RSG Media Wins MIT, NYU and Carnegie Mellon to Take Home the 2022 INFORMS RM&P Section Practice Award

RSG Media has been named the winner of the INFORMS RM&P Practice Award 2022 for their advancement in the science of price and revenue management for using machine learning and predictive modeling to plan television advertising more profitably.

NEW YORKJuly 5, 2022 /PRNewswire-PRWeb/ — The Institute for Operations Research and the Management Sciences (INFORMS) has announced that RSG Media is the winner of the prestigious 2022 INFORMS Revenue Management & Pricing (RMP) Section Practice Award. RSG Media won for his work in applying machine learning, artificial intelligence and predictive modeling to the art of television advertising planning. Their competitors included Massachusetts Institute of TechnologyMITNew York UniversityNYU), and Carnegie Mellon University

Led by academics and operational research experts, the RSG Audience team demonstrated how their proprietary Log Optimizer micro-places ad units to deliver on campaign guarantees, while respecting all deal restrictions and avoiding under- and over-delivery.

The submission included a formal document titled “9 Years of Substantial Sales Growth by Optimally and Seamlessly Scheduling Advertising on Cable TV”. The paper highlights that the system works by taking advantage of the variation in audience composition for each time slot and that the revenue from each ad unit is based on the guaranteed delivery against a unit. The Log Optimizer uses predictive analytics to predict Nielsen audiences and then create the optimal schedule to maximize the guaranteed audience for each unit, generating more revenue per unit and per day.

The submission team included RSG Alums Professor Sridhar Seshadriz from Gies College of Business, Dr. Sebastian Souyris of the University of Illinois Urbana-Champaigndr. Sriram Subramanian from Pinterest and Vinod KumawatVarun Verma and Shiv Sehgal of RSG Media.

Facing increasingly complex challenges in today’s rapidly changing TV viewing landscape, media companies need new tools to compete in the future of television. RSG’s ad sales optimization engine achieves annual increases of 6-11% across more than 30 networks , which provides a strategic advantage for Broadcast & Cable Networks to free up inventory and generate more revenue every day,” said Shiv Sehgal, Executive Vice President Audience Analytics at RSG.

The RMP Section Practice Award, presented by INFORMS since 2004, recognizes outstanding applications of revenue management and pricing techniques. Four finalists were selected on May 18 by an RMP Practice Award Committee of four esteemed judges from the Johns Hopkins Carey School of Business and the University of Chicago’s Booth School of Business. Finalists presented their work at the INFORMS RMP Conference on June 20

Supporting Resources

RSG AdVant
AdVant by RSG Audience is our end-to-end SaaS application built specifically for broadcast and cable companies. It revolutionizes the ad deal lifecycle, supporting pricing, scheduling and inventory, and ad operations teams all within one platform.

About RSG
RSG Media believes in using both art and science to deliver radical insights and deeper connections to drive the evolution of the media ecosystem. RSG Media drives customer revenue and profits through rights, audiences and advertising across platforms using in-depth analytics, artificial intelligence, business systems and expert advisory services. Its customers include cable and broadcast networks, MVPDs, studios, OTT, brand licensors and sports leagues

  • RSG Rights: Corporate rights management, strategically aligned to how each business group needs it.

  • RSG Audience: Cloud-based AI decision-making platform for media companies to decide data for radical insights into their content, advertising and marketing inventories.

RSG Media was founded in 1985 and is located in New York City with offices in Los AngelesLondonand Delhi/gurgaon. For more information visit

Media contact

Shiv Sehgal, RSG Media, 646-839-4297, [email protected]


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