
They then had the computer software randomly generate "individuals" who had "competence" values ranging from 1 to 10, and ages ranging from 18 to 60. If an individual was incompetent (a value less than or equal to 4) or of retiring age (60) they were removed, a spot opened at that level, and an individual from the next level down was promoted to fill the vacancy. Several strategies were applied: 1. the "best" approach, where the most competent at a given level was promoted, 2. the "worst" approach, where the least competent person was promoted, and 3. the random approach, where the individual that was promoted was chosen at random. Each of these strategies was applied for the two hypotheses being tested: 1. The common sense hypothesis, where an individual's level of competence transfers from one level to the next (i.e. it is assumed that good floor sweepers generally make good managers, though the authors did build in a possible swing of plus or minus 1 point allowing that some floor sweepers could be slightly worse, or even better, managers than they were sweepers.) 2. the Peter principle, where a person's competence did not transfer to the next level with their promotion, but rather competence at a new level was again randomly assigned. Finally, the measure of success for each of these methods was a valuation of the company's "global efficiency" which was calculated by adding up the competence values at each level and weighting them more as the level approached the top of the company (basically assuming that better or worse performance at the top of the company would have more of an effect on the overall performance of the company than competence or incompetence at lower levels). What the computer simulations showed is that when the common sense outcomes applied (that is, when competence was basically the same from one level to the next) and you promoted the best people at each level, not surprisingly, you got very good global efficiency for the company. When the worst person was promoted, the company had pretty lousy efficiency. What was surprising was that if competence at one level had no effect on competence at another level (the Peter principle) then promoting the "best" person at each level actually resulted in the worst global efficiency, and promoting the "worst" person at each instance resulted in the best global efficiency. Finally, under both hypotheses (common sense and Peter principle) promoting people at random resulted in small increases in global efficiency. From this, the authors conclude that, if you don't know whether common sense principles or the Peter principle is at work, your best bet would be to promote individuals at random because even though the effect was small, you would always get an increase in global efficiency rather than risk the loss in efficiency that would result from using the best strategy if the peter principle really is at work. And, of course, since we don't know if the Peter principle really is at work, you wouldn't want to risk promoting the worst candidates only to find the common sense principle was right. Of course, there are definitely some considerations that need to be made before instituting the random promotion policy. First, I think the assumption that a highly competent person at one level (a 10) could be so inept at the next level to be randomly assigned a 1 and then be fired (even if the probability of this is small, since the re-assignment is not totally random, but falls along a normal distribution). To me, if you excel at one job, you likely have skills that apply at every level (being punctual, organized, responsible, hard working, smart, easily trainable, etc.) Therefore, I would like to see the simulations re-run with promotions in the Peter principle assigning random values between 4 and 10, rather than 1 and 10 (or at least skew the distribution more to the right). Second, I think that even if you tweaked the game this way, and it still came out that randomly promoting people was the better strategy, one still has to consider the repercussions of a random promotion policy that might kill the incentive for workers to excel at their job (since they know it will have no impact on whether or not they get promoted). Ultimately, I think that this would lead to the majority of employees operating at a level of competence just high enough to not get fired. Still, the article is interesting, and suggests that the Peter principle is something that companies and other hierarchical institutions need to be wary of, and perhaps, look for a better way to assess the skills that will be needed at each new level and base promotions off of a combination of excellence at the current level and this potential for excellence at the next level.
Figures were taken from the article, the reference for which is:
Pluchino, A., Rapisarda, A., & Garofalo, C. (2010). The Peter principle revisited: A computational study Physica A: Statistical Mechanics and its Applications, 389 (3), 467-472 DOI: 10.1016/j.physa.2009.09.045

Many thanks for your nice quotation of our work. I'm Andrea Rapisarda one of the authors of this study. Of course our simulation is very schematic
ReplyDeleteand we did not include any psychological effect.
However evolution in nature proceeds in the same way by random mutations which give a finite probability of success even to the most remote possible changes, reinforcing (and not removing) them when they are successful. We have had a lot of positive comments see here for example
http://spedr.com/3gkuu and we have just discovered
also a real experiment applying a successful job rotation (very similar to what we have found). You can see here some info http://spedr.com/vk3c
Best regards
Andrea Rapisarda
http://www.dfa.unict.it/home/rapisarda/
Thanks for the info, and congrats on the paper and on the award. The paper is most certainly interesting, and even more so if you are finding real life examples to support your model. I have had an intuitive understanding of the Peter principle for years, but only thought about it in the context of corporations and other hierarchical "career paths". I will have to give this some thought as to how it pertains to evolution/adaptive peaks, and perhaps how it might map to the fitness of a species based on whether or not the mutations within the population are completely random or not. In the meanwhile, perhaps I will check out the story of Ricardo Semler and his company.
ReplyDeleteCheers,
Brad
I am a consultant that markets talent management selection and development psychometric tools. The tools I market utilize criterion-related validation which means that are validated against on the job performance.
ReplyDeleteGiven my above context, how would you propose I use the Peter Principle in my psychometric product marketing?
If you like the book Sleights of Mind I would think you might also like Dan Ariely's Predictably Irrational
ReplyDelete