WHITE PAPER
The Big Data
Opportunity
Instrumenting Your Business
for Competitive Advantage
WHITE PAPER
The Big Data Opportunity
2
Executive Summary
Big Data strategies—those that use massively parallel, specialized systems
to tap the intelligence held in high volumes of distributed, unstructured
data—are changing industries, and creating winners and also-rans. Invaluable
information, culled from data collected at customer interaction points, is being
used to drive product and service development, marketing and other activities
to achieve unprecedented gains in market share, wallet share, revenues and
loyalty.
These Big Data Analytics concepts aren’t new—companies like Harrah’s,
American Airlines and Wal-Mart pioneered them long ago—but they’re now
feasible for more organizations to attempt. Why? First, commodity-class
storage technology has made it feasible to keep data that organizations once
threw away (because keeping it was simply too expensive). Also, more data is
captured now, in electronic, mobile, web and contact center touchpoints.
Where once only resource-rich organizations could afford to leverage Big Data
and focus on centralized, information-rich data sources, now enterprises of
all sizes can apply Big Data strategies to larger collections of distributed, less
structured data—if they employ the right tools and techniques.
To launch a successful Big Data initiative, an enterprise must first identify, then
instrument—that is, set up automated data collection—at customer interaction
points within its business activities. Mobile and online activities will be
prevalent among these, but there are others—and any new business processes
should be designed with an eye to instrumentation. There’s also a need to
build an organizational competency, featuring strong analytical, exploratory
and creative resources capable of identifying opportunities to leverage Big
Data and of implementing solutions.
To fully realize the benefits of a Big Data initiative, the enterprise should
also create a tiered feedback loop. This loop begins with exploratory, ad hoc
analysis of huge data stores, continues by refining and condensing data, then
applies high-performance data management and analytics to the refined data
for both monitoring and further exploration. This tiered approach will provide
its own competitive advantage, enabling organizations that use it to identify
and leverage more types of information, more quickly.
Repeatedly, the first company in an industry or market to launch a Big Data
initiative focused on customer interactions gains a virtually irreversible
advantage. Companies can choose to pursue their own Big Data strategies... or
watch their competitors take the spoils.
WHITE PAPER
The Big Data Opportunity
Customer Interactions:
The Heart of Big Data
Because knowing how customers
behave and think is the key to driving
loyalty, growth and revenue, customer
interactions represent the most
valuable Big Data you can choose
to leverage. Mining this intelligence
can lead to truly strategic leaps. In
addition to web analytics, consider
POS, customer service/support and
even interactions with marketing
campaigns. If your product, service or
solution makes it practical, capture
interactions there, too—it will lead to
new or improved offerings and their
attendant revenues.
Time and motion data, in all its variant
forms, might help boost efficiencies
or reduce the cost of labor and other
resources. But revolutionary changes
to products, channels, delivery
methods and more nearly always
result from a better understanding of
customer interactions.
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The Opportunity
As a widely discussed but loosely understood term, Big Data merits a quick
working definition. For our purposes, let’s say the Big Data opportunity exists
when:
• Some kind of potentially useful information exists, and is (or could be)
captured
• The data exists in quantities large enough to require the use of massively
parallel, specialized systems to manage it
• The data is collected, primarily, at points of customer interaction
• There exist the analytic means to cull useful information from the data
Note that Big Data isn’t a new concept: as we shall see, any number of
now-legendary organizations have tapped its power, typically when an
overwhelming opportunity justified exorbitant costs. What’s different today
is that more data is captured, and the technologies to manage that data have
advanced and are more affordable.
That third qualifier above deliberately excludes (again, for our purposes)
certain large data stores used for scientific, process automation and other
purposes. While those pursuits are essential in specific environments, they
focus on doing things faster and/or at lower costs. Yes, those are opportunities,
strictly speaking, but not in the scale we’re discussing here.
Information about customer interactions is the key to revenue opportunities
larger by orders of magnitude than what most industries and organizations
have imagined. To see why, let’s consider a few illustrative (and, in some cases,
illustrious) case histories.
Big Data Game Changers
First up: Harrah’s Entertainment, the gaming industry’s largest player—in
part because the company chose early on to invest more in understanding its
customers than in glitzy casinos.
