Shruti’s professional journey is rooted in her passion for evidence-based policymaking and development. With a PhD in governance and development, she began her career as a researcher, diving into new doctrines and theories. Her desire to bridge the gap between policy and implementation led her to the World Food Programme (WFP), where she has worked for over seven years in donor-facing roles focused on policy advocacy and strategic influence.
Now based in Rome at WFP’s headquarters, Shruti leads a team specializing in reporting and forecasting, integrating analytics and knowledge management into policy agenda setting. Her role allows her to harness data to guide policy, ensuring sustainable and impactful development initiatives.
In this spotlight interview with UNSSC’s Itziar Arispe Ruiz de Gauna, Shruti reflects on her experience with the UN Data Analytics Professional Certificate, sharing how it enriched her understanding of data visualization, storytelling, and the transformative potential of machine learning.
Itziar: Briefly tell us about yourself and your professional background. How did you join the United Nations (UN) and how has your experience been so far?
Shruti: I started my career as a researcher focused on new doctrines and theories but soon realized the importance of implementing development programs in relation to government policies and data. Without this alignment, initiatives risk becoming merely a development assembly line without achieving sustainable outcomes. This led me to the UN, where I was drawn to the World Food Programme (WFP) due to its role in influencing policy and access to food systems. Over the past seven years with WFP, I’ve worked in a donor-facing role, engaging in policy advocacy and transferring insights from the country office to the headquarters in Rome, where I now focus on reporting and forecasting. This role aligns with my curiosity about how data informs policy, and it has been a continuous learning experience.
Itziar: Why was it important for you to pursue the UN Data Analytics Professional Certificate? Based on your experience, what did you hope to gain from the learning?
Shruti: In my current role, I focus heavily on reporting and forecasting, leading a team dedicated to these areas. This work falls within the broader context of analytics, governance, and knowledge management. We deal with large volumes of data, which involves both data management and data cleaning on one hand, and data storytelling and visualizations on the other. The field is dynamic and fast-moving, with numerous technologies, ideas, and platforms continually emerging. Navigating this landscape can be challenging, especially when trying to determine which tool is suited to a specific purpose. I often find myself asking, “Does this tool meet my needs?” There was a lot of confusion, and I experimented with various platforms, while also feeling apprehensive about others. When I discovered the content of this course, I realized it could help me address these challenges. I hope to gain valuable insights into the tools available, empowering me to understand which ones are most applicable to my context. That's what I aim to achieve through this course.
Itziar: What are some of the most memorable parts of your learning experience with UNSSC?
Shruti: For me, the most beautiful and awe-inspiring moment was getting a sneak peek into the world of machine learning. This was something I had been hearing and reading about and discussing all the time, but I really didn’t understand what it meant. I found it completely alien to ask what happens when you engage in machine learning. However, as we went through the webinars and explored the tool BigML, I realized that this was a whole new world. It felt like a journey through "Alice in Wonderland," and it truly empowered me. Now, when I return to discussions about our new tech strategy and how it will unfold in the future, my contributions are no longer based on prejudices or preconceived notions. Although I still have some fears or inhibitions about certain technologies, I feel more grounded when I speak about machine learning or artificial intelligence. My ideas are shaped by genuine experiences rather than half-formed thoughts. I have learned what machine learning can achieve and the costs involved. That part of the course truly felt like my "Alice in Wonderland" moment, and it will remain with me forever.
Itziar: An essential part of this learning offering is that you are able to use what you have learned practically. Can you share with us two key takeaways from the On-Job-Practice of the course?
Shruti: So, as I mentioned, I am leading a team which is largely about reporting and forecasting, and for both these elements, visualization is very important.
One of the major challenges I faced in my context was that, despite having access to vast amounts of data, everything was organized in a very tabular format. This made it difficult to drill down and gain a strategic, one-glance view of the information. Senior management and leadership at various levels—such as country offices, regional bureaus, and headquarters—require a way to glance at the data and quickly understand the historical trends and contributions. This need for a comprehensive overview was a significant gap within the team. Just before I joined the course, we had begun experimenting with Tableau, but we were struggling to create a dashboard that fulfilled this requirement. The goal was to develop a dashboard that provided an immediate big picture, showcasing contributions across different elements like regional bureaus and thematic areas. Specifically, I was focusing on contribution data from a historical perspective, categorized by themes and regions.
This course came in very handy because during the sessions, I could share what challenges we were facing during our experimentation with Tableau. This led to my "Eureka" moment. I realized where we were going wrong. I discussed this with my team, and together, we developed a new visualization that corrected the mistakes we had made. This experience was a significant breakthrough for me: I learned during the sessions, applied that knowledge, and corrected our errors.
The other big takeaway storytelling is emerging as a very important way for A) advocacy, and B) shedding light on areas where we need more attention to support senior leadership in making evidence-based pitches. We had tried certain things, but we were not quite there. Our small reports which were just scratching the surface. When we were going through the course, it not only empowered us with the knowledge of how to use the tools, but also the dos and don’ts and how to structure the story for better impact.
I created 'Wired Deep Dives'. We take one issue, go deep into it, compare it from different perspectives, and bring out a narrative. We’ve institutionalized 'Wired Deep Dives', and we plan to produce one every quarter, looking at any one issue which could be relevant for the time.
Itziar: Can you tell us more about how it was working with your peers during the course?
Shruti: One of the most exciting sessions was data storytelling, and in one of the initial sessions we were given a readout. Some of us had already done the modules, so we knew what was coming. The task given to us during the webinar focused on the number of refugees and the type of storytelling we could create around this topic. In the group I was part of, everyone became deeply engaged with the process. We began discussing different tools, saying things like, “Let’s check out Canva,” followed by “No, let’s try Flourish.” One person shared their screen, and we started brainstorming ways to depict boats filled with people. Then someone else proposed, “No, let’s switch; I have a better idea,” and shared their screen. Even though we were all strangers and didn’t know each other well, the topic united us. In the end, our group successfully created an impactful image and presented it to the larger group. We felt very proud of our work.