Recientemente di una charla TED en la cual destaqué lo útil que es tener esta capacidad con un grupo  de personas como trabajadores de salud comunitaria o de gestión de suministro de medicamentos que ya poseen celulares básicos: es posible reportar información extremadamente útil a cerca de sus actividades o niveles de inventario con un simple mensaje de texto.

Esta función fue financiada por IRC de manera de facilitar el trabajo que venían realizando con trabajadores de salud comunitaria en Sierra Leona y vale agregar que ha resultado todo un éxito. Otras organizaciones como la Federación Internacional de la Cruz Roja también han estado utilizando esta función pero para combatir la malaria.

Sin embargo, el inconveniente se ha dado en que para hacer que la función sea tan simple de utilizar como lo ha sido Magpi (y anteriormente EpiSurveyor), hemos tenido que recurrir a un SMS “agregador” o “gateway” (una especie de mayorista que consolida acuerdos con las prestadoras de servicio de cada país) para que nos provea la conexión entre el sistema SMS del celular y la aplicación web de Magpi.

En resumen nuestros usuarios han podido establecer sistemas SMS de recolección de datos en apenas unos minutos—mediante una subscripción a Magpi—comparado a las semanas o meses y miles de dólares que tomaría hacer lo mismo pero con la contratación de programadores o técnicos.

El problema radica en que para personas en países emergentes que envían datos por SMS lo deben hacer a números que pertenecen a los agregadores en Inglaterra o Estados Unidos, incrementando substancialmente los costos: un mensaje de texto en Kenia puede costar entre u$s 0,01 a u$s 0,02 mientras que un texto a Inglaterra puede costar u$s 0,50. De manera que nuestros usuarios han estado solicitando una manera más sencilla de establecer números locales para subir sus datos a Magpi.

Por suerte, nuestros amigos de Ushahidi, más reconocidos por su software de mapas, ya resolvieron este problema! Resulta que crearon una aplicación para Android llamada SMSSync que cuando se utiliza con una tarjeta SIM de Kenia puede enviar los mensajes SMS a un servicio en la nube como Magpi. Tuvimos que hacer unos pequeños ajustes a Magpi pero el SMSSync ya está funcionando y listo para probar.

Entonces las opciones son:

1.       Si no es inconveniente enviar mensajes de texto a un número internacional o no se tiene el tiempo para descargar y configurar la aplicación SMSSync, ningún problema ya que se puede comenzar a recolectar datos con SMS ahora mismo haciendo uso de la función ya presente en Magpi.

2.       La preferencia es ahorrar haciendo uso de un número local para enviar mensajes de texto, bien, sólo es cuestión de bajar e instalar SMSSync en minutos (por supuesto es necesario una tarjeta SIM local y un móvil Android para el país en que se realice la copilando datos).

Imagine: puede subscribirse a Magpi y establecer un portal SMS en cualquier país del mundo en tan sólo minutos, utilizando un número local o internacional!

Haga clic aquí para leer instrucciones (en inglés) paso a paso sobre cómo utilizar SMSSync con Magpi

Muchas gracias a Ushahidi por esta herramienta y por hacer de Magpi más útil, económica y fácil de instalar!

Invention versus Innovation

To understand the importance of our Magpi mobile data collection product as a model of “disruptive innovation” for mHealth and ICT4D (information and communications technology for development), it’s important to understand the difference between invention and innovation.  Although the two terms are often used synonymously, in fact they convey very different ideas.

In a famous example of the difference, there were many different MP3 music players before the iPod: Apple clearly did not invent the concept of MP3 player.  However, Steve Jobs managed to create an MP3 player, the iPod, that solved many problems for users and made it very easy to legally download music – so much so that many people who had previously been illegally downloading pirated music began instead buying it legally via iTunes.  And millions of people who had not previously bought an MP3 player (perhaps because of the complexity) bought iPods.

The invention was the MP3 player, but the innovation was the iPod.

What’s “Disruptive” Innovation?

