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ResearchLeader
Opinion excellence
Sustaining the machine
Mind and brand relevance with the connected consumer




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Mind and the machine




It may be immense, fast and
mind-bendingly varied. But
researchers must remember:
Big Data can no more speak
for itself than the smaller sort.
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Mind and the machine




Big things can be intimidating. Research


                                                   90 percent of the
cannot allow Big Data to be one of them.
We stand on the edge of the most exciting and
transformative period in our industry’s history:
90 percent of the data in the world today was


                                                   data in the world
created in the last two years and “data taps”
such as mobile, social and POS will continue to
pour out raw information for us to work with
at an ever faster rate.

However, if our response to the new era of
data is to retreat behind number-crunching         today was created
                                                   in the last two years
technologies, then clients and indeed humanity
as a whole, will be much the worse for it.
It may be tempting to conclude that human
intuition must surely give way to computers
and algorithms when it comes to keeping up
with Big Data. But now, more than ever, we
need to recognise the immense, unique power
of our own minds when it comes to dealing
with information – and deciding how to act
on the basis of it.




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Mind and the machine




So what do we mean by “Big” exactly?                created and stored simply by virtue of things
Big Data wouldn’t be half as intimidating if it     happening. It’s broken free of human control
were just a question of having more numbers         – and therefore isn’t limited as to how big it
to deal with. But Big Data is bigger than that.     can get and how fast it comes at us. Data’s
It represents the coming together of several        Velocity, the speed at which huge volumes of it
different themes, each of which would be fairly     can be generated, is every bit as breathtaking
paradigm-shifting in its own right.                 as its sheer size. And the speed with which it is
                                                    available raises the opportunity and the demand
First of course, is the sheer scale of the data     to work with it in real-time.
now being produced and stored. Walmart
currently handles more than 1 million customer        Yet perhaps the most challenging shift of all
transactions every hour, in databases estimated       is that this size and speed is combined with
to contain more than 2.5 petabytes. Such an           an explosion in variety of data forms. Big Data
organisation may soon have created more data          comes in all shapes and sizes. Researchers are
every hour than research surveys have ever            leaping on new types of data source – and
delivered. With data storage doubling every           new types of source are leaping on us: from
year, there appears no constraint on the amount       mobile activity to Twitter feeds, geo-location
of information that we are dealing with.              information, facial expression capture and
                                                      much more. We are quickly moving from
Connected to the size of data but equally             dealing in numerical scores to dealing in shapes,
significant is the fact that it now generates itself. movement patterns, expressions – and human
Data no longer needs to be created through a          language. And such data does not come readily
questionnaire carefully crafted by a researcher,      packaged for analysis; using it must involve
or painstakingly collected by a field agent; it is    translating it as well.



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Mind and the machine




You created it: you deal with it                    that we should try to solve, what we think the      In his book The Signal and The Noise, US
Faced with such challenges, it’s tempting to        answers should look like, and what data forms       election poll guru Nate Silver devotes a chapter
believe that computational power, which has         we can enlist to help provide those answers.        to global warming and the fact that it would
taken the lead in creating this new world of        And these judgements are human ones.                be impossible to find any evidence of this in
information, must also take the lead in defining                                                        the notoriously unstable climate record, were
how we deal with it. In this view of the world,     In the Big Data era, the human imagination          scientists not armed with a theory telling them
the researcher starts to look less like a person,   continues to play an essential role in envisaging   exactly what to look for – and which data to
more like supercomputer in a bunker: one            what our many different data sources can be         prioritise. It’s an important reminder that...
where we simply have to feed in the right           made to do, and in aggregating, translating and



                                                                                                                       bigger
question or combination of questions, plug it       coding them to enable them to do it. To take
into the river of Big Data – and wait for the       a very simple example, Google can predict a
answer to pop out. But there are significant
dangers to this approach. If Big Data ends up
                                                    flu epidemic by spotting spikes in searches on
                                                    cold and flu remedies. This is a tremendously
                                                                                                         ...the
becoming processed and commoditised data,
then we are all in trouble.
                                                    cool thing, but it only works because somebody
                                                    realised that this pattern is significant – and      data is, the more it
                                                                                                         needs to become
                                                    that it correlates to something meaningful and
Digesting really raw data                           useful. Similarly, micro-location data gives TNS
It’s a mistake to believe that data can ever        a powerful new tool for mapping movement
speak for itself. Data always speaks with a
human voice; it can’t say anything otherwise.
                                                    around stores – but it is only powerful because
                                                    we have established an understanding of what
                                                                                                         articulate.
Every statistic that we deal with is the result     these movements mean.
of subjective judgement about the problems




