I was skyping with Cheryl Burgess earlier this week and knowing how easy it is to wind me up, she asked me the seemingly innocent question “In Social Business, are we measuring the right things?”. At which point I lept up onto my soapbox just in time to see Cheryl smirking :-) She’d got me! But the question did get me thinking and since not everyone will understand my strong reaction, I thought I’d explain it.
I’ve been talking for several years now about the untapped potential of social & collaboration data and how its forcing us to look at analytics through a different lens; moving away from counting transactions and towards understanding interactions. However unfortunately the majority of folks are not thinking in these terms which is the reason I reacted so vociferously to Cheryl’s question. So if we are not measuring the right things, what should be measuring? I think the easiest way to describe this is with a very simple example.
I was talking to someone last week who is a social transformation leader and was looking to understand geo-diversity across their social network, specifically communities. She started the conversation by asking how she could measure community membership and content (posts, comments, …) by geo. This is the typical transactional viewpoint; counting membership and creation records.
However when we delved a little deeper to understand what it means to have a truly geo-diverse community, she recognized very quickly that it wasn’t transactions that she actually cared about; it was the interactions. For example; She may have lots of people from different geos creating content, but they may not be interacting in a meaningful way.
What we really need is a new measure for community geo-diversity. In much the same way that we’ve created new engagement KPIs for the individual that are driven by a series of sophisticated graph algorithms (see “Maximize the Value of your Systems of Engagement“), we need a new geo-diversity algorithm that traverses the graph and can explore and quantify deeper and more meaningful insight.
So let’s imagine that we use our graph algorithms to create a really sophisticated measure for geo-diversity. It might navigate the graph to understand which geos have joined the community, the geos of their respective networks, and the breakdown of their interactions? It might look at the type of interactions? High-impact, such as commenting or co-creation, or low-impact, such as tagging or liking? Were the interactions reciprocal? Which geo instigated? Which responded? Are certain geos “closer” in network connectivity than others?
Now that we’ve created this geo-diversity measure for each community, it can easily be integrated into any standard BI & Reporting tool. This is the critical point! It’s just one more number that can then be crunched for trends, correlations, deviations, etc. However its a much more meaningful measure that is more representative of the realities of a human network and allows the insights from the social scientist, cyber-anthropologist, and data scientist to be easily integrated into standard reporting tools. Not everyone gets up in the morning dying to analyze people networks — hard to imagine I know :-) — but for those that do they can provide huge value to the business.
And if you are interested in further discussion around Social Network Analysis, please join our upcoming Tweet Chat, Upcoming Tweet Chat: Turbo-charge your Enterprise with Social Network Analytics, it should be an engaging conversation.