For a few years now I’ve wanted to see different parts of the world without putting a pause on my career. Earlier this year I took the opportunity to do it, after taking a remote job position. The following post isn’t about that story — maybe more to follow. This is about how I chose where to go.
It’s crazy to think that my entire life changed partly because of a spreadsheet I decided to build for fun one Sunday evening. Yet, here I am with Jenny, my girlfriend, in Chiang Mai, Thailand — one of 20 locations I originally threw in a Google doc — still getting used to the idea that this is our new home for the next few months. This spreadsheet, which I’ll creatively refer to as The Spreadsheet from here on, wasn’t something I took seriously at first. I built it when I was only half considering the idea of picking up and living abroad. But putting together 20 locations of where I might live, and starting to research them, made the process more real in my head. The Spreadsheet made the idea of living somewhere new more concrete to me, and it made me seriously consider what I was looking for in a destination. For anyone else half-considering to live abroad, build yourself The Spreadsheet. You can make a copy of my original, which I have below. But be careful! If you make a copy and play around with it, you may find yourself packing up and finding a new home.
About The Spreadsheet
The purpose of the spreadsheet is to try and combine all the many factors that made me want to live in a new place. I’d like the idea of one city because it had great weather, but then get discouraged it was so expensive. Another felt easier to live in because the people spoke some English, but the crime rate was too high. With so many pros and cons to weigh about destinations, I wanted a way to quantify everything I cared about. The Spreadsheet takes all the factors I cared about, even some I didn’t originally think I could measure, and ranks each city.
To see The Spreadsheet click here. Open it up and follow along. Let’s look at its 4 main components:
1. The cities
2. The country and regions
3. The “Scores”
4. The Average Score
My spreadsheet now has 35 locations. I chose these in a mostly random fashion — listing off countries I was somewhat interested in. Some of the countries I threw in there on a whim, and I’m glad I did. Lisbon for example wasn’t somewhere I particularly saw myself living, but now I’m planning to move there next year. Other cities I included I knew I wouldn’t end up in, but I wanted to see how they compared. Boston, for example is where I started. Tokyo as another example is a city I’ve badly wanted to visit, but not one I could see myself living in for more than a few weeks (it’s too massive). The logic here is to not rule anything out. You are after all in the brainstorm phase of your travel. You never know how later research will change initial perceptions.
The Countries and Regions
The point of The Spreadsheet is to quantify many factors and compare. With that in mind I wanted to see not only how each city ranked, but also larger regions.
Listing country and region helped keep this broad. By thinking more of the broader buckets than the specific cities the research becomes flexible, especially if you don’t feel attracted to urban centers. Use major cities as an indicator to research more in the surrounding area. But when quantifying factors such as weather, it’s a lot easier to find numbers for a major city than a small one. More on that later.
This is the main function of the spreadsheet. I wanted to combine many different factors to rank, or quantify, 32 cities. If you use The Spreadsheet I encourage you to think of some of your own scores.
For example, I quantified Jenny’s general appeal to a city (Column D: “Appeal — J”). This is an interesting one because it’s subjective. It’s a feeling. But even gut feelings can be quantified. The way I did this is I asked her to score each city on a 1 to 3 scale. No thinking about it too hard. I would say the city and she would say a number. I repeated every day for a week and recorded the answers. I liked to see how some cities went from a 1 one day to a 3 the next and then back to a 1. After a week of responses, I took the average of these. I did this with myself too. Personal interest was just as important to consider as cost of living, weather, and other factors.
Everything I left as a 1, 2, or 3 even though I could have used decimals. Maybe decimals would have been best practice, but I like forcing everything to an integer. It makes it cleaner, and it takes pressure off small details. This is a habit I picked up from growth marketing when using the I.C.E. scoring process by Sean Ellis.
Some of the columns I standardized on a 1–3 scale from outside sources. Take the Cost of Living (CoL) for example. This I took from Numbeo.com which has a Cost of Living Index of the top 372 cities in the world. However, Numbeo’s index uses a 1–100 scale. To make this work I recorded the CoL Score for each city in my spreadsheet, which is hidden on Column G. Then, in some scratch work in Column H I found the range (R) of column G, divided by 3, and added this to the minimum in G (Min).
Min to [Min + (R/3)] equals a 1 in column G . This number to Min + 2*(R/3) equals a 2 in column G. The remaining third of numbers are a 3. This method is reversed with the Crime Index so that a 1 is always best.
The scores I’ve already talked about are Appeal, and CoL. Let me quickly review the others.
Surrounding Area is my appeal to other destinations in the region. For example, Southeast Asia destinations have a 1 because I’m eager to visit Burma and Indonesia. Living in Thailand or Vietnam would make it easy to do this. Portugal has a 1 because I want to visit Morocco.
The Weather Score (now removed) required manual research and was based on my preferences and the time of year it was for. I didn’t want to live in a city that always rains, for example. Pluviophiles however should check out Mumbai during monsoon season (I’ve done it. It’s rough).
Crime Score is important to me for obvious reasons. I standardized this from Numbeo.com’s Crime Index. Look into this number further though as one number is not enough to understand a city’s criminal behavior. Did it get a high crime rate for kidnappings or petty theft? And what kind of people are targets for criminals in that area?
How to Copy and Edit
I’ve locked The Spreadsheet to the public so nothing gets edited or deleted. To make your own copy to edit click “File” then “Make A Copy”.
Unhide column’s by clicking on the double-sided arrows such as between column E and H.
Get creative and make your own scores. For examples if you’re a long distance runner look into air quality. Maybe you could create a score to measure a city’s restaurant scene, or number of dog parks. Whatever it is that will make you happiest or unhappiest to be there. I originally had more columns in here with subjective scores, but took them out for the public version. Read my directions in The Scores section on how to standardize numbers on a 1–3 scale.
Important Things to Consider
I created The Spreadsheet because when I was thinking on where I might want to live it seemed like there were too many factors to keep track of. Personal preference, cost of living, and crime rate sometimes conflicted and made the planning process difficult. The Spreadsheet solves this. But it’s not everything. If you want to live in a coastal city, don’t go somewhere hours away from the ocean, no matter how it ranks. If you want to be surrounded by mountains, make sure they exist at your destination.
The Spreadsheet gave me direction, and helped me find my leaping off point. Since I started living abroad I haven’t looked back. After 6 months here in Chiang Mai we’re doing 2 months in Bali, then 6 months in Portugal. My hope is that someone reading this uses The Spreadsheet for a sense of direction and empowerment to find their next home.
Email me with any questions: ElliotMillerMarketing@gmail.com.