I find, like many of my colleagues, coworkers, and professors, that the amount of bootstrapping that I do every morning before even considering my work is phenomenal. It’s become an intuitive reflex to open up Slashdot, ZDNet, BoingBoing, TechCrunch, DamnInteresting, The Great Beyond, IT Facts, The Star, among many others, after having turned on my computer and combed my hair. What ends up happening is that I waste away at least an hour reading these news blogs and my Golden Hours often slip through the cracks, leaving me doing 20% of my work using 80% of the rest of my day.

Aside: Golden Hours is the name I’ve given to the two, three, or four hours during the day when we get 80% percent of our work done. My golden hours are 9:30-11:30 am and 8:30-11:30 pm, if I’m really lucky. And of course not all of that time is used efficiently. And when it comes to writing poetry, my golden hours are between 11:30 pm and 1:30 am. What about you?

So what’s the solution to this quagmire? Well, before we even start asking questions like that, we should consider whether solving this problem is a prudent thing to do to begin with. I mean what if, at some psychological level, we need this bootstrapping. Or maybe at a very concrete level we need the daily news, after all this is our line of work.

Well, even if we do need this news, whether at a concrete or physiological level – where our brains have become so hard wired to flip to these sites without doing which we would be agitated all day – there must be a way to somehow reduce the influx of information and the time required to parse and process it all.

And this is really important. Not just because it requires time, but more so because, with such amazing inundation of data, we become less attached to any single item of news, our ability to feel compassion and our ability to deeply analyze a thing become mitigated, and we begin to loose site of the little things, causing our short term memories to adapt evolve into this machine that accepts short bursts of information and is unable to handle anything of meaningful size.

So do we agree that this is a problem?

The traditional solutions involve further minifying the incoming data using such things as RSS and Atom feeds. This consolidates the information and displays only the most relevant articles of interest. But does this really solve the problem? No! It makes it worse, in fact. What we’ve done is allowed for even more information to come in at an even higher fast-and-dirty rate, spreading us thinner and thinner.

Another traditional thing to do is ask whether we need all of this information to begin with. This question forces us to prioritize our incoming data and only read the most rel event facts. But is this always possible? Is this really what we want? Is this a solution or a compromise? I don’t want to compromise… do you?

So what can we do? Here are some suggestion I have to which I hope to add as time goes on. Let me know what you think of them and how they work out for you.

1. Modularize your incoming data and group it into sets of related content. Put each set into a prioritized circular queue (where A may be visited twice or more before B, despite the fact that it’s a Round Robin queue, because it has higher priority). Then accept data from the first N groups on Monday, the next M on Tuesday, the next O on Wednesday, and so on. Modify this algorithm to suit your schedule and size of each set.

So how does this help… is what you have done just spread out across the week now? NO!! You have spread things out, but what is much, much more significant is that you’ve modularized your data into relates sets. Therefore, the context switch between types of data has been minimized.

2. Figure out when your Golden Hours are. Then, create and firmly adhere to the rule that you will never visit these data during these hours and will do so only AFTER them (not even before).

This ensures that you’ve got 80% of your work done, even if the rest of the day is spent frivolously. This is actually a difficult one to do since the very premise of this inundating data paradox (for me at least) is that it happens before work begins.

3. In tandem with suggestion 1, identify data that is large (e.g. essays you read). Factor these large data out and set aside a time of week to revisit them whilst only visiting the small data on a daily basis.

Large pieces of datum are naturally things that are not typically pressing; they can be pushed back. So visiting them once a week or so and setting aside a specific time for them ensures that they are given due analysis, that context switching is minimized, and that they do not interfere with day-to-day activities.