My D.O.E

When I decided to ditch my over a decade career in engineering and ventured into Human Resources, I didn't exactly know what I want to ended up as. It was like playing back my 1980's memory of being asked that lame question of "What do you want to become when you grow up?" Ironically enough, I remember being confident with my answer...it was either Lawyer or Teacher. I really am envious with that confident 8 year old...what have happened to her since then? Why am I no longer have that humongous confidence to announce to the world of what I want to 'grow' up into?!

Through out my journey on seeking that 'ideal' job, I begin to realize that I am actually going through a huge experiment. Sadly though, I am the lab rat. I thought that the best way to derive a conclusion of this experiment is to use DoE which I have learned and applied during my tenure as a design engineer for Motorola. Design of Experiment (DoE) is a structured, organized method that is used to determine the relationship between the different factors (Xs) affecting a process and the output of that process (Y). This method was first developed in the 1920s and 1930, by Sir Ronald A. Fisher, the renowned mathematician and geneticist. While I can not guarantee the accuracy of the formula I have came up with, but it sure does eliminate the 'white noise'.

Let's say, the output (Y) that I seek for is 'happiness @ work'. From my experience of 13 years earning an income as a living, my Xs are:

F(happiness @ work) = f(boss; gender & race) + f(work nature) + f(environment/culture) + f (income)

1st stop; R&D Engineer @ Robert Bosch Penang
Formula = F(happiness @ work) = f(male European) + f(R&D, creative, always changing) + f(coorperative) + f(moderate $)
Output = okay

2nd stop; R&D Engineer @ Motorola Penang
Formula = F(happiness @ work) = f(male American) + f(R&D, creative, learning) + f(cooperative, respectful) + f(high $)
Output = Happy

3rd stop; HR Consultant @ Motorola Singapore
Formula = F(happiness @ work) = f(female chinese) + f(HR, administrative) + f(competitive) + f(high $)
Output = Miserable

4th stop; HR Senior Manager @ Mimos, M'sia
Formula = F(happiness @ work) = f(female Malay) + f(HR, administrative, strategic) + f(complacent) + f(high $)
Output = Miserable

5th stop; HR Consultant @ Consulting firm
Formula = F(happiness @ work) = f(male chinese) + f(HR, strategic) + f(competitive) + f(moderate $)
Output = unhappy

There you have it, the various findings at various stops so far. Using the following scale, I studied each X factor and determine whether or not they play a role as a determinant of my Y.
0= miserable (can't bear it)
1=unhappy (dragging my feet to work)
2=okay(not looking fwd to work, but don't drag my feet either)
3=happy (feel belong and add value)
4=Estatic! (looking fwd to work every day!)

1st X factor = Boss
1st stop --> (2)okay = f(male European)
2nd stop --> (3)happy = f(male American)
3rd stop --> (0)miserable = f(female Chinese)
4th stop --> (0)miserable = f(female Malay)
5th stop --> (1)unhappy = f(male Chinese)

Conclusion = x(boss) = gender does not play a role. Race seems to have an effect. I work well for non-Asian boss.

following the same deduction method, I reach the following conclusion
x(work nature)= I am happier in R&D than HR
x(environment/culture) = I am happier in cooperative environment than competitive or complacent
x(income)= money seem to have no impact to my fulfillment at work

Hence, in DOE terms, my finding can be concluded as below;

F(happiness @ work) = f(non Asian boss) + f(job which deals with things,not people) + f(cooperative culture)

There could be more X factors which I have not considered since I have not experienced them (i.e having no boss at all), but I'll improvise my formula as I go. But as of today, the above is good enough determinant should I decide to apply or accept a new job offer...or maybe try an entirely new experiment to have a career break!