I recently gave a talk at the American Association for the Advancement of Science about Big Data and Analytics and why it matters for development. Unlike other speakers who warned about risks associated with big data - when too much is known about too many people without their consent - I discussed the problem of data gaps and data poverty in the developing world. The challenge of measuring of poverty is different because if we don’t have the data, we can’t know whether we’re making progress in fighting this stain on our collective moral conscience.
The World Bank for example, monitors poverty in 155 countries, but we only have recent poverty estimates for half of them, and those estimates are already 5 years old. This is problematic for an institution whose stated goal is to eliminate extreme poverty over the next 15 years. How will we know when we get there?
As we’re learning from our staff and others working in data-starved environments - high frequency and real-time data from a variety of new sources can be really useful. We can use digital signals to see what's happening in a country at a micro-level to target interventions like the distribution of food, medicine, and other essential services. For example, in areas where mobile penetration is high, mobile airtime and the geographic distribution of pre-paid credits can signal in real-time that incomes are fluctuating and where it’s happening. Similarly, the movement of mobile phones across geographies reveals migration patterns that are useful in tracking the spread of diseases like Ebola. While this data is not perfect, it's often the best we have and an entirely new source of intelligence.
But beyond the data buzz, its important that we subject data to hypotheses to ensure our theories are sound and ‘data proxies’ are reliable. We need to test theories before acting on them. One challenge is that N is not equal all. Tim Harford reminds us that correlations can be misleading and are often just wrong. In several examples above, the patterns we observe in call detail records are not related to all people who live in a specific geography but people with phones. So we need to recognize these limitations and acknowledge what data does and doesn’t t tell us.
Then there is the challenge of data noise. As Nate Silver reminds us most big data is just noise and that noise is increasing must faster than the signal. He writes, “there are so many hypotheses to test, so many data sets to mine--but a relatively constant amount of objective truth.” Formulating good questions is always difficult but even more critical when parsing through very large data sets and looking for meaningful correlations. In a recent publication, " Big Data in Action for Development," the World Bank Group collaborated with Second Muse, a global innovation agency, to explore big data's transformative potential for socioeconomic development. The report develops a conceptual framework to work with big data in the development sector.
The emergent field of big data analytics and data science is a combination of statistics, computer science and social science. The first two without the third can lead to spurious and often dangerous conclusions. Imagine a health intervention that completely misses vulnerable populations because they don't own GPS-enabled smart phones. We have learned from Google’s flu trends that big data sets need to be regularly ground-truthed and subjected to scrutiny.
As someone who works with large data sets within a global development institution, I'm a firm believer in the power of real-time data. But our analytics must be backed by credible hypotheses and sound social science. It’s important to be clear about what data does and doesn't tell us. Only then can we move from data to knowledge and from intelligence to actionable insight.
The World Bank for example, monitors poverty in 155 countries, but we only have recent poverty estimates for half of them, and those estimates are already 5 years old. This is problematic for an institution whose stated goal is to eliminate extreme poverty over the next 15 years. How will we know when we get there?
As we’re learning from our staff and others working in data-starved environments - high frequency and real-time data from a variety of new sources can be really useful. We can use digital signals to see what's happening in a country at a micro-level to target interventions like the distribution of food, medicine, and other essential services. For example, in areas where mobile penetration is high, mobile airtime and the geographic distribution of pre-paid credits can signal in real-time that incomes are fluctuating and where it’s happening. Similarly, the movement of mobile phones across geographies reveals migration patterns that are useful in tracking the spread of diseases like Ebola. While this data is not perfect, it's often the best we have and an entirely new source of intelligence.
But beyond the data buzz, its important that we subject data to hypotheses to ensure our theories are sound and ‘data proxies’ are reliable. We need to test theories before acting on them. One challenge is that N is not equal all. Tim Harford reminds us that correlations can be misleading and are often just wrong. In several examples above, the patterns we observe in call detail records are not related to all people who live in a specific geography but people with phones. So we need to recognize these limitations and acknowledge what data does and doesn’t t tell us.
Then there is the challenge of data noise. As Nate Silver reminds us most big data is just noise and that noise is increasing must faster than the signal. He writes, “there are so many hypotheses to test, so many data sets to mine--but a relatively constant amount of objective truth.” Formulating good questions is always difficult but even more critical when parsing through very large data sets and looking for meaningful correlations. In a recent publication, " Big Data in Action for Development," the World Bank Group collaborated with Second Muse, a global innovation agency, to explore big data's transformative potential for socioeconomic development. The report develops a conceptual framework to work with big data in the development sector.
The emergent field of big data analytics and data science is a combination of statistics, computer science and social science. The first two without the third can lead to spurious and often dangerous conclusions. Imagine a health intervention that completely misses vulnerable populations because they don't own GPS-enabled smart phones. We have learned from Google’s flu trends that big data sets need to be regularly ground-truthed and subjected to scrutiny.
As someone who works with large data sets within a global development institution, I'm a firm believer in the power of real-time data. But our analytics must be backed by credible hypotheses and sound social science. It’s important to be clear about what data does and doesn't tell us. Only then can we move from data to knowledge and from intelligence to actionable insight.
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I agree with your point. ICT's workflows can change the way how a government get information and even the way it acts and the perception that citizens have about the state. Good services are not in dispute with new tech. In contrast, new tech leads society to new paradigms of efficiency. The general behavior in public policies is the herd mentality that only thinks in short terms, and this is a very... wrong solution.
