chevron icon twitter logo facebook logo linkedin logo Youtube logo download icon quote icon posted icon clock icon author icon arrow icon arrow icon plus icon Search icon location icon location icon document icon plus-alt

Better data for better social outcomes. 

We are joining and playing our part in global efforts towards better data use for better social outcomes. As the Government Outcomes Lab (GO Lab) at the Blavatnik School of Government in the University of Oxford, our contribution is to convene an “International Network for Data on Impact and Government Outcomes” or “INDIGO.”  

INDIGO is a community of peers from different countries, sectors and policy domains with an interest in sharing data about the design, implementation and evaluation of cross sector collaborations to address complex social problems. We believe that helping more people share and use quality data will improve both the efficiency and effectiveness of these projects.  


Where we are now... 

Imagine you work in a local government and want to improve the lives of homeless people in your area. You might be able to find a few case studies of projects that address homelessness, but do you know how other local governments have defined goals for programs to tackle this problem? Can you find examples of projects that seek to address similar issues? In a similar context?   

Across the world, people are working to solve a wide range of complex problems such as homelessness, long term unemployment or reducing crime rates through projects that use cross sector collaboration. Addressing these challenges often involves the joint work of governments, private sector, and third sector organisations. Even though these collaborations share similar rhetoric and promise, it is often too difficult and expensive to access information about these projects.  

This is why we have started this INDIGO initiative.  Its main objective is to support the use of quality data by policymakers who are addressing complex social and environmental problems. Data standards initiatives already exist in particular sectors, but INDIGO’s key contribution is to harmonise those standards – and culture – across sectors involved in impact bonds and other outcome-based approaches. We are collaborating with existing standards. We are borrowing wheels, not reinventing them.   

INDIGO this way:

1. Join User Community  

INDIGO is fundamentally about supporting use of data for policymaking. You can join our INDIGO peer learning group and participate in our hack-and-learn events. 

2. Use Data Standards

INDIGO aims for an open data standard for adoption and use by outcomes funders, investors, and service providers. This will help link to existing data standards, such the Open Contracting Data Standard and 360Giving. For example, we are working with the Brookings Institution on data definitions for a core impact bond dataset. We encourage our partners to use these standards and routinely share their data. We offer template contract language and can help you build this into your projects or portfolio of projects.  

3. Share Quality Data 

An outcomes-based approach fundamentally involves data on outcomes. Data may be used within an organisation, among a group of organisations, and with external parties including the public. We know that not all data are shared with everyone in the same way. However, INDIGO partners should start with the default position that their data should be shared openly with the public unless there is a good reason not to do so. The public is likely to be another funder, investor, or provider trying to solve a complex social problem so this data will be hugely useful to them. If you need a place to publish your open data and documents consistent with the INDIGO and/or related, relevant standards, the GO Lab may be able work with you to publish your data. 

INDIGO Theory of Change - A Draft for Discussion (June 2020)

Here we describe our "theory of change" or "programme logic." It is a simple table describing our aspirations in terms of inputs (resources), activities, outputs, outcomes, and impact. Such a table is sometimes referred to as a "logic model," which suggests something complex, but is actually (deceptively) simple in appearance. As of June 2020, this is a draft for feedback at our June 25th INDIGO Peer Learning Group session

INDIGO Draft Logic Model For Discussion June 2020

INDIGO Use Cases - A Draft for Discussion (June 2020)

Below we describe our use cases in a simple table set up to bring clarity to the potential INDIGO user about what they want from INDIGO, and why they want it. Accordingly, the columns are "As a...,"  I want..." and "so that..."  This arrangement is based on an agile software methodology which focuses software development efforts around "user stories." Here we are borrowing this agile method to focus our INDIGO initiative squarely on users and use cases. As the GO Lab, we understand the researcher user well because we are that user. We have varying levels of confidence in our understanding of other users and welcome input. As of June 2020, this is a draft for discussion and improvement at our June 25th INDIGO Peer Learning Group session.

INDIGO Draft Logic Model For Discussion June 2020

Contact us

We hope that the spirit of innovation and collaboration, so integral to the success of outcomes-based projects themselves, will also carry this initiative forward. Let’s work through these issues together. For more information, please email