Open data fuels economic growth. Many believe in the theory and ask for the proof. A new report by Nesta and the ODI adds to the evidence of the impact of open data. The report's analysis, undertaken by PwC, examines the effects of the Open Data Challenge Series (ODCS) and predicts the programme will result in a potential 10x return (£10 for every £1 invested over three years), generating up to £10.8m for the UK economy.
Economists use terms such as information asymmetry, allocative efficiency and network effects to explain why open data creates this return. Others might say that open reduces friction in transactions and markets operate better in low friction environments.
To put it more simply, by publishing data openly we may be able to make better use of existing resources and create new products and services. These can be of huge benefit to an economy - they may help people choose what type of transport to use, decide where to build a new house or look up the weather on their smartphone.
A growing body of evidence quantifies the utility of open data and demonstrates its impact in many countries and sectors, based on a number of studies with varying approaches.
Macroeconomic studies create models that estimate the impact of change on an economy as a whole. They may consider countries or geographies of very different sizes, and by considering the whole economy they often produce large numbers. To make these numbers comparable it is useful to consider them as a percentage of the gross domestic product (GDP) for the economy that they are focused on.
Here are a few of the most frequently referred to studies that quantify the benefits of open data in this way:
|Date||Study||Scope||Benefit of open data (% GDP)|
|2011||EU Commission||Europe (public sector data only)||1.5|
|2013||Shakespeare||UK (public sector data only)||0.4|
|2014||Lateral Economics||G8 countries||1.1|
Although their methodologies may differ, the studies determine a financial value for similar economic effects, such as better consumer decision-making, optimised business operations (including processes and procurement) and maximising the value obtained from existing and new infrastructure.
McKinsey found potential benefits amounting to 4.1% of global GDP for data across all sectors. Those studies focused on the value of public sector open data alone found that it is worth between 0.4% and 1.5% of an economy's GDP. Indeed, a UK study found that we may actually underestimate the gains from lower prices of public sector information because of the difficulty in valuing the full effects of downstream and future activities.
Big numbers can be useful for high-level analysis. But some question the credibility of macroeconomic studies, challenging the 'top-down' view of impact and the creation of generalised models.
More detailed studies support the strong claims made about open data by their macroeconomic counterparts.
Microeconomic studies focus in more detail on the behaviour of individuals and organisations, usually focused on a specific sector. A number of microeconomic studies into the impact of certain types of open data have been conducted.
For example, a study of the US Landsat dataset, comprising satellite imagery of the Earth's surface, showed the huge annual economic benefit of it being made openly available was $2.19bn in 2011 alone.
Research into the value of Danish address data found benefits amounting to around DKK 471m (€60m) in the period between 2005 and 2009 for an investment of just DKK 2m (€0.25m).
In the UK, the London transport authority, TfL, commissioned a report into the release of their data. This report concluded that the value of the time saved by passengers due to better access to information can be estimated at between £15m and £58m in 2012.
Arup, a multinational services firm that specialises in the built environment, has published a report stating that public sector open data could be used to generate between $720bn and $920bn globally through the development of digital transport applications alone.
Whilst these studies adopt a more 'bottom-up' approach they still predict behaviour from examples. We can look more closely at those specific examples themselves through case studies.
Case studies give us individual evidence points from research, usually focused on the experience of one organisation or actor. They can be used to tell a story that may then be extrapolated more widely.
In agriculture, Monsanto's buyout of The Climate Corporation for $930m in 2009 was a tangible demonstration of the value created by the US Landsat data. The Climate Corporation ingests extensive weather and geological open data to generate 10 trillion simulation data points. It uses them to accurately underwrite weather insurance for farmers and protect the $3tn global agriculture industry from extreme weather events.
Similarly, the ubiquitous Citymapper app helps to demonstrate the economic value predicted by TfL and Arup. Citymapper currently provides public transport advice in 29 cities and general manager Omid Ashtari has recently said that "Citymapper was created [in the UK] because of the existence of open data. It's the essential backbone of what we're working on."
In Spain it was found that at least 150 companies like Citymapper sell products or services using data published through the nation's data portal, employing around 4,000 people in 2012. Pew Research demonstrated widespread usage of similar products and services based on open data, finding that at least 84% of Americans with a smartphone have used open data through their phone's applications.
Research conducted this year by the ODI identified 270 companies, large and small, that use, produce or invest in open data in the UK, with a combined annual turnover of over £92bn.
The ODI itself has seen more than 50 jobs and over £9m generated via its network of startups. You can read more about them on our website.
Open data has a proven economic impact
Although the case studies provide insight only into those sectors in which open data has been made available, they do reinforce the wider findings of micro and macroeconomic studies, and economic theory. We can expect similar proof to appear in more sectors as open data continues to be adopted.
Whilst the figures, methodologies, researchers, countries and motivations involved in understanding its value may vary, the weight of evidence is clear. Open data is helping to fuel innovation and has a proven and significant economic impact.
What do you think?
The ODI will be continuing to explore the economic impact of open data in the coming months. Do you have thoughts or experience to share about economic impact or how to capture it? Pitch us a blog to share your views, or tweet us at @ODIHQ.