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Revisiting Expectations

Mini-Lesson #2


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One very simplistic but useful way of thinking about our career path is to imagine a very simple two-dimensional graph.

The horizontal axis of this graph represents your age. The vertical axis represents “professional success.” Now, you’re probably thinking to yourself: “Professional success? What does that really mean?” That’s a great question.

Professional success in this instance means different things: it could mean...

  • annual salary

  • social status

  • responsibility over resources and other people

  • impact on the world

Or, in all likelihood, it means some complicated combination of all of those things. Everyone will have a slightly different idea of what “success” means to them in their career and that’s just fine – this exercise works regardless of how you define success for yourself.

Such a graph would look something like this:

Now, let’s think back to the story of Rick that we encountered in Mini-Lesson #1. Rick was 52 years-old and had just lost his job as VP of Production at BOLT Industries – the company where he had steadily climbed the ranks for two decades.

Imagine having a conversation with Rick a month before he was let go and asking him about his expectations for the rest of his career. How do you think Rick would draw out his career trajectory on our simple graph? It might look something like this:

While the story of Rick’s career we encountered in Mini-Lesson #1 (steady upward trajectory for decades eventually punctuated by job loss) is a statistically common one, so too are Rick’s expectations as displayed in the previous graph. Many of us typically expect a career trajectory that looks something like the one that Rick drew above:

Now, back to Rick. Imagine you were talking to Rick a few weeks or months after he lost his job at BOLT. He asks you to help him map out his career trajectory moving forward so he and his wife could start to think about what the next few years might look like. What do a few possible career trajectories for Rick look like at this point? They might look something like this:

Obviously, it’s hard to say exactly what Rick’s professional future will look like (in fact, it’s impossible!). But in this updated graph there is something new for Rick to consider: his zone of possible professional futures.

This broader set of expectations will very likely contain Rick’s true career path. Thinking this way leaves Rick a little less likely to be caught off guard by the ups and downs of the rest of his career.


Now, it’s your turn. With your two pieces of blank paper, draw two graphs.

Drawing 1: For the first one, think back to a few weeks or months before you lost your job. Draw the career trajectory that you expected then with a single line.

Drawing 2: For the second graph, consider your situation today. Make sure to include your job loss and break in employment. For this graph, draw three lines: one where things go fantastically well in the future (“upper bound”), one where things really don’t go well at all (“lower bound”), and one that represents an okay or average outcome (“middle outcome”).

Now, compare your two graphs. Ask yourself:

 How does the line you drew in the first graph map onto your second graph?

 Would it be close to the “upper bound” of your second graph? The “lower bound”?

 What might that tell you about your expectations and how they might be adjusting to your new reality?

It’s important that you do the following questions in quick succession. Do not break in between answering them.

Question 1: Set a timer for 8 minutes. Focus only on the “lower bound” of your second graph. Write a short paragraph in an email that summarizes the imaginary scenario of how this “lower bound” outcome came to be and how your life looks different in that imaginary world than the life you live today.

Question 2: Set the timer again for 8 minutes. Now, focus only on the “middle outcome.” Write a short paragraph in that same email that summarizes this scenario. How does your life look in this imaginary life? In particular, what are some specific ways that it’s better than the “lower bound” scenario you just wrote about in Question 1?