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                                                                                                                                                           5
Mind and the machine




From data creators to data curators
In the old days (of six months ago), the raw
numbers that we sat down to analyse weren’t
really raw at all; they were shaped by human
hands even before they came into existence.
The art of designing a questionnaire involves
finely balanced judgements on which questions
to ask and how to ask them. Whether to score
preferences out of five, seven or ten can trigger
some pretty serious debates with good reason –
these things have a big influence on our ability
to spot patterns, make connections and provide
meaningful insight. And judging how to ask         of research, we must continue to apply the         as linking spend and retention data to customer
questions should, of course, be closely related to same standards to independently generated          experience surveys, as we already do at TNS.
the challenge of what you are looking for.         Big Data that we would if we had created it        In the future, we will find more and more
                                                   ourselves. And this will require leveraging much   scenarios where the data we aggregate does
In the Big Data era, we are no longer data         hard-won experience about how data works.          not include traditional surveys at all. In all of
creators, designing the structure of information   The skills that once went into the design of       these contexts, it’s not just a question of being
from the outset; instead we are data curators,     research instruments such as questionnaires will   excited about what data can do. It’s equally
working with information that has been             remain crucially important in aggregating and      important sometimes to step back, look at how
generated independently. As such, we will          selecting data sources, and deciding exactly       complete and representative a given set of data
face many new challenges and require many          how they relate to one another. For now, this      is, and ask ourselves rigorous questions about
new skillsets. However, as we evolve the role      might involve incremental improvements such        what questions it is really qualified to answer.




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Mind and the machine




The continuing evolution of analytics              competitive relationships, owned and disputed
At TNS, we’ve already evolved from the era of      territory and areas of opportunity. We then
ad-hoc analysis, when researchers collected data   build on this structural understanding with more
with little reference to how it would eventually   action-oriented means of addressing the data:
be used (and then looked through it in the         “Groupings” to segment the subject matter and
hope it would reveal something useful). Today      “Drivers” to reveal the variables that influence
the design of the instruments for a particular     relevant results, including causal connections
piece of research is informed from the start by    that can be far from immediately apparent.
the challenge of how best to answer business
questions.                                         This approach may be structured, but it retains
                                                   grounds for flexibility. It provides a checklist
The conceptual framework that we use for           for where and how to look for patterns and
any type of analysis reflects how the human        themes. In the Big Data era, we will learn to       and expecting machines to design them in the
brain naturally makes sense of information.        look for different types of patterns in vastly      first place. We must not fool ourselves that
This framework consists of four different          diverse forms of data, but human reason             Artificial Intelligence (AI) is ready to take on the
ways of looking at any set of data, whether        remains the key driving force in identifying them task of formulating questions and crafting the
it was generated through research or arrived,      and drawing purposeful connections between          algorithms to answer them. After all, even those
Big Data-style from independent sources.           them.                                            157984631069555555345791326054
                                                                                                       that welcome the concept of a technological
“Dimensions” and “Landscape” address the                                                               singularity in which human-designed AI
structure of information; the first seeking        Computational muscle can give research the
                                                                                                    057879894455555555555204654765
                                                                                                       surpasses that of humans themselves, don’t
out common themes across a data set (the           scale and speed that we will increasingly        573457913555555555555502106187
                                                                                                       envisage it happening until at least 2045. That’s
key themes defining a product category, for        require in the Big Data era, but it is important    a long time to wait to take real advantage of
example), the second looking more closely at       to distinguish between automating processes      141662046555555555555511579846
                                                                                                       Big Data.
                                                                                                916305021055555555555120578798
                                                                                                676461157985555555552145734579
               Share this                                                                       605487916305021061879214166204
                                                                                                                   Opinion Leader
                                                                                                765141676461157984637916305021  7
                                                                                                879465050312057879894465654214
Mind and the machine




Data and the human imagination
Imposing structure on Big Data will throw up
some intriguing challenges – and these challenges




                                                        Big
will involve logical leaps and lateral thinking
for which the human brain remains our best
available tool. What is a meaningful means of
scoring a positive tweet or Facebook rant? What
                                                                                                                      Business
aspect of somebody’s location is actually relevant
to the client brief – and what other sources of
information can be integrated or overlaid to give
context to this information? The location of a car
                                                         data                                                         solutions
by itself is meaningless. If it’s a car unable to fit
into the WalMart parking lot on Black Friday, it
becomes a whole lot more interesting.

