The MRII Data Analysis Award, sponsored by Infotools Harmoni, recognizes individuals with exceptional skill in using data to deliver actionable insights for real-world business challenges. All applicants submitted a 10-page presentation featuring actionable insights based on their analysis of a global New Zealand tourism dataset, which was housed on the Harmoni platform. Catherine Novita Kusumaningrum from Indonesia, who earned second runner-up on the award, shares her background and her experience using Harmoni and the New Zealand dataset. She won a free Principles Express course from MRII and the University of Georgia.
MRII: Can you tell us about your background and what led you to a career in market research?
Catherine: Shortly after finishing my Bachelor’s degree, I found my way into the world of market research when I joined MHz Group in 2019, a boutique software and consulting firm based in Dubai, and spent the next six years working with clients on conjoint analysis (among other things), mainly in telecom and media industries. Looking back, it made perfect sense: I’ve always had this funny, selective sense that when I’m in conversations with my friends, I could accidentally zone out when someone said something that sparks my curiosity because my brain is itching to look for information. I also love experimenting with ideas, testing hypotheses, and figuring out how things work in the background. So when I found myself analyzing datasets, solving modelling problems, or connecting dots on customer data, that part of the work was where I could easily enter the state of flow.
At MHz, I led market research projects as Research Associate, working together with many product and strategy teams internationally in designing product and pricing studies, as well as simulating the optimal product-pricing mix based on the research. It showed me how powerful insights can be for organizations, as our clients’ decision-making on product launch and pricing adjustments heavily relied on the conjoint insights. That experience sparked a great motivation to deepen my analytical and strategic foundations to help organizations with data-driven decision-making, which led me to pursue my Master’s in Management Analytics at Mannheim Business School in Germany, which I just completed this year. I’m now on a sabbatical back to my home country in Indonesia to reflect all of the great learnings I’ve received throughout these years (which I’m super grateful for), and to continue honing my skills, building an analytics portfolio, tinker with personal projects, take a coffee course for fun, travel whenever I can, and explore what’s next for me professionally.
MRII: Where do you see yourself in the next 5-10 years?
Catherine: Looking ahead to the next 5-10 years, I hope to work in roles where I can make a positive impact: by leveraging insights and analytics to shape decisions, improve products, or guide organizational strategy. I would also welcome an opportunity to work with larger, cross-functional teams to collaborate closely and solve problems at the intersection of data, product, and strategy, whereas in my past jobs, I’ve worked in relatively small groups. In the future, I also hope to contribute through teaching and mentorship, because I genuinely believe that sharing knowledge is one of the most powerful ways to keep learning while at the same time empowering others. As the world of insights and analytics continues to evolve, I’m excited by the idea of eventually stepping into leadership or even building something of my own, anything that allows me to contribute meaningfully to the field and to the community around me.
MRII: Can you describe your experience using the Harmoni platform, any challenges you faced, and what the overall process taught you as a researcher?
Catherine: My first glance working with Harmoni was that it’s pretty intuitive – easy to use even for first-time users, and produces great visuals. Harmoni also provided video tutorials that really helped me navigate the functionalities further, and I noticed they have ChatHarmoni, which is pretty cool (though for some reason I ended up not using it too much, oops!). The only downside is that while it comes in handy for cross-tabs and descriptive analysis, I wish it had the functionality to do correlation analysis or simple regression, to further prove our hypotheses and relationship between different factors.
I loved how the survey datasets were so comprehensive and allowed me to explore many different things. I chose the challenge of increasing visitor spend, and coincidentally, just three weeks before the submission deadline, I was on a long-haul trip, so my approach was inspired by a traveller’s decision funnel; from inspiration, to planning, to booking, and finally to what influences spending once travellers arrive. I began with a simple hypothesis: people tend to spend more on their travels when they understand a destination’s value. With that in mind, I started my analysis by profiling historical high-spenders (e.g., demographics, origin markets, length of stay) and then segmented them behaviorally (e.g., why they visit New Zealand, how they plan their trip, which activities and regions they explore, and their overall spending patterns). From there, the patterns that emerged helped validate my solutions, highlighting where New Zealand can leverage strengths already present in the funnel, which friction points need to be addressed, and where bundling and upselling opportunities could sustainably increase value and drive visitor spend.
I’m incredibly grateful for the opportunity to take part in this competition. It was not only a chance to challenge myself creatively and analytically, but also a meaningful reminder of why I enjoy this field so much. Thank you to MRII team – the organizers, the judges, and the team behind Harmoni for creating a platform that encourages learning, curiosity, and fresh perspectives. I truly appreciated the experience, and I’m honored to have been placed among so many talented participants.
To learn more about the MRII award programs, visit our Awards page.
