NBC-Universal Uses a Novel Qualitative Forecasting Technique to Predict Advertising Demand

  • Authors:
  • Srinivas Bollapragada;Salil Gupta;Brett Hurwitz;Paul Miles;Rajesh Tyagi

  • Affiliations:
  • GE Global Research Center, Niskayuna, New York 12309;GE Global Research Center, Niskayuna, New York 12309;ESPN Media Networks, New York, New York 10023;GE Global Research Center, Niskayuna, New York 12309;GE Global Research Center, Niskayuna, New York 12309

  • Venue:
  • Interfaces
  • Year:
  • 2008

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Abstract

NBC-Universal (NBCU), a subsidiary of the General Electric Company (GE), implemented a novel demand prediction and analysis system to support its annual upfront market. The upfront market is a brief period in late May when the television networks sell a majority of their on-air advertising inventory. The system uses an innovative combination of the Delphi method and the Grass Roots forecasting methodology to estimate demand for television commercial time. We embedded this forecasting methodology within a workflow system that automates the demand estimates gathering process and seamlessly integrates into NBCU's existing sales systems. Since 2004, over 200 sales and finance personnel at NBCU have been using the system to support sales decisions during the upfront market when NBCU signs advertising deals worth over $4.5 billion. The system enables NBCU to sell and analyze pricing scenarios across all of NBCU's television properties with ease and sophistication, while predicting demand with a high accuracy. NBCU's sales leaders credit the system with having given them a unique competitive advantage.