As I mentioned in December's column, I think that Malcolm Gladwell's book The Tipping Point offers some guidance to data managers. This month's column explores how the book's subtitle, "How little things can make a big difference," directly applies to data management.

The book begins with an explanation of how the popularity of a particular a shoe style (Hush Puppies) reached a tipping point between 1994 and 1995. Hush Puppies achieved a sudden, unplanned fashion revival, with sales experiencing huge increases.

To fully appreciate the story, one also has to know that the parent company was considering phasing out the Hush Puppies brand due to poor sales in 1994. So what happened? As told by Gladwell, a handful of kids started wearing the shoes precisely because they were seen as decidedly untrendy - no one else would wear them. As these individuals began wearing Hush Puppies to clubs and restaurants, they exposed others to the overall style - harkening back to "a dated, kitschy, '50s image." Gladwell estimates that approximately 150 individuals wearing these shoes would have been enough to start the trend or, using his term, a "Hush Puppies virus." The wearers were noticed by designers who incorporated the shoes into their trend-setting fashion lines, multiplying the effect. All of this happened, and Wolverine (the manufacturer) had nothing to do with it!

I don't want anyone to take away the idea that data management is comparable to a fashion trend. (Although we have seen fortunes somewhat akin to rising and falling skirt hemlines.) Rather, I want to highlight the manner in which the shoes (and other topics covered by Gladwell: falling crime statistics, epidemics, Paul Revere's ride, etc.) achieved remarkable feats (no pun intended). The rebirth of Hush Puppies and the way to grow a data management program occur the same way that epidemics spread.

Epidemics occur as a function of people transmitting an agent, the agent itself and the environment in which the agent and the people interact. Everyone is all too familiar with the behavior of the dreaded winter cold and flu. Epidemics require three conditions:

  • Contagiousness: The ability of something to be "caught" relatively involuntarily (such as a yawn).
  • Little causes having big effects: This leverage is the strength exhibited by the duration of the effect (e.g., gathering susceptible children in large numbers in schools and daycare centers can result in more infections).
  • Change happens dramatically: Demonstrable results are perceived in a measurable time period (e.g., everyone is touting XML as a technological solution in 2006).

Gladwell asks why some ideas, behaviors or products start epidemics and what can we do to deliberately start and control positive events? This triggered my formal thinking about our relative positions as data managers within organizations. The book, The Tipping Point, provides a framework for the consideration of data management practices to be implemented within organizations.

I believe that data management can benefit from a tipping point approach to its implementation. Little things making a difference is a direct articulation of our principle of using a relatively small amount of metadata to manage a much larger amount of data. We need to explore the possibility of creating positive epidemics of good data management practices precisely because these practices are contagious and they can cause change to happen dramatically. Proving to organizations on a small, feasible and obviously justifiable basis that good data management can achieve positive payoff within a single budget cycle while not easy, is definitely doable. The upcoming Wilshire Meta-Data and DAMA International Symposium will offer many opportunities to learn from the experience of others in a deliberately stimulating environment (see http://www.wilshireconferences.com/MD2006 for details).

The key to successful implementation is doing some of the little things that can make a difference for your organizations. Next month's column will explore key roles played by certain types of individuals: connectors, mavens and salesmen, and how they can help your data management program.

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