Innovation with Old Math

May 27th, 2025
Westley Ritz | Vice President, Analytics
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Innovation must be shiny, fancy, and new. Ha, says who? Because I beg to differ.

Remember that scene from the movie Hidden Figures (Spoiler alert! But c’mon, it is an 8-year old movie) when Katherine Johnson (played by Taraji P. Henson) discovered the correct mathematical formula to bring the astronauts home from space? A team of the biggest brains in the US were struggling to solve the problem when she made her discovery and declared that it wasn’t new math but old math. That was innovation.

Now let’s apply similar logic to market research. A healthcare provider approached TRC wanting to do conjoint pricing research on 200+ medical procedures. And if you know conjoint, doing just 1 requires some effort if you’re doing it right. 200 was out of the question both due to time and budget. So OK, we needed a way to reduce the list from 200 to something more manageable, like 20. Skipping the details and cutting to the chase (this isn’t a 3-hr movie), we employed a shiny and new methodology called Multidimensional Scaling. Just kidding, its origins trace back to the 1930s! So indeed, culling through our repertoire of methodological knowledge, the best tool for the job was an old one. It pays to know your history.

And because I’m feeling generous, how about some bonus innovation? Think of this as the cutscene as the credits are rolling. Executing 20 conjoints in a study is no cinch either. But as I keep telling my mother, that choice modeling expertise pays off. Making use of some conditional assignments and advanced hierarchical Bayesian modeling while accounting for the type of procedure, we were able to field our study with the necessary sample without blowing the budget or taxing our respondents.

Start with a solid base of knowledge, add in some brainstorming, and you’ll innovate and problem-solve in no time!

Reference: Theodore Melfi, director. Hidden Figures [Film]. Fox 2000 Pictures, Chernin Entertainment, Levantine Films. 2016.

Westley Ritz | Vice President, Analytics

Wes Ritz leads the analytics practice at TRC Insights, where he has spent his entire 20-plus year career moving up from analyst to Vice President. He holds a B.S. in Statistics and Economics from the University of Michigan and an M.S. in Statistics from Temple University’s Fox School of Business, and he puts both degrees to work every day translating technical complexity into decisions clients can actually act on.

His methodological toolkit covers the full span of quantitative market research, with a clear soft spot for choice-based techniques like conjoint analysis and Max-Diff. He also works extensively in pricing research, segmentation (with emphasis on machine learning techniques), brand and equity research, and the occasional multivariate deep dive when a client’s question really deserves one. Across all of it, the pattern is the same: shape the research design up front, keep the methodology honest, and finish with a story an executive can use in a room.

Wes partners closely with clients from the RFP and kickoff stage through fieldwork, analysis, and delivery. Teams tend to bring him in when the question is hard or the stakes are high, because part of his job is knowing which technique actually fits the business problem and which one just sounds impressive on a proposal.

He writes and publishes regularly. His work has appeared in Quirk’s (including articles on machine learning for segmentation and the original two-dimensional Max-Diff approach co-developed with TRC President Rajan Sambandam) and on GreenBook, and he maintains a steady presence in TRC’s white paper library and blog archive.

Wes also leads TRC’s R&D agenda, with a current focus on applying AI responsibly to the insights process. That includes practical work on synthetic data, digital twins, and digital personas, along with ongoing collaboration with academic partners to pressure-test what these tools can and cannot do.

Outside of client work, he stays engaged with the broader marketing community through AMA Baltimore, where he serves as a mentor in the chapter’s Mentorship Program and was a panelist at the 2026 Collegiate Career Connections Workshop on marketing in the age of AI. He also regularly attends leading market research and analytics conferences—including Sawtooth Software events, Insights Association conferences, and other industry forums—to stay current on methodology and best practices.

He lives in Baltimore with his wife and dog, and you’ll often find him at Camden Yards for an Orioles game.

Education: M.S. in Statistics, Temple University. B.S. in Statistics and Economics, University of Michigan.

Contact Wes.

Wes’ LinkedIn profile.