HR Metrics and Strategy

[Excerpt] The idea that an organization\u27s people represent a key strategic resource is widely accepted. The business press is filled with examples of top executives proclaiming how important it is to engage people\u27s minds and spirits in the quest for competitive advantage (Boudreau & Ramstad, 1997; Boudreau, 1996). There is also mounting scientific evidence that certain bundles of high-performance work practices (e.g., performance-contingent pay, team-based work structures, selective recruitment and hiring, extensive training, etc.) are associated with higher organizational financial performance (Becker & Huselid, forthcoming; Ichniowski, Arthur, MacDuffie, Welbourne & Andrews)

Global Human Resource Metrics

[Excerpt] What is the logic underlying global human resources (HR) measurement in your organization? In your organization, do you measure the contribution of global HR programs to organizational performance? Do you know what is the most competitive employee mix, e.g., proportion of expatriates vs. local employees, for your business units? (How) do you measure the cost and value of the different types of international work performed by your employees? In the globalized economy, organizations increasingly derive value from human resources, or “talent” as we shall also use the term here (Boudreau, Ramstad & Dowling, in press). The strategic importance of the workforce makes decisions about talent critical to organizational success. Informed decisions about talent require a strategic approach to measurement. However, measures alone are not sufficient, for measures without logic can create information overload, and decision quality rests in substantial part on the quality of measurements. An important element of enhanced global competitiveness is a measurement model for talent that articulates the connections between people and success, as well as the context and boundary conditions that affect those connections. This chapter will propose a framework within which existing and potential global HR measures can be organized and understood. The framework reflects the premise that measures exist to support and enhance decisions, and that strategic decisions require a logical connection between decisions about resources, such as talent, and the key organizational outcomes affected by those decisions. Such a framework may provide a useful mental model for both designers and users of HR measures

An Axiomatic Analysis of Diversity Evaluation Metrics: Introducing the Rank-Biased Utility Metric

Many evaluation metrics have been defined to evaluate the effectiveness ad-hoc retrieval and search result diversification systems. However, it is often unclear which evaluation metric should be used to analyze the performance of retrieval systems given a specific task. Axiomatic analysis is an informative mechanism to understand the fundamentals of metrics and their suitability for particular scenarios. In this paper, we define a constraint-based axiomatic framework to study the suitability of existing metrics in search result diversification scenarios. The analysis informed the definition of Rank-Biased Utility (RBU) -- an adaptation of the well-known Rank-Biased Precision metric -- that takes into account redundancy and the user effort associated to the inspection of documents in the ranking. Our experiments over standard diversity evaluation campaigns show that the proposed metric captures quality criteria reflected by different metrics, being suitable in the absence of knowledge about particular features of the scenario under study.Comment: Original version: 10 pages. Preprint of full paper to appear at SIGIR'18: The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, July 8-12, 2018, Ann Arbor, MI, USA. ACM, New York, NY, US

On the Measurement of Privacy as an Attacker's Estimation Error

A wide variety of privacy metrics have been proposed in the literature to evaluate the level of protection offered by privacy enhancing-technologies. Most of these metrics are specific to concrete systems and adversarial models, and are difficult to generalize or translate to other contexts. Furthermore, a better understanding of the relationships between the different privacy metrics is needed to enable more grounded and systematic approach to measuring privacy, as well as to assist systems designers in selecting the most appropriate metric for a given application. In this work we propose a theoretical framework for privacy-preserving systems, endowed with a general definition of privacy in terms of the estimation error incurred by an attacker who aims to disclose the private information that the system is designed to conceal. We show that our framework permits interpreting and comparing a number of well-known metrics under a common perspective. The arguments behind these interpretations are based on fundamental results related to the theories of information, probability and Bayes decision.Comment: This paper has 18 pages and 17 figure

Strategic Human Resource Management Measures: Key Linkages and the PeopleVantage Model

The field of human resource management faces a significant dilemma. While emerging evidence, theory and practical demands are increasing the visibility and credibility of human capital as a key to organizational success, the measures used to articulate the impact of human resource management decisions remain misunderstood, unwanted by key constituents, or even counter-productive. This article proposes that the key to creating meaningful HR metrics is to embed them within a model that shows the links between HR investments and organizational success. The PeopleVantage model is proposed as a framework, the application of the model is illustrated, and the potential of the model for guiding research and practical advances in effective HR measures is discussed