Long term career development paths in large institution or business corporation. Dynamic Simulation model of effect of expansion contraction
MJMcCann Consulting
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Once upon a time...
In the days when people had lifetime careers in one major corporation, we looked at the long term effect to be expected from shifts in corporate growth rate. Similar issues affected, and still affect, any large organization, institution or administration such as the military, armed services, police and civil service. We could see disparities appearing between divisions of the same company, apparently operating similar career development policies but getting different age vs grade (rank) distributions.

Important Factors
We had heard of policies in the armed services like "If you don't make 'Major' by 40, you're out" and "No one stays beyond 55" as being essential to control the 'more admirals than ships' effect.
So what did this mean for a commercial operation, growing fairly steadily overall, seen as a good employer caring for its staff? At the time the Personnel Department (that name shows this was done a while back!) was thinking long term as being three or four years and were planning recruitment on the basis of business plans that rarely went further. But those of us on the staff and the new recruits were looking at lifetime commitments.
Different divisions of the company were growing at different rates and the faster growing ones had younger senior managers appearing, despite policies that would allow moves between divisions to fill vacancies as they appeared. We could see stresses appearing and a mismatch between what was 'policy' and what really happened.

A Mathematical Model
To get a quantitative handle on what was going on we analysed the internal demographics of an entirely hypothetical corporation. (That was politic, of course). This corporation had say, ten thousand employees, the layers of management were set up with a fixed, uniform fan-out ratio (number of subordinates per manager, e.g. five to one).
Thus for any given growth rate we could define the new size for each period of analysis, hence the number of new recruits (young) required, the number of promotions to fill the growing managerial needs and hence the shift in age vs grade demographics in the corporation.
With such a model we could see the effects of getting recruitment out of step with needs, of death in service (not much, this wasn't the military), retirement (usually in those days at age 62 to 65), changes in fan-out ratio, or any other policy or social effect.

What we saw
The military policies made good sense. The fast growing divisions couldn't get managers by transfer as there were not enough suitable spares, but it only needed very small differences in growth rates to give big differences in career prospects.
Any large organization with long term pretensions needs to know the effects to be expected from its recruitment policies and organizational structure (fan-out ratio and where promotions come from, as examples).
The analysis is too complex to be done with pencil and paper. HR departments need quantitative help.
For us personally, the warning was there to see: Make sure you are in a growing organization... Well you can always hope.

Other Experience
My experience with problems over these time scales is that people rarely expand their time horizons far enough to see the whole picture. Even if they try, they tend to miss interaction effects and think more in terms of extrapolating, sometimes with statistical models, from the recent past. My (MJMcC) observation is that the demographics and the compelling force of reality can be quantified to make a big improvement in perception. You only have to contact me to get help!

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Invitation. McCann can help if you have a design or operational problem that needs some technical support that is outside your team's experience, some quantitative assessment of what is really the cause of the difficulties, some design alternatives or just a fresh look by an intelligent interrogator.
If you have a problem with the behaviour of a market sector, plant, process or item of equipment and would like to get a quantitative handle on it to improve yield or optimise performance, then contact me. I'm always ready to give a little time to discuss a new puzzle, in confidence, of course. We'll only worry about fees when there is some defined work. I can be flexible about how I work with you.
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Dr M.J.McCann,
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E: mjmccann@iee.org
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