Clayton Christiansen of the Harvard Business School (author of  The Innovator’s Dilemma) coined the term “disruptive innovation” to describe a particularly significant innovation that wasn’t just an improvement on previous technologies, but which used an approach that dramatically lowered the price compared with previous technologies.  And by doing so made that product available to many more people:

To me the perfect example of this kind of “disruptive innovation” is the automobile.  Not many people realize that the invention of the automobile did not occur in the early 20th century, or even the late 19th century.  In fact,  Nicolas-Joseph Cugnot demonstrated a steam-driven vehicle in 1771.

Those early automobiles, however, were complex, buggy, and difficult and expensive to build and use and maintain.  Basically, you needed to be an engineer, or at least a serious tinkerer – and a well-off one – to have a car in those days: what today we would call a hacker.

Because of these problems, the automobile didn’t really catch on: hardly anyone owned one for more than 100 years – even though an enormous number of people could have benefited from them.

So what changed?  Well, Henry Ford – often incorrectly thought of as the inventor of the automobile – invented a new way of producing the automobile, the assembly line, that reduced the cost tremendously and which standardized the parts, which made the cars easier to maintain and fix. And the economies of scale meant that for several years, Ford dropped the price of the car every year.

And the result was that car ownership in the US went from essentially 100 years of nothing to hundreds of thousands of car owners.

Those early experimenters in the 1700s invented the car, but Henry Ford’s innovation around the car actually made it accessible to the masses, as this graph of car sales in the USA demonstrates:

mHealth: Still Stuck in 1771

Sadly, in mHealth we are still stuck in 1771: very few health-related organizations, particularly in international development, are using mobile software for health (compared with those that might benefit – which is likely ALL of them) and the technology is generally complex, buggy, and difficult and expensive to build and use and maintain.  This means lots of technology consultants and programmers are needed for implementation, and that means lots of money.

Think what a big difference there is between the way almost all your personal software works nowadays:

and the way mHealth and ICT4D work:

Magpi: Like Gmail but for Data Collection

Magpi is different: Magpi is taking the same approach as our favorite apps – and was the first software in global development to do it:

Why is this so important? Because most of the money spent on mHealth programs is eaten up by non-local programmers, tech consultants, and their associated costs (like airfare, hotels, and per diem payments).  Unfortunately, if you’re one of the organizations or individuals building mHealth “solutions”, and you make most of your money from things like training . . . well, you’re not very incentivized to simplify your software to the point where it doesn’t need any training.

At some point, we’re all going to recognize this simple fact: we can have programmer-intensive, non-cloud-based, lots-of-training-required mHealth or we can have affordable mHealth scaled to everyone who needs it.

But we can’t have both.

As I highlighted in my recent TEDx talk, this is extremely useful if you have a group of people, like community health workers or drug supply workers, that already have basic phones: they can report incredibly useful information about their activities or supply levels using just a simple text message.

The feature was funded by IRC in order to facilitate their work with community health workers in Sierra Leone, and has worked well.  Other organizations, like the International Federation of the Red Cross, have been using the same feature for malaria work.

One sticking point, however, has been that in order to make the feature as easy as the rest of Magpi (and EpiSurveyor before it), we have been using an SMS “aggregator” or “gateway” company to provide the connection between the phone’s SMS capability and the internet-based Magpi web application.  The aggregators basically make agreements with many, many local carriers in many countries and provide a middle layer of software between the local carrier and Magpi.

The bottom line is that users have been able to set up worldwide, SMS-based data collection and reporting systems in just a few minutes — with the requirement that they have a paid Magpi subscription — as opposed to doing the same thing by other methods which would take weeks or months and tens of thousands of dollars of programmer/technician time.

The only problem is that for many developing countries the people sending data in by SMS have to send it to the aggregator’s UK or US number, and that raises the costs substantially: a local SMS in Kenya might cost one or two US cents, while texting to the UK could cost US $ 0.50.   So users have been asking us for a simple way to set up a local number that will route their data into Magpi.

