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Activity Number: 611 - Applications in Business and Markets
Type: Contributed
Date/Time: Thursday, August 1, 2019 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistical Learning and Data Science
Abstract #304983
Title: Using Simple Descriptive Statistics to Drive Critical Decision Making
Author(s): Peter John De Chavez*
Companies: PepsiCo
Keywords: benchmarks; product development; quantiles; food industry
Abstract:

Food and Beverage companies with large R&D organizations rely on external consumer tests to assess if new product prototypes can already move past product development or should still be reformulated. Because of the high cost required to run such tests, it is necessary to determine if consumer test results indicate that product development should already come to a conclusion or further product modifications are necessary. To address this goal, this research mined historical consumer test data on different product categories from the past five years to obtain statistics that can serve as benchmarks for key consumer metrics such as overall liking and the expectation index. The benchmarks were simple descriptive statistics that indicate the points where there would be minimal return on investment from doing further product development. Hence, product prototypes whose consumer test results meet or exceed said benchmarks are deemed ready to exit the product development phase. This paper presents the challenges of obtaining said benchmarks, and illustrates that even simple statistics can provide insights that R&D teams can confidently move forward with for critical decisions.


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