The Fiercening of Individual Competition
Following up from the previous post: How can we measure the fiercening of individual competition?
Answering the question requires finding a common scale to measure both the impact of individual decision-making, and the nature of an individual’s task environment.
The Age of “Me Inc.”
On August 31, 1997, Fast Company published an article written by Tom Peters, titled “The Brand Called You”, and with the following sub-title:
- “Big companies understand the importance of brands. Today in the Age of the individual, you have to be your own brand. Here’s what it takes to be the CEO of Me Inc.”
Peters’ article goes on to explain that the professional services firms exemplify the understanding of personal branding. They see people as their only asset, managing them to compete aggressively with one another to deliver value to clients:
- “…if you’re really smart, you figure out how to distinguish yourself from all the other very smart people …”, and
- “… you create a message and a strategy to promote the brand call You.”
- “You are the CEO of your own company, Me Inc.”
The article closes with a dual prediction of (i) the disappearing protections offered by membership in vertical organizations, rank on career ladders, and other group affiliations, and (ii) the rise of the individual standing alone, and fully responsible for the perceived value of his portfolio of projects.
However, Peters’ ideal individual brand seems limited to the feature-benefit model that works on time, on budget, real-time, and all-the-time: a model with low variance, and no bias in a world of projects - not jobs - running on an accelerating competitive treadmill.
A Common Scale to Measure Impacts and Types
Carlo Cipolla’s paper, published in English ten years before Tom Peters’ “Me Inc.” manifesto, provides a tool to map the fiercening of individual competition. See Cipolla’s original chart in an earlier post shown at the link below.
This post quantifies the x/y axes of Cipolla’s orginal chart with the statistical distinction between precision and accuracy. See chart below.
Statistical thinking best applies to “Small Worlds”, such as games of chance, where population parameters exist with true and fixed values. Playing in small worlds means creating random samples that will display variations from these parameters.
Accuracy relates to the closeness of sample observations to the population parameters, “The International Vocabulary of Basic and General Terms in Metrology defines accuracy of measurements as follows: “… closeness of agreement between the result of a measurement and a true value.”
Accuracy is measured with an estimate of bias: the difference between the expected value from the sample, and the true value of the parameter.
Accuracy looks at a benchmark outside of the individual sample. Thus, accuracy works as a quantitative measure to estimate a benefit (high accuracy), or a damage (low accuracy) to others on Cipolla’s chart.
Precision relates to the variation of sample observations. It is measured with an estimate of variance, the variability of a specific sample around its expected value.
Precision looks inside the individual sample. Thus, precision works as a quantitative measure to estimate a benefit (high precision), or a damage (low precision) to self on Cipolla’s chart.
Finally, taking the perspective of Gerg Gigerenzer in “Heuristics” where he describes Herbert Simon’s ecological view of individual behavior, and differentiates it from the traditional “internalistic” view, we add a diagonal from top-left to bottom-right on Cipolla’s chart. This diagonal creates a boundary between two different types of task environments for individual decision-makers;
- “Small Worlds” task environments have conditions with both good accuracy (against known & unknown parameters), and good precision (low variance), and
- “Large World” task environments have conditions with both poor accuracy (against unkown & unknowable parameters), and poor precision (high variance).
Source: Gigerenzer, Gerd, Hertwig, Ralph, and Pachur, Thorsten (20110, Heuristics, The Foundations of Adaptive Behavior, Oxford University Press
This last step means that we can use the same scale on Cipolla’s chart to measure both the impact of the decision-making process of individuals, and the nature of an individual’s task environment.
Matching Decision-Making Processes with Task Environments
Under the traditional internalistic view of human behavior, Cipolla-intelligent individuals, in the upper-right quadrant, make decisions that benefit themselves using decision-making tools and behaviors that deliver high precision (low variance) toward their goals, as well as high accuracy (low bias) with respect a group benchmark. They benefit themselves as well as others.
Conversely, Cipolla-stupid individuals, in the lower-left quadrant, make decisions that harm themselves with decision-making tools and behaviors that deliver high variance (low precision) toward their goals, as well as high bias (low accuracy) with respect to a group benchmark. They harm themselves as well as others.
However, under Herbert Simon’s ecological view of human behavior and decision-making, individuals optimizing with mathematical models in the Large World of low accuracy and low precision task environments will harm themselves as well as others. Optimization becomes brittleness, not goodness.
Conversely, individuals acting on the basis of single-focus, narrated heuristics (or reference narratives) in such Large World task environments will often benefit themselves as well as others. Simplification becomes goodness, not shortsightedness.
The fiercening individual competition comes from Peters’ observation that:
- “… everything you do, and everything you choose not to do – communicates the value and character of (your) brand”, and
- As we should all know by now, the Internet-never-forgets, and never forgives.
This competitive individual branding treadmill will not stop, but we can control its speed when we manage our brand (our promise of value as impacted by our decision-making process and behaviors) based on our awareness of the matching task environment:
- When should we use math models?
- When should we use reference narratives?
Winning in the fiercening of individual competition means using a decision-making process that matches the task environment.
Mapping the Types of Tasks Environments
Quantifying Cipolla’s chart with the dimensions of accuracy and precision makes it possible to differentiate tasks environments as follows:
- Cipolla-Intelligent:
o Known (good accuracy)-Knowns (good precision) task environment
- Cipolla-Helpless:
o Known (good accuracy)-Unknowns (poor precision) task environment
- Cipolla -Bandit:
o Unknown (poor accuracy)-Knowns (good precision) task environment
- Cipolla- Stupid:
o Unknown (poor accuracy)-Unknows (poor precision) task environment
Future posts will match task environments with individual decision-making styles, tools, and branding models.
“CTRI by Francois Gadenne” connects the dots of life-enhancing practices for the next generation, free of controlling algorithms, based on the lifetime experience of a retirement age entrepreneur, and as the co-founder of CTRI continuously updated with insights from Wealth, Health, and Statistics research performed on behalf of large companies.