Luckily, it turns out that the folks at Ushahidi, famous for their mapping software, have already solved this problem!  They have created an Android phone app called SMSSync that when equipped, for example, with a Kenyan SIM card can route users SMS messages to an internet service like Magpi.  We had to make a couple small adjustments to Magpi’s web application in order to work with SMSSync, but now it’s working just fine – and it’s ready for you to try yourself.

So now you have a choice:

1. Don’t mind sending your SMS messages to an international number, or don’t have the time to download and configure the SMSSync app?  No problem, you can start collecting SMS data immediately using the built-in system in Magpi
2. Want to save money by using a local number to send SMS messages to?  Downloading and installing SMSSync to use with Magpi will take only minutes (of course, you’ll need to buy a local SIM card and Android phone for whichever country you’re working in).

Imagine: you can now sign up for Magpi and set up an SMS data entry system in any country on earth in just minutes, using either a local or an international number!

Click here to read step by step instructions on how to use SMSSync with Magpi

Many thanks to Ushahidi for this great tool that is making Magpi even more useful, inexpensive, and easy to set up!

Phase 1: In the Beginning There Was Paper

Since the beginning of what we now call international development, we have relied on the collection of data using paper forms.  Today, because of the technologies available to us, the  field is beginning to undergo tremendous changes.  In a sense, paper-based data collection was “phase 1″: health workers carrying huge stacks of paper forms to the field in a process that was difficult and time-consuming.

Not to mention environmentally disastrous: ever think about how many trees have been sacrificed to get data for, ironically, environmental studies?

Global health has been no exception: though we often don’t have good data, when we have any data it almost invariably comes from a paper-based data collection activity:

In the 1990s, tools like Palm PDAs, the first affordable handheld computing devices, raised the possibility of moving to faster, more accurate electronic data collection – and many attempts were made to make that into a reality, including the first versions of DataDyne’s Magpi mobile data system (under its former name of EpiSurveyor).  Unfortunately, PDAs were aimed at the rich world market of businesspeople and other professionals, and so you could walk into a store in New York and buy one — but in order to use them for a health survey in Namibia, for example, the difficult and expensive burden of getting them to Namibia was placed squarely on the shoulders of the global health system.  As it turns out, this was too heavy a burden to bear: the PDA-based data collection activities typically collapsed after just a few years.

Phase 2: Replicating Our Paper Approach with Phones

PDAs gave us the idea of practical electronic data collection in the field, then, but we had to wait until the commercial sector was able to develop a business case for bringing pocket computers to poor countries — and this has famously happened in the form of the mobile phone.  And the presence of ubiquitous mobile phones in poor countries has largely let the international development community focus on collecting data, rather than on importing hardware in the form of phones.

Because of the hyper-successful introduction of mobile “phones” (really, mobile computers) to poor countries, we’re now moving quickly into Phase 2: replacing the paper forms with electronic ones.  Our Magpi mobile data system makes the process of creating electronic forms a free and simple process, and those forms can easily be deployed on anything from a $20 Nokia phone to an iPad.  But as the diagram below shows, Phase 2 is in most aspects just like Phase 1: it still requires time-consuming, expensive and often dangerous trips to the field, but carrying a phone instead of a clipboard:

This is the classic experience with new technologies: at first we use them to do the same things we’ve always done, just better in some way.   The first book printed with the printing press was the same book that was most often copied by hand: the Bible.  But gradually people came to realize that that new tool could be applied to do things that had never been done before: like make inexpensive and widespread newspapers.

While most global development data collection is stuck in the paper-based phase, we now have nearly 17,000 people using our Magpi mobile data system, which is a pretty good start.  Not surprisingly, they’re using it mostly in a Phase-2 style: going to the field as they always have, but with phones instead of paper.  This is saving time, money, and lives, without question.

