Consumer
Big Data Lessons from the NSA
One of the biggest news stories lately has been the
revelation that the National Security Agency (NSA) has been using big data from telecommunications
companies to spy on people. The reaction to this story has been divided. While
a portion of the American public has responded with shock, anger and fear,
accusing the federal government of becoming Big Brother and ignoring citizens'
right to privacy, others have defended the surveillance as necessary to our
homeland security and, ultimately, not a big deal.
revelation that the National Security Agency (NSA) has been using big data from telecommunications
companies to spy on people. The reaction to this story has been divided. While
a portion of the American public has responded with shock, anger and fear,
accusing the federal government of becoming Big Brother and ignoring citizens'
right to privacy, others have defended the surveillance as necessary to our
homeland security and, ultimately, not a big deal.
The merits of whether the government should mine
telecommunications data will likely be debated for many years to come, and it
is probably best to have that debate in the press and at dinner tables across
the nation. However, for market researchers who specialize in data sciences and
big data methodology, there are important lessons to learn (or perhaps to be
reminded of) from the NSA debacle.
telecommunications data will likely be debated for many years to come, and it
is probably best to have that debate in the press and at dinner tables across
the nation. However, for market researchers who specialize in data sciences and
big data methodology, there are important lessons to learn (or perhaps to be
reminded of) from the NSA debacle.
There is Huge Value
Locked Away in Your Company's Big Data
Locked Away in Your Company's Big Data
The government is interested in understanding behavior
patterns that look suspicious. They want to know who is communicating with
whom, where these communications take place and how frequently they are occurring.
From this, they can paint a picture of who might be a 'bad guy' at risk of
doing harm to the US.
patterns that look suspicious. They want to know who is communicating with
whom, where these communications take place and how frequently they are occurring.
From this, they can paint a picture of who might be a 'bad guy' at risk of
doing harm to the US.
Similarly, data generated from your customers' transactions
reveal a treasure trove of information. While your company might not be
interested in identifying bad guys, it is likely interested in identifying
brand advocates and detractors.
reveal a treasure trove of information. While your company might not be
interested in identifying bad guys, it is likely interested in identifying
brand advocates and detractors.
Utilizing big data analytics, we can learn much about how
your customers use your products and services'information that could never be
learned through a survey. Big data analytics also help discern behavior
patterns that lead your customers to having a poor experience. Likewise, they
can identify fraud, minimize waste and isolate endless opportunities for
improving operational efficiency. Seemingly innocuous data that, when taken
alone, would appear to be meaningless, becomes valuable and actionable when
combined with other data'and data is right in front of you waiting to be
harnessed.
your customers use your products and services'information that could never be
learned through a survey. Big data analytics also help discern behavior
patterns that lead your customers to having a poor experience. Likewise, they
can identify fraud, minimize waste and isolate endless opportunities for
improving operational efficiency. Seemingly innocuous data that, when taken
alone, would appear to be meaningless, becomes valuable and actionable when
combined with other data'and data is right in front of you waiting to be
harnessed.
Big Data Doesn't Tell
the Why Behind the What
the Why Behind the What
If you listen carefully to how politicians and bureaucrats
describe big data surveillance programs, it is clear that mining
telecommunications data is just a starting point. While this data does a
remarkably good job of telling the government what people are doing, it doesn't
adequately explain why people are doing it. For this, the NSA needs to go back
to the Foreign Intelligence Surveillance Court to request a new court order to
expand the surveillance to allow for eavesdropping, stakeouts and other
'traditional' methods of police work.
describe big data surveillance programs, it is clear that mining
telecommunications data is just a starting point. While this data does a
remarkably good job of telling the government what people are doing, it doesn't
adequately explain why people are doing it. For this, the NSA needs to go back
to the Foreign Intelligence Surveillance Court to request a new court order to
expand the surveillance to allow for eavesdropping, stakeouts and other
'traditional' methods of police work.
The same is true with most corporate big data analysis. Big
data reveals what happened but 'traditional' qualitative and quantitative
research reveals why it happened. The real magic happens by combining
traditional and big data research in a framework that looks at the way
customers interact with your company holistically. At Market Strategies, we have
created such a framework. It is called the Continuous Improvement Cycle, and it
systematically integrates qualitative, quantitative and big data analytics to
paint a complete picture of your customers, what they are doing, and, most
importantly, why they are doing it. Once you fully understand the what and the
why, you will have the power to make changes that improve both your customers'
experience as well as your bottom line.
data reveals what happened but 'traditional' qualitative and quantitative
research reveals why it happened. The real magic happens by combining
traditional and big data research in a framework that looks at the way
customers interact with your company holistically. At Market Strategies, we have
created such a framework. It is called the Continuous Improvement Cycle, and it
systematically integrates qualitative, quantitative and big data analytics to
paint a complete picture of your customers, what they are doing, and, most
importantly, why they are doing it. Once you fully understand the what and the
why, you will have the power to make changes that improve both your customers'
experience as well as your bottom line.
Never Forget 'The
Wall Street Journal Test'
Wall Street Journal Test'
The NSA and other government officials seemed surprised by
the public's outrage. Collectively, they said the program has been in place for
seven years, and it is simply business as usual. The public is not convinced
and, as a result, the NSA is on the defensive.
the public's outrage. Collectively, they said the program has been in place for
seven years, and it is simply business as usual. The public is not convinced
and, as a result, the NSA is on the defensive.
