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Steven Condly Interview  -  October 1, 2008, 2:30 p.m. Conversations on HPT Webcast

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Guest:

[Dr. Steven Condly]

Dr. Steven Condly
HSA Learning & Performance Solutions


Steven J. Condly, Ph.D., is Senior Associate at HSA Learning & Performance Solutions LLC. He has worked with organizations such as Intel, DaimlerChrysler, Coffee Bean & Tea Leaf, the International Association of Fire Fighters, and the Building Owners and Managers Institute on such issues as employee performance, the design, development, and validation of test and survey instruments, computer science education, and employee motivation and incentive systems. Dr. Condly is the recipient of several grants and awards related to his work and research, including the ASTD’s 2004 Research Award for his meta-analysis article on incentives.

Hosts:

[ Elliott McClelland]

Elliott McClelland
Communication Specialist
School of Information Science and Learning Technologies



[Dr. John Wedman]

Dr. John Wedman
Director, School of Information Science & Learning Technologies
University of Missouri-Columbia








Summary:

Incentive systems are motivation-focused structures designed to maximize improvements in employee behavior and/or decision-making to the benefit of the organization. They are specifically associated with particular goals or outcomes and thus are distinguished from the more general compensation systems. Though governed by different circumstances and goals, all incentive systems include common elements: goals, stakeholders, incentives, time frames, implementation and data collection procedures, and support structures. To the degree management and targeted employees negotiate the details of the incentive system, rely upon fair and reliable procedures, and incorporate system goals within the larger goals of the organization, the system can be a success. As with any system, potential pitfalls abound, such as offering unacceptable incentives, not communicating the existence of the program, or changing rules or criteria midway through without consultation. However, evidence is abundant that properly designed systems have positive effects that are reliable, replicable, and measurable.

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