Social service organizations have long used data in their efforts to support people in need for the purposes of advocacy, tracking, and intervention. Increasingly, such organizations are joining forces to provide wrap-around services to clients in order to “move the needle” on intractable social problems. Groups using these strategies, called Collective Impact, develop shared metrics to guide their work, sharing data, finances, infrastructure, and services. A major emphasis of these efforts is on tracking clients and measuring impacts. This study explores a particular type of Collective Impact strategy called Promise Neighborhoods. Based on a federal grant program, these initiatives attempt to close the achievement gap in particular geographic communities. Through an analysis of publicly available documents and information, the study analyzes the ways these strategies enact (and fail to enact) a collective intelligence for the common good. The analysis focuses specifically on issues surrounding data collection and use, youth agency, leadership and governance, and funding streams. Together, these foci develop a story of an increasingly used “intelligence” with a limited sense of “collective” and a narrow vision of a “common good.” Using this as a platform, the paper explores alternatives that might develop more robust practices around these concepts….(More)”.
What do we know about when data does/doesn’t influence policy?
Josh Powell at Oxfam Blog: “While development actors are now creating more data than ever, examples of impactful use are anecdotal and scant. Put bluntly, despite this supply-side push for more data, we are far from realizing an evidence-based utopia filled with data-driven decisions.
One of the key shortcomings of our work on development data has been failing to develop realistic models for how data can fit into existing institutional policy/program processes. The political economy – institutional structures, individual (dis)incentives, policy constraints – of data use in government and development agencies remains largely unknown to “data people” like me, who work on creating tools and methods for using development data.
We’ve documented several preconditions for getting data to be used, which could be thought of in a cycle:
While broadly helpful, I think we also need more specific theories of change (ToCs) to guide data initiatives in different institutional contexts. Borrowing from a host of theories on systems thinking and adaptive learning, I gave this a try with a simple 2×2 model. The x-axis can be thought of as the level of institutional buy-in, while the y-axis reflects whether available data suggest a (reasonably) “clear” policy approach. Different data strategies are likely to be effective in each of these four quadrants.
So what does this look like in the real world? Let’s tackle these with some examples we’ve come across:
Building State Capability: Evidence, Analysis, Action
(Open Access) Book by Matt Andrews, Lant Pritchett, and Michael Woolcock: “…Governments play a major role in the development process, and constantly introduce reforms and policies to achieve developmental objectives. Many of these interventions have limited impact, however; schools get built but children don’t learn, IT systems are introduced but not used, plans are written but not implemented. These achievement deficiencies reveal gaps in capabilities, and weaknesses in the process of building state capability.
This book addresses these weaknesses and gaps. It starts by providing evidence of the capability shortfalls that currently exist in many countries, showing that many governments lack basic capacities even after decades of reforms and capacity building efforts. The book then analyses this evidence, identifying capability traps that hold many governments back – particularly related to isomorphic mimicry (where governments copy best practice solutions from other countries that make them look more capable even if they are not more capable) and premature load bearing (where governments adopt new mechanisms that they cannot actually make work, given weak extant capacities). The book then describes a process that governments can use to escape these capability traps. Called PDIA (problem driven iterative adaptation), this process empowers people working in governments to find and fit solutions to the problems they face. The discussion about this process is structured in a practical manner so that readers can actually apply tools and ideas to the capability challenges they face in their own contexts. These applications will help readers devise policies and reforms that have more impact than those of the past….(More)”.
Decentralized Self-Organizing Systems
Fred Wilson at AVC: “Mankind has been inventing new ways to organize and govern since we showed up on planet earth. Our history is a gradual evolution of these organization and governance systems. Much of what we are using right now was invented in ancient Greece and perfected in western Europe in the 17th, 18th, and 19th centuries.
I have been thinking for some time that we are on the cusp of something new. I don’t know exactly what it will be but I think it will be inspired by the big technological innovations of the late 20th century and early 21st century and it will be based on decentralized and self-organizing systems.
The Internet is, at its core, a scaled decentralized system. Its design has been a resounding success. It has scaled elegantly and gradually to well over 2bn users over fifty years. No central entity controls the Internet and it upgrades itself and scales itself slowly over time.
Open source software development communities are also an important development of the past fifty years. These communities come together to create and maintain new software systems and are not financed or governed by traditional corporate models. The goals of these communities are largely based on delivering new capabilities to the market and they don’t have capitalist based incentive systems and they have shown that in many instances they work better than traditional corporate models, Linux being the best example.
