A lot of information is lost when data are aggregated into averages and statistics. For example, the best books often get mediocre 2.5 star average reviews on Amazon. Why? That statistic conceals the reality that nobody is giving the book a 2.5 star rating, they either love it and give it a 5 or hate it and give it a 1. The statistic says apathy, the granular data says controversy.

Considering data at a more granular level uncovers meaningful variations that cancel each other out at the aggregate level.

For example, web site stats are useful, but I also like to look at the path an individual visitor took through our web site. This granular look often suggests areas of confusion, or sometimes draws my attention to weaker parts of the site that can use work.

Another application of this idea is to use itemization to stimulate creativity. For example I recently broke the pre-sale customer experience at one of my companies into about twenty distinct steps. I brainstormed how we might improve each step, even the ones that don’t normally seem the most important.

Give yourself the mental limitation of considering only one part of the whole at a time to encourage new combinations of non-obvious ideas.