Via Roo Reynolds I just came across Dale Lane’s TV scrobbling project. For those of you who don’t use the social music site Last.FM, ‘scrobbling‘ is the act of gathering attention data for analysis. Last.FM pioneered the scrobbling of listening data from people’s computers, allowing them to see at a glance what they listened to, what their friends listened to, and discover people with similar taste in music.

Dale has taken this idea a step further and has whipped up a scrobbler for his TV data. This wouldn’t be possible if it weren’t for the fact that Dale’s TV is also his computer. This gives him access to data that would otherwise be stuck inside a set-top box:

Similar software exists to track your attention during day-to-day work on your computer. I have RescueTime installed on my laptop. That gives me access to information about which applications I use and how much time I spend using them, and allows me to decide if an app is productive or not. It then scores my overall productivity accordingly. Sometimes the results can be surprising, for example, I spend a lot less time in email than I had thought, often less than half an hour a day, and I never look at email on the weekends. RescueTime also illustrates changing preferences for software. Here’s me experimenting with Google’s Chrome browser (olive green = Firefox; teal green = Chrome):

The aim of RescueTime, if you put the effort in to set it up properly, (e.g. choose which applications and websites you find distracting, neutral or productive), is to reveal where you can make productivity gains. If, for example, you discover that you spend a lot of time on Twitter and you find it to be very distracting then you can use RescueTime to track your progress in resisting its lure.

Of course, attention data can just become infoporn, producing endless pretty graphs that don’t help alter behaviour, so scrobbling isn’t a solution by itself. It could, however, form the basis of behavioural analysis and change projects that would not otherwise be possible. Productivity is the holy grail of the knowledge worker, but it’s hard to know how productive one is being as we’re not built to accurately track our actions as we carry them out. My guess for amount of time spent in Twitter, for example, was wildly higher than reality – I generally use it for less than an hour a day, which is not bad given my line of work.

Attention data scrobbling could also, with a clever bit of functionality design, help do away with timesheets, which I loathe to the core of my being. The key there, as with RescueTime, is understanding what constitutes ‘productivity’. Splitting behaviours out by application, or even by website, doesn’t necessarily tell you if you’re being productive. Time in instant messenger, for example, could be productive or it could be a distraction, depending on who you’re talking to and what you’re talking about. Scrobbling won’t solve that bit of the puzzle, but it would make a good starting point.

There is an obvious dark side to attention data scrobbling in business, though: such data could easily be misused by management as a stick to beat employees with. Care would need to be taken as to who could access what data, perhaps with data anonymised when accessed by management to prevent victimisation. There would also need to be an educational component to any scrobbling project to ensure that people knew what the data meant and how to act on it.

There’s such great opportunity here for both knowledge workers and the businesses who employ them. I’d love to hear from anyone using or interested in collecting and using attention data in this way.