Harrah’s set up the industry’s first loyalty program, issuing membership cards
to anyone who wanted to play. Customers could swipe their cards at every
gaming table, every slot machine, every dining venue (and earned rewards
for every swipe). The company captured and analyzed all this customer
interaction data—investing millions in Teradata storage and SAS analytics
software to do so—and began reaping its own rewards.
By understanding the behavior patterns borne out in hundreds of thousands
of interactions per day, Harrah’s created the industry’s first model of each
customer’s potential value, then launched targeted marketing campaigns
with highly relevant offers enabled by the new intelligence. The result? A 25%
increase in Harrah’s share of customer gaming budgets, and a similar jump in
profits.
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The Big Data Opportunity
4
In another example, American Airlines and other industry leaders responded
to deregulation by advancing the science now known as yield management,
which involves strategic control of inventory (flights and seats) in order to
maximize revenues generated by each. The industry uses similar processes,
known as load optimization, to maximize airfreight revenues.
To experience another Big Data success that affects nearly all of us, call a
catalog retailer to make a purchase, or a support line to get help on just
about anything. The modern call center at the other end of the conversation
is capturing customer interaction data—and, if it’s doing a good job, it’s also
using data from previous interactions to inform and guide your experience.
“When
instrumenting
a business
process
becomes
feasible
within an
industry,
the first
organization
finding a way
to leverage
the data gains
an immense
competitive
advantage.”
That call center agent is probably viewing a “screen pop” portraying you
and a history of your experience with the retailer, pulled from a CRM system.
New information captured during the call is captured and returned for future
analysis. All this data and analysis enables a better experience for you, while
helping the call center to maximize the productivity (in sales, customer
satisfaction or whatever else matters) of its agents.
Rounding out our success stories is online gaming company Zynga, which
captures and analyzes data from sales and support interactions as well as from
gameplay itself. Their goal? To maximize sales of game currency, promote
growth through targeted advertising and maximize game appeal.
Worth noting: in all of these success stories, the potential (and, later, real)
benefits of capturing and analyzing huge amounts of data completely justified
the very substantial IT costs. At the time of these successes, most organizations
did not have the resources to pursue Big Data strategies. But that’s changing
quickly.
Why Big Data is Evolving—and Why It Matters
The Big Data opportunity is now more accessible to more organizations, for
a number of reasons. First, it’s easier to instrument—that is, set up automated
data collection—customer interactions. With the rapid expansion of online
activity and the proliferation of mobile devices, more customer touchpoints
are electronic. Additionally, Web clickstreams and the like represent
touchpoints that previously didn’t exist, while the rise of the automated
contact center has put more—and more kinds of—interactions within reach.
All of this newly available data (plus data that has long been captured
but wasn’t feasible to keep) is now easier to store and manage, thanks to
technologies that have become commoditized—think rack servers, open source
operating systems and data platforms and cloud services. At the same time,
data access and management technologies like Hadoop, NoSQL and columnar
databases are making it technically feasible for organizations with fewer
resources to work with large, less-structured data stores.
Importantly, the costs for tools used to collect and analyze Big Data have
plummeted as well. Harrah’s spent tens of millions for SAS licensing and more
WHITE PAPER
The Big Data Opportunity
5
than that on Teradata platforms. Today’s commoditized technologies, chosen
carefully, would make the price tag much lower, and could all but eliminate
outlays of precious capital.
Finally, analyzing data has become easier, thanks to more sophisticated tools,
some cloud-based. These newer analytics technologies facilitate the essential
“explore and discover” analysis mode that can help uncover game-changing
patterns and trends that aren’t specifically being sought.
A Big Data Imperative. Harrah’s, the airlines, Zynga and all the rest
have transformed their industries (and, by the way, leapt ahead of their
competition) by targeting high volume processes, capturing large volumes
of data, then somehow measuring and analyzing it. Here, too, a pattern has
emerged: when instrumenting a business process becomes feasible within
an industry, the first organization finding a way to leverage the data gains an
immense competitive advantage.
One shining example? Wal-Mart. The retail giant has instrumented virtually
every activity in its business—and the data it collects informs everything it
does. Being the first brick-and-mortar retailer to pursue a Big Data strategy put
the company so far ahead in the industry that some competitors may never
catch up (or even survive).
