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Recent learning‐by‐doing research highlights the importance of examining multiple measures of experience and their relationship to the performance of work teams. Our paper studies the role of individual experience, organizational experience, team leader experience, and experience working together on a team (team familiarity) in the context of improvement teams. To do so, we analyze successful and failed six sigma improvement team projects at a Fortune 500 consumer products manufacturer with multiple business groups. Such improvement project teams focus on deliberate learning, which differs from the primary focus of work teams.Our analysis uses archival data generated by these improvement project teams over a six year time span. Of the four experience variables we study, we find that team leader experience exhibits the strongest relationship with project success, followed by organizational experience. Further, in contrast to prior‐related research on work teams, we find no relationship between individual experience or team familiarity and project success beyond that explained by team leader and organizational experience. These results suggest that a well‐developed and deployed structured problem‐solving process—characteristic of effective six sigma deployments—may reduce the importance of team familiarity in the context of improvement teams.

An ongoing, important question in the operations strategy literature pertains to tradeoffs: Can manufacturers focus on multiple priorities simultaneously or achieve strength on multiple capabilities without sacrificing performance of another? In this paper, we accumulate, integrate, and examine the wide spectrum of conclusions reached in the literature concerning tradeoffs using modified meta‐analysis methods. Based on two decades of empirical research in operations strategy, we find that the evidence in the literature indicates manufacturers, on average, do not report experiencing tradeoffs among the competitive dimensions of quality, delivery, flexibility, and cost as suggested by the classical tradeoffs model. Our meta‐analysis also reveals that the way variables are operationalized, whether initiatives are implemented, and the unit of analysis are all related to the degree and nature of the evidence a paper contains with respect to the tradeoffs issue. We interpret our meta‐analysis results in the context of the prevailing model of manufacturing strategy and the theory of performance frontiers. We also discuss how the research designs used in this literature, which are predominantly cross‐sectional, affect the nature of the evidence generated and the conclusions that can be drawn. We go on to suggest research designs that more directly assess the tradeoffs issue.