From Excel to Advanced Analytics: MSF’s Data-Driven Evolution

At the Analytics for a Better World (ABW) conference, Ralf van Otterdijk, Data and Analytics Lead at Médecins Sans Frontières (MSF), shared an inspiring journey of how the organization has transformed its approach to data. From its early days of ad hoc Excel reporting to implementing advanced analytics, MSF’s evolution highlights both the challenges and successes of using data to drive humanitarian efforts.

A Data Revolution in Humanitarian Aid

MSF, known globally as Doctors Without Borders, provides medical aid in crisis zones, responding to conflicts, disease outbreaks, and natural disasters. While its humanitarian mission has remained steadfast, the way MSF utilizes data has undergone a major shift. Eight years ago, MSF centralized its data practices, implementing a new ERP system to manage financial, operational, and supply chain data. This allowed for automated data warehousing and Power BI reporting, significantly improving efficiency and decision-making.

Scaling Up: The Challenges of Success

However, success brought new challenges. As demand for data-driven insights grew, the central data team found itself overwhelmed. Without an overarching data strategy, prioritizing tasks across departments became difficult. While self-service BI tools empowered teams to create their own reports, the burden of maintaining and guiding these efforts remained with the core team.

At the same time, MSF aimed to move beyond reporting into advanced analytics. Yet, with daily operations consuming much of the team’s capacity, transitioning to predictive and prescriptive analytics required a fundamental shift in approach.

Breaking the Cycle: A Strategic Approach to Advanced Analytics

Recognizing the need for a structured strategy, MSF implemented three key milestones:

1. A Clear Strategy with Management Buy-In – Establishing an official data analytics strategy, backed by leadership, ensured organizational alignment and long-term commitment.
2. Infrastructure Investments – Moving to a cloud-based data lake provided scalability and security, enabling MSF to host and run predictive models more effectively.
3. Building Skills and Partnerships – Acknowledging the need for specialized expertise, MSF partnered with organizations like ABW to co-create analytics solutions and develop in-house capabilities.

Real-World Impact: Forecasting Malaria Outbreaks

One of the most compelling applications of MSF’s advanced analytics efforts is in epidemic response. Through predictive modeling, MSF is now able to anticipate malaria outbreaks based on climate patterns, enabling teams to take preventive action rather than simply reacting to crises. This shift from reactive to anticipatory action has the potential to save countless lives by optimizing resource allocation and response times.

Looking Ahead: The Role of AI in Humanitarian Data Science

As MSF continues its journey in advanced analytics, the rise of artificial intelligence presents both opportunities and challenges. While AI promises transformative capabilities, van Otterdijk humorously likened the hype to the early days of big data—where “everyone talks about it, but few really know how to do it.” The key, he emphasized, is learning from past experiences to ensure AI is implemented effectively and ethically.

A Data-Driven Future for Humanitarian Aid

MSF’s journey underscores the importance of strategic planning, infrastructure investment, and collaboration in advancing humanitarian analytics. By embracing data, MSF is not only improving operational efficiency but also making a real impact on global health crises. The partnership with ABW ensures that MSF remains at the forefront of using analytics for good—turning data into action where it matters most.

Watch Ralf van Otterdijk’s keynote here!