding ways to get fresh data on the dynamics of the organization. How we acquire, analyze and interpret this data is still full of uncertainty. However, if HR isn’t taking the lead on fresh ways to make sense of organizational dynamics then who is?

Probing the pulsing flows of collaboration is quite different from running off to hire an engineer or lead a training session on supervisory skills. It requires a broader conception of the HR role.

However, that new conception is where the big new opportunities to add value will be found.

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