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The rise of open data driven businesses in emerging markets

Alla Morrison's picture
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Mapping traffic flows using real time data.

Key findings --

  • Many new data companies have emerged around the world in the last few years. Of these companies, the majority use some form of government data.
  • There are a large number of data companies in sectors with high social impact and tremendous development opportunities.
  • An actionable pipeline of data-driven companies exists in Latin America and in Asia. The most desired type of financing is equity, followed by quasi-equity in the amounts ranging from $100,000 to $5 million, with averages of between $2 and $3 million depending on the region. The total estimated need for financing may exceed $400 million.
The economic value of open data is no longer a hypothesis
How can one make money with open data which is akin to air – free and open to everyone? Should the World Bank Group be in the catalyzer role for a sector that is just emerging?  And if so, what set of interventions would be the most effective? Can promoting open data-driven businesses contribute to the World Bank Group’s twin goals of fighting poverty and boosting shared prosperity?

These questions have been top of the mind since the World Bank Open Finances team convened a group of open data entrepreneurs from across Latin America to share their business models, success stories and challenges at the Open Data Business Models workshop in Uruguay in June 2013. We were in Uruguay to find out whether open data could lead to the creation of sustainable new businesses and jobs. To do so, we tested a couple of hypotheses: open data has economic value, beyond the benefits of increased transparency and accountability; and open data companies with sustainable business models already exist in emerging economies.

Encouraged by our findings in Uruguay we set out to further explore the economic development potential of open data, with a focus on:

  • Contribution of open data to countries’ GDP;
  • Innovative solutions to tackle social problems in key sectors like agriculture, health, education, transportation, climate change, financial services, especially those benefiting low income populations;
  • Economic benefits of governments’ buy-in into the commercial value of open data and resulting release of new datasets, which in turn would lead to increased transparency in public resource management (reductions in misallocations, a more level playing field in procurement) and better service delivery; and 
  • Creation of data-related private sector jobs, especially suited for the tech savvy young generation.

We proposed a joint IFC/World Bank approach (From open data to development impact – the crucial role of private sector) that envisages providing financing to data-driven companies through a dedicated investment fund, as well as loans and grants to governments to create a favorable enabling environment. The concept was received enthusiastically for the most part by a wide group of peers at the Bank, the IFC, as well as NGOs, foundations, DFIs and private sector investors.  

Thanks also in part to a McKinsey report last fall stating that open data could help unlock more than $3 trillion in value every year, the potential value of open data is now better understood. The acquisition of Climate Corporation (whose business model holds enormous potential for agriculture and food security, if governments open up the right data) for close to a billion dollars last November and the findings of the Open Data 500 project led by GovLab of the NYU further substantiated the hypothesis. These days no one asks whether open data has economic value; the focus has shifted to finding ways for companies, both startups and large corporations, and governments to unlock it. The first question though is – is it still too early to plan a significant intervention to spur open data driven economic growth in emerging markets?

First findings of open data companies research in emerging economies
In April, the Open Finances Team at the World Bank, in partnership with the International Finance Corporation (IFC), initiated research of companies in regions and countries that have been making progress in opening up their data – Latin America, Asia, Africa, India and Russia. We wanted to know how many data companies are out there and what the nature is of their businesses? How many of them use open public data? How many are tackling a social problem? We also hoped to get a glimpse of their specific needs and challenges. If we were to set up an investment facility, would there be a sufficient pipeline? What type and size of financing do these companies need? While the research is still in progress in Africa and in Russia, we have uncovered some initial noteworthy trends.

First, many new data companies have emerged around the world in the last few years. Of these companies, the majority use some form of government data. Latin America, in particular, has a fast growing data-driven startup sector, and the necessary structures – quality data, financing systems and supporting institutions – are in place. Countries with the largest number of data companies found in Latin America within the scope of our study were Mexico, Chile, and Brazil, with Colombia and Argentina close behind. Southeast Asia, on the other hand, has significantly fewer examples of innovative data companies, with the exception of the Philippines and Indonesia. There is a large number of “me too” startups in Southeast Asia with localization of existing products as an evident trend.  India stands out with a vibrant open and big data sector, entrepreneurial ecosystem and technical talent, with the latter also true for Russia and Eastern Europe. In Africa, early stage research indicated promising findings in Kenya, South Africa and Nigeria.

Second, the study confirmed that data companies are in a wide range of sectors: business services/analytics, health and wellness, food and agriculture, education, finance, transport, real estate, travel and hospitality. Especially interesting, however, were a large number of data companies in sectors with high social impact and tremendous development opportunities (this is especially important for us at the Bank – given our focus on fighting poverty and increasing shared prosperity). For example in India, after excluding business analytics companies, a third of data companies seeking financing are in healthcare and a fifth in food and agriculture, and some of them have the low income population or the rural segment of India as an intended beneficiary segment. Ten percent of companies provide education solutions, an area of particular interest to the head of IFC, Jin-Yong Cai, who said in his recent blog: “The interface between data and education holds the promise of new educational products for improved learning, with large potential benefits, especially for the poor.” In Latin America, the number of companies in business services, research and analytics was closely followed by health, environment and agriculture; in Southeast Asia business and consumer services and transport came out in the lead.

Third, actionable pipelines of data-driven companies exist in Latin America and in Asia. The most desired type of financing is equity, followed by quasi-equity in the amounts ranging from $100,000 to $5 million, with averages of between $2 and $3 million depending on the region. Analysis of more than 300 data companies in Latin America and Asia indicates a total estimated need for financing of more than $400 million. Based on interviews with founders, moving beyond seed stage is particularly difficult for data-driven startups. While many companies are able to cobble together an initial seed round augmented by bootstrapping to get their idea off the ground, they face a great deal of difficulty when trying to raise a second, larger seed round or Series A investment. From the perspective of startups, investors favor banal e-commerce (e.g., according to Tech in Asia, out of the $645 million in technology investments made public across the region in 2013, 92% were related to fashion and online retail) or consumer service startups and ignore open data-focused startups even if they have a strong business model and solid key performance indicators.

A theme that emerged across the conversations was the need for more success stories to spark investor imagination. Perhaps that’s a topic for the next blog – and if you have a story to share, we would love to hear from you!

You can reach the author at amorrison@worldbank.org or @allamorrison.

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