Phase 3: Hearing Directly from the Field, and Saving Ourselves the Trip

Some of our more adventurous users, though, have begun to experiment with Phase 3.   In Phase 3, we no longer replicate the old data collection process of sending data collectors to the field.  Instead, recognizing that many of the people we were previously interviewing – citizens, community health workers, etc – now have mobile phones of their own, these adventurous users are having the people who are already in “the field” transmit data themselves, often using the mobile phone they already own:

Critically, by creating a completely new approach, this lets us do some things things we simply couldn’t do before, like having community health workers providing real-time birth registration via SMS.  And by making that kind of SMS system so easy and inexpensive (the total tech budget is roughly $5000 per year, with no tech personnel required, and the tech side can be set up in just minutes by non-techies), we’re unleashing the creativity of many people and organizations that could never have afforded this approach before.  In the upcoming year, we’ll be sponsoring contests to find out the most revolutionary uses of our Magpi mobile app, in both Phase-2- and Phase-3-style.

Phase 4: the Internet of Things

As I’ve mentioned, most of those in global development and health are still in Phase 1 (paper), but more and more are moving to Phase 2, and some are beginning to experiment with Phase 3.  We expect this co-existence of these phases to continue for years (I won’t be surprised 20 years from now to find some organizations still using paper for data collection, sadly) – and we can already see another phase on the horizon.

You could think of Magpi data collection as composed of two parts:

1. the “client” – a person in the field using a mobile device to send data. In Phase 2 that person in the field is a professional interviewer, while in Phase 3 that person could be a community health worker, a teacher, or an average citizen.
2. the server system – a back-end system in the cloud (www.magpi.com) that can receive and process and safeguard that data.

We’re now working on ways for Magpi to receive data from devices without a person being involved: imagine a sensor in a vaccine refrigerator that transmits a daily temperature reading, or sends an alert if the temperature goes out of range:

Or thousands of inexpensive electronic rain sensors deployed in environmentally sensitive areas, each of them sending data cheaply and reliably once a day (or once an hour!). That kind of data could revolutionize our understanding and management of so many fields.

The main obstacle to achieving a system like that isn’t in connecting things like thermometers with Android phones – that part is actually not very difficult, and even a single programmer or technician may be all that is needed.  No, the main obstacle is in building, serving, operating, and maintaining a reliable back-end system to receive, analyze, and visualize the data — which requires a whole team of people, from customer support technicians to programmers to a server maintenance staff.

That team sounds expensive, and usually is, but DataDyne has managed to bring that cost down with Magpi.  This opens the pathway for lots of experiments: anyone can create an application or device that sends data into a Magpi account (including a free account) and not have to worry about the difficulty and expense of maintaining the back end.

You’ll hear more about this from us before very long. Stay tuned!

In my recent TEDx talk, I talked about the difficulties in getting good data in the field. I think there is no better example than one recently conveyed to me by Maria Trujillo of the World Bank.

Maria has been working for on the Nutrition and Social Protection project in Honduras, which supports the expansion of nutritional and health services for children under 2 through a strategy called Atención Integral a la Niñez en la Comunidad (AIN-C, “Comprehensive Child Care in the Community”) since the 1990s.

Here’s some background:

First a USAID project, then a World Bank investment, the project is aimed at reducing the chronic early childhood malnutrition by expanding the development of community-based networks that monitor children’s development, train mothers in nutritional and health practices, and provide curative primary care services. As of June 2011, this program had already expanded to more than 1,000 of the poorest communities where 98% of children have their weight monitored and are referred to health centers. Data collected in the field by the health workers takes at least one month to reach central level, limiting the ability of the program to respond to acute nutrition emergencies.

To reduce the time required to get this data at the central level, the project has been using Magpi (formerly EpiSurveyor) to collect the data on mobile phones. Remarkably, their move to mobile has been accomplished at very low cost — using the free version of Magpi, with no outside technical support or programming needed — but while Magpi eliminates many of the technology obstacles, the field staff still must overcome the amazing challenges of the environment.

