A startup ecosystem is an immense source of data: just think for a while all type of possible interactions amongst the different players. Every entrepreneur, team member, mentor, investor, service provider, community, startup event, pitching competition, incubator, accelerator, platform, even our favourite place to grab a coffee with our team generates impactful data: numbers, words, tags, audio, videos, photos, geocodes, etc. Everything in real time.
Most advanced startup ecosystems in the world with their governments at the forefront have begun to become aware of such vast of data as a high value asset for overall goals of efficient government, public safety, but also to change how government operates for the benefit of all and in the context of startup ecosystems, how it can be used to generate more effective policies to serve startups in the most effective ways possible to facilitate innovative companies development, bring more economic development and make cities and countries more prosperous. This is also something that even few early stage startup ecosystems like Ho Chi Minh City, in Vietnam, are seriously planning as they have understood how it will help a city or country to “skip a generation” of trying to only build or grow traditional “offline” models to support entrepreneurs, innovation or startups and that by moving towards the digital side, they will accelerate the pace of growth.
This is a journey with no turning back and an ongoing challenge, which begins by:
Certainly, many cities everywhere see the potential of data and analytics to develop their startup ecosystems, like for example Malaysia is doing by putting in place Adax, an initiative by MDEC to enable businesses, governments, academia and professionals to rapidly adopt Data Analytics as a tool to empower decision making and innovation. But at the same time there is a natural fear to initiate this journey to firstly collect data and then turn data into knowledge to later put knowledge to work for the sake of the startup ecosystem growth. That’s the goal: make your startup ecosystem more intelligent.
Implementation requires to work at multiple levels, from grassroot to decision making level but as it happens in most of data-driven projects, one key component of its success depends on solid infrastructures and when it comes to data-driven startup ecosystems, it is mandatory to have an infrastructure (both offline and online) that reflects a deeper understanding as well as holistic view of startup ecosystem development. Startup ecosystems are about networking, collaboration and connectivity, and while offline infrastructures get it, - digital is no different and should reflect that: interactions, service processes, service development, ecosystem management, etc.
To gain that holistic view, the startup ecosystem should gather data not only from the public supporting services and programs but also from private side so therefore private sector data is key to changing policy to support entrepreneurs, startups and innovation and therefore building public-private partnerships (PPP) is another key component in order to create more comfortable environments where public and private sector can operate together at different levels, causing more volume and variety of data that will enrich startup ecosystem analytics. Additionally, this PPP models should be built so that cities and countries own the data and not let them to hands of foreign government or some private businesses. At stake is nothing less than the future economic of your towns, cities and countries and the digital economic development is so important that it must be under own control.
This huge amount of data by itself is useless and the digital startup ecosystem infrastructure must process and store data in appropriate form (which data must be collected from the interactions among the different user roles of the startup ecosystem, frequency of data collection, accuracy of data, and are current databases suitable for collecting real-time data) to turn data into actionable information and, ultimately, knowledge, and then the startup ecosystem will be better positioned to respond and be more efficient in all levels.
Data will only deliver value to the whole startup ecosystem, if it is translated into specific improvements tracked by traditional KPIs such as company birth rates, company death rates, rate of high growth firms (based on employment growth), rate of high growth firms (based on turnover growth), survival rates at 3 and 5 years, net job creation, job quality, volume of deal flows, and valuation of startups, which are very important to answer questions like what innovation is happening in sector x, y, z, at what phases the startups are, what is the ROI of innovation support services, where to invest to further improve and accelerate, what startups to promote, showcase to global investors, etc. The real challenge comes, when you wonder, what are the operative sublevel indicators that contribute the most to these traditional KPIs and this is where the digitalisation process fits for producing, collecting and analysing real primary data to match those supporting organisations, services and activities that produce more funding attracted, big investments, more exits, more disruption and eventually more economic development.
The good news are that no matter where you are on your startup ecosystem maturity level, the first step is to evaluate your status and to begin to plan for the future and there’s no doubt that future will be digital.
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