startup mapping over the years
In 2017, 2018 and 2020, dandolo was commissioned by LaunchVic to develop the Victorian Startup Ecosystem Mapping Reports. One of our consulting analysts, Bokyong Mun interviewed Lotti O’Dea, who was the project manager for the 2020 mapping report about some of her highlights.
BM: Can you give us a little bit of context behind what these reports were about?
LO: The Victorian Startup Ecosystem Mapping Reports provided a comprehensive and up-to-date view of Victoria’s Startup Ecosystem. Each report we updated and explored the different elements and strengths of the ecosystem as well as changes over time.
Startups are organisations with the potential to change the way we live and work for the better. They are able to quickly adapt and adopt new approaches to solve problems where a solution might not be obvious. While they often centre around technology, startups are not only technology-based and can be found across almost all sectors.
Developing these reports is particularly valuable for the startup ecosystem, as stakeholders such as policy makers and investors, need regular insights to inform decisions as well as celebrating achievements of the sector.
BM: What exactly does a startup look like? When you gathered your baseline data, how did you calculate the number of startups in Victoria’s ecosystem?
LO: While there is a lot of interest in startups globally, there actually isn’t one agreed approach to what a startup is, and the method that should be used to calculate the number of startups in an ecosystem. One reason why there isn’t a total consensus is because not all startups look the same, or share the same characteristics. For example, not all startups are registered businesses.
In our most recent report, we used a number of objective and subjective criteria to define a startup. These criteria were commonly used in internationally recognised definitions and surveys. Objectively, we looked for startups that were headquartered in Victoria, were less than 10 years old, and were active at time. Subjectively, eligible startups also needed to be innovative / disruptive, and be using technology to scale up.
On this basis we trialled multiple methods to estimate the number of startups in Victoria, so we could triangulate these estimates to a give us a credible figure. Our most conservative method was to count only those firms that we could identify as startups in the datasets we were using. We estimated a number more than twice that figure, by applied the rate of growth of new firms to the number of startups that had been identified in previous years. Trialling these different measures allowed us to work towards a robust figure, while recognising the conflict that exists on defining and estimating the number of startups.
BM: That is very interesting! Did these differences impact how you were able to gather your data for the report?
LO: We definitely had to be creative in how we gathered our data, but this was primarily because startups are known for being over surveyed. There are a lot of stakeholders such as government and venture capitalists who are very interested in startups. Our challenge was to figure out a way of collecting comprehensive data without putting too much burden on what are often, young and very busy organisations who may not see the immediate benefit of sharing data.
For our 2020 report, our base data was gathered through the Startup Genome Global Ecosystem survey. We supplemented this with a range of secondary sources and analysis such as data on key metrics that had been previously collected, and desktop research through sources like Crunchbase.
BM: Was there a part of the analysis that you have really enjoyed or were surprised by?
LO: Something I’ve really enjoyed is grappling with the conceptual and methodological complexities that sit behind what seems like a simple descriptive project, for example identifying the number of startups. I also enjoyed doing additional exploratory analysis on high growth startups in the 2018 report. In this analysis we looked to see if there were any particular patterns and features of these high growth firms. We found that on average high growth firms: are older, are more likely to have diversity and inclusion policies, have a higher proportion of firms using disruptive technologies and have founders that are older, have more a lot more sector experience and have founded more startups previously.
It’s also been rewarding to see how the ecosystem has changed and matured over the years. I feel a little bit like a parent, and watching the startup ecosystem grow and go out into the big wide world.
BM: What were some of the more conceptual and methodological challenges that you mentioned above?
LO: I think a clear example is illustrated by the fact that in the startup ecosystem, there is no “average” case, more so than in other sectors. Startups vary considerably, and there are outliers on all spectrums. The challenge is being able to summarise the ecosystem while still being accurate to individual cases.
Another particular challenge for the startup ecosystem is that the sector can often move really quickly. We have to take this into consideration when doing our analysis to ensure it is still up to date and be careful about any trends or comparisons that may no longer be relevant. The impact of COVID-19 on the startup ecosystem is a good example of this.
BM: What about these reports do you think makes it iconic to dandolo?
LO: I think at dandolo we’re proud of the way that we are able to communicate complex things in a simple way – and that is something we definitely do in these startup mapping reports. The startup ecosystem is complex and nuanced, and we’ve been able to bring some really valuable insights to a project that might just seem like straightforward descriptive analysis. Finally, at dandolo we love introducing our team and our clients to the joys of data and quantitative analysis – these reports have been the perfect project for our consultants to get deep into large datasets and pull out the insights that really matter.