And, for the past decade or so, we have seen that modern cryptography and some important computer science innovations have led to decentralized blockchain systems, most notably Bitcoin and Ethereum. But there are many more to study and learn from. These blockchain systems are pushing forward our understanding of economic models, governance models, and security models.
I think it is high time that political scientists, philosophers, economists, and historians turn their attention to these new self-organizing and self-governing systems….(More)”.
Using Crowdsourcing to Map Displacement in South Sudan
The Famine Early Warning Systems Network: “…partnering with Tomnod to improve population information in five South Sudanese counties by using crowdsourcing to gather evidence-based food security analysis.
Through Tomnod, volunteers from around the world identify different elements such as buildings, tents, and livestock in satellite images that are hosted on Tomnod’s website. This approach creates data sets that can more accurately assess the level of food insecurity in South Sudan. …
This approach will help FEWS NET’s work in South Sudan obtain more information where access to areas of acute food insecurity is limited…(More)”.
Networked Governance: New Research Perspectives
Book edited by Betina Hollstein, Wenzel Matiaske and Kai-Uwe Schnapp: “This edited volume seeks to explore established as well as emergent forms of governance by combining social network analysis and governance research. In doing so, contributions take into account the increasingly complex forms which governance faces, consisting of different types of actors (e.g. individuals, states, economic entities, NGOs, IGOs), instruments (e.g. law, suggestions, flexible norms) and arenas from the local up to the global level, and which more and more questions theoretical models that have focused primarily on markets and hierarchies. The topics addressed in this volume are processes of coordination, arriving at and implementing decisions taking place in network(ed) (social) structures; such as governance of work relations, of financial markets, of innovation and politics. These processes are investigated and discussed from sociologists’, political scientists’ and economists’ viewpoints….(More)”.
These Refugees Created Their Own Aid Agency Within Their Resettlement Camp
Michael Thomas at FastCompany: “…“In the refugee camps, we have two things: people and time,” Jackl explained. He and his friends decided that they would organize people to improve the camp. The idea was to solve two problems at once: Give refugees purpose, and make life in the camp better for everyone….
It began with repurposing shipping material. The men noticed that every day, dozens of shipments of food, medicine, and other aid came to their camp. But once the supplies were unloaded, aid workers would throw the pallets away. Meanwhile, people were sleeping in tents that would flood when it rained. So Jackl led an effort to break the pallets down and use the wood to create platforms on which the tents could sit.
Shortly afterwards, they used scrap wood and torn pieces of fabric to build a school, and eventually found a refugee who was a teacher to lead classes. The philosophy was simple and powerful: Use resources that would otherwise go to waste to improve life in their camp. As word spread of their work on social media, Jackl began to receive offers from people who wanted to donate money to his then unofficial cause. “All these people began asking me ‘What can I do? Can I give you money?’ And I’d tell them, ‘Give me materials,’” he said.
“People think that refugees are weak. But they survived war, smugglers, and the camps,” Jackl explains. His mission is to change the refugee image from one of weakness to one of resilience and strength. Core to that is the idea that refugees can help one another instead of relying on aid workers and NGOs, a philosophy that he adopted from an NGO called Jafra that he worked for in Syria…(More)”
A How-to Book for Wielding Civic Power
Interview by David Bornstein at the New York Times: “Last year, the RAND Survey Research Group asked 3,037 Americans about their political preferences and found that the factor that best predicted support for Donald Trump wasn’t age, race, gender, income, educational attainment or attitudes toward Muslims or undocumented immigrants. It was whether respondents agreed with the statement “People like me don’t have any say about what the government does.”
A feeling of disenfranchisement, or powerlessness, runs deep in the country — and it’s understandable. For most Americans, wages have been flat for 40 years, while incomes have soared for the superrich. Researchers have found, unsurprisingly, that the preferences of wealthy people have a much bigger influence on policy than those of poor or middle-income people.
“I don’t think people are wrong to feel that the game has been rigged,” says Eric Liu, the author of “You’re More Powerful Than You Think: A Citizen’s Guide to Making Change Happen,” an engaging and extremely timely book published last week. “But we’re in a period where across the political spectrum — from the libertarian Tea Party right to the Occupy and Black Lives Matter left — people are pushing back and recognizing that the only remedy is to convert this feeling of ‘not having a say’ into ‘demanding a say.’ ”
Liu, who founded Citizen University, a nonprofit citizen participation organization in Seattle, teaches citizens to do just that. He has also traveled the country, searching across the partisan divide for places where citizens are making democracy work better. In his new book, he has assembled stories of citizen action and distilled them into powerful insights and strategies….