Consider the off-the-grid community of Capire, where there is no electricity, no cell phone signal, no place to meet, and other obstacles. Despite all of the above, the three young “monitores” (field workers; two young men and a young mother in their 20s) had scheduled the monthly meeting with 8 mothers and their children for December 14th. The AIN-C program had given a phone to this  team of monitores during training in November, and the team saw this as an opportunity.

The cell phones were charged with a car battery, a service paid for by a monitora’s personal funds. As result, she was promised a solar cellphone charger from the AIN-C project for the following month. The AIN-C meeting place usually took place at the school, but the school was under construction, so the team successfully requested the use of a private home. At the meeting at 9am, 8 children were weighed and charted, and counseling was given to each mother. The Capire team carried this out despite missing ‘carnets’ or AIN-C booklets assigned to each child to track weight (these were also promised for their next monthly meeting).

After the meeting with mothers was concluded, the team entered the collected information on the cell phone without a problem. They helped each other, called the data for each other, and rotated the use of the phone to make sure each one of the team knew how to input data. Time required to type each child record ranged between 1.5 and 2.26 minutes. This is fast for the expected standards (3+ min), especially for a team that had no refreshing course or technical support, after their training several weeks ago.

So this team of child health monitors has no electricity, no official place to meet or work, no booklets to provide to the parents with the child’s weight measurements, and little training in using the phones for data collection.  But these are not the only problems.

Sending the data to the cloud was the greatest challenge. There was no signal (neither carrier Tigo or Claro) whatsoever in the area where the meeting had taken place. The closest place where a signal was known to exist was 5 km away, approximately a 30-40 minute walk. It also required asking for permission to access a hill, which is private property. All the team travelled there, asked for permission to climb the hill, only to find the signal was not strong enough (1 bar only) and not constant. The team decided to travel 5 km. more to find appropriate signal (2 bars and constant). The team was delighted when all the data was sent successfully. They brainstormed and concluded that the area in which one monitor lived could be the best area to send data.

So the team winds up walking 6 miles in order to get a signal and transmit their data.  But are they discouraged?  No! In fact, their enthusiasm for the work has only increased, because they realize that the data is now available in minutes, not months.

Not only has the technology been adopted, but buy-in is complete. In fact, technology in this community has galvanized the AIN-C meetings, and renewed the monitores team’s important role in this community. Furthermore, in the Unidad de Salud (Health Unit), data was available immediately, as we were able to verify some minutes after leaving the Capire area and travel to Trojes (the nearest city). All 11 records sent by the Capire team were available via the EpiSurveyor [Magpi] cloud for all to access. And the dedication and good will from teams like the Capire team was never stopped by any challenge — leading to the first real-time AIN-C data via cell phone for the program.

The difficulties of Maria’s team seem remarkable, but in fact are part of the day-to-day work experience for health workers in poorer regions of the world.  Their amazing and unfailing enthusiasm seems equally remarkable, but it is really astonishing once you have spent time in the field to realize that the world is filled with dedicated and hardworking health workers just like this.

And with Magpi we can help those workers to achieve real-time data for child nutrition in a truly sustainable way, with annual runnings costs for the technology measured in just hundreds of dollars (for phones and airtime) — not hundreds of thousands of dollars.

Read more about the AIN-C project:

• John Donaghy’s blog — John is a lay volunteer with the Catholic diocese of Santa Rosa de Copán, Honduras
• World Bank blog by Marie Chantal Messier 

BAD NEWS from Gabon, 1st child death survey in 10 years shows no improvement inspite of high GDP/capita http://t.co/yXWbI32VJO

2013/02/23 15:49:41 via web

Hans Rosling

HansRosling

On one level, of course Dr. Rosling is right that it IS very bad news to find out that there has been no reduction in child mortality in Gabon in 10 years. What I find just as tragic, though, is the unstated assumption that it is normal for child mortality in Gabon to be measured authoritatively only every 10 years (in the DHS survey that he was referring to).

