Looking back on our inaugural class of Data Fellows, I’m inspired by the drive and focus that each Fellow brought to the programme and to our team at the Centre. Aziz, Haoyun, Laith and Manu have each written blogs and shared their reflections on their projects. As the manager of the programme, I’ll focus here on what we learned from them, and how the structure of the fellowship will evolve as a result. You can read more about the programme design in Part I of this blog series.

What we thought the programme would look like before the Fellows arrived turned out to be different in a number of ways from what we got by the end of the eight weeks. Three elements of the programme stand-out in this regard: 1) the Fellows’ curriculum and related learning journeys; 2) the balancing of time between problem framing and solution development; and 3) the Fellows’ collaborations with technical and subject matter experts.


Image taken from Entrepreneur Fail.

  1. From Learning and Doing to Learning-by-Doing

In designing the programme, we expected to have sufficient time each week for structured learning exercises across a range of topics, summarized in the box below.

       Proposed Topics of Curriculum for Summer 2018 Data Fellows
  • Week One: Connecting People and Data to Improve Lives
  • Week Two: Assessing Humanitarian Need, Financing the Response
  • Week Three: Planning and Managing a Humanitarian Response
  • Week Four: Coordination for a Better Response
  • Week Five: Data → Insights → Action
  • Week Six: The Promise and Peril of Humanitarian Data — Whose Benefits, Whose Risks?
  • Week Seven: Pathways to Scale
  • Week Eight: Toward a More Data-Driven Humanitarian System

The curriculum aimed to expose the Fellows to contextual knowledge about the humanitarian system. We also wanted to teach them new skills and methods that could support delivery of their projects. We thought that the Fellows would benefit from structured learning alongside their more hands-on project work, and hoped that the balance of ‘learning and doing’ could be maintained throughout the programme.

Just a few weeks in, it became clear that we would have to cut some of the more structured learning exercises to ensure that the Fellows had sufficient time to complete their projects. As a result, we shifted focus to learning-by-doing and, in a way, to more individual learning journeys for each Fellow.

For year two, we will balance structured, whole-group learning activities with a hands-on, individual approach. This will involve the Fellows forging their own learning path with support from members of the Centre team and the broader partner network. We may also consider a crash-course or boot camp model (inspired by our colleagues at the WFP Innovation Accelerator) through which the entire class of Fellows spends the first week of the programme getting oriented with the humanitarian system, and exploring major questions, challenges, and opportunities around the use of data in the sector.

  1. Kickstarting the Problem-Solving Process

As described in my previous blog on the programme design, the Fellows spent their first two weeks identifying, researching and framing a problem statement around a data-related challenge facing OCHA and the humanitarian community. We did this to make sure they had ownership over the problems they were working to solve.

Although the problem-framing period paid-off in many respects, it also meant that the Fellows only had about 5 weeks to design and develop their solutions. In the final week of the programme, each of the Fellows reflected that they would have liked more time for additional testing, feedback and development of their ideas, prototypes or models. While one option would be to simply extend the overall length of the fellowship, we believe eight weeks is the appropriate length for practical and strategic reasons.

In the next round, we will restructure the arc of the fellowship by kick-starting the problem-solving process earlier in the programme. We will likely do this in two ways. First, we will identify problem areas for each of the Fellows before the programme begins. Second, we will include an intensive problem definition exercise in the first week of the programme. This will require more preparatory work by our team and the Fellows before the programme kicks off, but will ensure that the Fellows still feel ownership of the problems. Finally, and just as important, this will allow us to build more effective relationships for each Fellow with subject matter experts and ‘clients’ who they can engage with throughout their time with the Centre.

  1. Stronger Relationships for Mentoring, Feedback and Uptake

As each of the Fellows mentioned in their blog posts, staff from OCHA and partner organizations were generous with their time. For instance, over twenty people conducted hour long interviews with Laith, and OCHA’s financing team provided consistent support to Manu as she developed her predictive model. This input and feedback proved invaluable to the solutions that each Fellow delivered, and helped to ensure that their solutions will be integrated into the work of the Centre beyond the fellowship period.

Although some of these interactions were planned from the beginning of the programme, the majority were made in an ad hoc fashion as the Fellows got deeper into their work. While we want to allow for some flexibility in how different colleagues and partners engage with the Fellows, the programme would benefit from a more structured approach to ensuring mentorship, feedback and uptake.

In the future, we will invest more in building strong project partner or ‘client’ relationships for each Fellow. These partners could be colleagues within OCHA or members of the Centre’s broad network of partners and collaborators. The key here is to find people who are committed to spending time with our Fellows in exchange for deep technical expertise and a fresh perspective on a complex data-related challenge. Looking at the impressive projects that our first class of Fellows delivered, I’m confident in saying that this is an investment worth making.

If you are interested in working with our next class of Fellows on data challenges, we would love to hear from you. Email us at centrehumdata@un.org. For those of you interested in applying to the programme, we will advertise the new fellowships in early 2019. Sign up to our mailing list and follow us on Twitter @humdata for the announcement.

If you missed Part 1 of his summary posts, read on to learn more about the programme from Senior Data Fellow Stuart Campo. You can also read the blogs by the 2018 Data Fellows, including their work on data sciencedata storytelling, predictive analytics and user experience research.  Plus, watch the Data Fellows summary video here.