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Report of the Meetup on Smart use of Data in a Humanitarian Context

Report of the Meetup on Smart use of Data in a Humanitarian Context

Event – December 3rd, 2018

DCHI and KUNO joined forces and invited Hein Fleuren, Professor Operations Reseach at Tilburg University, and winner of the DCHI Best Humanitarian Innovation Award and Harwin de Vries, Post-Doctoral Research Fellow at the INSEAD Social Innovation Centre, to share with everyone how Data can be put to use in the Humanitarian sector. The variety of the projects that both have worked on,  could hopefully trigger others to come up with ideas in their own environment.

Hein Fleuren began with a general overview of what is happening in Data Science and how this might play a role in Humanitarian Innovation. With this basic introduction, he set the scene to share a number of projects in which data science had been used in the humanitarian context. Interesting in his examples was that Hein showed successes and insights can be realised, though at the same time not all challenges can be solved with data alone. Interesting was the variety of projects and insights that were found by using data analytics, for example the different coping mechanisms used by urban refugees from different countries, now living in Greece (Athens and Thessaloniki); where for examples refugees from Iraq are likely to ask help from family and otherwise not at all, whereas Afghani refugees, the data showed, are more likely to turn to different people for support. These are important indicators for local organisations to plan their programmes on, as it gives insight in how to reach different groups of refugees. Hein also took time explaining Optimus, the data tool developed for WFP, creating a cost efficiency of $1 mln a month in Iraq alone. For more information about Optimus, please refer to our other news item.

Harwin took us through some interesting examples in addressing global health challenges through data analytics; Goal 3 of the United Nations sustainable development goals (SDGs) is to “Ensure healthy lives and promote well-being for all at all ages”. While much progress has been made in this area – global life expectancy has doubled over the past century – substantial health challenges persist and many new ones arise. Many of the barriers to reaching these goals relate to operations and supply chain problems. For example, in low and middle income countries they lie at the heart of the low availability of essential medicines and difficulties in scaling up access to health services. Tackling such problems is often hugely complex. Decision makers face many challenges, including scarce resources, immense needs, complex links between decisions and effects, and many (often conflicting) objectives. Moreover, solutions affect or can be affected by many stakeholders, including the private sector (e.g., pharmaceutical companies), policy makers (e.g., WHO), governments, NGOs, and patients. Data analytics can play and is playing a key role in informing such solutions. Methods from this field help estimating the effects of decisions, characterize good or optimal decisions, and yield tools, policies, guidelines to support decision makers. This talk discusses these opportunities, using research projects on network design for roadside HIV clinics, vehicle routing in the humanitarian sector, sleeping sickness control, and family planning outreach as examples.