Big Data Handbook - 8 Juy 2013

Big Data Handbook
How to Unleash the Big Data Opportunity
7/8/2013
By Lora Cecere
Founder and CEO
Supply Chain Insights LLC

Copyright © 2013 Supply Chain Insights LLC Page 1
Contents
Research...........................................................................................................................................................2
Disclosure..........................................................................................................................................................2
Executive Overview...........................................................................................................................................3
Is It a Big Data Problem?...................................................................................................................................5
What Is Big Data?..............................................................................................................................................6
Companies Focused on Clean Data Today Are in a Better Place.......................................................................7
The Opportunity...............................................................................................................................................10
Recommendations...........................................................................................................................................12
Conclusion.......................................................................................................................................................13
Appendix .........................................................................................................................................................14
Other Related Reports.....................................................................................................................................20
About Supply Chain Insights LLC ....................................................................................................................21
About Lora Cecere ..........................................................................................................................................21

Research
Data is piling up on corporate doorsteps. It is growing in volume, velocity and variety. New forms of data, in
combination with advanced analytics, offer a wealth of new possibilities. How do companies get started?
We want to help. The goal of this report is to break through the hype and understand where companies are on
their Big Data journeys. The recommendations in this report are based on survey data conducted online during
the period of May-June, 2013. The quantitative analysis is augmented by interviews with manufacturers and
retailers working on advanced analytic concepts. The overview of this study is shared in figure 1. For more
detailed respondent demographics, reference the additional charts in the Appendix.
Figure 1. Overview of the Big Data Study
Disclosure
This report was solely funded by Supply Chain Insights. The analysis is an independent and objective read of
the current market.
As a research firm, we are committed to Open Content research. These reports are intended for you to read,
share and use to improve your supply chain decisions. Please share this data freely within your company and
across your industry. As you do this, all we ask for in return is attribution. We publish under the Creative
Commons License Attribution-Noncommercial-Share Alike 3.0 United States and you will find our citation policy
here.

Executive Overview
The use of new forms of data is not an evolution. Instead, powering big data supply chains, and innovating
through new forms of analytics, is a step change.
New forms of data do not fit traditional architectures. Traditional supply chains were architected to use
structured data with software using relational databases. The big data era will make many of the investments
from the last decade obsolete.
Big data offers the opportunity to redefine supply chain processes from the outside-in (from the channel back)
and define the customer-centric supply chain. This is in stark contrast to the inflexible IT investments installed
over the last decade to respond inside-out based on order shipments. These traditional investments in
Enterprise Resource Planning (ERP), Advanced Planning Systems (APS) and traditional Business Intelligence
(BI) for reporting, improved the supply chain response, but did not allow the organization to sense, shape or
orchestrate outside-in. New forms of data (e.g., images, social data, sensor transmission, input from global
positioning systems (GPS), the Internet of Things, and unstructured text from email, blogs and ratings and
reviews) offer new opportunities. They also require new techniques and technologies.
Figure 2. Is Big Data a Problem or an Opportunity?
Big data offers new opportunities for the corporation to listen, test and learn, and respond faster. In this study,
companies see the greatest opportunity to use big data for “demand” (to better know the customer and improve

the response); however, actual investments are in “supply” not “demand.” Respondents view supply-centric
projects like product traceability (involving product serialization and traceability), supply chain visibility and
temperature controlled handling as important.
Is big data a problem or a new market opportunity? Like the respondents of this survey, we believe that big
data represents an opportunity for all. In the study, one-fourth of respondents currently have a big data
initiative. However, interest is growing. Sixty-five percent have or plan to have a big data initiative in the future.
Despite the hype, and the intensity of marketing rhetoric in the market, in our year-over-year studies on big
data we see very little change in activity.
Despite the fact that the IT group is more likely to see big data as a problem, 49% of those with a big data
initiative report that it is headed by an IT leader.
Big data represents a new opportunity, but seizing it requires a new form of leadership. It can ignite new
business models and drive channel opportunities. However, it cannot be big data for big data itself. Instead, the
initiatives need to be aligned to business objectives with a focus on small and iterative projects. It requires
innovation. To move forward, companies need to embrace new technologies and redesign processes. It is not
the case of stuffing new forms of data into old processes. In the survey, as shown below in the sample of
quotes from respondents, business leaders have a range of emotions. The path forward requires leadership.
People need a nudge to think beyond traditional data types and applications. Here are some quotes from
respondents in the survey:
Big data is a distraction at the moment. [Our] key challenge is how to automate useful
insight.
We have not explored this opportunity. Skillsets in supply chain and IT are limited.
This information can give companies a “heads-up” to help sense, analyze, and better
respond to market changes.
Data equals information and information equals profit.
In capitalizing on the opportunity, data-driven companies—focused on the use of analytics and clean data—
have an advantage. One of the first steps is to get good at managing data. In this study, we find that
companies that are more advanced in Master Data Management (MDM) are more likely to have a big data
initiative today.
Unfortunately, the term “big data” is the buzzword du jour. Due to the size of the prize, many consultants and
technology partners are hyping the concepts. We find that most technology providers and consultants use it in
their marketing pitches. Confusion reigns. To drive the opportunity, companies must bypass the hype. To help
readers, we share insights on how to navigate the hype and maximize the opportunity in the recommendations
section of the report.

