I once had a top executive from a US Bank in a workshop who explained a worthy aim for her organisation – they wanted to increase the representation of minority ethnic groups among their senior staff to better reflect the wider population. The bank had gone very public with this objective, to send a strong signal that it was an equal opportunities employer at all levels.
At the time, the senior cohort included about 10% of people from the defined groups, and management had set a target to get that representation to 25% within 5 years. That only means switching 3% of the cohort each year. So surely that would be do-able right?
Turnover among the senior cohort was running at about 10% per year, implying that minority groups would have to make up 4 in 10 of each year’s promotions (1 to replace the minority individual among each 10 retirees + 3 to drive the desired change.
But minorities only made up 15% of the mid-level staff, so promotions from the middle ranks would have to run at nearly 3x the rate of promotions among non-minority staff. And there were nowhere near the number of mid-level minority staff with enough experience to step into senior roles, even if the bank cut the experience requirement substantially.
… and the problem repeated at the mid-level – not enough junior staff from minority groups to fulfil the faster promotion rate to mid-level that was needed to replace those who had been moved up to senior levels
… and they already struggled to find enough qualified minority college graduates to hire.
My friend from the bank was shocked to realise that their very worthy objective – heavily publicised – would be thwarted by simple physics!
What they could do was raise minority representation amongst those promoted each year, but even the fastest rate they could achieve would take many more years to raise representation among the senior population to the desired level.
Understanding and managing how staff numbers change over time is complex enough, given the many moving parts in the system – hiring, promotion, transfers and turnover at all levels. Promote too slowly, for example, and you may lose frustrated juniors. But those dynamics change the experience at each level too – promote too fast and you shrink the experience at both the junior level and the next level.
See a workshop recording and more on this issue in my post ‘HR gets Dynamics‘.
A digital twin model of your staffing system can play out exactly how and why all those numbers have changed over time as they have, and project forward how they will likely change under alternative policies. This is one class of resource pipelines you can learn to model and use in class 6 of our Dynamic Business Modeling course.