When we talk about deploying computational              questions that we can ask, and the speed with     dangers: that we define in advance what it must
power in the Big Data era, we must therefore            which we can answer them. Big Data can unleash    look for and how it must look for it, leading to
be pretty clear about what we are asking                the potential of human insight and human reason   standardisation and blinkered, undifferentiated
computers to do. We must continue to exercise           in ways never envisaged before.                   thinking, and that we confuse correlation with
our judgement as to which information is valid                                                            causation, failing to exercise human judgement
and valuable, and how its many varied forms can         The greater computational power that will         about which results are meaningful and which
be coded in meaningful ways. As data curators,          enable us to make the most of Big Data must       are not. The challenges of the Big Data era will be
that’s our job. But by unleashing the power of          be harnessed to an expanded role for the          challenges for the human imagination and human
today’s machines we can dramatically increase           human mind. Depending too much on non-            judgement as much as for IT infrastructure.
the scope of data that we can use, the range of         human processing power creates two potential      We need to welcome them as such.


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About Opinion Leaders
Opinion Leaders are a regular series of articles from TNS consultants, based on their expertise gathered through
working on client assignments in over 80 markets globally, with additional insights gained through
TNS proprietary studies such as Digital Life, Mobile Life and the Commitment Economy.

About TNS
                                                                                                                                About the authors
                                                                                                                   Mark Kingsbury is Global Head of Marketing Sciences,
TNS advises clients on specific growth strategies around new market entry, innovation, brand switching and
                                                                                                                   leading the TNS Advanced Analytics teams around the
stakeholder management, based on long-established expertise and market-leading solutions. With a presence          world and driving initiatives to ensure that TNS defines
in over 80 countries, TNS has more conversations with the world’s consumers than anyone else and understands       and delivers best practice approaches to addressing
individual human behaviours and attitudes across every cultural, economic and political region of the world.       our clients’ business issues. Mark began his career
TNS is part of Kantar, one of the world’s largest insight, information and consultancy groups.                     at Research International and held senior roles at
                                                                                                                   Quadrangle and Ipsos before joining TNS at the start
                                                                                                                   of 2012.
Please visit www.tnsglobal.com for more information.
                                                                                                                   Bob Burgoyne is Development Director, Global
Get in touch                                                                                                       Marketing Science at TNS. Bob has a background
If you would like to talk to us about anything you have read in this report, please get in touch via               encompassing both digital and analogue research
enquiries@tnsglobal.com or via Twitter @tns_global                                                                 methodologies, answering business questions for
                                                                                                                   primarily mobile sector clients in both emerging and
                                                                                                                   developed markets. He now focusses on non-traditional
References                                                                                                         research techniques and data sources, exploring the
1. Nate Silver, The Signal and the Noise                                                                           opportunities which they offer to provide better (richer,
2. Daniel-Kahneman, Thinking Fast and Slow                                                                         quicker, more exact) answers to our clients’ questions.




