Every year, the FAECTOR Consultancy Project unfolds, offering students a unique opportunity to harness their econometric expertise in the realm of practical data analytics. This initiative pairs students with non-profit organizations and small businesses, enabling them to apply their econometric knowledge in real-world scenarios. Last year, the project featured collaborations with War Child, SNV, World Wide Fund for Nature (WWF), KWF (Dutch Cancer Society), and Hartstichting (Dutch Heart Foundation). To delve deeper into the project's intricacies, I conducted interviews with Niels Huijgens, the head of KWF's Data and Intelligence team, and Aditeya, a fourth-year student pursuing a double bachelor's degree, who participated in the project.
Every successful project commences with meticulous organization, a facet well understood by Rutger, the former Marketing Officer of the preceding FCP committee. Being asked about the purpose of the project, Rutger highlighted many non-profit and small-scale enterprises lack the resources to engage prominent consultants for data analysis, leaving them with untapped potential hidden within their data. "Simultaneously," he emphasized, "we aim to expose students to the realities of working with data, revealing that data sets often deviate from the pristine datasets we encounter in our academic studies."
The initial steps in orchestrating such a substantial project can be quite challenging. Rutger explained that after meetings with the outgoing committee, their top priority was swiftly securing partnerships with interested organizations. "That proved to be the most demanding part of the process," he acknowledged. Once these partnerships were established, devising suitable projects presented its own set of challenges. Several factors had to be considered, including the students' existing knowledge, the project's timeline, and more. However, extensive pre-project discussions with the partner organizations paved the way for success.
"Subsequently," Rutger continued, "we largely entrusted communication to the students themselves." Each student team was assigned a team leader responsible for liaising between the committee and the group, as well as between the group and the non-profit organizations. Additionally, each team received guidance from a professional consultant from My Company or Amsterdam Data Collective, with the group leader also overseeing this aspect. Rutger expressed immense satisfaction with the outcomes, a sentiment shared by all involved. The committee successfully executed five remarkable projects.
One of these projects centered around KWF. The students involved in this project focused their efforts on developing a marketing plan geared towards nurturing donor relationships, specifically with corporate donors. Their approach entailed a comprehensive analysis of corporate donors to pinpoint those most likely to recurrently contribute to KWF's cause. This strategic approach aimed to optimize KWF's outreach efforts, thus reducing costs associated with broad-scale donor engagement.
Aditeya, a current fourth-year double bachelor's degree student, was enthusiastic about his participation in the KWF project. His motivation sprang from a profound desire to gain hands-on experience with real-world data while making a meaningful contribution to a charitable organization. As Aditeya shared his experiences, he revealed a distinct shift in perspective during the project. “As econometric student it’s always ‘built a model, make some predictions’,” he explained, “but we realized what would be more important for the company would be to clean up their data a little bit and add some insights because in my opinion sometimes even that in itself is quite useful.”
One of the most valuable lessons Aditeya learned during the project was resilience. Working with such complex data can be quite challenging, he admitted. “After a bit you realize you just have to work with it.” When asked about his most memorable experience, Aditeya fondly recalled their survival analysis, which offered insights into the expected duration of engagement for specific customer segments. “It was very cool seeing the curves that came out.” As a double bachelor student, his participation in the project reaffirmed his passion for econometrics over economics, as it allowed him to witness the practical applications of his academic pursuits and their direct impact on real-world challenges.
Aditeya mentioned that KWF expressed satisfaction with the work they presented, which was corroborated in my conversation with Niels Huijgens. In addition to leading KWF's Data and Intelligence team, Niels also serves as the Product Owner of the Data Warehouse team, influencing their project prioritization and direction. His team is actively engaged with the evolving landscape of technology, particularly in the realm of AI. While they employ specific marketing software for their analyses, they are also venturing into predictive data utilization using R Studio, creating predictive models to harness the power of data.
"What intrigued us, particularly," Niels remarked when asked about involving students in the data team, "was the opportunity to view certain issues from a fresh perspective. We developed our expertise in a different era, as econometrics and data-focused programs weren't as prevalent when we began our careers." His motivation to engage with the project stemmed from the curiosity of how a younger generation approaches challenges and what KWF could learn from them. The academic background of the students was another point of interest for Niels. He noted that the students' approach to the task was deeply rooted in statistical underpinnings, a perspective that his team didn't necessarily prioritize. "This proved to be a highly instructive experience for me," he admitted. "I believe these are concepts we can genuinely apply." Niels mentioned that one of the analysts on his team, who has a strong statistical foundation, was particularly enthusiastic about exploring how KWF could resolve problems using statistical insights.
Viewing data through different lenses and interpreting it in novel ways yielded surprising insights. Niels also observed that the students, in addition to leveraging the provided data, had consulted external sources. While KWF's team typically focuses on their own resources, the students, in the process of working on the project, had explored ways to combine the obtained data with industry-wide data and broader trends from across the Netherlands.
Niels provided the students with the freedom to explore various avenues, as he believed there was no wrong approach. "I encouraged them to share their decision-making process with us as they worked on the assignment," he stated. The students took this to heart, and the recommendations they presented were meticulously structured, enabling KWF's team to readily integrate and act upon them.
Backed by robust statistical foundations, the team gained a unique perspective on specific customer segments. "We aim to apply these insights," Niels emphasized. "These findings are invaluable and will actively inform our future strategies." On the topic of collaborating with students in the future, Niels expressed enthusiasm, affirming that both organizations and students stand to benefit from such partnerships. Often, econometric graduates opt for roles with prominent consulting firms. However, smaller organizations and non-profits house substantial data that could lead to exciting projects. "While they may not seem as flashy," Niels admitted, "they can be equally enjoyable."
Possibly even more enjoyable. Therefore, make sure to keep an eye on FAECTOR's channels for future opportunities to engage with real-world data, emphasizing the invaluable practical experience you could gain. Are you interested in organizing this year’s FAECTOR Consultancy Project? Applications are open until September 15th. You’ll be providing students the opportunity to apply their econometric expertise in practical scenarios. Organizing a project with non-profit organizations and smaller businesses is a rewarding experience not to be missed.