SPOT: Scheduling Programs Optimally for Television

Srinivas K. Reddy, Jay E. Aronson and Antonie Stam
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Srinivas K. Reddy: Terry College of Business, Brooks Hall, University of Georgia, Athens, Georgia 30602
Jay E. Aronson: Terry College of Business, Brooks Hall, University of Georgia, Athens, Georgia 30602
Antonie Stam: Terry College of Business, Brooks Hall, University of Georgia, Athens, Georgia 30602

Management Science, 1998, vol. 44, issue 1, 83-102

Abstract: This paper introduces SPOT (Scheduling Programs Optimally for Television), an analytical model for optimal prime-time TV program scheduling. Due in part to the advent of new cable TV channels, the competition for viewer ratings has intensified substantially in recent years, and the revenues of the major networks have not kept pace with the costs of the programs. As profit margins decrease, the networks seek to improve their viewer ratings with innovative scheduling strategies. Our SPOT models for scheduling network programs combine predicted ratings for different combinations of prime-time schedules with a novel, mixed-integer, generalized network-based flow, mathematical programming model, which when solved provides an optimal schedule. In addition to historical performance, subjective inputs from actual network managers were used as input to the network flow optimization model. The optimization model is flexible. It can utilize the managers' input and maximize profit (instead of ratings) by considering not only the revenue potential but also the costs of the shows. Moreover, SPOT can describe the scheduling problem over any time period (e.g., day, week, month, season), and designate certain shows to, and restrict them from, given time slots. The methodology of SPOT is illustrated using data for the first quarter of 1990, obtained from a cable network. The optimization model produces solutions that would have generated an increase of approximately 2% in overall profitability, representing over $6 million annually for the cable network. SPOT not only produces more profitable TV schedules for this network, but also provides valuable general insights into the development of mixed programming strategies for improving future schedules.

Keywords: Television Network Scheduling; Generalized Networks; Integer Programming; Judgmental Models (search for similar items in EconPapers)
Date: 1998
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Citations: View citations in EconPapers (20)

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