Making "data-driven" 1099 decisions

"Data-driven" decision making is a pseudo business fad that describes a process in which executives or organizations use data analysis to make important decisions, in contrast to making decisions based on executive or organizational hunches.

If you're looking for a cool story about the successful implementation of analytics in an organization, read the book or watch the movie Moneyball which covers how the general manager of the baseball team the Oakland Athletics implemented an analytics program to recruit players based on data, rather than old-timer baseball scouts' intuition.

I say this whole thing is a fad not because there is no underlying value, but because organizations think they can click their heels and say "big data" three times and all their problems will be solved, which is obviously unrealistic.

As an aspiring 1099, you can actually use data to see if it makes sense to make the leap.

For example, one of the most common fears for people considering making the leap is that they're not good enough.

The trick here is not to spend a year in therapy trying to build your self esteem, but rather to look at the external data and assess whether that fear is based in reality.

Here are some examples of external data:

  • Client praise for your work
  • Your boss' praise for your work
  • The number of significant raises, bonuses, or promotions you have received in your career
  • The number of recruiter e-mails
  • The amount of money you make
  • The amount of money other companies offer you
  • The number of job openings in your field
  • The number of friendly professional contacts you could e-mail

Your feelings and intuitions are important pieces of data too, but it must be balanced against external data to make accurate assessments of your situation.

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