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“To cease smoking is the easiest thing I ever did; I ought to know
because I've done it a thousand times.”
- Mark Twain
The Time-Behavior Model
To achieve goals that matter, many have recognized the need for long-distance strategies over the quick-win sprint. Our brains, however, are built to respond to the siren of the big-win when the opportunity presents itself. The managers of lotteries and credit-card companies know this psychology better than their customers.
The ability to focus on the long-term requires more than moral exhortation. It requires a way to see our relationship to time from the point of view of multiple timescales. We call this “Seeing in Time.” With the ability to see the consequence of behaviors with different timescales, it then becomes possible to make choices among those behavioral options. To frame the analysis more precisely, we have developed a model of time-behaviors that accounts for both incremental time-effects and the powerful network effects of behavioral replication.
Time-behaviors are divided into four categories:
- tØ-behaviors reflect short-term events that are the noise of life. TØ events include both urgent reactions to emergencies and responses to the small, but frequent demands of email, cell phones, news and entertainment media, ordinary conversation as well as the continuing, semiconscious input of our senses as we navigate our most immediate world.
- A t1-behavior is the first of three types of persistent time-behaviors. It consists of a series of linked similar events or activities, which produce a cumulative impact on an individual or organization. T1 effects often grow exponentially or according to a logistic curve where there is a limiting factor restricting potential impact.
- t2-behaviors are t1-behaviors that are replicated across a population from a central point. A corporate policy that establishes incentives for wellness practices, such as exercise and weight loss, follows a t2 model.
- t3-behaviors are similar to the t2 category, except that each node becomes a source for propagating the t1-behavior across the network (the population or social group). There are many examples of t3-behaviors: changes in music purchase behaviors among iPod owners; patterns of commuting between home and work; the social enforcement of best practice in work groups; adoption of new patterns of consumption -- from the use of soymilk at Starbucks to production of chicken in China.
From a mathematical standpoint, it is generally the case that impacts of persistent behaviors overwhelm the effects of short-term events (tØ behaviors). Long-term investment behaviors dominate the impact of individual trades. Long-term habits that postpone the onset of chronic disease can affect individual and public health more than improvements in specific procedures.
The time-behavior analysis tools make the consequences of time-behaviors visible. They enable us to identify the behaviors that are most important and the effects of continuing or changing those behaviors. Time-behaviors depend on a support system that we call the time-behavior infrastructure. In an organization, the infrastructure consists of the policies, norms, monitoring procedures, communication mechanisms and other management practices that encourage the implementation of core t1-behaviors. T1-behaviors form part of that infrastructure. There is a matrix of t1-behaviors that sustain the core behaviors and culture of the organization. Understanding the basis by which these behaviors are sustained enables a corresponding understanding of how the behaviors can be changed.
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