Interruptions, Style Changes, and the Gap to a Team Target
Abstract
The question concerns target gap conditional on interruptions and style changes. The secondary ordinary least squares analysis contains 1,197 observations and uses cluster covariance. The coefficient on idle_time is -7.722e-04, with a 95 percent interval from -0.0010 to -5.120e-04. The gap preserves the difference between actual and targeted productivity. Interruptions and style changes are recorded contemporaneously, so their association does not identify the effect of eliminating them. Opportunity-cost retention could prioritize consequential unresolved cases, but requires a measured loss and review policy. Those workflow outcomes are absent from the projection. The estimates describe the released collection and its conditioning set. No new data collection, simulator experiment, or deployment-policy evaluation is claimed.
References
- S. Gao, W. Chen, and L. Shi, “A New Budget Allocation Framework for the Expected Opportunity Cost,” Operations Research, vol. 65, no. 3, pp. 787–803, 2017.
- S. Gao and W. Chen, “Efficient Subset Selection for the Expected Opportunity Cost,” Automatica, vol. 59, pp. 19–26, 2015.
- Productivity Prediction of Garment Employees. UCI Machine Learning Repository, 2020. Dataset. https://doi.org/10.24432/C51S6D.
- White, Halbert. “A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity.” Econometrica, vol. 48, no. 4, 1980, pp. 817–838. https://doi.org/10.2307/1912934.
- Cameron, A. Colin, and Douglas L. Miller. “A Practitioner’s Guide to Cluster-Robust Inference.” Journal of Human Resources, vol. 50, no. 2, 2015, pp. 317–372. https://doi.org/10.3368/jhr.50.2.317.
- Rasmussen, Carl Edward, and Christopher K. I. Williams. Gaussian Processes for Machine Learning. MIT Press, 2006. https://gaussianprocess.org/gpml/.
- Ankenman, Bruce, Barry L. Nelson, and Jeremy Staum. “Stochastic Kriging for Simulation Metamodeling.” Operations Research, vol. 58, no. 2, 2010, pp. 371–382. https://doi.org/10.1287/opre.1090.0754.
- Kim, Seong-Hee, and Barry L. Nelson. “A Fully Sequential Procedure for Indifference-Zone Selection in Simulation.” ACM Transactions on Modeling and Computer Simulation, vol. 11, no. 3, 2001, pp. 251–273. https://doi.org/10.1145/502109.502111.
- Frazier, Peter I., Warren B. Powell, and Savas Dayanik. “A Knowledge-Gradient Policy for Sequential Information Collection.” SIAM Journal on Control and Optimization, vol. 47, no. 5, 2008, pp. 2410–2439. https://doi.org/10.1137/070693424.
- Bertsimas, Dimitris, and Melvyn Sim. “The Price of Robustness.” Operations Research, vol. 52, no. 1, 2004, pp. 35–53. https://doi.org/10.1287/opre.1030.0065.