Publication Date
June 29, 2017

"There are many different the mobile data for social good field, and all play a role in converting mobile data into actionable insights. The large number of stakeholder groups - and the plethora of organizations and individuals who make up these groups - can create a complex environment for implementing solutions. Every setting will have a specific set of stakeholders; identifying and engaging those stakeholders is essential to forging effective partnerships."

This report, which outlines the value of harnessing mobile data for social good, is intended to inspire social impact organisations and mobile network operators to collaborate in the exploration and application of new data sources, methods, and technologies. Created by UN Global Pulse and the GSMA, it identifies over 200 projects or studies leveraging mobile data for social good, aims to survey the landscape today, assess the current barriers to scale, and make recommendations for a way forward. The report also details some of the main challenges with using mobile data for social good and provides a set of actions that (i) can spur investment and use, (ii) ensure cohesion of efforts and of customer privacy and data protection frameworks, and (iii) build technical capacity.

For the purposes of this report, "mobile data for social good" is the use of mobile data to improve development programmes, humanitarian action, and the production of official statistics. Mobile data is defined as information elements contained in call detail records, or CDRs. Mobile network operators (MNOs) are already capturing, storing, and securing CDRs. Once anonymised and aggregated to appropriate levels, CDRs can provide a variety of insights with value for development or humanitarian organisations, including:

  • Mobility: As calls and messages are sent and received through the cell towers of a mobile network, records are produced that can reveal community or population-level movements. This data has particular relevance in the wake of natural disasters or disease outbreaks, but it may also be used for urban planning.
  • Social interaction: Information about how groups of individuals engage with their social community, including whom they call, how often they speak with these contacts, and how long they speak with them, can be used to understand behaviour and socio-economic trends.
  • Economic activity: Monthly airtime top-up patterns, consumption of value-added services (VAS), and the use of mobile financial services can be used to extrapolate insights about the economic health and resilience of a community.

Converting massive amounts of mobile data into meaningful insights is done first through data analytics, the application of hardware and software to detect patterns. The resulting insights are supplied to policymakers and programme managers primarily by academic researchers, non-profit organisations, and MNO research labs. These insights are almost always combined with other data sources to contextualise them into actionable steps.

Most of the 200 projects identified in the literature review were scientific research or feasibility studies, some of which were operationalised. (Several case studies are provided in the report.) These studies have thus far demonstrated that:

  • MNOs are willing to participate in social good projects.
  • Data can be made accessible for use in ways that protect subscriber privacy.
  • Academics and social impact organisations can partner with MNOs in ways that protect privacy.
  • Governments have found ways to successfully partner on projects with MNOs and third parties.
  • Donors are willing to fund mobile data for social good projects.
  • Mobile data when combined with traditional data sources may be used to generate information that is richer, more precise, or less costly than is possible with traditional sources alone.
  • Mobile data may yield unique and valuable insights that cannot be obtained from traditional data sources.

A range of issues preventing mobile data from being used for social good has been documented. These challenges arise from both the demand and supply sides of mobile data, and from the lack of a bridge between the two. In brief, they include: lack of a strong evidence base to support investment, lack of a shared vision and cohesive implementation mechanism, lack of common approach to data privacy and risk mitigation associated with data use, and lack of technical capacity globally and in low- and middle-income countries (LMICs). Proposed solutions to overcome these challenges are described in the report. They include:

  • Identify and build sustainable business models - e.g., consider stage-based business relationships between the private sector and governments or ministries where data are shared at no cost for purposes of research and programme development, with the explicit agreement that this upfront investment will lead to long-term relationships.
  • Address gaps within the data privacy and data protection landscape and mitigate risks - e.g., active participation of data advocates is an ingredient in a successful approach to managing data-related risks. These are people or organisations "who can speak with confidence about the legitimate and appropriate application of this information and could be trusted by the key stakeholders, including, operators, to do so. Furthermore, sophisticated communication techniques from sources trusted by the public should be employed to avoid even the perception that data privacy will not be protected. Education and involvement of policy makers and the media will be critical."
  • Build capacity in the right places - e.g., develop local technology capacity and engagement with local experts, identify passionate "data evangelists" to better communicate how mobile data can be used to benefit the interests of all relevant stakeholders, foster improved coordination among countries to enable learning from best practices and to create cohesive strategies for working with multinational operators, and introduce big data into existing development and humanitarian sector learning networks.
  • Create global tools for public good - e.g., develop an open-source data handling toolkit.

Looking to 2018, the experts consulted for this report were clear that holding one more meeting to "discuss" mobile data is not an adequate call to action. What is needed is a commitment of key stakeholders, backed by funding and resources from donors, to design, plan, and implement an impact demonstration project that will decisively establish the value of mobile data for social good. The steps are outlined in the report and include:

  • Step 1: Bring key leaders from the involved sectors together to align around a vision.
  • Step 2: Build a community-driven roadmap for the impact demonstration project.
  • Step 3: Secure catalytic funding for roadmap activities.
  • Step 4: Create a public-private partnership to oversee the demonstration project.

"With an abundance of research and pilot studies that have demonstrated proof of concept, the field is now poised to move beyond short-term and ad hoc projects to more systematic and institutionalized implementations....Data from nearly five billion unique mobile subscribers and eight billion mobile connections are housed in the data systems of MNOs. Using that data to improve the well being of communities requires a concerted effort by all stakeholders to meet the prevailing development and humanitarian needs of communities and reassure all parties that the benefits to society outweigh the risks."