Optimization of innovative products and services using quantitative design-by-experimentation models: the context of techno-driver startups

The business management literature defines an innovative startup as a “human institution, which delivers a new product-service in conditions of extreme uncertainty”. For its part, the design engineering literature proposes methods to experiment the prototype of a new product-service before its launch on the market, but without systematically analyzing its business implications. Thus, few research works seem to combine both business and design aspects of a new product-service development. This research aims at adopting both visions, by developing a tool made of quantitative decision-making indicators. These indicators help startups to evaluate their potential of value creation (adequacy of their solution to the targeted market segments) and to identify the best cost-effective investment strategies in terms of product-service experimentation. Alexandre Bekhradi has developed this tool and its indicators, following a diagnosis of 60 startups in Paris. The applied mathematics skills of the Optimization Laboratory of McGill University offer an ideal opportunity for the validation and completion of this research. The outcome of this collaboration will be disseminated in referred journals and conference publications, and used by innovative startups.

Faculty Supervisor:

Michael Kokkolaras

Student:

Partner:

Université Paris-Saclay

Discipline:

Engineering

Sector:

Education

University:

McGill University

Program: