Category winner:
Netflix: Leveraging Big Data to Predict Entertainment Hits

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This case won the Knowledge, Information and Communications Systems Management category at The Case Centre Awards and Competitions 2016
 
The case
electric meter

Who – the protagonists

Ted Sarandos, Chief Content Officer at Netflix.

What

Netflix, a DVD rental and video streaming company, began to employ big data to track, record and assess detailed information about its customers’ viewing preferences, choices and habits. This became possible when the company launched its streaming service in 2007.

Why

house of cards

Using big data in this way gave Netflix a level of insight into its subscribers’ needs and preferences that none of the television or studio networks could ever tap into. The captured data enabled Netflix to offer customers personalised recommendations for future viewing and even commission original content, including the highly popular House of Cards programme.

When

netflixNetflix was set up in 1997. In 1999, the company launched a DVD rental service and in 2000 it introduced a personalised movie recommendation service based on subscribers’ ratings. Towards the end of 2007, Netflix was shipping around 1.6 million DVDs every day. In the same year it launched video streaming services in the US. The company’s global expansion began in 2010.

Where

Netflix is based on Los Gatos, California, US. The company’s services are now available almost worldwide.

remote

Key quote

‘Here is what the data from our DVD business tells us: we know what we shipped to you and we know when you returned it. I have no idea if you watched it. I have no idea if you watched it 20 times. With streaming, we have insight into every second of the viewing experience. I know what you have tried and what you have turned off. I know at what point you turned it off.’ – Ted Sarandos, Netflix’s Chief Content Officer

What next?

coupleSome observers remained concerned that Netflix would get into trouble if it failed to protect the privacy of its customers’ data, while others suggested that Netflix might stretch itself too far financially. Creative concerns have also been raised by industry experts with one asking: can the auteur survive in an age when computer algorithms are the ultimate focus group? And as another pointed out: ‘Data can only tell you what people have liked before, not what they don’t know they are going to like in the future.’

 
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Netflix: Leveraging Big Data to Predict Entertainment Hits
Debapratim Purkayastha and Tangirala Vijay Kumar
ICFAI Business School (IBS)
Ref 913-006-1

Teaching note
Ref 913-006-8

The authors

author

Debapratim Purkayastha and Tangirala Vijay Kumar

Debapratim explains why ‘big data’ is not just a buzzword – it’s here to stay.

A good feeling

There is a lot of prestige attached to these awards. Seeing your case being used by so many colleagues in other business schools worldwide is a very good feeling. It took a lot of our time and attention, and we are really happy that it turned out to be so popular – becoming the No.1 bestselling case in its category for 2015.

The Netflix and chill generation

Netflix has not only disrupted the movie rental market but has also become a big part of popular culture. Phrases such as ‘Netflix and chill’ now form part of the Internet slang dictionary and the present generation is called (rightly or wrongly) the ‘Netflix and chill generation’. So, a case on Netflix is bound to be interesting to teach. More so, as it deals with how the company leverages big data to predict entertainment hits.

Here to stay

mapBig data is not just the new digital buzzword; it’s here to stay. Students who want to remain relevant to the job market better pay attention! It’s imperative that today’s managers understand how to effectively leverage this explosive growth in the volume of data in meaningful ways that can be used to drive business decision-making.

Wheat and chaff

If information is not relevant to any of the questions you will be asking in class, it probably shouldn’t be included in the case. But remember, a case analysis does require a student to separate the wheat from the chaff, so some extra information is needed to add to the complexity. Overall, you should have a good reason for including each piece of information in your case.

big dataDefining moments

Writing a case in a fast-moving industry is always challenging as by the time you have drafted the case there may be key developments that make much of the case redundant. However, even very fast-moving industries have some defining moments that provide great scope for exploration and learning with many teachable moments. The key is to look for such moments and fix the time of the case there. Instructors will then find the case interesting and useful even five, ten, or 15 years after it was written. 

About the authors

Debapratim Purkayastha is Associate Dean at ICFAI Business School (IBS) and a recipient of The Case Centre’s prestigious Outstanding Contribution to the Case Method Award.
e debapratim@icmrindia.org
tw @dpurkayastha

Tangirala Vijay Kumar is a former Faculty Associate at ICFAI Business School (IBS).
research@icmrindia.org

 

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