How Data-Driven Decision-Making Impacts Both Murder And Movies

BY ADAM GROSSMAN

When it comes to Chicago, movies, and murder, the only commonality many people will likely think of is Public Enemies – the film that features Johnny Depp playing notorious criminal John Dillinger. Both the city of Chicago and the movie studio Warner Bros., however, are now also using data-driven decision to address critical issues with these topics. More specifically, Chicago is using big data analysis to reduce its homicide rates while Warner Bros. is using artificial intelligence (AI) to better predict the success of its movies.

In a recent editorial, The Philadelphia Inquirer recently called for Philadelphia to take similar steps to Chicago to deal with the “homicide crisis” plaguing the city. Philadelphia has a “steep rise” in murders from 246 in 2013 to 356 in 2019. Chicago faced a similar problem when the city experienced a 56% increase in homicides from 2015 to 2016 alone leading President Donald Trump to compare the city a “war zone.”

Chicago’s war on homicide started in 2016 by taking “gun violence seriously.” This meant focusing efforts of multiple government and non-profit entities in clear and tangible ways using data. More specifically, Chicago targeted both “hot spots” within the city where homicides were most likely to occur and the most high-risk individuals that they identified using large datasets from multiple sources.

For example, READI Chicago data analysis found that high-risk men in this context were those with “18 arrests, five of those for felonies. More than 30% have been shot and close to 80% have been victims of violence.” READI then provided those specific men with “jobs, cognitive behavioral therapy, and assistance connecting to other services” during an 18-month period to decrease the probability of them committing a homicide.

In the past, municipal governments and non-profits would often focus on higher-level approaches that would spread resources across multiple agencies and entities to cover the entire city. This targeted approach has been critical in enabling Chicago to reduce its homicide rate by 37% over the past three years with the city dropping its total number of homicides from 778 in 2016 to fewer than 500 in 2019. 

While clearly not as critical as reducing murder rates, better predicting the financial success of a movie is one of the most important challenges facing the entertainment industry. That is why Forbes featured Warner Bros. recent announcement of a new deal with Cinelytic. The company “licenses historical data about movie performances over the years, then cross-references it with information about films’ themes and key talent, using machine learning to tease out hidden patterns in the data.” It then determines the specific factors, such as actors, budget, and brands, that will most likely predict a movie’s financial success and delivers these insights to its clients.

Cinelytic’s is one of several companies that major movie studios are beginning to work with to leverage AI, machine learning, natural language processing (NLP) and big data analysis to predict movie success. For example, studios work with Scriptbook to “analyze a film's script and arrive at an estimation of the revenues that film is likely to earn” with an 86% accuracy rate according to the company. This level of performance (which should increase over time as products improve with larger datasets and system training) likely will help studios generate and / or save millions of dollars by predicting hits or flops better than humans can without these data-driven insights.

Homicides and movies are not the only two places where data is driving the decision-making process. B6A has covered this topic as it applies to corporate partnerships and sports in multiple Blog Six posts. Leveraging big data, AI, machine learning, and NLP technologies to generate specific insights that drive critical sponsorship results is also at the core of our Corporate Asset Valuation Model (CAV), Media Analysis Platform (MAP), Social Sentiment Analysis Platform (SAP), and Audience Inference Analysis Platform (AIP) product offerings.  

The point of featuring the city of Chicago and movie studios in this post, however, is to highlight two distinct entities that each have been slow to adopt data-driven approaches in the past. In fact, the slow adoption of data-driven strategies by both governments / non-profits and movie studios is the reason The Inquirer and Forbes featured Chicago and Warner Bros., respectively, in recent articles.

If cities and movie studios are moving in this direction then it is clear that data-driven analysis is likely here for the long-term. It is critical for those people now working in the sponsorship industry to examine how they can use data-driven decision-making to drive results if they have not already.