Last week I finished up almost a month’s intensive investigation, analysis, synthesis, and creation, and planning.
We have a major product family that needed a huge refresh. The product manager for that line was transferred elsewhere in the company … and I got the file 3 weeks before a executive meeting in which I had to present the plan. Tens of millions of dollars are at stake.
So I had to plow through a ton of data, figure out what was happening with the line, understand it, decide where to take it, plan the new approach, formulate my presentation and style, and sell it to the top stakeholders.
That was an intensely interesting experience, and made me think about the relationship between data, complexity, and the quality of decisions. In honor of Kathy Sierra and her wonderful charts, I fumbled together this graph in 37 seconds or less:
So here’s my back-of-the-envelope theory:
- With little data, decisions are a crapshoot. Who knows: might be right, might be wrong.
- With lots of data but inadequate synthesis, decisions are even worse. Still might be right and might be wrong, but even more likely than the little data scenario to be fuzzy, unfocused, and confusing.
- With even more data but extremely rigorous synthesis (lots of interesting but not ultimately relevant datapoints dying on the cutting room floor) you have the chance – repeat, the chance – to make good decisions that can actually be implemented in a clear, direct, and powerful way.
I’m sure there’s lots of holes in this bathtub analysis: poke away![tags] decisions, matrix, data, complexity, kathy sierra, analysis, synthesis, john koetsier [/tags]
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