Social Network Analysis – cure or curse?

In this blog I am going to outline a highly risky yet potentially foundational part of Knowledge Management and especially Intellectual Asset Management – Social Network Analysis (SNA).

SNA is a method of mapping either the connectivity of concepts (like twitter-feed), or more importantly to us, communication between people (like a kite network).

SNA is a tool of Knowledge Management in general (Tran 2007), but becomes a core aspect of building Communities of Practice (Wenger, McDermott et al. 2002)

The reason that it is highly risky should become self evident as we proceed, but in case I don’t make it clear – it stands a reasonably good chance as being seen as invasive, manipulative, and intrusive, and will alienate the very knowledge workers and staff that you are trying to unite in purpose.

You could very well unite them – against you!

The basic idea is pretty fundamental to Knowledge Management: You want to figure out who your thought-leaders, subject-matter experts, and influencers are by seeing who communicates with whom – the experts are consulted more than they consult others.

In a sense you are using the “well worn path” and letting the activity of staff show you who your SMEs are (or at least who the staff think they are) and the conduits and paths that information and knowledge takes in your organization – both internally and with partners.

Before you go down this path at all, you need to be sure of two things – How you will communicate the program to staff, and what safeguards there will be over the use of the information.

Once you know who is talking to whom, it will be very tempting to use that information for disciplinary actions as well as for knowledge management. This spells disaster because using it just once to nail the office lovers or a gossip, (or even the person leaking company secrets) will easily undermine the further trust of staff in a dramatic and probably catastrophic fashion.

So before you start planning SNA, be very sure that you are going to explain the purpose and the need very carefully as well as making it very clear if content of messages will be sampled, and that no information will be used for any other purpose than knowledge management.

I have split the methods into several categories of ever-increasing accuracy and reliability, but also unfortunately also in escalating levels of intrusiveness.

Non-Intrusive Methods

This is the easy one, simply don’t do anything, or just fish it out of your own memory or imagination.
This is how most organizations do it, and it is just marginally better than a Ouija-board or reading tea-leaves.
It is subject to all the normal human cognitive biases – halo effect, concurrency, freshness, proximity, likeness, and so forth.

If you want to be no better than any other firm, then do it this way.

Partially-Intrusive

This is where you just ask and hope you asked clearly and that the answers are accurate and truthful. You can improve the odds with a well crafted questionnaire of the “Who do you ask” variety.
The biggest problem will probably be the limit of your expertise in building a good questionnaire instrument that has high construct-validity and reliability, and the recall of the respondents. People often don’t recall who they get information from when asked to report them on the spot, and they will suffer the same biases you would – they will tend to remember the most recent more than more frequent but remote events, and some events will be more memorable and overshadow others. They will also tend (like you) to over-sample people they like and people who they perceive to be “more like them”.

This is a valid but somewhat spotty measure.

Intrusive Methods

These sample actual activity and communication traffic rather than relying on people’s memories and willingness to report on their own behavior.

Basically you are going to snoop by monitoring the source and destination of messages, and record who talks to whom by using electronic records captured on office systems:

  • Telephone records
  • Email traffic
  • Instant Message activity
  • Newsgroup activity
  • etc.

Other than the fact that people might object to what they feel is being spied upon, two immediate issues raise their heads with any of these methods – your mapping will be neither exclusive nor exhaustive.

  • Exclusivity
    It will pick up the gossips, the lovers, and the experts alike and without very careful and even more intrusive sampling you won’t easily be able to tell them apart. You simply won’t know if the high traffic between two or more people is due to knowledge exchange for business, a hobby, a secret office romance, or just plain office gossip about who is having a romance in the office!
  • Exhaustivity
    There are several modes of knowledge transfer that it won’t pick up, as well as those SMEs who are reclusive and don’t advertise or signal their competencies. In the former case, people may be physically visiting and consulting the SME, using electronic media that you aren’t monitoring, or contacting them outside the premises or business hours and thereby escape detection.

This is the best way in terms of accuracy and immediacy – it harvests more broadly and without human biases in the sampling and reporting, and it can be updated on the fly.
Some of the tools available also automatically produce very readable and attractive network maps that are easily interpreted compared to lists and numbers.

Often a single glance will show nodes, portals, and hubs – that is people who others go to often, people who connect different groups, departments, or companies, and people who connect other people.

Real, Really Intrusive

This is where you pull a [name deleted] and actually sample the content of message in addition to source and destination. This would allow you to discard a high proportion of private or business-irrelevant messages from the computation and thus tend to exclude the lovers and gossips from the mapping.

It also allows you to automatically build the foundations of a Controlled Vocabulary, and pick up information to build Concept and Topic Maps, and to find both needs and sources for specific topics.

For instance, you might be able to discover that Betty is the expert in Oracle Index tuning and that there is a popular need for Index tuning because there is a lot of and frequent traffic from several sources to Betty using key words in the messages.

Not only could you spot problems and issues and trends as they develop, but also know who needs to be served and who is serving knowledge on the fly. The potential for Just In Time training alone is quite stunning, not to mention the ability to have early detection and rapid response to business problems.

It goes without saying that this level of intrusiveness requires either a Byzantine degree of spying or an extremely high level of trust amongst staff, and whilst it would enable some pretty terrific advances with compound business advantages, it also has the capability to detonate into a big fireball that will rip your organization apart if it ever lost trust.

Really, Really, Horribly Intrusive

Ok, let’s just not go there – wires dangling from people’s bodies is just too dystopian to contemplate and besides, fMRI machines are darned expensive.

Conclusion

Knowing your Social Network Architecture allows you to know who your respected SMEs are, what the communication conduits look like, and how the knowledge in your organization is interconnected – no small achievement!

However, a proper communication plan and careful presentation and execution are vital because the level of intrusiveness can easily lead to a revolt amongst your knowledge workers.

If you use the information in a disciplinary or punitive fashion, you will do more harm in a single stroke than if you had cut wages and perks and fired the office mascot.

Bibliography

Tran, L. A. (2007). Encyclopedia of communities of practice in information and knowledge management .

Wenger, E., R. A. McDermott, et al. (2002). Cultivating communities of practice: A guide to managing knowledge , Harvard Business Press.

Please contribute to my self-knowledge and take this 1-minute survey that tells me what my blog tells you about me. – Completely anonymous.

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Matthew Loxton is a Knowledge Management professional and holds a Master’s degree in Knowledge Management from the University of Canberra. Mr. Loxton has extensive international experience and is currently available as a Knowledge Management consultant or as a permanent employee at an organization that wishes to put knowledge to work.

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One Response to “Social Network Analysis – cure or curse?”

  1. Latest Social Network Mapping Software Auctions | Uncategorized | Information about Social Bookmarking Software, Social Bookmarking Tool Says:

    […] Social Network Analysis – cure or curse? « Matthew Loxton's KM & OL Blog […]

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