In business, as in politics, every action brings with it a
certain amount of risk. In creating a surveillance program, the NSA failed to
consider The Wall Street Journal test. Simply put, this means an organization
should ask itself what would happen if the details of the proposed action were
to become a page one headline in The Wall Street Journal. Would the fallout
outweigh the benefit?
certain amount of risk. In creating a surveillance program, the NSA failed to
consider The Wall Street Journal test. Simply put, this means an organization
should ask itself what would happen if the details of the proposed action were
to become a page one headline in The Wall Street Journal. Would the fallout
outweigh the benefit?
All companies should consider this test before undertaking
any big data analytics project. Big data can be scary and intimidating to the
public, and it is critical to consider the impact to your customers, investors,
regulators and competitors. By taking The Wall Street Journal test in advance,
companies can tweak their big data projects to minimize risks. Companies need
an experienced partner who appreciates the inherent risks associated with big
data analytics and is able to keep them safe while gaining the most value from
the data. Sometimes less data is beneficial in the interest of minimizing
corporate risk. For instance, a company might choose to change privacy
policies, give customers the ability to opt-out or even decide to limit which
data will be included in the analysis. The point is proactive measures can help
avert a crisis or provide a defensible position in times of crisis.
any big data analytics project. Big data can be scary and intimidating to the
public, and it is critical to consider the impact to your customers, investors,
regulators and competitors. By taking The Wall Street Journal test in advance,
companies can tweak their big data projects to minimize risks. Companies need
an experienced partner who appreciates the inherent risks associated with big
data analytics and is able to keep them safe while gaining the most value from
the data. Sometimes less data is beneficial in the interest of minimizing
corporate risk. For instance, a company might choose to change privacy
policies, give customers the ability to opt-out or even decide to limit which
data will be included in the analysis. The point is proactive measures can help
avert a crisis or provide a defensible position in times of crisis.
Big Data is Here to
Stay
Stay
There is no denying that big data analytics is here to stay.
Data sciences allows you to learn things about your customers that were
previously impossible to discern. Big data, however, does not exist in a
bubble, and it does not answer all things. To succeed, you need to integrate
big data analytics with the traditional methods that have served you well in
the past. In combination with traditional research methods, big data analytics
allows organizations to get past a sea of chaotic data to proactively isolate
the few individuals that really require attention. This is just as true for the
NSA trying to identify a would-be terrorist as it is for a major telecom
provider trying to identify which customer is likely to churn or to spread
negative word-of-mouth via social networking. The benefits to operational
efficiency and the bottom line are enormous and if your organization is not
harnessing this power, you can be sure your competition is.
Data sciences allows you to learn things about your customers that were
previously impossible to discern. Big data, however, does not exist in a
bubble, and it does not answer all things. To succeed, you need to integrate
big data analytics with the traditional methods that have served you well in
the past. In combination with traditional research methods, big data analytics
allows organizations to get past a sea of chaotic data to proactively isolate
the few individuals that really require attention. This is just as true for the
NSA trying to identify a would-be terrorist as it is for a major telecom
provider trying to identify which customer is likely to churn or to spread
negative word-of-mouth via social networking. The benefits to operational
efficiency and the bottom line are enormous and if your organization is not
harnessing this power, you can be sure your competition is.
Market Strategies is on the leading edge of market
research's big data revolution. We have created proprietary frameworks that
integrate traditional research and big data analytics, and we know how to
extract value from all of your data assets while proactively managing risk. Let
us help you understand what is happening and why'then, and only then, can you
unleash the power of your company's big data.
research's big data revolution. We have created proprietary frameworks that
integrate traditional research and big data analytics, and we know how to
extract value from all of your data assets while proactively managing risk. Let
us help you understand what is happening and why'then, and only then, can you
unleash the power of your company's big data.
Mishkin will be presenting at TMRE
in Nashville October 21-23. Register for TMRE here:
in Nashville October 21-23. Register for TMRE here:
About the Author: Greg
Mishkin is a vice president of research and consulting at Market Strategies
International, working across all divisions and serving as the company's
primary subject matter expert for the wireless communications industry. His
responsibilities include managing and growing key client relationships within
the Communications division while maintaining a special focus on the
integration of large-scale behavioral data with Market Strategies' traditional
market research solutions. Greg is known for turning extremely complex data
into actionable insights and providing competitive advantages for his clients.
He earned a master's degree in business administration from Kennesaw State
University in Kennesaw, GA; a master's degree in clinical psychology from
University of Hartford in Hartford, CT and a bachelor's degree in psychology
from Union College in Schenectady, NY. Contact him at 404.601.9561, greg.mishkin@marketstrategies.com
or follow him on Twitter @GregMishkin.
Mishkin is a vice president of research and consulting at Market Strategies
International, working across all divisions and serving as the company's
primary subject matter expert for the wireless communications industry. His
responsibilities include managing and growing key client relationships within
the Communications division while maintaining a special focus on the
integration of large-scale behavioral data with Market Strategies' traditional
market research solutions. Greg is known for turning extremely complex data
into actionable insights and providing competitive advantages for his clients.
He earned a master's degree in business administration from Kennesaw State
University in Kennesaw, GA; a master's degree in clinical psychology from
University of Hartford in Hartford, CT and a bachelor's degree in psychology
from Union College in Schenectady, NY. Contact him at 404.601.9561, greg.mishkin@marketstrategies.com
or follow him on Twitter @GregMishkin.