Can you explain the three “core laws of power” you outline in the book?
L. No. 1: Power compounds, as does powerlessness. The rich get richer, and people with clout get more clout.
No. 2: Power justifies itself. In a hundred different ways — propaganda, conventional wisdom, just-so stories — people at the top of the hierarchy tell narratives about why it should be so.
If the world stopped with laws No. 1 and 2, we would be stuck in this doom loop that would tip us toward monopoly and tyranny.
What saves us is law No. 3: Power is infinite. I don’t mean we are all equally powerful. I mean simply and quite literally that we can generate power out of thin air. We do that by organizing….(More)”
Confused by data visualisation? Here’s how to cope in a world of many features
The Conversation: “The late data visionary Hans Rosling mesmerised the world with his work, contributing to a more informed society. Rosling used global health data to paint a stunning picture of how our world is a better place now than it was in the past, bringing hope through data.
Now more than ever, data are collected from every aspect of our lives. From social media and advertising to artificial intelligence and automated systems, understanding and parsing information have become highly valuable skills. But we often overlook the importance of knowing how to communicate data to peers and to the public in an effective, meaningful way.
The first tools that come to mind in considering how to best communicate data – especially statistics – are graphs and scatter plots. These simple visuals help us understand elementary causes and consequences, trends and so on. They are invaluable and have an important role in disseminating knowledge.
Data visualisation can take many other forms, just as data itself can be interpreted in many different ways. It can be used to highlight important achievements, as Bill and Melinda Gates have shown with their annual letters in which their main results and aspirations are creatively displayed.
Everyone has the potential to better explore data sets and provide more thorough, yet simple, representations of facts. But how can do we do this when faced with daunting levels of complex data?
A world of too many features
We can start by breaking the data down. Any data set consists of two main elements: samples and features. The former correspond to individual elements in a group; the latter are the characteristics they share….
Venturing into network analysis is easier than undertaking dimensionality reduction, since usually a high level of programming skills is not required. Widely available user-friendly software and tutorials allow people new to data visualisation to explore several aspects of network science.
The world of data visualisation is vast and it goes way beyond what has been introduced here, but those who actually reap its benefits, garnering new insights and becoming agents of positive and efficient change, are few. In an age of overwhelming information, knowing how to communicate data can make a difference – and it can help keep data’s relevance in check…(More)”
Technology and the Voluntary Sector: Don’t (always) Believe the Hype
Gareth Lloyd at the NCVO: “One of the most important questions for voluntary sector organisations of all sizes is how their work can be supported by technology. We have talked before about how the sector needs to identify technology that is replicable and has low barriers to uptake, but we have also recently carried out a research project with Tata Consultacy Services on this issue, which involved an evidence review, mapping exercise and workshop with voluntary sector experts.
Here’s a brief overview of what we learned, including the different challenges for large and small organisations; as well as those that apply to everyone.
Grand ambitions
First, our work looked at the attraction – and possible dangers of – investing in new and largely unproven technologies. We have seen the voluntary sector undergo fleeting love affairs with new and exciting types of technology, such as big data, crowdfunding and bitcoin; and we go through periods of hearing about technologies that have the potential to change the way that the sector works…..
Defining problems and choosing solutions
For all the challenges mentioned so far, the underlying issue is the same: a mismatch between the problem to be solved and the solution implemented. The answer is to focus on the problem that you’re trying to solve, whether approaching it as a technology issue or not, and then look at the ways that technology can help you. For example, Jointly – the app developed by Carers UK to enable conversation between groups of carers – stands out as a problem that could have been addressed without use of technology, but was eventually enhanced by it.
But organisations also have to ensure that the technology used to solve those problems is cost effective, time effective, and appropriate for them in terms of where they are starting from. If the solution you choose is tying you up in knots, maybe it isn’t a solution at all.
Our research came up with some high level principles that organisations can use to avoid these problems, and try to ensure that adopting technology transforms the day-to-day activities of organisations while minimising disruption…
Think iterations, rather than discrete projects
Participants at our workshop talked about how the discrete project model doesn’t quite work when trying to embed technology at an organisation. That is, rather than these projects having straightforward planning and implementation phases, they need to be introduced iteratively, as an ongoing process of deployment, evaluation and redesign. Introducing technology in this way minimises risk, helps to ensure that the solution fits the problem, and ensures that it is tailored to the needs of the people who will use it on a day to day basis.
If you are interested in this research you can read the executive summary here, the full slide deck here, or find details of the Spark Salon event where it was launched here….(More)”