The present and future of post production business and technology | Philip Hodgetts

Oct/12

17

Using Analytics to Predict Hollywood Blockbusters

http://blogs.hbr.org/cs/2012/10/using_analytics_to_predict_hollywood_blockbusters.html

Traditionally movies got greenlit on the “gut feeling” of some executive. After failures like John Carter from Mars perhaps it’s time to consider some modern, data-intensive methods instead. (I love big data and what it can tell us.)

The increasing availability of data coupled with the abundance of sophisticated technologies, tools, and applications give filmmakers an opportunity to improve decision making for better forecast revenue before a movie is released. Producers can have a mechanism in place to effectively predict profitability to secure investment capital. Investors can understand the economic consequences and break-even thresholds of films. Sales teams could be equipped with likely sales for a given film to sell appropriately. All of these aspects can be measured by analyzing many different variables such as genre, rating, cast and release date.

This seems to be a trend. Recently I wrote about Amazon Studios use of pretesting and data analysis to reduce the risk of failure.

This looks very promising:

Analytics allow studios to go beyond simple focus groups or established financial modeling to determine how audiences might respond to a given film. It’s all about identifying patterns in past data, melding them with current data points that are readily available, and then taking action to improve business performance. To effectively leverage historical data, it is vital to look at the past performance of a large volume of films as the basis for revenue forecasts and in the development of any forward-looking financial plans for a particular film.

As these new technologies and new players become dominant then those who rely on the old methods will slowly bleed their money against the newer players who take a data-driven, analytic approach to what they produce.

No tags

Comments are closed.

<<

>>

October 2012
M T W T F S S
« Sep   Nov »
1234567
891011121314
15161718192021
22232425262728
293031