Harvard Business School 9,894,011 November 22, 1993 Professo

Harvard Business School 9 894 011 November 22 1993professor George W

Harvard Business School November 22, 1993 Professor George Wu prepared this case as the basis for class discussion rather than to illustrate either effective or ineffective handling of an administrative situation. reproduce materials, call , write Harvard Business School Publishing, Boston, MA 02163, or go to No part of this publication may be reproduced, stored in a retrieval system, used in a spreadsheet, or transmitted in any form or by any means—electronic, mechanical, photocopying, recording, or otherwise—without the permission of Harvard Business School.

Paper For Above instruction

This paper analyzes the strategic considerations of Colonial Broadcasting Company (CBC) and its programming decisions related to TV movies, with a focus on factors influencing ratings, the relationship between fact-based or fictional content and audience response, and optimal scheduling strategies. It emphasizes the importance of rating determinants, regression analysis, and risk assessment in maximizing network success and advertising revenues.

In the context of the 1992 television landscape, CBC, along with ABN and BBS, significantly contributed to prime-time programming, including the production and broadcast of TV movies. These movies, created either from factual stories or fiction, aimed to attract large audiences during peak viewing hours. Ratings, measured by Nielsen ratings, served as a critical metric for success, directly linked to advertising revenue. Therefore, understanding what factors influence ratings is crucial for network decision-making.

One of the core issues in this case involves analyzing how content type—fact-based versus fictional—affects viewer ratings. Understanding this relationship requires statistical analysis, such as regression models, which can quantify the impact of different variables on ratings. For CBC, this insight is vital for making programming choices, especially when considering new concepts or scheduling strategies designed to boost ratings and revenue.

The case highlights that TV movies are primarily financed through licensing fees and production costs underwritten by networks. Ratings not only influence advertising prices but also determine the overall profitability of broadcasts. High-rated movies attract more advertisers willing to pay premium prices, making rating optimization a central goal for CBC’s programming team.

Regression analysis in 1992 revealed correlations between various factors and viewing ratings, such as network, month, day of the week, presence of a star, preceding program ratings, and competition levels. These models help predict viewer response and inform decisions about scheduling and content selection. For example, understanding whether fact-based movies tend to attract higher ratings than fictional ones can guide content acquisition strategies. The analysis also considers the role of star power, timing, and competition in shaping audience size.

Strategic decision-making also involves risk assessment, particularly in sponsorship deals like the offer from Harsanyi Electric, which promises a hefty payment contingent on achieving a specified rating. The decision to accept such deals hinges on predictive ratings and their statistical distribution, emphasizing the importance of accurate forecasting models. CBC must assess whether the potential revenue outweighs the risk of falling short of the target ratings.

Optimal scheduling is another critical aspect, where the timing of TV movies and their subsequent effects on ratings are examined. Factors such as the typical ratings of preceding programs, competing networks' scheduling tactics, and specific slots' demographics play a role in maximizing viewership. The decision on whether to move "Josette and Yvette" or to avoid scheduling other high-rating programs against CBC’s movie can directly influence the network's success.

Furthermore, the case explores the implications of programming choices on market share versus total audience size. Whether networks should focus on maximizing their share of viewers or total ratings impacts their advertising strategy and competitive positioning. Regression analyses support or challenge these strategic viewpoints by revealing the influence of scheduling and content factors on audience dynamics.

Warrington’s decisions regarding content (fact-based versus fictional), stars, timing, and sponsorship deals demonstrate the complex interplay between statistical analysis, strategic planning, and market forces. She must weigh the predicted ratings, potential risks, and revenue implications to arrive at optimal programming strategies that increase ratings and advertising revenue while managing competition and audience preferences.

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