My professional career has centered on consumer behavior, analytics, research and measurement. I have worked with some of the largest brands in the world, helping organizations understand what people believe, how they behave, why they make the decisions they make and how those behaviors ultimately affect outcomes.
Opinions are easy to find. Reliable comparisons are harder. RMBI was created to ask whether measurable outcomes can add something useful to conversations about religion.
My work has rarely been about simply collecting data. The real challenge is deciding what should be measured, how it should be measured, which evidence deserves the most confidence and what conclusions the evidence can actually support.
That work has included consumer research, marketing analytics, audience measurement, segmentation, statistical modeling, media effectiveness, behavioral science and large-scale business strategy.
I have worked with organizations and brands whose products and services are found in millions of homes, and the research and analytical work I have led or influenced has touched trillions of dollars in revenue.
RMBI requires many of the same disciplines I have used throughout my professional career: research design, measurement, data integration, behavioral interpretation, methodological discipline and communicating complex findings clearly.
My career has focused on understanding how people think, choose, spend, respond and behave. That has meant working with large datasets, survey research, consumer segmentation, behavioral patterns and competing explanations for why people make the decisions they make.
I have built and led analytics, research and strategy teams ranging from small specialist groups to organizations of more than 250 people. The goal was always the same: turn complex information into useful decisions.
At AT&T, I was responsible for analytics supporting approximately $2 billion in advertising investment. The work connected consumer behavior, marketing investment and actual business outcomes. That requires more than reporting what happened. It requires understanding why it happened.
I have been responsible for developing new research methodologies, analytical frameworks and measurement approaches. Some of that innovation ultimately went beyond the organizations where it was developed and was productized by major research and measurement companies, including Nielsen.
My career has involved consumer research, large-scale surveys, segmentation, behavioral data, statistical relationships, measurement systems and competing explanations for why people behave the way they do.
Data rarely arrives with an answer attached. The work is defining the right question, identifying the strongest evidence, recognizing limitations, testing alternative explanations and communicating the conclusion in a way people can understand.
Two people can look at the same information and reach very different conclusions depending on how the question is defined, how evidence is selected, how measurements are constructed and how results are interpreted.
Religion is often evaluated through theology, history, personal experiences or institutional controversies. Those questions matter. But there is another question that receives far less attention: What happens in people's lives?
Do people who actively practice a faith experience measurable differences in volunteer service, life and youth outcomes, family stability, access to member resources, charitable giving, institutional reach or religious engagement?
Those are research and measurement questions. They are precisely the type of behavioral and measurement questions I have spent my career studying.
I am a practicing member of The Church of Jesus Christ of Latter-day Saints. I do not pretend that I approach questions about religion without personal beliefs.
My professional experience explains why I am comfortable working with complex research, measurement and behavioral data. It does not make the conclusions automatically correct.
The methodology, underlying sources and evidence should determine whether those conclusions deserve your confidence.
My job isn't to tell the data what to say.
My job is to listen carefully enough
to understand what it is saying.