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MetricsVis: A Visual Analytics System for Evaluating Employee Performance in Public Safety Agencies

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TLDR
MetricsVis as discussed by the authors is a visual analytics system composed of multiple coordinated views to support the dynamic evaluation and comparison of individual, team, and organizational performance in public safety organizations, and provides four primary visual components to expedite performance evaluation: a priority adjustment view to support direct manipulation on evaluation metrics; a reorderable performance matrix to demonstrate the details of individual employees; a group performance view that highlights aggregate performance and individual contributions for each group; and a projection view illustrating employees with similar specialties to facilitate shift assignments and training.
Abstract
Evaluating employee performance in organizations with varying workloads and tasks is challenging. Specifically, it is important to understand how quantitative measurements of employee achievements relate to supervisor expectations, 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 in order to identify shortcomings and improve overall productivity. To facilitate this process, we summarize common organizational performance analyses into four visual exploration task categories. Additionally, we develop MetricsVis, a visual analytics system composed of multiple coordinated views to support the dynamic evaluation and comparison of individual, team, and organizational performance in public safety organizations. MetricsVis provides four primary visual components to expedite performance evaluation: (1) a priority adjustment view to support direct manipulation on evaluation metrics; (2) a reorderable performance matrix to demonstrate the details of individual employees; (3) a group performance view that highlights aggregate performance and individual contributions for each group; and (4) a projection view illustrating employees with similar specialties to facilitate shift assignments and training. We demonstrate the usability of our framework with two case studies from medium-sized law enforcement agencies and highlight its broader applicability to other domains.

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Citations
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A Visual Analytics Interface for Formulating Evaluation Metrics of Multi-Dimensional Time-Series Data

TL;DR: In this paper, a visual analytics interface for formulating evaluation metrics of multi-dimensional time-series data is proposed, which represents metrics as a linear combination of data attributes and provides a means for adjusting it through interactive VA.
Proceedings ArticleDOI

DARC: A Visual Analytics System for Multivariate Applicant Data Aggregation, Reasoning and Comparison

TL;DR: In this article , a visual analytics system for facilitating decision making on multivariate applicant data is proposed, where users are supported to gain insights of the multivariate data, picture an overview of all data cases, and retrieve original data in a quick and intuitive manner.
References
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Journal Article

Visualizing Data using t-SNE

TL;DR: A new technique called t-SNE that visualizes high-dimensional data by giving each datapoint a location in a two or three-dimensional map, a variation of Stochastic Neighbor Embedding that is much easier to optimize, and produces significantly better visualizations by reducing the tendency to crowd points together in the center of the map.
Journal ArticleDOI

The Impact of Human Resource Management on Organizational Performance: Progress and Prospects

TL;DR: In this paper, the authors describe why human resource management (HRM) decisions are likely to have an important and unique influence on organizational performance, and their hope is that this research forum will help advance...
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The Impact of Human Resource Management Practices on Perceptions of Organizational Performance

TL;DR: In this article, the authors found positive associations between human resource management practices, such as training and staffing selectivity, and perceptual firm performance measures, and suggested methodological issues for consideration in examinations of the relationship between HRM systems and firm performance.
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