From Development 2.0 to Development Squared: what skills for the aid sector of the future?

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It was O’Reilly’s seminal article on “What is web2.0?” that inspired my first Development 2.0 article and the subsequent Development 2.0 manifesto.

So it was with great interest that I read O’Reilly’s follow-up thinkpiece in preparation to the upcoming Web2 summit. The paper tries to anticipate what will be next in the evolution of the web (the era he dubs “Web Squared”). Once again, there are lots of interesting implications to be drawn for the development sector

To summarize, the key tenet of the Web Squared era is: “the web is now the world”. Thanks to the increased ability to process ever growing amounts of digital data that have a relationship to real world objects (the world’s “information shadow”), the web is “in a collision course with the physical world”: our cameras, and microphones are becoming “the eyes and ears of the web”, our GPS its sense of location and our sensors its sense of position. The web is a baby that is growing up and becoming increasingly sophisticated in its understanding of the various inputs provided by humans: as a result “we are all its collective parents”.

Interestingly, it is O’Reilly himself who now calls for applications of Web Squared to solve real-world problems: from energy to health care. So, here’s an initial attempt at looking through the crystal ball and anticipate what a Development Squared world might look like:

  • The “information shadow” of development projects (and professionals) will increase exponentially, opening up a whole new world of opportunities. So far, due to connectivity and infrastructure issues, the “information shadow” of development projects has been somewhat limited. Go to development agency websites and most digital information about projects is confined to unfrequently updated databases with structured metadata that are helpful for archiving purposes, but do not allow for meaningful heuristics. With mobile phones, digital cameras and other low-cost and small size devices becoming increasingly ubiquitous, the amount of information that will be possible to collect about projects in real time is much greater – and much more sophisticated. Sensors attached to real world objects (from energy meters to cabs) will allow users to accumulate data at a rate unthinkable before and help inform better policy-making (see an example applied to energy efficiency here). New technologies (from speech recognition to biometrics) will allow for the conversion of data into the right format for effective use (as argued in this report). Augmented reality and the internet of things are just around the corner for development workers. And, speaking of people: now that the information shadow of staff in development agencies is much greater (just think about the information you can gather from one’s twitter, tripit, flickr and delicious accounts combined!), entirely new ways to collaborate and connect will emerge that will hopefully relegate the silos that plagued the development 1.0 world to history.

  • The ability to process high quantities of data and identify and visualize patterns in unstructured data is going to be a key skill of the Development Squared sector. Just like university students, specialized workers in development agencies will need to learn how to “climb an Everest of digital data” (as the NYT recently put it). Development agencies will increasingly differentiate themselves by their ability to make sense of large datasets for field work, advocacy and policy making. In case they don’t have the resources to do this in house, crowdsourcing will be the answer if they are to remain relevant, further straining the “ivory tower” legacy of the Development 1.0 world. Maps and other visualization tools will become part of the standard toolkit for advocacy and policy making, but they will need to go a step further. If Gapminder inspired us to identify the patterns in structured data, it is now time to move to the unstructured. Think about Google’s Flu Trends to anticipate diseases outbreaks or language pattern analysis to foster activism.


  • Real time response will move beyond the traditional confines of disaster management or disease outbreaks control to become a mainstream feature across development operations: from donors having real-time access to aid recipients, to on-demand microvolunteering. This also entails that NGOs and aid organizations will need to develop the tools and skills to quickly sift through large amounts of user-contributed data and validate it against official resources (think about user contributed accounts of an election or pictures from a disaster zone). The folks at Crowdflower seem to have already found a solution for this, providing jobs to Kenyan refugees in the process.

Admittedly, the development sector is still stuck in the transition towards the development 2.0 world. Development Squared might be still a long way to go, but the few examples provided so far are perhaps a glimpse of things to come. Just like with web2.0, business model innovation is where we can expect the major breakthroughs to happen. And it is likely that, once again, it is going to be small and agile new players that will lead the charge. At the same time, given the increased level of technological sophistication and the infrastructural needs of processing high quantities of data, it is likely that partnerships between big IT companies and development actors will become increasingly the norm. Which leaves us with the question: what can traditional players do to get ready for Development Squared? Here’s some initial suggestions:

  1. Strategically identify areas where the “information shadow” of projects needs to be increased and where real-time access to information can have a major impact
  2. Forget about developing in-house solutions. Initiate partnerships with organizations with higher IT capabilities, be it Silicon Valley powerhouses or small innovators who can quickly scale up
  3. Develop specific competencies and career paths around processing/visualising unstructured digital data and integrate them as a standard into project work
  4. Develop tools to enhance the information shadow of employees and make the most of it to encourage the breaking down of silos and foster innovation

I would love to get your views on this.

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