E xtending research on organizational learning to multiproduct environments is of particular importance given that the vast majority of products are manufactured in such environments. We investigate learning in a multiproduct facility drawing on exceptionally rich data for a manufacturing firm that is a leading producer of high-technology hardware components. Weekly data for 10 years from the firm's production and human resource tracking systems are augmented by surveys of managers and engineers and by extensive firsthand observation. We find that productivity improves when multiple generations of the firm's primary product family are produced concurrently, reflecting the firm's ability to augment and transfer knowledge from older to newer product generations. No significant transfer of knowledge is evident between the primary product family and other products. Productivity is, however, adversely affected when the production facility is faced with extensive within-product buyer-specific customizations. We develop the implications of these findings for theory and practice.
During code review, developers critically examine each others' code to improve its quality, share knowledge, and ensure conformance to coding standards. In the process, developers may have negative interpersonal interactions with their peers, which can lead to frustration and stress; these negative interactions may ultimately result in developers abandoning projects. In this mixed-methods study at one company, we surveyed 1,317 developers to characterize the negative experiences and cross-referenced the results with objective data from code review logs to predict these experiences. Our results suggest that such negative experiences, which we call "pushback", are relatively rare in practice, but have negative repercussions when they occur. Our metrics can predict feelings of pushback with high recall but low precision, making them potentially appropriate for highlighting interactions that may benet from a self-intervention.
Insights-Cross-tool log data offers an opportunity for organizations to understand the behaviors of software engineers. -Google gained insights from building a logs-ingesting system called InSession, whose design is described in this paper. -We use InSession to show that an engineer certification process reduces the time engineers spend reviewing code.
Extending research on organizational learning to multi-product environments is of particular importance given that the vast majority of products are manufactured in such environments. We investigate learning in a multi-product facility drawing on exceptionally rich data for a manufacturing firm that is a leading producer of high technology components. Weekly data for 10 years from the firm's production and human resource tracking systems are augmented by surveys of managers and engineers and by extensive first-hand observation. We find that productivity improves when multiple generations of the firm's primary product family are produced concurrently, reflecting the firm's ability to augment and transfer knowledge from older to newer product generations. No significant transfer of knowledge is evident between the primary product family and other products. Productivity is, however, decreased when the production facility is faced with extensive within-product buyer-specific customizations.We develop the implications of these findings for theory and practice.
Interpersonal conflict in code review, such as toxic language or an unnecessary pushback, is associated with negative outcomes such as stress and turnover. Automatic detection is one approach to prevent and mitigate interpersonal conflict. Two recent automatic detection approaches were developed in different settings: a toxicity detector using text analytics for open source issue discussions and a pushback detector using logs-based metrics for corporate code reviews. This paper tests how the toxicity detector and the pushback detector can be generalized beyond their respective contexts and discussion types, and how the combination of the two can help improve interpersonal conflict detection. The results reveal connections between the two concepts.
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