Opinion: Data and people sitting in a tree...

Bryan Melmed
By Bryan Melmed | 20 March 2014
Bryan Melmed, director of Insights.

While reading a recent article about the perceived drain of talent from Hollywood studios to HBO and Netflix, my attention was drawn to this comment: "Netflix and Amazon are all about giving their customers what they want by constantly tweaking complex algorithms to determine how to anticipate consumer desires." The role of big data in shaping House of Cards has been well documented, but this quote seemingly overlooks the fascinating human side of the story, revealed in an article that was published earlier this year when most Australians were on holiday.

The Atlantic’s 'How Netflix Reverse Engineered Hollywood' article is very well worth a read but for those who are time-poor, the in-depth story documents just how Netflix created 76,897 micro-genes to understand how people look for movies. Large teams of viewers, specially trained using a 36-page manual, were paid to watch the movies and then intricately and precisely tagged them with metadata. It was the efforts of this army of movie-watchers that aided Netflix in its effort to deconstruct Hollywood – and in doing so, compile what is probably the largest stockpile of movie data in the world.

While this data was able to tell the production team what they should be making, including some incredible granular detail as to specific actors and nuances, it couldn’t tell them how to make a TV show. And this is what was missed by those commentators who used the launch of House of Cards last year as an illustration of how data would reduce the creative process to a paint by numbers hollow process. Because while it was based upon extensive data insights as to what people wanted to watch, they got there because of the applied expertise, opinion, analysis and excellence of real people. And let’s face it, using big data seems to have worked out pretty well for them and for the millions of fans around the world who, like me, spent most of last month watching the second series.

That it worked so well shouldn’t really come as a big surprise. Because when you think about it, Netflix did not identify a revolutionary approach, but used data as a natural extension of what studios (and indeed most commercial enterprises) have done for decades. In order to thrive and survive in a competitive market it is imperative to listen to your customers, find out their needs and wants, and figure out the best way to serve them. With all the attention paid to automating the levers and switches, we should never forget that the first mile and the last mile belong to analog, organic people. Just as it takes people to design and build the technology, it takes people to understand its limitations and it takes people to ask the questions that lead to meaningful insight.

Most recently we worked with a client in the retail industry who was surprised to learn that our data identified a large Hispanic fan base shopping almost exclusively online. Based on our recommendations, the client revised the product lineup and display for both its online and retail stores to capture and leverage this previously unrecognised customer segment. They were impressed that our online data was a leading indicator of a shift in their business, but it is really just a new approach to a fundamental task: listening to what people want and provide that service to them.

After all, a tidal wave of data is just that: entirely overwhelming unless you have people who can find the pattern and meaning and turn its suggestions into actionable insights. As media continues to fragment, stack, mesh and all of the other things that scare the old guard, businesses should be ensuring that they are hiring or appointing their own people with these kinds of smarts if they want to find, keep and expand their audience.

The marriage of data and human insight holds tremendous potential for most enterprises and is only just beginning to be realised. Advances in instrumentation and technology means that individual and aggregated behavioural models are getting more accurate by the minute. But to complement the astounding granularity of available data, you will always need someone to think laterally, read between the lines, make practical decisions... and add some magic.  

Bryan Melmed
Director, Insights Services
Exponential

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