I was doing some of my Sunday lazy reading through Twitter when I came across the following “tweet-report” about the kind of jobs that make people happier, and it triggered one of my lifelong obsessions. It was my random call to action. I consider myself significantly happy at work, but I have always wondered, can we objectively measure and quantify the attributes of a job that influence happiness in order to build some kind of (completely subjective and “unscientifical”) recipe to help people target jobs which can potentially bring them more happiness?

For those of you who don’t know me or my background (hopefully lots of you, as that would mean that not only my family and friends read my posts), I started my professional life working as a researcher at university, until I moved to the corporate world, where I have always been involved with innovation and R&D (visit my Linkedin for further details). After interacting with people through my professional life I have realized the following: people with a clear mission or goal are happier in their jobs. My “business owner” friends, as well as my colleagues at R&D and University all have missions, they work with a clear target in mind. They don’t work for the sake of working or “simply earning money”, they wake up every day with a goal in mind that motivates them. And they, as me, seem really happy about it. They are happy about being obsessed with their job and their mission.

Let me build up on this for a moment. According to the aforementioned report, people at white collar jobs are generally happier than people at blue collar jobs (let me add that I hate this way of classifying jobs, but it comes pretty handy for my current discussion). This seems like a clear result of what I just mentioned. Blue collar workers definitely work for money. They most probably aren’t aligned with their employers or companies’ goals, and they see their jobs as monotone means for making a living, without a mission in mind.

White collar workers, or at least the ones I’ve met which curiously all had clear missions, on the other hand, see their jobs as a challenge and a mean to reach their personal goals. This motivates them to wake up early every day, and happily go to work. A mission can range from “building a passive mean of income to be the owner of my time” (personal), to “curing malaria and putting an end to hunger in the world” (philanthropic), or “building a new payment system to make people’s lives easier” (social, professional). These missions may be completely personal, or they can be aligned with your company mission. What is clear is that the happiest people at work I have ever met all had a clear mission, or at least where aligned with their company’s mission (of course, first thing’s first, and apart from having a mission you have to love what you do).

Something that we should not forget is that even when people love their job, they still need to make a living, and here is where some second order variables come to play in our discussion, such as social benefits, salary, company ethics, etc. You may be aligned with your companies objectives, but if you are doing an excellent job and offering great value to your company and not being consequently rewarded (psychologically, economically, and every other “-*ally” someone values) this can lead to frictions that reduce a person’s happiness at work. Nonetheless, individuals with a strong mission will definitely cope better with all these frictions (a fact that may be seen clearly at business owners).

Now with your permission, my dearest reader, I will take the liberty of defining happiness at work as a function of all the variables which have appeared along our above discussion in an attempt to summarize my ideas in a more mathematical and “quantifiable” way:

Happiness at work equation

Where each α represent the specific factor of preference and sensitivity of an individual to different dimensions and aspects of their jobs (some of which have been slightly presented during my discussion). Thus, the following vector defines the specific preferences and sensitivity of an individual to these dimensions:

Individual’s Sensitivity Vector

You may see that my proposed equation is divided in to two parts:

A base happiness factor defined by the sensitivity vector of an individual to different job dimensions. It is without doubt that a worker with a higher salary and better social benefits and a work-life balance, even if he does not have a clear mission, will most probably feel happier at his job than someone with a lower salary and worse overall benefits.

What I call the “mission factor” measures in what extent an individual has a clear mission at work. This factor multiplies the base happiness factor and increases the base level of work happiness. Inside the mission factor there is another variable to take into account at this level, the monotony at work. Even if two workers have no clear mission, the one with less monotony at his daily job will definitely feel happier than the other one. Monotony affects happiness negatively.

I came to this equation after working at several jobs, some observational work and a lot of thought and reflection. This is the better way I can find to “a priori”, and without deeper knowledge, identify how happy a worker can potentially be at his job. I’ve been trying to test this equation empirically for a while, so I am thinking about interviewing some of my colleagues and friends to empirically validate this equation and see how accurate it is predicting their happiness at work. Cool experiment, right? Follow me in Twitter to stay tuned and contact me if you want to be part of this fun experiment.

This discussion about “happiness at work” is something I have always been looking forward to formalizing. I would really appreciate feedback and further improvements to this discussion. Work represent a high percentage of our waking hours, let’s try to be happy in them as much as we can. If from the feedback I receive I see interest in this topic, I will transform this “fun experiment” into a more serious parallel project. See you soon!

Idea of the week #1