Throughout all of our visits we have become very familiar with the ‘cybers’ around the city and the slums. A cyber, short for cybercafe, is a pay per use internet cafe without the coffee. With computers, printers, and local supplies they are everywhere. For the diminishing groups of people without a smartphone, this is still how you access the internet. But even with the growth in mobile phones, the cybercafe is far from obsolete. This is where you get a full screen, a printer, more advanced apps, unlimited bandwidth for videos. It’s the compliment to the phone.

Over the last couple of years we have gotten to know a few cybers well and so we wanted to share our “designers” look into the cafe we know best. How does the cyber work? Vivien Lim, a student from a past Groupshot program, worked with us to illustrate this anatomy of a cyber cafe. Explore it here. (http://www.communitydata.org/cybercafe/front)

Today, in places like Kenya, where money and energy are being poured into these data driven projects, there are two first steps that are being taken:

1) Get the data open and online. From open source data collection projects to government level initiatives to liberate data, there is a growing collection of open data.

2) Get people online. Mobile phones, especially, are driving this effort.

These two steps are not enough to create data access.

Technical access to data is not automatically access. For this data to be meaningful the content must be accessible conceptually. Someone who has never used or understood a regression isn’t going to benefit just simply because it is online or she can query the dataset via sms. People need to know what the data looks like and means. We need to foster data literacy.

Data literacy takes two forms: education and representation. Education is more obvious. We need to continue and expand efforts to teach people to be data literate–familiarizing people with common charts, maps, and tables so they can access the data in them, and importantly be more critical of the data behind them.

Data literacy through representation means taking a dataset and representing it in a way that is easy to understand. Commonly in the US we take geographic data and put it on maps, like google maps. Or we take a table and plot it as a line graph. Or increasingly artists create powerful infographics for major newspapers or blogs. These artists and data experts are the translators of data who make more people data literate by writing the data in a different, more familiar, language. No economics PhD or accounting degree requires.

The current approach for expanded data access in Kenya is to encourage these translators. Individuals who can take data and represent it in a way that a wider audience can benefit from it. These translators are often young techies around the world–creating apps and infographics. Apps which can analyze a dataset into a singular recommendation or prediction–infographics that show you how many phones are in Kenya and can thus inform business or NGO strategies.

But we still need more and different translators. The language of hackathons and apps is still out of reach for most people in slums and developing communities around the world. We need to foster local data literacy through expanded education and local translators. They need to create new local forms of representation. Maps that don’t always rely on the global coordinate system but instead use local landmarks. Charts that don’t just use vertical lines or millions of dollars to compare two costs but use local stories, imagery, and experiences.

The third step will be the key step for open data–as it will make the first two count. In August, I spent three weeks researching data literacy in slums around Nairobi to find ways of making step three more local. Over the coming months we will be sharing some of the preliminary examples and inspirations from this research.

While on this workshop we learned a lot about the Social Enteprise design process, both through our own case studies and discussion with social entrepreneurs across India. Over the coming months we will be turning this insight into some short publications and content which we will share here and with a wider community. In the meantime though I wanted to share some keys tips on Social Enterise design that came out from the workshop.

• Start With Context: I am surprised by the lack of context centered social entrepreneurship. To truly have a positive impact you need to be clear on where/who you are working with and why. We met one seemingly great social enterprise in Hyderabad that was conceived of in the States. After a few short scouting trips the idea was formed, and the project went into development–but it was full of assumptions about how education in India happens. It’s taken them two years and counting to evolve their model back to something that actually will work and have impact in the real India.

• Users are Key, but not Everything: User centered design is a great tool. Understanding who your users are and what their lives are like makes the difference between a product and a service that changes their lives, or sits on a shelf unused forever. But a user is not usually the best starting point for a social enterprise. We met one social enterprise that truly understood their user. Their concept was brilliant–the only trouble was that they had chosen the wrong user from the start. Their poor customer could never afford their product (or anything even related) no matter how ‘user-centered’ and ‘affordable’ they made it. Most of the problems social enterprises hope to tackle are systems that have a complex network of stakeholders. Understanding these systems will unravel who the key user(s) you need to keep in mind actually are, and how they all fit together.

• Start With (parts of) a Vision: You need a clear idea of your values, agenda, and skills so you can make decisions. Of course this will change as you research and learn but if you come in with no idea (other than to just do everything right), making decisions will be impossible. A wicked problem doesn’t have a right answer, and looking for the one answer will drive you in circles. Some vision that can focus your efforts onto a particular approach, sector, skillset, or even intervention will allow you to evaluate your project and opportunities throughout the process. Build in flexibility. If you are commited to expanding water access via wells, that may be fine, but don’t commit to building a well in a place you know only a little about that may not be able to maintain or use this well.

• Not every Social Enterprise Can be for Profit: While there are a few places that a for-profit social enterprise can work without undermining its own impact, this is not true for every sector. The debate on for-profit and not-for-profit social enterprise is ongoing, but from our time in India there were lots of examples of good social enterprise ideas that would just never see a real profit. Some sectors just don’t have the profit or business  infrastrcuture to make money and have the same scale of impact. For-profit social enterprise is not the same as a non-profit organization (or unprofitable business) that can generate income, pay reasonable salaries, and make a profit.

• Be Patient and Open: While advice on being flexible is common and obvious, this flexibility must come from an openness to learn. If you are not open to being surprised or wrong at times you won’t be able to find the true insight that will help you design a smart enterprise. Take time to talk to all different people and don’t write off any perspective or person without properly understanding their take–you never know who you might be speaking with.

Impact + Scale aims to capture examples and ideas about how we can improve the design of social enterprise through contextual research. By understanding context and locality an idea can be both local and global and draw from these two areas of expertise.

The Impact + Scale website documents our ongoing research and workshop starting in India in June 2012. Future workshops and research will be hosted on I + S. Follow us on twitter at @impactandscale

Having worked with a number of technologists, innovators, and international development practitioners in Nairobi and elsewhere–it is clear to me that there is a disconnect in lots of the projects which try to join these fields. And so I set to create a practical, project-focused, program that would get creators to think critically about the challenge before setting down to code and create.

One of the most interesting discussions came from the iHub research group session where we mapped out the mechanisms for government service provision and feedback. Today, a lot of developers, many centered at the iHub and Cambridge, MA, my base, are creating apps and websites for citizen feedback. These systems will ask citizen responders to report everything from corruption to potholes.

Our first step was to list a number of ways that governments and citizens engage with one another. This list ranged from protests, elections, and strikes, to TV, radio, and, of course, Apps. We diagrammed a typical service delivery system, such as roads (transport?).. As we expanded our concept to include service providers and added layers for transfer of money, influence, and communication, and nodes for tools and stakeholders, it was clear that the key point of impact for many of the technologies in citizen feedback are in creating a new connection between citizens and governments. The challenge however is in the interfaces between these new system and the existing stakeholders–citizens and government.

Lots of the focus today is on increasing citizen participation–advertising your platform and incentivizing participation. These techniques can make a site popular and visible. But zooming into the government end it is important to consider who will bother to check out your site or project from that end. This challenge brings about the importance of the wider diagram–this is where you recognize the other stakeholders in the process who might have the influence your project needs–from the media to contractors etc. What if the point of your platform isn’t to have an officer in the government read the reports in the spare time, but instead communicates directly to the contractor to make their maintenance job easier, or straight to the media to put pressure on the politicians come election season.

The goal of these workshops, discussions, and stakeholder diagrams was not perfect accuracy. We didn’t spend hours trying to correctly model the entire system–but instead tried to approximate the systems at work so we could begin to identify new avenues for change and continued discussion. These conceptual discussions are the source of innovation and new ideas. Too often the tech innovators of the world and Kenya are encouraged to sit down and code. Our workshops encouraged our groups to get out, ask questions, and think about where to engage. And then, only if its really the right tool, open up the terminal and get to work.

