My weekly readings have brought much enlightenment (English native speakers: can I say that?) in the field of “Organisational Behaviour”. Some people are studying how e-mail flows and forwarding can help build maps of social networks. Others propose new “de-motivational” ways of managing staff in a radical fashion (thanks Miss N for the link):

So far, so Swiftian; especially the suggestion that managers “cleanse” after shaking hands with a worker, even by simply wiping your hands on clothing, just to reinforce to them that they represent a contamination.

Based on this and surfing on a few other blogs, I made a couple of observations that I want to share with the scientific community under the name of “Blognus Plan” theory.

Abstract: Use blogging rates, profiling and a correlation model to determine bonus plans.

It seems you can measure your white collar employees’ efficiency and dedication to the fulfilment of their tasks or whatever you pay them for by using the frequency with which they post on their blog. Given the development of blogging and provided you can identify which employees are blogging and where (Google anyone?), you can then monitor their activity and develop a model to give you an index of their actual workload, provided also that you know their “profile”. An educated guess is that some people blog more when they have spare time (the “Happy” profile: “nothing to do? Let’s blog or get home earlier”) or when they feel literally exploited (the “Complaining” profile: “Too much work; I’m too tired – I need to complain and share online”). Other profiles should be established from further study.

My very primary research using two MBA students’ blogs (names disguised) indicates there is a correlation between workload and blog publishing rate – You have to be able to isolate other factors I guess.

Student 1:
Phase 1: had a training in the US for a few weeks. 4 posts in 4 weeks.
Phase 2: is now back and fully working in Europe. 1 post in 2 weeks (and counting).
Analysis suggests the subject is working harder in phase 2.
Yet to determine: further analysis might suggest we need to add a “Party Boy” profile (the more free time, the less blogging). Introducing a set of geographical dummy variables might be a good idea (US suburbs vs. European city).

Student 2:
Phase 1: training and working on a presentation template. 4 posts in 1 week.
Phase 2: less motivating work and waiting for data to start 2nd project. 1 post in 2 weeks
Phase 3: second project starting. 3 posts in 1 week.
Analysis suggests the subject is blogging more in phases of excitement.
Yet to determine: Can the model be also used to track motivation of “Thrill seeking” profiles? We need to introduce a “work interest” index to refine the regression.

I know I should link to existing theory etc. A good preparation to my shadowing project report it seems.

Notes:

  • It is too early and it would be erroneous to apply any of these findings to the author’s current post. Seriously, if companies also tracked exact post time… :)
  • Does anyone know about someone using blogs and links to establish maps of social networks?