Optimal Deployment of Parallel Teams in New Product Development

Speed in product development is the thin line that determines success or failure in many fast growing industries today. Strategies like set-based concurrent engineering and parallel team deployment have been used to accelerate new product introduction by successful companies like Toyota. In this paper, these two strategies are combined to investigate the impact of generating sets of alternatives using parallel teams on the revenue generated from new product development. The trade-off between cost and speed of development due to deployment of parallel teams in product development using the multi-armed bandit (MAB) framework are also explored. Quantitative models to determine the optimum number of product development teams at different stages of development have been constructed using the Gittins Index strategy. These models are tested using hypothetical data and the results show that the higher flexibility induced quality results in higher rewards, despite the higher cost of deploying multiple teams.

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