Participants in the workshop were introduced to context-oriented research and design methods through the real challenges Kiva is looking to overcome. Through problem definition, stakeholder interviews, field research, group brainstorming and a final critique the team was able to develop a series of new and interesting strategies while learning tools and approaches useful in their other projects.

We described the workshop as a hackathon with no hacking allowed. Our goal in the workshop was to encourage more technical social entrepreneurs to start with context, rather than technology, and develop the tools and perspective necessary to do so.

At ICTD there has been mention of a lot of projects that didn’t go well–from the light-hearted Fail Faire to a number of individual presentations. Discussing when things don’t go as planned is important and these panels and events have played an essential role in creating the open and honest dialogue that is necessary–and so I applaud the participants and organizers for this.

The idea behind the Fail Faire comes from the similar idea in the start-up world of ‘failing fast’. In both cases we try and turn failure into an inflection point and teachable moment to change your idea and evolve your assumptions. But while we might praise a new start-up for jumping out of gate full speed ahead into their pivot point of total failure, I don’t think this model is as applicable when you are working with either vulnerable populations, non-market groups, or public services and fundamental needs. We aren’t just gambling with an investors funds. Importantly, I think we can do better than failing fast and especially better than failing often.

The biggest challenge of this type of work is in making sense of our assumptions. From the big ones, like assuming that development should look a particular way, to the smaller ones, choosing a particular color, the more work we can do to check and change our assumptions the better work we can do. Also note that assumptions aren’t just a foreign thing, they come from all sides and local groups can also assume things, for example that an unfamiliar technology can and will function in a particular way.

The result of our discussions of failure is a growing list of past assumptions–a database of things to look out for and check off in each project. This is not a  waste of time, we can learn a lot from these lists, but we will never be able to have and use an exhaustive list. So what we really need are the relationships and partnerships across communities–geographic communities, expert communities, practitioner communities–that constantly teach us to identify our assumptions. Working with new people let’s us practice finding our assumptions and questions our expertise, not so we can list and remove them all, but so we can learn how to become aware of them and eventually check them or change them before a big failure.

• The Social in Social Media:  We need to be careful not to interpret every encounter with Facebook and Twitter the same. It is important to understand when you are talking about the more social part of social media. What I mean is that around the world people use Facebook or Twitter all the time–often the way I use e-mail–to keep up with friends or plan a meeting via direct or group messages. Too often we give credit to ‘social media’ that organized something among existing offline groups while other systems can and do play the exact same role.
• Local and Foreign Facing: Both panels touched on US facing technology that impacts audiences here and other technology with remote touch-points around the world. The takeaway is that the technological and cultural landscape in different places is also different and doesn’t take the same skills or tools on both ends. For example, just because you can organize a crowd in Boston via a web platform to support a project in Haiti, doesn’t automatically mean that same technology should also be in Haiti, or that you have the skills to create the same network or impact there.
• Technology for a Few:  In lots of places almost everyone will have a cell-phone and so this may be the communication channel of choice to reach the crowd. Likewise, only a select group of people may have smart phones or use twitter or social media expertly. Sometimes only this group is needed to have an impact. Every project should not be designed for the lowest-common denominator of local technology. You have to design for community–consider when you need one to many, many to many, and one to some to many.
• Rumors and Aggregation: A big topic of concern for social media is how to make sense of the overflow of information while also pulling fact from fiction. When I was in middle school I was taught how to read a newspaper. How to pull the facts in the articles from the opinion in the op-ed. This taught me to be a critical reader and a contextual thinker. While some fascinating technical tools exist to help make sense of social media, we also need to educate about and on social media to embed these processes and skills everywhere.
• Open isn’t Everyone: Open data doesn’t mean that everyone is using it or making sense of it. Just a few people can do a lot with data–and create some powerful and supportive tools. But at the same time, making your data open online doesn’t mean that everyone has access to it, or can draw meaning from the data–there can be technical or data literacy challenges. Open data can be great in a lot of contexts, but we should look for the opportunities to get new people and expertise into open data.

Once again a special thanks to everyone involved in all of these panels–it was a great weekend.