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Machine Learning and Product Design – Summer of Research

Catherine Loughlin, Associate Dean, Research and Knowledge Mobilization

Do you remember when the first iPhone hit the market? It was a breathtaking departure, at the time, in both design and concept. No keyboard, when plenty of phone companies were still trying to figure out how to get a full keyboard onto their product? And just one button? The technology press went wild.

Cell Phone Evolution to demonstrate product design concepts

It was recognizable as a phone, and yet dazzlingly different. This equation of recognizability versus unique and different is one that product designers have come to recognize as essential. This has led to companies spending a lot of money on focus groups and user feedback mechanisms over the years.

Marketing professor Dr. Ethan Pancer studies how visual information is processed. He has conducted research to determine if an automated process, using machine learning, could stand in for part of the product design development process. Can a new product be appropriately categorized on sight? How does that affect the potential funding accessible to the product designer?

Using a simple, easily available tool like Google Cloud Vision, Dr. Pancer demonstrates how an algorithm can help designers determine the right ratio of familiar to unfamiliar in order to maximize their profit potential.

Dr. Pancer’s use of machine learning to help quantify potential future sales and investment points to the continued importance of evidence-based decision making in business. All business decisions have inherent risk – but solid numbers can help businesses determine how much risk is involved.  Many managers may still struggle to determine the right way to find the evidence they need. Research like Dr. Pancer’s can help point the way.

-Catherine Loughlin, Associate Dean, Research and Knowledge Mobilization
(contact info – sobeyschool@smu.ca, 902-420-5422?)