Jule Kegel on her secondment experience at Public First

Finding common ground: Scientific standards across sectors

My name is Jule Kegel, and I am currently an IP-PAD doctoral candidate at the University of Vienna. Over the past three months, I was the second doctoral candidate from our network to complete a secondment at Public First, a company in London that combines opinion research, economic modelling, and policy consulting. Until now, my working experience had been almost entirely in academia. As a political scientist, I know that it can be sometimes hard to figure out what exact possibilities there are with this degree outside of academia, and I was excited to get a glimpse into this.

I indeed learned a lot about the differences and similarities between the sectors. For example, both sectors rely on good questionnaire design to get high-quality data. However, they approach it very differently, and I will use it as an example to explain what I learned.

I came to appreciate that academia places a strong emphasis on replicability, rigour and robustness. When designing surveys, it is common practice to use items that have already been tested and validated extensively and to only adapt them when necessary. When entirely new questions are required, they usually go through several rounds of piloting and validation. This helps ensure that questions measure what they are intended to and are easy for respondents to understand. At the same time, this careful approach can limit creativity and slow down the process of collecting data.

In contrast, the private sector often develops new questions tailored to each project, with less reliance on established items. This is mostly on purpose, as many clients are interested in unique and original data points. I had the chance to try this myself and quickly learned that the process is more complex than it may appear. Even without long rounds of validation, we still worked to ensure that questions were balanced, non-leading and accurately reflected the issues under study, as well as the clients’ wishes. This sometimes posed a further challenge: incorporating client feedback while carefully avoiding suggestions that might reduce the scientific soundness of the survey. The fact that questions are developed more quickly does not mean they lack quality or produce biased results, but rather that they are designed to meet different requirements.

Having now worked in both settings, I can say with confidence that each is committed to high standards, in different ways. It would not be accurate to describe one as producing better or worse data. Instead, both generate insights that are valuable for their respective contexts. In times where data and evidence are increasingly questioned by anti-democratic actors, I find this reassuring and believe we should be firm in pushing back against such sentiments, no matter which sector collected the data.

For doctoral candidates considering their next steps after the PhD, this comparison may also be helpful. Both academia and industry use scientific methods in their own way, and both offer opportunities to make a meaningful impact. The choice is less about quality and more about values: whether you prefer perfection and rigour or the faster pace of projects that move quickly from idea to completion. As for my own preference, I think I have started to find an answer. Perhaps that is the clearest sign that the secondment has fulfilled its goals.