Choosing a place to travel for a week or two is not usually a big challenge. With tens of thousands of awesome places to go to, it is likely that many will be equally satisfying, give or take whatever fate may throw at you. I won’t say it is easy to choose, but rather that the difficulty is between equally wonderful opportunities to fit into a small window of opportunity.
For a digital nomad, things are a bit more complicated. A digital nomad is someone with a remote work job who is traveling frequently and for long periods of time to live at different locations. Cost of living, internet quality, and community become much more important. You are looking to live in a country, however briefly. Critically, a lot more of these factors can be judged quantitatively, with hard data.
Originally, I planned my trips based largely on cost of airplane tickets. I would spend time searching the map on Google Flights or Kayak’s Explore feature. I had been wanting to visit New Zealand and Scandinavia in detail, and so in due course I did. Being privileged as I am, I also of course have visited numerous places in my earlier life on family or university vacations. I have met people who never left home, until they decided to leave for a year. Generally, however, I would recommend starting small before going so extreme, and start with those places you have always dreamed of (if you lack such dreams, might I suggest Rome, Paris, or London as a surrogate dream?).
The internet already has a number of tools for helping you plan your digital nomad adventure:
- https://nomadlist.com/ (many filters but no customization in score, city level but only big cities, limited free access)
- https://www.ef.edu/epi/ (limited data)
- https://www.expatexplorer.hsbc.com/survey/ (mostly focused on mid-career professionals)
- https://en.wikipedia.org/wiki/Big_Mac_Index (yes, really, a decent indicator of cost/wages for a country)
There are surprisingly few tools for choosing your next vacation, and most are rather shallow in their criteria. In short, I find they don’t suit my needs. Here are some: wander, tripzard, triptuner, travelpicker.
While there may be a paucity of tools to choose from, there are millions and billions of ‘Top 10 Places!’ articles to reference. I shan’t bore you with most of them, as they tend to be written by people who have never been to any of the locations they list. I did rather like this one.
What does the internet appear to lack? A customizable way to score countries based on a depth of metrics beyond a simple beaches/museums selection. Ideally this would be at a city level, but data at the city level is not comprehensive and comparable for most metrics, which I believe is the main reason NomadList does not offer you the ability to tune their ‘Overall Score’ – it probably relies rather more on discretion than they would like to admit.
Here I give you my own score, based on data from the World Bank, the UN, Pew Research, Education First, Numbeo, Institute for Peace and Economics, and Speedtest.net. The World Bank is the primarily source of information, as it is about as consistent and reliable as global data comes. Data is generally an average of 2012 – Most Recent Available in June 2020. The process was basically: find and select the data, manually align the data from each source, then scale with scikit-learn MinMaxScaler.
Two important things I did not consider: Visas (can you stay somewhere, and how long?) and Timezones (relative to your home office). One obvious disadvantage is the country level of the data, big countries like the US really can’t be summarized readily (NYC != Detroit != Montana != Seattle).
In order to use this index fully, you will need your own copy of it (Google Sheets or Download). For every Aspect you find important, place a Value for it, the larger the value, the more overwhelming that component will be to the score. If you don’t care about that Aspect, place a zero for the Value. Finally, sort the countries by Score, largest to smallest. Larger is better.
One note of warning, although generally a value of ‘1’ for two pieces of data should mean they have the same effect on the score, this isn’t quite true as the underlying data have different distributions. What does this mean? It means you should try different combinations of scores and aspects to see how things change, and use the highest scoring overall as your fav.
To start off with, here are a few rankings based on several different combinations of attributes.
Nomad Index Top 10 Cheap, Mild Winters, Decent Internet
- Sri Lanka
Nomad Index Top 10 Safe and Developed
- Czech Republic
Nomad Index Top 10 My Personal Values
- United States
- United Kingdom
- New Zealand
What is yours? Feel free to annoy me with comments about it.