Around a year ago I found myself thinking that it was time for a career change. Architecture (the kind where you design buildings) was the only profession I had ever known, and while I loved my work I wondered what else the wider world could offer me. Yet, several months of soul searching — including talking to various professionals, attending university open days and researching online — did not get me any closer to selecting a new career. The number of choices was so great, and the array of pros and cons for each choice was so complex, that I just could not see the proverbial wood for the trees.
So I decided to use a spreadsheet to quantify my soul searching options. As a geek, I love spreadsheets and routinely use them for everything from managing house renovation projects to picking where to buy my favourite perfume.
My new spreadsheet mapped all my career possibilities— a total of six — combined with the means of achieving them (such as “MSc course” or “self taught”), against eleven carefully selected quality metrics that were important to me. I allocated a score of 1 to 10 (1 being the worst and 10 the best) to each one of the six possibilities against each quality metric.
These were my six career possibilities (or career paths):
- Urban planner:
Planning MSc course at UCL (London)
- Urban planner / environmental specialist:
Planning / Environment MSc course at Westminster University (London)
- UX designer:
MSc course in HCID at City University (London)
- UX designer:
Self taught + short paid course
- Specialist in building health:
Health of Buildings MSc course at UCL (London)
- Remain in construction:
Stay in my current job or find another job in the same field
The quality metrics
I picked these particular quality metrics after examining my own values and beliefs and how these related to my professional life. These metrics were unique to me, although they had partly been inspired by Richard N. Bolles’ excellent job seeker’s book, What Color Is Your Parachute?
The 1-to-10 scoring I gave to each metric was subjective; but it was good enough for my needs and had grounding in my previously conducted career research.
Here are the metrics I used:
- Work/life balance. A stable and functional balance between my career and other aspects of my life.
The greater the expected work/life balance of a career possibility, the higher the score given to it.
- Job satisfaction. How happy will I be getting out of bed every morning?
Careers with expected greater satisfaction are given a higher score.
- Salary (initial). As a newbie in an unfamiliar field, I expect my initial pay to be lower; whereas if I were to stick around with my status quo (construction) I could maintain my previous salary level.
Careers with higher initial salary prospects are given a higher score.
- Salary (long term). The six possible career paths on my list have different pay distributions and pay ceilings.
Careers with higher long-term salary prospects are given a higher score.
- Crusade factor. How much is this career about saving the world? How well does it match my own personal crusade for a fairer and just society?
Careers with a higher ‘crusade factor’ are given a higher score.
- Education quality. Some careers on my shortlist may need a brand new formal education; whereas with others, I could attempt self schooling. Also, various institutions differ in their quality of education, and this disparity is reflected in this metric.
I have given a higher score to career paths where I expect the depth, breadth and structure of education to be superior. I have also given a low score to self-schooling — as I have a strong preference for institutional education over self-education.
- Ease of finding first job. If I switch to an entirely unfamiliar field I may find it harder to waltz effortlessly into a new job.
The easier the process of finding the first job, the higher the score.
- Conversion time. How long will the switch take?
A shorter conversion time is given a higher score.
- Conversion cost. This ranges from expensive Masters courses to cheap self schooling.
This metric assumes that cheaper is better and gives cheaper options a higher score.
- Career flexibility. Once I commit, am I locking myself into this choice or does it keep my avenues open?
The greater the perceived flexibility of a career path, the higher the score under this metric.
- Comfort zone. Some career paths could push me quite far from my comfort zone of architecture and construction.
This metric attempts to measure my level of comfort for each of the career paths. The greater the perceived comfort, the higher the score.
Charting it up
I used a simple radar chart to visualise my spreadsheet (using the Google Sheets chart tool and a bit of Photoshop). I was expecting the chart to highlight one or perhaps two winning career possibilities, scoring higher than the others on some or most of the metrics.
This was my first version of the chart:
Bingo?… Well, not really. Having done all this work, frankly, I did not feel any more enlightened than I had been before starting the exercise. Every one of my six paths did well on some metrics but not so well on others, so overall all of them seemed pretty equivalent. How was I to choose just one option?
Then a thought came:
“These quality metrics are actually not equal at all. Even though I chose them myself, some are much more important to me than others.”
So I revised the original spreadsheet to include a factor of importance, by allocating each of my metrics a number ranging between 1(not very important) and 10 (extremely important) to establish a hierarchy between them, and changing the scores accordingly:
The result was this weighted chart:
Bingo! Doesn’t one path immediately jump out at you?..
…Shortly after this exercise I found myself applying for a MSc in Human-Computer Interaction Design at City University.
But wait, wasn’t there some jiggery-pokery involved here? How reliable or well-researched were my original assumptions? Wasn’t my scoring a bit simplistic and one-dimensional — and perhaps even inaccurate? (See note ***)
Yeah, yeah, all of the above. Mine was a pretty crude solution — or an approximate model, as Don Norman would have more elegantly put it. However, despite its crudeness, this solution proved good enough for what I needed it to do: it helped me make a decision by cutting through the clutter of bewilderingly complex choices.
*** A note on the ‘crusade factor’ metric:
Since creating that chart, I have discovered much more about the power of UX as a tool for changing the world for the better, including projects such as fempower.tech and the Thomson Reuters’ Foundation Climate Project, after a visit to the inspiring City University HCID Design For Good Conference earlier this year. I know now that UX can open the door to a brilliantly broad range of projects and jobs to choose from, many of which are well aligned with my own personal crusade. So I am now even more convinced that I am making the right decision by choosing UX.