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# Modeling & Simulation

Article Review   by:LuriAnomBesari

Consider a consulting company which has 120 employees. These 120 employees are composed of 60 rookies and 60 professionals. The company wishes to maintain the total number of employees at 120 so it hires a new rookie for each professional who quits. Rookies don't quit! Professionals quit at a rate of 10 per month and it takes 6 months to develop a professional from a rookie. Additionally, the company bills out rookies at \$10k/month and professionals at \$15k/month. All 120 employees are fully applied (I know it's a pipe dream).

An I think model for this system might look like the following:

If you run this model you find it exists in essentially a steady state, and is about as exciting as watching paint dry!

Now, in the 10th month the company notices its revenue has dropped from \$1.5m/month to \$1.35m/month and it wonders what has happened. And where do you think it looks for the problem? All around the 10th month of course. And what does it find? The company finds that it still has 120 employees, yet there are now 30 professionals and 90 rookies. A most puzzling situation!

As it turns out, there was an organizational policy change made in month 3 which seemed to annoy professionals more than in the past, and the quit rate jumped from 10 to 15 professionals a month. The system, with it's built in hiring rule, essentially an auto pilot no thought action, hired one rookie for each professional that quit. What this one time transition in quit rate actually did was set off a 6 month transition within the organization leading to a new equilibrium state with 30 professionals and 90 rookies. The following graph represents this transition.

Thus, one of the real benefits of modeling and simulation is its ability to accomplish a time and space compression between the interrelationships within a system. This brings into view the results of interactions that would normally escape us because they are not closely related in time and space. Modeling and simulation can provide a way of understanding dynamic complexity!
Published: July 05, 2012
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