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Mind and the machine

  • 1. ResearchLeader Opinion excellence Sustaining the machine Mind and brand relevance with the connected consumer Share this Opinion Leader
  • 2. Mind and the machine It may be immense, fast and mind-bendingly varied. But researchers must remember: Big Data can no more speak for itself than the smaller sort. Share this Opinion Leader 2
  • 3. Mind and the machine Big things can be intimidating. Research 90 percent of the cannot allow Big Data to be one of them. We stand on the edge of the most exciting and transformative period in our industry’s history: 90 percent of the data in the world today was data in the world created in the last two years and “data taps” such as mobile, social and POS will continue to pour out raw information for us to work with at an ever faster rate. However, if our response to the new era of data is to retreat behind number-crunching today was created in the last two years technologies, then clients and indeed humanity as a whole, will be much the worse for it. It may be tempting to conclude that human intuition must surely give way to computers and algorithms when it comes to keeping up with Big Data. But now, more than ever, we need to recognise the immense, unique power of our own minds when it comes to dealing with information – and deciding how to act on the basis of it. Share this Opinion Leader 3
  • 4. Mind and the machine So what do we mean by “Big” exactly? created and stored simply by virtue of things Big Data wouldn’t be half as intimidating if it happening. It’s broken free of human control were just a question of having more numbers – and therefore isn’t limited as to how big it to deal with. But Big Data is bigger than that. can get and how fast it comes at us. Data’s It represents the coming together of several Velocity, the speed at which huge volumes of it different themes, each of which would be fairly can be generated, is every bit as breathtaking paradigm-shifting in its own right. as its sheer size. And the speed with which it is available raises the opportunity and the demand First of course, is the sheer scale of the data to work with it in real-time. now being produced and stored. Walmart currently handles more than 1 million customer Yet perhaps the most challenging shift of all transactions every hour, in databases estimated is that this size and speed is combined with to contain more than 2.5 petabytes. Such an an explosion in variety of data forms. Big Data organisation may soon have created more data comes in all shapes and sizes. Researchers are every hour than research surveys have ever leaping on new types of data source – and delivered. With data storage doubling every new types of source are leaping on us: from year, there appears no constraint on the amount mobile activity to Twitter feeds, geo-location of information that we are dealing with. information, facial expression capture and much more. We are quickly moving from Connected to the size of data but equally dealing in numerical scores to dealing in shapes, significant is the fact that it now generates itself. movement patterns, expressions – and human Data no longer needs to be created through a language. And such data does not come readily questionnaire carefully crafted by a researcher, packaged for analysis; using it must involve or painstakingly collected by a field agent; it is translating it as well. Share this Opinion Leader 4
  • 5. Mind and the machine You created it: you deal with it that we should try to solve, what we think the In his book The Signal and The Noise, US Faced with such challenges, it’s tempting to answers should look like, and what data forms election poll guru Nate Silver devotes a chapter believe that computational power, which has we can enlist to help provide those answers. to global warming and the fact that it would taken the lead in creating this new world of And these judgements are human ones. be impossible to find any evidence of this in information, must also take the lead in defining the notoriously unstable climate record, were how we deal with it. In this view of the world, In the Big Data era, the human imagination scientists not armed with a theory telling them the researcher starts to look less like a person, continues to play an essential role in envisaging exactly what to look for – and which data to more like supercomputer in a bunker: one what our many different data sources can be prioritise. It’s an important reminder that... where we simply have to feed in the right made to do, and in aggregating, translating and bigger question or combination of questions, plug it coding them to enable them to do it. To take into the river of Big Data – and wait for the a very simple example, Google can predict a answer to pop out. But there are significant dangers to this approach. If Big Data ends up flu epidemic by spotting spikes in searches on cold and flu remedies. This is a tremendously ...the becoming processed and commoditised data, then we are all in trouble. cool thing, but it only works because somebody realised that this pattern is significant – and data is, the more it needs to become that it correlates to something meaningful and Digesting really raw data useful. Similarly, micro-location data gives TNS It’s a mistake to believe that data can ever a powerful new tool for mapping movement speak for itself. Data always speaks with a human voice; it can’t say anything otherwise. around stores – but it is only powerful because we have established an understanding of what articulate. Every statistic that we deal with is the result these movements mean. of subjective judgement about the problems Share this Opinion Leader 5
  • 6. Mind and the machine From data creators to data curators In the old days (of six months ago), the raw numbers that we sat down to analyse weren’t really raw at all; they were shaped by human hands even before they came into existence. The art of designing a questionnaire involves finely balanced judgements on which questions to ask and how to ask them. Whether to score preferences out of five, seven or ten can trigger some pretty serious debates with good reason – these things have a big influence on our ability to spot patterns, make connections and provide meaningful insight. And judging how to ask of research, we must continue to apply the as linking spend and retention data to customer questions should, of course, be closely related to same standards to independently generated experience surveys, as we already do at TNS. the challenge of what you are looking for. Big Data that we would if we had created it In the future, we will find more and more ourselves. And this will require leveraging much scenarios where the data we aggregate does In the Big Data era, we are no longer data hard-won experience about how data works. not include traditional surveys at all. In all of creators, designing the structure of information The skills that once went into the design of these contexts, it’s not just a question of being from the outset; instead we are data curators, research instruments such as questionnaires will excited about what data can do. It’s equally working with information that has been remain crucially important in aggregating and important sometimes to step back, look at how generated independently. As such, we will selecting data sources, and deciding exactly complete and representative a given set of data face many new challenges and require many how they relate to one another. For now, this is, and ask ourselves rigorous questions about new skillsets. However, as we evolve the role might involve incremental improvements such what questions it is really qualified to answer. Share this Opinion Leader 6