Every ten years??? No wonder they don’t seem to be making any progress! It’s hard to imagine making progress in any activity when you only measure things every ten years.¹

And all of global health typically reacts in the same way: most global health institutions and practitioners grew up in the days before the internet and the mobile phone had really expanded into Africa and the rest of the developing world, and they’ve gotten used to extremely infrequent data. In the “old days” — up to the last decade — the only possible way to get data was on paper: it was normal, and understandable, to gather data only infrequently.

The problem is that times and the technology infrastructure have changed — but global health hasn’t changed with it. Despite 10 years of explosive growth of mobile telephony even in rural Africa — and our Magpi mobile data system (formerly “EpiSurveyor”) freely available to all and used by more than 15,000 worldwide — we are still collecting almost all global health data on paper. And in some cases only every ten years.

Really, this has changed from a situation where we were limited by lack of technology and limited infrastructure to a situation where we are more limited by the inability of global health leadership to understand and take advantage of the new reality.

Happily, a few organizations have moved to the leading edge and are using these very cost-effective technologies right now, and they show us a way forward.

The IRC (International Rescue Committee — www.rescue.org), for example, is a long-time Magpi user and gives us a great example of how things might be different: how we can achieve real-time data on child mortality, for example, cost-effectively and at scale.

IRC uses the SMS data capture feature of Magpi in Sierra Leone. They have rural community health workers utilizing incredibly cheap mobile phones (typically costing $10 or so — and that is not a misprint) to send child birth and death counts for a population of about 10,000 from their villages on a weekly basis (I highlighted this in a recent TEDx talk).

Yes, weekly. Not every 10 years, or every 10 months, or even every 10 weeks. Every single week.

That is effectively a real-time mortality monitoring system in just the kind of rural environment found in Gabon, yet IRC manages to supplement the very extensive (and incredibly useful) data collection in the DHS survey at that frequency for a total technology cost of less than $6000 a year.

For the whole program. And that is not just the software cost:

• The servers are operated by DataDyne and so that cost is included in the $6000 cost.
• The phones are $10 phones.
• No programmers are required, so that cost is eliminated.
• No tech consultants are required, so that cost is eliminated.
• No outside trainers were required — since the system is designed to require little or no training — so only IRC local or international staff already working in Sierra Leone were needed.
• The tech support is provided by DataDyne as part of the IRC’s paid subscription to Magpi, so that is also included in the $6000 cost — although it should be said that IRC has required almost no technical support at all, and no one from DataDyne has even visited the project.

To expand such a system to give an excellent weekly picture of child mortality for the entire country of Sierra Leone would only cost about $100,000 annually — roughly the annual salary and benefit cost for a single international development consultant.

Given that Gabon has about one-third of the population of Sierra Leone, the cost for implementing a country-wide system for weekly mortality monitoring would be correspondingly less. But even at $100,000 it’s a bargain: we’re talking about a country-wide real-time mortality system that would truly help the health system to understand what’s happening on the ground, and to save more lives.

And one can easily imagine how much better those with such data can plan and implement their programs — designed to decrease child and maternal mortality.

Bill Gates recently wrote about the importance of better tools for measuring data for international development, education, and other purposes in the Wall Street Journal, but in the section of his article on global health the mobile data projects he discusses are all pilots and still-to-be tested technologies, which typically spend most of their budgets on programmers and consultants. That is a model that is simply too expensive to scale. Magpi is utilizing the cloud and mobile to deliver scaleable, real-time data for health and other purposes at incredibly low-cost, right now.

It is ironic that Mr. Gates’ vision of inexpensive and scaled real-time measurement in health, education, and other areas is already being implemented by organizations like IRC (and our other users like Abt and JSI and Camfed and WHO and many others), but Mr. Gates seems to be unaware of it.

I’d love to hear suggestions for how we can change that!

—

¹ Of course, progress may have been made in those ten years: the mortality rate may have fallen, then risen again — or the reverse. We just cannot say: a ten year interval just does not give enough information.

Those without access to YouTube can view and download the video file here (46MB).

