Making hard choices

From time to time, we all have to make some hard choices in life. Recently I went through just such a time, when I found myself with 3 different job-offers, that I had to act on relatively swiftly. Now admittedly, this situation belongs to the luxury category of problems, but none the less, it represented a serious decision making challenge to me. None of the jobs were perfect in all aspects (I don't believe such a job exist), so depending of the time of day, I would lean towards one of them, only to change my mind later on that very same day. Clearly, I was in need of a more objective and systematic way of analyzing my options.

Prioritization and rating

A simple pro-con list did not do much for such a complex scenario, and neither Google nor any of my "self-help literature" had any obvious tools. However, by attacking the problem in a divide-and-conquer fashion, realizing one can't compare apples to oranges, things started to look a bit more clear to me.

Aspects identification and prioritization
I started by listing a bunch of "job quality aspects" such as salary, commute time etc. and then rearranged these in a prioritized list. The least important aspect got a priority score of 1 associated with it, while the most important one got the highest (in my case 9 since I had a total of 9 different aspects identified). Being forced to classify and prioritize one unique aspect over another is essential in avoiding getting almost the same score for each job.

Aspect rating for each job
After aspect identification and prioritization, I gave each job a rating between 1 and 9 for each aspect. A job with a long commute would get a lower score than a job with a shorter commute and so forth.

Weighted score
Now it's time to multiply the aspect priority with the rating in order to get a weighted value. This way, a job with a lower pay but shorter commute, could trump a job with a higher pay and a longer commute, if commute time priority is higher than the pay.

Total score
By accumulating all the weighted values for each job, a total sum is obtained which can be directly compared to the sum of the other jobs. The job with the highest sum is likely the best choice! Some will argue that the sum should be divided by the number of aspects in order to get an average, but that just changes the scale, the relative outcome is exactly the same.

Example: Choosing between 3 jobs

As a software developer, I have some job quality aspects which will be hard to understand to non-developers. It doesn't matter so much if you understand what is important to me, but it should allow you to see how it plays out in practice.

In my case, company B won out with quite a way down to company A and even further down to company C. Now, it just so happens that this result matched well with my gut instinct. Whether or not it holds out in real life as well, remains to be seen of course. :)

I have shared the spreadsheet on Google Docs, feel free to give it a try with your own difficult decision making. Just remember, I am not responsible for what you may choose - I simply wrote down and shared my thoughts. Also, if this is a known methodology or you think its flawed, please let me know in the comments!


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