Read more Read lessHi Jay, Thanks for your comment. You are right that short-term thinking is part of the issue. It is just that there are not many incentives out there for policymakers to be "first-movers" in many areas. And it is true that new services should leverage on the information that can now be collected. It is not only about "digitizing" current workflows, ICTs are so disruptive that many services should... probably be re-designed from scratch. Cheers, amk
Read more Read lessYou make some excellent points, Arturo. It would be phenomenally motivating if we could have a design lab right here at the Bank to test innovative services and ideas that might have the potential to become public goods, absorbing the costs of innovating (within boundaries), and celebrating successful failures. regards, -tina
Hi Arturo, Design Thinking for government services is exactly what I'm trying to do! Thank you very much for your post. I'm pretty encouraged:) As you mentioned, I understand that it's not easy to introduce innovative services into government services. So I'm thinking of offering some instructive courses about design thinking for the workers. Yuki
Hi Tina, Thanks for your comment. What a great idea. There are some interesting and innovating ideas in the Bank, but they are not that well disseminated and seem to be the exception rather than the norm. Evoke (http://www.urgentevoke.com) is one that comes to mind (you can check several posts on it on the Edutech blog - http://blogs.worldbank.org/edutech), or CAPRA (http://go.worldbank.org/XH2KMUQR70)...... but that's all I can think of. Your point on failures is also huge. It is ok to fail, as long as we learn from these experiences. Edutech actually had a post on the FailFair which took place in DC around July / August. Anyway, let's try to put together a proposal on a Design Lab! Cheers, amk
Read more Read lessDear Yuki, Congratulations! I am sure such a course will open many opportunities to create new and better services at your office. If you are interested in reading material, I recommend the following books: - Tim Brown, "Change by Design: How Design Thinking Transforms Organizations and Inspires Innovation", HarperCollins, 2009 - Roger Martin, "The Design of Business", Harvard Business Press, 2009 -... Thomas Lockwood (editor), "Design Thinking", Allworth Press, 2009 Here is another book I've seen but haven't gone through: - Roberto Verganti, "Design-driven innovation", Harvard Business Press, 2009 Note that all these books have been published last year... Good luck and let us know how it goes! Regards, amk
Read more Read lessINFORMATION AND COMMUNICATION TECHNOLOGIES: PLATFORM FOR ECONOMIC DEVELOPMENT… First of all, information and communication technologies (ICT) remain essential in improving resource use and service supply. However, the relationship between ICT and governance is a powerful but nuanced one. For instance, governance reforms (1) need to be informed, not just by performing ICT, but also by basic data and... strategic information obtained through a stark departure from traditional views on the architecture and the scope of conventional information systems. How to do that depends on context and background. Why? INFORMATION SYSTEMS: PLATFORM FOR SOCIAL COHESION AND SUSTAINABLE DEVELOPMENT… The paradigm shift required to make ICT instrumental to governance reforms is to focus on what is effective and efficient in building a critical mass of capacity for positive change. Unfortunately, regardless of whether or not they are controlled by the public sector or by the business world, many, if not most, information systems in low- and high-income countries can be characterized as closed administrative structures through which there is limited flow of data on resource allocation for service delivery. They are often only used to a limited extent by a limited number of top officials at national and global level when formulating policy reforms, while little use is made of critical and strategic information that could be extracted from other tools and sources – e.g. opinion surveys, NGOs, professional associations, academic institutions, research centres, etc. -, many of which are located outside the public sector and (sometimes) far away from the business world… Now more than ever, from a policy point of view, the crucial information is that which allows identification of the operational and systemic constraints. In this context, the multiplication of information needs and users implies that the way information is generated, shared and processed also has to evolve. This critically depends on transparency (availability and accessibility), for example, by making pertinent information readily accessible via the Internet (2). OPEN AND COLLABORATIVE MODELS: PLATFORM FOR BETTER GOVERNANCE AND EQUITABLE DEVELOPMENT… Today, governance reforms call for open and collaborative models, such as “Malaria Observatories” (3,4), to ensure that all the best sources of data are tapped and information flows quickly to those who can translate it into appropriate action. Once established, these state/non-state multi-stakeholder networks can play a key role in complementing and improving routine information systems, by directly linking the production and dissemination of intelligence on specific issues to the sharing of best practices. Generally speaking, these innovative structures reflect the increasing value given to cross-agency work: they thus institutionalize the linkages between local governance and country-wide policy-making… IN THE FINAL ANALYSIS... There is need for making information and communication technologies (ICT) instrumental to governance reforms. Unfortunately, the institutional capacities to meet this ambitious requirement are typically weak in countries classified as low-income. However, even in countries with well-resourced information systems and sophisticated communication networks, there is still need for far-reaching improvements and groundbreaking innovations in terms of architecture, scope, multisectoral response and multidimensional approach… Doctor Michel ODIKA (Congo-Brazzaville) 1. Governance reforms: balanced approaches to be found (http://blogs.worldbank.org/governance/comment/reply/841/1845) 2. Site internet pour le Ministère de la Santé (http://www.slideboom.com/presentations/169290/Site-internet-pour-le-Minist%C3%A8re-de-la-Sant%C3%A9-%28Congo-Brazzaville%29) 3. Advocacy for a Malaria Observatory in Congo-Brazzaville (http://www.booksie.com/health_and_fitness/article/michel_odika/advocacy-for-a-malaria-observatory-in-congobrazzaville/nohead/pdf/ver/8) 4. Observatoire du Paludisme: capital au service d’un idéal (http://www.slideshare.net/Odika/observatoire-du-paludisme-capital-au-service-dun-idal)
Read more Read lessThe discipline of human centered design planning offers rigorous methods based approach to identifying the problems to be solved and framing them correctly prior to the design and development of solutions. Without that, we're back to the spaghetti on the wall trial and error approach. http://www.nitibhan.com/2013/01/reflections-on-design-thinking-for.html