Quote of the Day
If men are to be precluded from offering their sentiments ... the freedom of speech may be taken away, and dumb and silent we may be led, like sheep to the slaughter.
— George Washington
Introduction
I recently had an employee retire in my group that caused me to look at the age distribution within our entire HW organization. After seeing the age of our engineering staff, I made a proposal to our management team for ensuring that the skills of our senior staff members were being transferred over time to our junior staff members. This post shows how I presented the age information to internal management. The presentation was successful, and I thought it would be useful to show here.
The data presented changes the names of the managers, and the data itself has been altered for privacy reasons. However, the overall message of the data is the same – nearly half of our engineers are 55 year old or older. These are also our most skilled employees. We need to begin working on transferring their skills to more junior staff. We are not the only companies faced with the graying of their workforce – NASA has been working on the problem for a number of years (Figure 1).
Background
Constraints
At my company, I am not allowed to know the age of individual employees. However, I can request data on the individual ages within Hardware Engineering without names attached. I requested this data and was able to generate a plot and produce some useful tables, which I show below. Note that I have modified the names of managers and altered the exact age data, but kept the overall message the same.
I arbitrarily chose 55 years as the age at which we need to beginning considering succession planning for an employee.
Tools
I analyzed the data using Rstudio. The actual tables were generated using Excel, because I like the look of Excel pivot tables. The raw source files are included here.
Analysis
Employee Age Distribution
Figure 2 was the chart that generated the most discussion. It showed just how many engineers that we have who are 55 or over. Note that some people are the same age, and I used ggplot2's jitter feature to show people of the same age by adjacent dots.
Employee Age Percentages
After showing the chart above, I then presented Figure 3, which shows a table of the percentages of our employee ages aggregated by manager and age group (less than 55, and 55 and over).
Conclusion
With nearly half of our hardware engineers with an age of 55 or over, we have quite a bit of work ahead of us.
The report can be made more comprehensive with the information about those 55 and above by skills they possess and what else they can do for the benefit of both the organisation and the staff.
That is a good idea. I think I need to create a graph that shows the critical skill sets and the fraction of those skills represented by the 55 and over group.
Thanks.
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