  • 7. Mind and the machine The continuing evolution of analytics competitive relationships, owned and disputed At TNS, we’ve already evolved from the era of territory and areas of opportunity. We then ad-hoc analysis, when researchers collected data build on this structural understanding with more with little reference to how it would eventually action-oriented means of addressing the data: be used (and then looked through it in the “Groupings” to segment the subject matter and hope it would reveal something useful). Today “Drivers” to reveal the variables that influence the design of the instruments for a particular relevant results, including causal connections piece of research is informed from the start by that can be far from immediately apparent. the challenge of how best to answer business questions. This approach may be structured, but it retains grounds for flexibility. It provides a checklist The conceptual framework that we use for for where and how to look for patterns and any type of analysis reflects how the human themes. In the Big Data era, we will learn to and expecting machines to design them in the brain naturally makes sense of information. look for different types of patterns in vastly first place. We must not fool ourselves that This framework consists of four different diverse forms of data, but human reason Artificial Intelligence (AI) is ready to take on the ways of looking at any set of data, whether remains the key driving force in identifying them task of formulating questions and crafting the it was generated through research or arrived, and drawing purposeful connections between algorithms to answer them. After all, even those Big Data-style from independent sources. them. 157984631069555555345791326054 that welcome the concept of a technological “Dimensions” and “Landscape” address the singularity in which human-designed AI structure of information; the first seeking Computational muscle can give research the 057879894455555555555204654765 surpasses that of humans themselves, don’t out common themes across a data set (the scale and speed that we will increasingly 573457913555555555555502106187 envisage it happening until at least 2045. That’s key themes defining a product category, for require in the Big Data era, but it is important a long time to wait to take real advantage of example), the second looking more closely at to distinguish between automating processes 141662046555555555555511579846 Big Data. 916305021055555555555120578798 676461157985555555552145734579 Share this 605487916305021061879214166204 Opinion Leader 765141676461157984637916305021 7 879465050312057879894465654214
  • 8. Mind and the machine Data and the human imagination Imposing structure on Big Data will throw up some intriguing challenges – and these challenges Big will involve logical leaps and lateral thinking for which the human brain remains our best available tool. What is a meaningful means of scoring a positive tweet or Facebook rant? What Business aspect of somebody’s location is actually relevant to the client brief – and what other sources of information can be integrated or overlaid to give context to this information? The location of a car data solutions by itself is meaningless. If it’s a car unable to fit into the WalMart parking lot on Black Friday, it becomes a whole lot more interesting. When we talk about deploying computational questions that we can ask, and the speed with dangers: that we define in advance what it must power in the Big Data era, we must therefore which we can answer them. Big Data can unleash look for and how it must look for it, leading to be pretty clear about what we are asking the potential of human insight and human reason standardisation and blinkered, undifferentiated computers to do. We must continue to exercise in ways never envisaged before. thinking, and that we confuse correlation with our judgement as to which information is valid causation, failing to exercise human judgement and valuable, and how its many varied forms can The greater computational power that will about which results are meaningful and which be coded in meaningful ways. As data curators, enable us to make the most of Big Data must are not. The challenges of the Big Data era will be that’s our job. But by unleashing the power of be harnessed to an expanded role for the challenges for the human imagination and human today’s machines we can dramatically increase human mind. Depending too much on non- judgement as much as for IT infrastructure. the scope of data that we can use, the range of human processing power creates two potential We need to welcome them as such. Share this Opinion Leader 8
  • 9. About Opinion Leaders Opinion Leaders are a regular series of articles from TNS consultants, based on their expertise gathered through working on client assignments in over 80 markets globally, with additional insights gained through TNS proprietary studies such as Digital Life, Mobile Life and the Commitment Economy. About TNS About the authors Mark Kingsbury is Global Head of Marketing Sciences, TNS advises clients on specific growth strategies around new market entry, innovation, brand switching and leading the TNS Advanced Analytics teams around the stakeholder management, based on long-established expertise and market-leading solutions. With a presence world and driving initiatives to ensure that TNS defines in over 80 countries, TNS has more conversations with the world’s consumers than anyone else and understands and delivers best practice approaches to addressing individual human behaviours and attitudes across every cultural, economic and political region of the world. our clients’ business issues. Mark began his career TNS is part of Kantar, one of the world’s largest insight, information and consultancy groups. at Research International and held senior roles at Quadrangle and Ipsos before joining TNS at the start of 2012. Please visit www.tnsglobal.com for more information. Bob Burgoyne is Development Director, Global Get in touch Marketing Science at TNS. Bob has a background If you would like to talk to us about anything you have read in this report, please get in touch via encompassing both digital and analogue research enquiries@tnsglobal.com or via Twitter @tns_global methodologies, answering business questions for primarily mobile sector clients in both emerging and developed markets. He now focusses on non-traditional References research techniques and data sources, exploring the 1. Nate Silver, The Signal and the Noise opportunities which they offer to provide better (richer, 2. Daniel-Kahneman, Thinking Fast and Slow quicker, more exact) answers to our clients’ questions. Share this Opinion Leader 9