Principal Investigator: David Ebert
Evaluating employee performance in organizations with varying workloads and tasks is a challenging problem. An efficient evaluation system can be beneficial for an organization to understand shortcomings and improve overall productivity. However, it is important to understand how quantitative measurements of employee achievements relate to supervisor observations (match or mismatch), what the main drivers of good performance are, and how to combine these complex and flexible performance evaluation metrics into an accurate portrayal of organizational performance. To facilitate this process, MetricsVis is a unique visual analytics framework composed of multiple coordinated views to support the dynamic evaluation and comparison of individual, team, and organizational performance. MetricsVis provides three primary visual components to expedite performance evaluation: (1) a reorderable performance matrix to demonstrate the details of individual employees; (2) a group performance view that highlights aggregate performance and individual contributions for each group; (3) a projection view to illustrate employees with similar specialties to facilitate shift assignments and training.
Students: Jieqiong Zhao
Zhao, J., Karimzadeh, M., Snyder, L. S., Surakitbanharn, C., Qian, Z. C., & Ebert, D. S. (2019). MetricsVis: A Visual Analytics System for Evaluating Employee Performance in Public Safety Agencies. IEEE transactions on visualization and computer graphics.
Zhao, J., Malik, A., Xu, H., Wang, G., Zhang, J., Surakitbanharn, C., & Ebert, D. S. (2017, April). MetricsVis: A visual analytics framework for performance evaluation of law enforcement officers. In 2017 IEEE International Symposium on Technologies for Homeland Security (HST) (pp. 1-7). IEEE.