The document discusses the limitations of using big data to predict human behavior. It examines Netflix's attempts to predict movie ratings, which were only off by 0.1 stars on average. Customer attrition predictions for wireless providers often failed when human decisions were involved. Google found its web advertising click-through predictions were wrong 98% of the time. The document concludes that while big data can improve some predictions, predicting human behavior with high accuracy is difficult since humans frequently change their minds. Managers should accept predictions have limits and use big data primarily for forecasting work levels rather than assuming behavior can be closely predicted.

1. Big Data Hype(and Reality)
NarasingaMoorthy V

2. Future Prediction:
• Decision-makers want to understand
the patterns in the past and the
present in order to anticipate what is
most likely to happen in the future.
• Can the Data Scientists predict
consumer actions and attitude using
the past data?

3. Film Ratings

4. Netflix’s Prediction:
• Netflix is a data savvy company
• It relies on customer generated data for
predicting future shows.
• How reliable is there prediction in the first
place?

5. • When a competition is organized to test Netflix’s
prediction, it turns out the error rate on IMDB
rating was around 1 on a 5 Start scale(0 being
the lowest and 5 being the highest.
• Average prediction of how a viewer would rate a
flim has been improved by less than a 0.1 star
which is of no use.

6. Customer Attrition

7. • Use Customer behavior data to predict the ones
that will jump from our ship.
• Targeted Marketing can be performed only for the
attrition customers.
• Lucrative offers can be provided to the subjective
audience for retaining them
Wireless Communication Provider

8. • Many data modelling algorithms has to be
developed for predicting the customer
attrition
• Even after doing all these calculations,
one’s work might be of waste whenever
human decisions are taken into picture.

9. Web Advertising Response

10. • “Knowing what you know about your business, is
there a plausible explanation for that result?”
• When Google wants to calculate the click through
ratio(CTR), it started using the previous data for
predicting the CTR on its advertisements.
• It turns out that 98% of the times, prediction was
wrong.

11. What are we to conclude from these THREE areas?

12. • Future predictions turns out to be right
when human decisions are not involved
• Humans change their mindset every now
and then.
• Therefore predicting Human behavior is
close to impossible using the past data.

13. Knowing it…!
• Big data analytics can improve predictions, but
the biggest effects of big data will be in creating
wholly new areas.
• The success of Facebook, Twitter, and LinkedIn
social networks depends on their scale, and big
data tools and analytics will be required for them
to keep growing.
• But if you’re counting on it to make people much
more predictable, you’re expecting too much.

15. Relevance for India Managers:
• Managers in India should accept the fact that human
behavior cannot be predicted more than a certain extent.
• Prediction can be used to forecast the amount of work that
will fall under everyone’s head.
• Managers should learn how to use the advantage of big
data analysis.

16. The End