Data Innovation Clinics at Bappenas
By Fahmi Ramadhan & Diastika Rahwidiati
Pulse Lab Jakarta worked with the Data and Information Centre of the Indonesian Ministry for National Development Planning (Pusdatin Bappenas) to run a series of data innovation clinics for policy analysts within the Ministry. This was also a good chance to test out UN Global Pulse’s data innovation toolkit!
Getting Policy Makers Engaged
In the middle of one of our regular catch-ups in September, Pak Suharmen — the head of Bappenas’ Data and Information Centre, and Pulse Lab Jakarta’s main counterpart — expressed the need to get the wider Bappenas team engaged in the Pulse Lab’s research agenda:
“I want research projects to be collaboratively designed — I don’t want people to just fling problems and ideas at PLJ, I want the teams in Bappenas to be part of the research projects and to own them.”
Pak Harmen and our team brainstormed several ideas, and subsequently opted for a series of on-site workshops. The workshops gradually took participants through the process of problem identification, ideation of possible ways of tackling a problem, the formulation of a data-related research questions and hypothesis, and the development of an initial concept for a data innovation project.
We wanted to give as much opportunity as possible for participants to tie these concepts to the issues that they are currently working on, so instead of sequestering the 40-odd participants in a meeting room for two days, we decided to break the sessions up into four half-day clinics that we ran every Tuesday morning in November. At the end of the workshop, participants presented their work in front of their peers to gain feedback on their data innovation ideas.
Cool Ideas That Emerged….
Presentation 1 — Using Big Data to Address Traffic in Big Cities
The first group aims to use data from mobile network operators to develop new insights and to identify traffic solutions. Using these data, they want to determine the peak amount of people using each form of transportation, helping inform policy changes related to transportation availability.
Presentation 2 — Tackling Food Shortages
The second group’s idea was to use social media and telecommunications data to predict food shortages in real-time across Indonesia. This would assist the Government’s efforts in detecting vulnerable areas and targeting food subsidies.
Presentation 3 — Policy Analysis on Electricity Subsidies
Group three presented on using a data-driven approach to analysing the effectiveness of Indonesia’s electricity subsidies, with a focus on getting feedback from ordinary citizens. In particular, on whether subsidies have been efficient in helping to alleviate power outages.
Presentation 4 — Improving the Registration Process in Public Health Services
Group four shared their ideas on utilising data from social media, radio and LAPOR! (the Government of Indonesia’s citizen feedback platform) to improve the registration process and service of the new health insurance scheme managed by Indonesia’s body for organising social security programs (BPJS), especially in remote areas. One area of concern was social media and smart phone prevalence in remote communities, suggesting an increased focus on radio. By extracting data related to complaints, they expect to identity issues related to registration requirements, the online system, accessibility and more.
Presentation 5 — Using Integrated Data to Monitor and Evaluate Specific-Purpose Grants
Group five wants to develop a comprehensive and accessible dashboard to monitor and evaluate the implementation of energy-related specific-purpose grants (DAK), for the internal use of Bappenas. The dashboard would allow officials to set priority areas, verify any requests and give specific feedback for certain allocations, thus ultimately helping better allocate energy grants.
What We Learned
In the process of running this series of workshops, we learned several things that we’ll use for future activities of this kind:
- We need to “code switch” our toolkit to the Indonesian policy context. It’s not just about translating the toolkits into Bahasa Indonesia — more importantly, it’s about adapting concepts, examples and facilitation approaches to something that is inherently relatable to Indonesian policy makers.
- A round of “socialisation” for each targeted working unit would have been an ideal precedent for the workshop series. We learned that participants of workshops are usually assigned to attend by their supervisors. While it would have been ideal to base workshop attendance on interest instead of on nomination, having briefings with the heads of each working unit would have probably helped the targeted work units to better assign participants for the data clinics. Preparatory meetings like these also could have helped shape and prioritise on what policy issues participants could focus during the workshop series.
- For an audience of policy makers, the workshop series could be structured into two main parts: the first part should be focussed on identifying salient policy issues and relevant research questions; the second part would focus on options for new data sources and building the research hypothesis — this would need the involvement of data scientists, data engineers, programmers and statisticians to brainstorm ideas and provide inputs on what is feasible.
Working Together for Big Data Innovation
This series of workshops is an example of how Pulse Lab Jakarta works with Bappenas to optimise their existing internal capacity for data innovation. After the workshops, the proposals were presented in front of the Bappenas Steering Committee at the end of December for further discussion. Some of these projects could potentially be implemented in the future by Bappenas, with the assistance of the Lab. Pulse Lab Jakarta works closely with its partners to foster a culture of data-driven innovation and provide technical guidance on big data to policymakers.
Pulse Lab Jakarta is grateful for the generous support of the Department of Foreign Affairs and Trade of the Government of Australia.