Digitalisation and big data – A cost-effective and reliable way for decision-making in the international development context
movimentar GmbH is a social enterprise providing advisory, training, and software development services for organisations and individuals working in sustainable development and humanitarian actions. Its founder Eduardo works as a project-management and data-science consultant, trainer, and facilitator in designing, managing, and evaluating projects and programmes across the globe. In the following interview, he outlines his work, his motivation, and why he thinks that using technology and data science in international development projects can speed up humanity’s efforts towards sustainable progress.
Eduardo, why do you do the job you do today?
Digitalisation and big data are gigantic challenges for agencies working in the international development and humanitarian sector including governments, international organisations, civil society, and the private sector. Our job is to help these actors, using technology and data science (statistical computing), to get the most of their data in a cost-effective and reliable way in time for decision-making. Science and technology can speed up humanity’s efforts towards sustainable progress by helping actions to become more evidence-based and results-driven.
Why are you working in this industry?
I do not believe that there are single industries anymore. Everything is connected, and data science can help us to see that better with increased precision and quality. My goal is to bring science and technology closer to project and programme management in different thematic areas. Independently from the topic, professionally designed digital data-collection processes together with big-data techniques (e.g., text mining) and artificial-intelligence algorithms such as machine learning methods can work just like glasses. They help one see better. They are not there to replace one’s eyes (and brains), but they allow for a more realistic picture of the world with reduced error and bias. Hans Rosling is a great inspiration to me, and I try to contribute to his legacy of promoting more factfulness in public policies and international development actions.
What do you enjoy most about your job?
Discovering new ways to contribute to sustainable development for thousands of people. Every assignment is full of discoveries. It always amazes me to see new and counter-intuitive relationships between variables and problems. As anything else, they are also continuously changing in space (geographic area) and time. Analysing the interrelations between variables and problems is the first step towards addressing the world’s problems.
What was the best decision in your career and why?
Start learning computer languages, especially R and Python. They are always evolving and one is always learning something new. I have always worked with international cooperation for development and humanitarian aid. This is a sector that has seen many impressive achievements such as the reduction of extreme poverty by half in the last 20 years. The more progress humanity achieves, the harder it gets to make further improvements. R and Python are the key languages when it comes to data science and artificial intelligence. They are free software and therefore extremely powerful through their worldwide community. Everyday one can see further developments by thousands of developers around the world. Data-science skills have increased my potential contribution to more evidence-driven decisions and transparency in the international development and humanitarian sectors.
What makes you excited about Mondays?
The possibility of taking part in the improvement of the lives of more people around the world.
What has been your greatest career disappointment? What did you learn from it?
Once I worked on a large action with environmental groups working with development education. I designed a system to provide them with real-time information on the satisfaction of participants about their activities with digital data collection. I was invited to present the system at a large initial partner conference, and I did. I had so far only exchanged ideas with the leading organisation and did not know the others. During my presentation, some of the older and more influential members were determined in not letting me even present the tools. We had to interrupt the presentation and exclude the data-collection system from our contract. My lesson from that: To never underestimate the fear of technology as well as the change-management efforts particularly among older and less technology-savvy decision-makers.
Describe the environments in which your leadership style is most effective. Where have you been frustrated and less successful?
Charles Darwin once said: “In the long history of humankind (and animal kind, too) those who learned to collaborate and improvise most effectively have prevailed.” Participation and collaboration are of crucial importance. Multiple minds can produce better than one. Technology is helping people to collaborate more effectively. Every now and then we come across cases where people still prefer a more top-down approach. Depending on the organisational culture of the client, some staff are not willing to make direct contributions to the text of a proposal, for example, and prefer to make general or subjective comments without taking ownership for the product. I understand that this is also a way to reduce risk exposure, but it can be inefficient and slows down processes. Luckily, these cases are becoming increasingly less frequent.
What does success look like for you?
Increased capacity of our clients to deliver humanitarian and development actions faster, at scale and with real-time information on their impact and beneficiary satisfaction.