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The Continuing Quest for Inbox Zero

Previously I wrote about my discouraging attempts to achieve zero inbox and decided I would do better at it.

Starting with the lessons learned (which sounds so much less depressing than saying post mortems), we can say that for my first attempt I didn’t read the instructions or stop to ask for directions and wandered lost in the desert for many years. Since it was less than 40 years, I might be qualified for certain well-chronicled leadership positions.

I was not only clueless, but I was also clueless about my level of cluelessness.

Turns out that zero was not the recommended time to be spent in planning and preparation.

I resolved to do better on attempt two. This time I read the instructions, the background literature, commentary and did the obviously required tool set up before beginning. Unlike the initial attempt that had no planning and no prep, this attempt had several hours of pre-work and as a result, it took only an hour to realize that I was on a failing path. Definitely sounds like serious progress.

What I had failed to do on the second attempt was to look at the actual data, in this case, a sampling of the email. My theoretical categorization was systematically wrong in several important ways.

This brings me to my third attempt. This has a richer categorization of the email and the problems. The initial mathematical model suggests that it should roughly 20 hours to achieve zero inbox. That is above and beyond what it takes to keep up with the new email as it comes in.

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After 1 hour, I am slightly ahead of the 5% prediction but have hit many fewer of the hard case than were expected.

Fewer as in identically zero.

There are reasons to believe that they are tail loaded rather than randomly distributed and taking that into account, I should be much further ahead than I am so that 20 hours may be very optimistic and the key mechanisms have not yet been tested.

What will a second hour bring?

If it brings continued success, then it becomes worth detailing the plan with the hopes that others can replicate and perhaps improve.  Otherwise, just stream and tears, and another post mortem — whoops, I mean lessons learned, and perhaps yet another plan.

Only time will tell which.

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Written by Russell Brand

Russell has started three successful companies, one of which helped agencies of the federal government become very early adopters of open source software, long before that term was coined. His first project saved The American taxpayer 250 million dollars. In his work within federal agency, he was often called, “the arbiter of truth,” facilitating historically hostile groups and factions to effectively work together towards common goals

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