The message to any enterprise, of any size, is clear: be the first in your industry
to instrument and analyze... or someone else will.
The Strategy
First: Start Looking Around
To seize Big Data opportunities in your industry, first take a long look at your
internal and external processes. Are they currently instrumented? If not, could
they be? In most cases the answer will be yes. Don’t worry yet about what you
might do with the captured data—just do an inventory of what’s out there, or
could be. This step alone will get you thinking about possibilities.
Next, assess your organization, industry and market(s). In what processes,
channels or business segments would an overwhelming advantage be
especially useful? What are the most impactful challenges faced by enterprises
in your industry? Don’t be surprised if Step 1 above informs and influences
this exploration. With luck (and, ideally, with creative, innovation-prone
staff assigned to the task), you’ll find areas where these two steps overlap,
combining a key industry challenge with the ability to instrument related
activities.
One way to facilitate this approach is to think mobile—because mobile
technologies enable instrumentation in more scenarios. Mobile devices and
apps are even creating new kinds of touchpoints that otherwise wouldn’t exist
(think GPS and Foursquare).
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The Big Data Opportunity
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Some activities may not appear to be easily instrumented. Don’t rule these
out, especially if they involve customer interactions. It may be worthwhile to
take on an instrumentation challenge—even an expensive one—if it helps you
understand the process and, more importantly, what opportunities exist for
better understanding your customers and their needs.
Note: it’s usually not ideal to dramatically change a process just so you can
begin measuring it. Instead, instrument it as is, then analyze. The results will
tell you if there’s data-intensive value worth pursuing further, and will help
guide how the process should be changed.
When you enter a new market, develop a new solution, open a new location
or split off a new business function, think again about instrumentation—in
fact, demand it. Don’t settle for new or evolved processes that can’t efficiently
capture data. Speed and quality are no longer enough—instrumentation is
mandatory.
When is this process complete? Never. You may identify, early on, some Big
Data opportunities to pursue. But keep looking—your competitors will be.
Putting Resources In Place
Fortunately, acquiring and deploying Big Data Analytics technology isn’t the
obstacle it once was—but some expertise is helpful. Find and/or designate an
architect to design your Big Data environment, which should include:
• Storage and management: Here you’ll take advantage of commodity
technologies, possibly implemented in the cloud, which can accept and
accommodate massive feeds of relatively unstructured data.
• Mapping and understanding: Some providers of Big Data “solutions” expect
you to complete this arduous task on your own, but it’s no longer necessary.
Some solutions include tools that facilitate and at least partially automate
this essential discovery and mapping process.
• Analytics: Not all Business Intelligence solutions are suitable for Big
Data. The right choice will be highly capable of both ad hoc, discoveryfocused analysis and efficient, ongoing measuring and monitoring. High
performance is critical, and solutions that are at least partially cloud-based
can provide data integration advantages along with the obvious scaling
pluses.
Note: we’ll likely see continued evolution in Big Data tools and techniques, as
well as with instrumentation tools and processes. Plan to dedicate resources
to follow, evaluate and deploy new assets as they become available.
Organizational Competency. Human resources matter here, too, so begin
immediately to build both a team and a culture within your organization.
Seasoned analysts accustomed to sifting through structured data may already
work with you or can be easily found. Rarer and less easily profiled are the
“explorers” who can work with unstructured data and identify what might be
valuable. Finally, those who will see the potential industry game changers
WHITE PAPER
The Big Data Opportunity
Big Data Analytics: A Tiered Approach
Many of the early Big Data successes
discussed here were made possible
by a ready source of information-rich
data that justified high infrastructure
costs. Most opportunities will require
more effort, with the need to cull
high-value information from widely
distributed, voluminous, unstructured
and information-poor data. The early
successes tapped rich, shallow veins
of precious material; most of us will
require a strip-mining approach
instead.
Fortunately, commodity architectures
(Hadoop, NoSQL, columnar databases)
give us cost-effective tools for these
large-scale sifting and filtering
operations. High-performance
databases and feature-rich analytics
and Business Intelligence solutions
can power the analysis of refined,
structured data.
hidden in your customer interaction data might come from any discipline
within your enterprise. Stay on the lookout for the “idea people” around you
and encourage them to focus on this important goal.
