Results Data Initiative

Rethinking how we collect, share, and use development results data.

Our Goal

To give government and agency leaders the information, tools, and approaches they need to base development management, policy, and planning decisions on actual results.

About the RDI Program

Launched in 2015 with support from the Bill & Melinda Gates Foundation, our first task for the Results Data Initiative (RDI) was to better understand how local-level development actors actually collect, share, and use results data to inform development programs. After speaking with over 450 government officials, donor representatives, and implementer staff in RDI Phase I, we are putting our insights into action.

Across RDI, we worked with five country governments and two development agencies to address critical barriers to results data use. How? By creating a combination of tools, datasets, resources, and approaches to help dynamic officials in each partner institution enable results-based decisions. With our partners at the Results for Development Institute, we've implemented an innovative joint learning approach to drive this program, ensuring our work meaningfully influences the actions of leading development actors.

RDI Phase I: Review our Findings

RDI Phase II

In Phase II, with new support from the Bill & Melinda Gates Foundation, RDI entered into implementing practical solutions. We worked alongside two country governments and two development partners to find new ways to promote results data use, and especially to connect resource allocation to results. Specifically, we applied theories of change – models of how strategies and inputs result in expected impact – to match political economy, institutional structures, human resources, and data sources. In doing so, we found ways to merge data into policy and decision-making processes.

While the first goal of RDI was to elevate the results focus of a few governments and agencies, our broader program goal was to provide real examples for how the "Data Revolution" can improve development policy and practice.

To achieve this goal,  we sought to transform these constraints into a virtuous cycle of data use by using a problem-driven and iterative approach (PDIA) to first identify a relevant decision; then work “backwards” to identify the right tools, resources, and data needed to support that decision. 

pdia1

Our Problem-Driven, Iterative, and Adaptive (PDIA) Approach

RDI Phase II at the Country Level

DG worked with the Governments of Tanzania and Malawi, in the health and agriculture sectors respectively. With each government, we  identified practical applications of data to support government leaders get the information they need to base management, policy, and planning decisions on actual results.

We also put our PDIA approach into motion – facilitating cross ministerial discussions around key problems and decisions for which data could be used, and potential data sources and tool designs to meet these needs. This new approach enabled us to leverage knowledge, capacity, and data from across ministries to design more holistic, needs-based solutions.

Our goal is to develop sustainable (and scalable) tools and analysis that outlast this program. These tools will be country-owned and co-created, developed based on the needs identified by decision makers themselves and tested through a PDIA approach. In the two countries, we are undergoing co-design workshops that value feedback and iteration in order to build tools that make the most sense for their users.

The Government of Malawi, Agriculture Sector

Since 2017, DG has collaborated with the Malawi Ministry of Agriculture, Irrigation, and Water Development (MoAIWD) in country level data use support. Our aim was to support framework design for the National Agriculture Management Information System (NAMIS).

DG and MoAIWD completed a detailed landscape analysis – of priority decisions, data and tools, and data use barriers in the agriculture sector. The below Conceptual Framework and its Executive Summary inform NAMIS design, and provide actionable recommendations for MoAIWD during system implementation.

The Government of Tanzania, Health Sector

In Tanzania, we worked with the President’s Office for Regional Administration and Local Government (PORALG) to address the data use gap at the local level by presenting relevant health data to facilities and communities. DG undertook a collaborative, cross-ministerial program to increase health data access and use in Tanzania. We aimed to:

  1. identify local priority health decisions, 
  2. identify the information needed to make those decisions, and 
  3. trial which visualization methods are most useful when communicating these data to local officials.

We conducted handover & training of the below Health Data Dashboards with government staff in January 2019, and look forward to follow-on work in Tanzania through support from the William & Flora Hewlett Foundation.

tz dash

ward report

tz dash 2

The Tanzania Health Data Dashboard, Ward Report Generator, and Facility Report Generator

RDI Phase II at the Agency Level

DG worked with Development Agencies – the United Kingdom's Department for International Development (DFID) and Global Affairs Canada (GAC) – to assess current results information use in each agency, and co-create, test, and scale tools and processes that increase the use of data and evidence in policy making.

This work included holistic assessments aimed at identifying the political, technical, and practical obstacles to improving results data use. Learnings from the assessments served as an input for developing, testing, and scaling the new tools and processes. This approach was collaborative, continuous, and iterative so as to arrive at tools that are useful and tailored to the needs of each agency. In working with DFID and GAC, we utilized the same PDIA approach that we do at the country level in Tanzania and Malawi, but adapt it to different contexts. We aimed to arrive at tools that are useful and made-to-measure for the specific needs of each agency.

Targeting data use pain points within agencies and development partners themselves is an exciting – and unique – opportunity to pave the road to effective policy implementation, improved accountability, and useful learning.

Global Affairs Canada

Working on both the data supply and demand side of data within GAC, DG reviewed GAC’s internal project-level data, extracted project-level data relevant to the FIAP indicators, and aggregated them for an initial baseline. Also, our landscaping work with employees revealed areas of data demand for results within GAC. GAC launched their new Feminist International Assistance Policy, and collaborated with DG to strengthen their results reporting system to inform the agenda. We used our insights inform the operationalization of GAC’s Architecture for Results in International Assistance strategy, and design an annual reporting template and methodology for the FIAP.

Department for International Development (DFID)

DG conducted in-depth interviews with approximately 60 DFID staff across four country offices, all sector teams, and senior management within the UK's DFID. This work examined the role that data plays in supporting key decisions taken by DFID at the strategy, portfolio (sector or country), and programme level.

DFID and DG recently released the report “Decision-Making and Data Use Landscaping: Better Data, Better Decisions - May 2017 to October 2018.” Its recommendations have been implemented by integrative work across analytical and technical professions in DFID, and made possible by the creation of a new cross-departmental DFID Statistics Hub. The report also informed DFID’s thinking on how to harness the potential of data in tackling extreme poverty.

RDI Phase III

Through 2019, we are pleased to be expanding RDI alongside our growing set of development partners and funders. 

RDI III focuses on agency-level engagement, and we are scaling our partnerships with development agencies to use results data to inform critical policy and programmatic decisions.

We are continuing to work across departments, with senior leaders and technical staff, to develop effective tools and data use strategies. Our goal is to strengthen capacity and mechanisms for leveraging data during key planning processes, from portfolio management to internal learning.  This also means continuing to support cross-agency peer learning via direct matchmaking of staff across agencies. Each step of the way, will utilize existing platforms like the OECD to share learnings and resources, aiming to achieve greater impact from results data.  

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