The Challenge, sponsored by USAID and Humanity United, comes with a $5000 prize, but far more importantly it recognizes the important contributions being made by PHR, Informacam, and DataDyne to meet the needs of the human rights community, and to fight against sexual violence and other human rights violations.

My talk, which we will post as soon as the video is made available available here, centered on the path we’ve taken at DataDyne over the years to really identify and overcome obstacles to getting better data for health and other programs. A major component of that was, and still is, our SSWFt (self-service, web-based, freemium tech) approach to technology:

• self-service (i.e., do-it-yourself) – no technology that requires consultants and programmers every time it’s implemented.  Unfortunately, the consultant-and-programmer approach dominates international development — not because it scales better (it doesn’t scale at all) or sustains well (it always dies soon after the project funding runs out), but because it’s more lucrative for the programmers and consultants.
• web-based – web- or cloud-based systems have taken the commercial and consumer software world by storm because they are dramatically cheaper to implement. Magpi (as it’s former version of EpiSurveyor) was the first cloud-based application for development, but although several years have passed it still has very few companions in the cloud.  Why? Because in the world of international development, organizations are often specifically looking for ways to spend more, not less.  If you think this isn’t true, you should hang around the offices of any US government or UN agency at the end of the fiscal year: people will be running around trying frantically to spend whatever is left in their budgets.
• freemium – because web-based and self-service systems are so much cheaper (think Skype), we can actually offer a great free service entirely supported by a tiny minority of users — another area in which DataDyne is leading the way in international development.

This approach has brought us to 14,000 users worldwide in just three years – with nearly 3000 new users added in just the last MONTH since Magpi came online.  To me this just shows the remarkable need for better data collection systems, and how much people really want to move away from paper.

DataDyne va dévoiler en janvier 2013 une version complètement nouvelle de EpiSurveyor, y compris son nouveau nom ! Oui, nous mettons à la retraite la vénérable “EpiSurveyor” – avec ses 10 000 utilisateurs dans 170 pays, il s’agit sans conteste du système de rassemblement de données pour portables la plus utilisée dans le secteur du développement, et du projet de technologie d’information et de communication pour le développement (ICT) le plus réussi qu’il y ait jamais eu — et nous la remplaçons par “Magpi”.

Nous avons choisi Magpi (rime avec “éventail”) parce que nous avons réalisé que beaucoup de gens pensaient qu’un produit baptisé “EpiSurveyor” n’était utilisé que pour des études d’épidémiologie.

C’est certes compréhensible, mais nous voulons être certains que les gens savent que EpiSurveyor est utilisé pour rassembler toutes sortes de données : dans les secteurs de la santé, de l’agriculture, pour les chaînes logistiques, les sondages de consommateurs, et bien d’autres choses. Nous abandonnons donc notre nom.

Plus de 40 nouvelles fonctions !

Notre équipe de développement à Nairobi a ajouté plus de quarante nouvelles fonctions, plus de vitesse, une plus grande facilité d’utilisation, et le tout pour le même prix, y compris pour la version gratuite. Magpi est une application complètement nouvelle, recréée à partir de zéro, et qui fonctionne comme EpiSurveyor (vous n’aurez donc aucun problème à l’utiliser si vous êtes habitué à EpiSurveyor).

Les tests bêta sur Magpi sont en cours, et la version 1.0 sortira en janvier 2013. Remarque : il n’y aura pas d’interruption de service lorsque nous effectuerons le changement. Abonnez-vous à notre liste de diffusion pour être sûrs d’être informés lorsque Magpi rentrera en service ! (si vous êtes un utilisateur de EpiSurveyor, vous figurez déjà sur la liste).

Voyez Magpi en action !

En attendant, vous pouvez regarder cette vidéo (réalisée avec l’aide de nos amis à TechChange) de Joel Selanikio, PDG et co-fondateur de DataDyne, présentant à la fois EpiSurveyor et certains des grandes améliorations de Magpi. La section sur Magpi démarre aux alentours de 3:25 minutes :