Creating a Feedback Loop
As your people, tools and processes ramp up, four ongoing activities will
emerge. Exploration and ad hoc analysis of interaction (and other relevant)
data will begin first (and never stop.) Next, as patterns are proposed, explored
and confirmed, they can be exploited with the more familiar modeling,
measurement and monitoring activities common in analytics.
Subsequently, intelligence from this ongoing analysis can serve as the basis of
any number of business activities, from forecasting to solution development
to marketing initiatives and beyond. And finally, each of these can be tracked
for success and ROI, then adjusted and optimized—along with the Big Data
Analytics that inspired them. This feedback loop achieves two goals: maximum
value from your Big Data efforts (as in market share, revenues, wallet share,
etc.), and input to ongoing efforts to discover and implement additional Big
Data strategies.
Next Step: Act Swiftly
In between, however, there’s a need
for tools that facilitate the process of
examining, refining and filtering large
pools of unstructured data stored in
commodity platforms. The complete
architecture most organizations will
need includes:
With the ubiquity of Internet and mobile technologies, virtually every
industry currently presents or will present Big Data opportunities of strategic
importance. Thanks to commoditized technologies, easier instrumentation
and affordable, cloud-enabled scaling capabilities, the playing field for
Big Data is nearly level for the first time, opening up opportunities even for
smaller and mid-sized organizations.
• Commodity architectures to store
unstructured data
• A toolset for refining and filtering
the unstructured data
• A high-performance database and
analytics platforms for managing
and leveraging the resulting,
refined (sometimes summarized)
data
Those organizations include your competitors—and you. Prudence and
opportunity both suggest moving quickly into your own Big Data initiative.
Yes, following behind the leaders has its advantages in some business
pursuits—but, as we have seen, Big Data isn’t one of them.
The relative scale of the “strip-mining”
(unstructured) operation and the
game-changing analysis of the
resulting, refined data will vary across
industries, the kinds of interaction
data available, and the Big Data
opportunities organizations choose to
pursue. But in every case, this tiered
approach—and the right tools to
enable it—will be a necessity.
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WHITE PAPER
The Big Data Opportunity
8
How Birst Enables Comprehensive Analytics On Any Scale
Drawing actionable insight from massive-scale, raw data demands
analytics technology with broader capabilities. Traditional analytics and BI
platforms work marvelously with limited amounts of structured data, but
aren’t designed to assist enterprises in assessing and exploring massive,
unstructured, information-poor data stores—the ones managed in commodity
environments with batch-oriented technologies like NoSQL and Hadoop.
Bridging the gap between these two classes of data and technology is the key
to efficiently, cost-effectively leveraging Big Data—but most BI solutions force
enterprises to build that bridge on their own. It’s a costly, time-consuming
task—and an unnecessary one.
Birst technology solutions combine all the elements of powerful, full-featured
BI— ETL, data warehouse automation, enterprise reporting, ad hoc query and
dashboarding—with innovative tools designed specifically to bridge this gap.
To achieve this, Birst taps the unique power of batch-oriented analytics tools
designed for large, unstructured data stores—combining it with traditional,
relational-based tools—to let analysts to explore that data through a more
structured, familiar lens.
The result? Enterprises more quickly and effectively extract maximum value
from their Big Data assets, and can more easily evolve and refine the Big Data
applications they create.
Birst solutions can be leveraged in rapid-deployment, low-cost Softwareas-a-Service (SaaS) mode or deployed on-premise as an appliance. For more
information on Birst’s end-to-end solutions for Agile Analytics on any scale,
contact Birst at 1-866-940-1496/+1-415-766-4800 (outside North America) or
visit www.birst.com.
Birst Inc.
153 Kearny Street
San Francisco, CA 94108
Call toll free: (866) 940-1496
Email us: info@birst.com
www.birst.com
About Birst
Birst is the leader in agile business analytics. It offers a single place to manage all of a business’ analytics and agility
to answer questions that span departments, data sources, and deployments—across both public or private Clouds.
Birst gives users the fastest way to answer their most pressing business questions—and then all the ones they didn’t
know to ask. At one-third the cost, time, and staff of traditional big BI, Birst brings the benefits of analytics and factbased decision-making to a much broader audience. For more information, visit www.birst.com.