Applying Science to Art: Dynamic Analytics Impact on the Media Industry

New simulation models for film and television companies will profoundly improve decision making and reduce risk.
This post was published on the now-closed HuffPost Contributor platform. Contributors control their own work and posted freely to our site. If you need to flag this entry as abusive, send us an email.

New simulation models for film and television companies will profoundly improve decision making and reduce risk. The entertainment and media ("E&M") industry is currently in a period of significant change brought on by evolving digital distribution technologies and the widening array of products and services that affect them. We explore the range of analytical techniques available today and focuses on simulation modeling as an effective tool to address macro strategic decisions in the rapidly changing industry.

With such a wide array of factors to navigate, including consumer delivery choices, new product and service offerings and ever-changing consumer behavior, the E&M industry needs to adopt new analytical techniques, such as simulation models, to deal with the increasing level of business complexity. Leveraging simulation modeling in the entertainment sector will be a critical differentiator to adapt to change and capture the complexity of a fast-paced industry to better inform decision making and reduce risk.

We produced the Feature Film Lifecycle Simulation and Television Content Value Simulation case studies to highlight the remarkable opportunities enabled by such dynamic analytics:

Film: This modeling approach provides a framework for analyzing how films generate revenue throughout their entire lifespan, including the full spectrum of release windows.

  • Optimizing revenue across release windows. The model estimates the revenues generated by each type of media platform depending on the release strategy deployed, including in-theater, Premium VOD release, DVD sales and other digital entertainment channels.
  • Planning media campaigns. The model can be extended to include the impact of targeted media campaigns on viewership to determine how to create the right impressions in front of the most important audiences.
  • Adjusting release strategies. The model uses sentiment analysis techniques to mine the social media space for the volume and direction of word-of-mouth messages, allowing studios to modify sleeper hits faster or act as an indicator for a film's future profitability.

Television: This modeling approach provides a framework for understanding how consumers select shows and share opinions within the market.

  • Estimates the total value created by existing programs by analyzing each show's impact on channel brand and viewership. The ability of a show to attract and retain an audience is measured as a basis for calculating its contribution to the streams of revenue generated by each program.
  • Tests policies to improve the value generated by current shows in the context of the entire ecosystem. The policies model can determine the marketing cost required to alert key consumer segments of an appealing new block of shows and forecast the impact of marketing initiatives.
  • Forecasts the potential value new programs could contribute to the enterprise by estimating their appeal to audiences watching the previous show, potential viewers and local viewers. Within this model, the contribution each program makes to the brand equity and total viewership can be calculated, including expected value of new shows and related content.

To learn more about dynamic analytics and to download a full copy of the report, and to review our other market research and findings, please go to pwc.com/us/em.

Popular in the Community

Close

What's Hot