A case example of assessment and evaluation: Building capability in a corporate university
ABSTRACT One corporate university makes measurement a priority by dedicating resources and assigning responsibilities to a centralized analytics function: the assessment, measurement, and evaluation team. As more measurement became a focus for learning and business leaders alike, the more the team became motivated to take a critical look at how it was approaching assessment, measurement, and evaluation activities and how it could leverage its capabilities, technology, and processes to have a greater reach across the organization.
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ABSTRACT: In this paper, a framework to support an object-oriented approach to performance analysis is described. The framework includes the use of collaboration, automation, visual modeling, and reusable repositories of analysis knowledge. The need for a new framework is related to the increasing concern with the cost effectiveness of student and employee development. Efforts to improve the return-on-investment in such development have been hindered by a craft orientation to the design and construction of learning and performance support materials. One solution to this problem has been to enhance the reuse of such materials.Rather than build every new system from scratch in a craft-oriented manner, it is envisioned that systems will be constructed largely of standardized, reusable objects shared through Web-based repositories. Currently, the main focus is on the technological framework necessary for an object-based approach to learning system development. There appears to be little consideration of the changes in analysis and design thinking required for the move towards object-based systems. Such systems should still be required to be directly linked to performance problems and opportunities at both the organizational and individual system levels.Performance Improvement Quarterly 08/2002; 15(3):81 - 93. DOI:10.1111/j.1937-8327.2002.tb00257.x
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ABSTRACT: Frustrated by the inadequacies of traditional performance measurement systems, some managers have abandoned financial measures like return on equity and earnings per share. "Make operational improvements and the numbers will follow," the argument goes. But managers do not want to choose between financial and operational measures. Executives want a balanced presentation of measures that allow them to view the company from several perspectives simultaneously. During a year-long research project with 12 companies at the leading edge of performance measurement, the authors developed a "balanced scorecard," a new performance measurement system that gives top managers a fast but comprehensive view of the business. The balanced scorecard includes financial measures that tell the results of actions already taken. And it complements those financial measures with three sets of operational measures having to do with customer satisfaction, internal processes, and the organization's ability to learn and improve--the activities that drive future financial performance. Managers can create a balanced scorecard by translating their company's strategy and mission statements into specific goals and measures. To create the part of the scorecard that focuses on the customer perspective, for example, executives at Electronic Circuits Inc. established general goals for customer performance: get standard products to market sooner, improve customers' time-to-market, become customers' supplier of choice through partnerships, and develop innovative products tailored to customer needs. Managers translated these elements of strategy into four specific goals and identified a measure for each.Harvard business review 70(1):71-9. · 1.27 Impact Factor
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ABSTRACT: Human performance (HP) practitioners rely on stakeholders to use quantitative data to make a multitude of performance improvement decisions. By improving stakeholders' capacity to process quantitative data, the quality of decisions made by those stakeholders can also be improved. This article describes a process for successfully communicating quantitative data to groups who make data-driven decisions. It also provides practical suggestions for improving three factors critical to the process: information integrity, information layering, and information processing.Performance Improvement 11/2008; 47(10):19 - 24. DOI:10.1002/pfi.20035