Price's Law
INTRODUCTIONDerek John de Solla Price (1922 - 1983) was a British physicist, historian of science, and information scientist. Price penned a law that states:
"In any area of science or enterprise, half of the total contribution is made by the square root of the total number of participants"
The law originally applied to scientific paper publishing. For example, if 100 papers were written by 25 authors, then 5 out of the 25 authors will have contributed 50 papers. However, it has proven to be valid in areas of business as well. If you have worked in a project or software development team, you will have observed that a few individuals perform at a higher level than their peers. Some individuals in a team will have higher productivity, are more self-managed than others and contribute more work than their peers. These are the individuals that exceed expectations. As a manager I've noticed his behavior first hand; there are star employees and then there are average and low performers.
When I was working at GE we had a process called the "vitality curve" to improve team productivity. We would assess the low performers, let them go on the basis of low performance and hire better performers. The goal was to incrementally grow a team with top performers only. This practice was also used by many other firms. GE eventually stopped using this performance method. You could say this was a way to beat the odds of Price's Law.
PRICE'S LAWSo how does this work? As an example, a software development team has 16 developers. The square root of 16 is 4. The law therefore implies that 50% of the software product contribution is derived from 4 developers. The other 50% of the software product was developed by 12 developers. This would imply that the top 4 contributors are potentially 3 times more productive than the rest of the team.
The table below illustrates this concept. As the team grows, the number of top contributors declines. Therefore a team size of 30 salespeople will have 5 top contributors and 25 low or average contributors according to Price's Law. The percentage of top contributors on the team is 18%. As the team size increases, the percentage of top contributors declines in relation to the team size.
Price's Law Example
As applied to business; given a sales team of 10, then 3 to 4 of them in a given year will generate 50% of the revenue.
The square root is an almost linear function but (x – square root) is an exponential function.
If the team were to grow to 40 salespeople, 6 to 7 of them would contribute 50% of the revenue.
Given that 7 out of 10 salespeople collectively contributed to 50% of the revenue, with a team of 40 salespeople, there would now be 33
salespeople (40 - 7 = 33) that contributed the remaining 50%. The takeaway is that as the team grows the number of
low contributors grow faster than top contributors; the number of low revenue contributors
in this sales team therefore grows exponentially as the team size increases. In summary, according to Price's Law,
performance is linear while incompetence is exponential .
The graph on the right, shows the top contributors in orange and the average contributors in gray for an increasing team size. The legend running along the horizontal axis shows the percent of staff that are top contributors as the team size grows from left to right.
This is similar to Pareto's 80/20 distribution stating that in many organizations 20 percent of the contributors will account for 80 percent of the results. In the software development context this would imply that 20% of the developers account for delivering 80% of the application/product.
Agile software development teams are kept small, typically from 7 to 10 resources, to keep lines of communication being overly burdensome but according to Price's Law, there is also an inefficiency consideration from growing a team too large, beyond 10.
According to Price, larger teams are less productive.
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