I have had the opportunity to talk to many college going students and fresh college passouts about their goals, and most of the time I hear them talking about ‘getting a job with highest possible salary’. Everytime I end up telling them to look for jobs with learning and growth potential instead, and most of the time I get the look of ‘what about money then?’. It takes some explaining, but I guess I am able to get through the point that I may be right. They still have gone ahead and ignored my advice, but I guess that is what free advice deserves!
I strongly believe that focusing on learning and growth potential at the start of the career is very important, money is probably the least important parameter. Here is a typical picture that I draw to illustrate my point. Note that the axis has salary, because that is the most measurable aspect of career development still.
Each of the curve above plots salary at a given point of time in one’s career. For simplicity, I have used straight line progressions for salary, actual progress will be a more complex curve, but straight line will prove the point. A, B, and C are various different types of salary progressions one can have in his/her life.
Let’s take A. This shows a steady increase in salary, but starts from a lower base. It increases rapidly in mid-years, and then tapers down towards the end since rate of increase of salary goes down as base salary becomes very high. This is a very desirable growth curve.
Contrast this with B. B starts with a higher salary, but the rate of change is less dramatic than A, but keeps increasing at a fair pace. As I said, towards the end, all curves taper. This is a good growth curve.
Let’s take C. It starts with a much higher salary, but the curve is very flat. So salaries change pretty slowly, and may barely take care of inflation. Of course this is extreme, but I have seen many people struggle with such a salary growth curve.
Points E1, E2, E3, and E4 are the times when one or more curves intersect, which is the number of years it takes someone on one of the growth path to overtake (or fall behind) someone on the other growth path.
Another useful metric to keep in mind is total earning over the career. TE=S x E (salary for a particular time interval), which is nothing but the area under a particular growth curve. So if the goal is to earn as much as possible over the entire career, it is important to look at the salary curve, and not just the starting point. In fact, in the example above, starting salary is negatively correlated with total earnings. Of course, that is not always the case, but it could be.
So, moral of the story is that look at more aspects than just starting salary to optimize the return on your career investment. The shape of the salary growth curve is defined by lots of factors, but all of them measure same thing: how valuable are you to the organization you are working for. And this value goes up only when you have something to offer, which in turn comes from various learning, industry experience, technology exposure and many other technical and soft skills.
How this curve unfolds depends on how you manage your career. Predicting what such a curve might be for you could be difficult but not impossible. I will talk about some facets of this in my subsequent post.
6 thoughts on “Career management gives better return on your talent investment”
I’m curious to know how did you plot the graphs A, B and C. It is one thing to draw things by imagination and quite another to draw graphs based on facts. Your theory will be credible only when it is backed by data and not by some pretty graph you conjured up to prove some point.
Thanks for your comments. This graph is illustrative only, a pictorial description of the word descriptions I provided about the various ways salaries might grow. Of course, if I plot the actual salaries of the people I had in mind when I wrote this, I will get a similar graph, but I didn’t see the need to do that. I understand your point about ‘backing by data’, I should have been more clear about the nature of this graph.
Invaluable information. Thank you very much.