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Startup ecosystems: US vs. France: Comparison Methodology

Despite abdicating any claim to objectivity, I still wanted to follow a methodology to give my startup-ecosystem comparison a clear structure. Given the highly-qualitative and very subjective nature of my analysis, I’m not entirely comfortable using the word “methodology” — “recipe” would probably be more appropriate.

To start, I identified the six factors I feel are the most important in evaluating any country as the potential birthplace of a startup.

These are, in order of increasing importance:

Access to Capital Education Workforce Legal & Admin. Culture Access to Markets
  • Access to Capital — yep, financing = fuel. Ya gotta have that. Capital is portable, so we’ll consider access to capital from all sources, not just local access to capital.
  • Education — by this I mean the quality, consistency, adaptability and content-relevance of the educational system. Quality in this context is not some vague notion of excellence but simply the answer to the question: can graduates exercise the knowledge they’ve gained in the real world? Consistency asks whether a given education achievement (a Master’s Degree, say) is a roughly-comparable measure of learning from one institution to the next. Adaptability asks how quickly, and how well, educational institutions internalize innovations and evolutions in the edge of the art into their curriculum. Content-relevance is the measure of how well skills acquired by students match up with the skills sought by newly-formed startups.
  • Workforce — are people ready, willing and able to work? Are they mobile? Are they easy to find, vet, hire and fire? What are the prevailing characteristics of relationships between employers and employees?
  • Legal, Administrative, Reporting — this rather broad category is the placeholder for all the bureaucratic burdens a given location places on those wishing to create and operate a business.
  • Culture — this least-quantifiable of factors is nonetheless my second most important factor in evaluating a startup ecosystem. What are the prevailing attitudes toward risk and innovation? How are small businesses regarded by people and institutions? Will people work for companies with uncertain futures, selling as-yet untested products and services? These questions cut across the other factors but still need to be addressed separately.
  • Access to Markets — whether your ambition is to be the next Mother Teresa or the next Steve Jobs, it all comes down to getting your stuff into the hands of those who want or need it. Many considerations go into market accessibility: how even is the playing field? How good, and how fair, is access to logistical support (be it Internet access for online services, or shipping and warehouses if you’re selling atoms and not bits)? Does your startup’s home country make it easier or harder to reach markets beyond its borders? Online startups (Web-based businesses, mobile apps and the like) enjoy some immunity from this issue in their home location, but only some.

For each of these factors and for each country, I determine two grades, on a scale of 0-100: the first for how the nation fares in that category now, in the present day; the second, for how it is likely to fare ten years from now, given current trends. A grade of 100 would go to a utopian ecosystem that is perfect for startups in every respect. A grade of 0 would represent some uninhabitable planet in the coldest part of outer space.

This gives us a simple arrow, from now to ten years’ hence, as the graphic to represent the ecosystem’s present state and anticipated future state.

Each of the six categories is given a numeric weight based on its importance, ranging from 1.0 (Access to Capital) to 2.0 (Access to Markets). The individual grades are multiplied by these weights, and this gives us our summary now-vs.-future arrow.

I must state categorically that the weights, and the individual grades, have been established at least in part using the finger-in-the-wind method. The purpose of the grades was mainly to provide a basis for readily-understood visualization of the overall tendencies as I see them. I don’t claim any scientific rigor in the values I’ve chosen. The process is more like a teacher grading homework than a surveyor taking a measurement.

If you like the methodology but disagree with my assessments (or my quantifications thereof) you should feel free to download the spreadsheet and put your own weights and grades into the model.

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