Open Data: A 21st Century Asset for Small and Medium Sized Enterprises

(Key Findings of the Paper: Open Data: A 21st Century Asset for Small and Medium Sized Enterprises, The GovLab)

Although we live in a data age, much information has until recently been privately held and access to it restricted. This is starting to change, however, with the rise of the open and shared data movement. Increasingly, it is clear that we are entering a new era of access, innovation, and transparency.

Today, it is widely held that open and shared data have the power to fuel economic growth, job creation and new business opportunities. The consulting firm McKinsey predicted the possible global value of open data to be over $3 trillion annually.[1] A study commissioned by the Omidyar Network concluded that open data could increase the output of G20 countries by some $13 trillion over five years.[2] But for all the excitement about the potential of open data, very little is known about how it actually works — the precise variables, parameters and pathways through which it translates into growth and opportunities.

The purpose of this paper is to better understand how open and shared data impacts the economy. Focusing on small and medium enterprises (SMEs) and startups, we consider 354 case studies of companies currently using open data to better understand how open data can be used, and how it can contribute to economic growth, new jobs, greater innovation and other improvements in our social and economic lives. Grounding our analysis in empirical studies allows us to identify the most important issues confronting any SME considering an open data strategy. It provides lessons and principles that have proven, real-world applicability.

Our analysis is structured around ten key questions. These questions encompass both the potential and challenges of open data. Among other issues, we consider:

  • Different sources and types of open data, and how these differences affect the economic potential of open data;
  • The relationship between open data in its “pure” form and other forms of open and shared data that often come with certain restrictions, but that nonetheless have the potential to foster economic growth and innovation;
  • Market segments, data products, and different models of value creation currently being explored by open data SMEs;
  • The importance (and difficulty) of establishing metrics to capture the impact of open data; and
  • Some of the risks involved in using open data.

Our discussion of these (and other) issues permits us to arrive at ten principles for the effective use of open data. We examine these principles in the conclusion. They should be considered preliminary and, given the rapidly evolving nature of the field, subject to change. Nonetheless, put together, they provide something of a roadmap or guide for SMEs considering an open data strategy.


  • Open data is publicly available data that can be universally and readily accessed, used and redistributed free of charge. It is released in ways that protect private, personal, or proprietary information and is structured for usability and computability.
  • Open data exists on a spectrum of openness. Not all data that is released to the public can be considered “pure” open data. In considering the benefits of open data, we should also consider the growing category of shared data, which can be reused and is frequently made public, but often with certain restrictions. Shared corporate data — in which companies release privately held information with other individuals or entities — is a particularly important phenomenon.
  • SMEs often lack access to data or sophisticated analytical tools to process and analyze large proprietary datasets. They are likely to be one of the chief beneficiaries of open data, which requires fewer resources to utilize.
  • Government data, science data, and shared corporate data are the three main categories of open and shared data being used by SMEs. Though government data is by far the most widely used, science data (especially clinical, research and health-related data) and shared corporate data (e.g., in the form of academic research partnerships, trusted intermediaries, and APIs) hold significant potential for SMEs.
  • Open and shared data is used most in the sectors of data and technology, finance and investment, business and legal services, and healthcare. Despite heavier regulatory barriers in finance and healthcare, the use of open and shared data is still growing rapidly in these sectors. Technical, organizational, or economic barriers are likely to play more significant challenges to the adoption of open data.
  • Open and shared data is being used primarily to serve the Business-to-Business markets, followed by the Business-to-Consumer markets (and, to a lesser extent, the Business-to-Government market). Though SMEs using open and shared data typically target a single segment, a growing number of the businesses studied here serve two or three market segments simultaneously.
  • In order to yield meaning and insight, “raw data” needs to be processed by SMEs and other organizations. The key steps involved in processing raw open data are cleaning and standardizing, consolidating and organizing, augmenting through linkages and aggregation, and analyzing data through descriptive, prescriptive and predictive analytics.
  • Open and shared data is being used to create a variety of new business offerings. These include platforms that help analysis, insight and decision-making (by both businesses and consumers); data-driven products such as insurance and loans; data interfaces and visualizations that help increase access to information; consulting services; new software, web, and mobile applications; and services and educational platforms for code and data literacy. Broadly, these offerings can be divided into new data-driven products and services, and enhancements of existing processes and products. The new business products using open data can be further separated into the categories of (1) Data-driven Products; (2) Data-driven Platforms; and (3) Data Intermediaries.
  • While open and shared data is usually a free resource, SMEs are monetizing their open-data-driven services in order to build viable businesses. Popular revenue models include subscription-based services, advertising, fees for products and services, freemium models, licensing fees, lead generation and philanthropic grants. SMEs must choose a revenue model based on their product, their market segment and the revenue models used by existing and potential competitors within their sector.
  • Developing metrics to measure the impact of open and shared data is a challenge. Efforts to develop such metrics should consider the direct economic value of open data to SMEs; the indirect value of open data to third-party organizations doing business with open data SMEs; the indirect value of open data to consumers using open data SMEs or third-party organizations using open data SMEs; the indirect value associated with open data SMEs on the wider economy (e.g., through increased consumer spending or B2B expenditure); and the wider societal impacts that can be attributed to open data SMEs. Metrics can capture both economic and non-economic variables, and can be either quantitative or qualitative in nature.
  • SMEs face significant challenges in their efforts to collect, store and use open and shared data. These challenges include difficulties in accessing open data, problems concerning data quality and consistency, insufficient financial and human resources, and issues surrounding privacy (particularly when open data sets contain personally identifiable information).

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[1] James Manyika, Michael Chui, Diana Farrell, Steve Van Kuiken, Peter Groves, and Elizabeth Almasi Doshi, “Open Data: Unlocking Innovation and Performance with Liquid Innovation,” McKinsey Global Institute, November 1213,

[2] Nicholas Gruen, John Houghton and Richard Tooth. “Open for Business: How Open Data Can Help Achieve the G20 Growth Target,” Omidyar Nework, June 2014,