Is It a Big Data Problem?
Today, most companies feel that they do not have a big data problem. While data volumes are growing, the
velocity of data is accelerating and the variety of data is increasing; the larger top-of-mind issue (as shown in
figure 3) is that companies cannot use the data that they have today. While they are intrigued about how to use
new forms of data to solve the issues of demand and supply volatility, few know how to get started.
Figure 3. Top Levels of Supply Chain Pain for the Respondents
Different forms of data offer a realm of new business challenges and opportunities. For companies new to
analytics, these data forms are often called “dirty” when they are really just “different.” They do not fit into
conventional relational database applications. The data often has different context and attributes. So while
people want to use new data forms, they struggle with how to get started.

What Is Big Data?
Let’s start with a definition. For the purposes of this study, big data is defined as data with a volume greater
than a petabyte coupled with a growing variety of data. A petabyte of data sounds like a lot of data; but, how
much is it really? A petabyte of data is 1024 terabytes. A terabyte of data is 1024 gigabytes. In more graphical
terms, a petabyte of data represents twenty million four-drawer filing cabinets filled with text or the storage of
13.3.years of HD-TV video. Twenty petabytes represents the amount of data processed by Google on a daily
basis. It also represents the total hard drive space manufactured in 1995.i
As shown in figure 3, companies cannot effectively use data today within their organization; and as will be
shown later in this report, they also do not have the levels of data volume that would qualify for the big data
definition used in this study. They are just beginning to understand and use the concepts. Those with a big data
initiative are more likely to consider their ability to use data to be one of their top business pains: 57% versus
38% for those without a big data initiative. As shown in figure 4, the concepts are emerging.
Figure 4. Currently Level of Understanding of the Concepts
So, where are we in the growth of databases? Do we currently have a big data problem? In our survey, 15% of
respondents report having a database that equals or is greater than a petabyte of data. In addition, another
28% of respondents expect to have a database this size within the next two years. Based on our interviews
with clients, these large databases are usually associated with customer and product data and the mining of

customer insights. It is less likely to be ERP. While ERP databases are growing, only 18% of the study
respondents currently have an ERP database that is more than 6 terabytes.
Figure 5. Current Database Size within the Corporation
Companies Focused on Clean Data Today Are in a Better Place
Respondents with a master data initiative are nearly three times more likely to have a big data initiative. For
most companies, Master Data Management (MDM) challenges are not new. MDM initiatives are ongoing.
Thirty-two percent of survey respondents currently have an MDM initiative, and 30% plan to have an MDM
program in the future.
In working with clients, we can clearly see that the understanding of MDM is more mature than the evolution of
big data concepts. Companies with maturity in MDM have a leg-up in the use of “different data”: the explosion
of data volume and types.

Figure 6. Survey Respondent Familiarity with Master Data Management
Figure 7. MDM Performance by Data Type

When companies focus on understanding data today and cleaning data for corporate use, as shown in figure 7,
they self-assess their ability to use reference data significantly higher than those who do not have an MDM
program.
Companies with well-established MDM programs understand the intricacies of data management better than
those that don’t. Traditional MDM techniques are problematic. Packaged approaches in ERP have not met
organizational requirements.
Companies with experience understand the needs for data context and attribution. They understand that the
problem is more complex than what can be delivered in one-to-one rules engines (Business Activity Monitoring
(BAM)) or the harvesting of unstructured data through Natural Language Processing (NLP). Instead, it requires
organizational discipline in the management of data and the combination of techniques found in emerging big
data analytics to meet the challenge. One of the barriers is that 49% of those with an MDM program report it is
headed by IT leaders. They struggle to get line-of-business vision and support.
Figure 8. The Relationship between Big Data and MDM Programs
When we hear the leaders of e-commerce speak on the use of data and their big data programs, they never
talk about the pain of MDM. Their work with cognitive learning and advanced analytics support the belief
statement in figure 8. We believe, based on interviews with big data leaders, that the approaches with big data
help to solve some of the historic and legacy issues of MDM.

The Opportunity
Big data investments are just starting. Over one-third of respondents in the study consider it one of the top
three supply chain trends. Today, as shown in figure 9, 37% percent of respondents plan to have a big data
initiative and 28% percent have a big data program today.
Figure 9. Current State of Big Data Initiatives
Big data initiatives are in their infancy. We are at the starting line. The big data opportunity is seen in “demand.”
The areas of demand management, order management, price management and channel sensing, as shown in
figure 10, rate the highest in terms of areas to benefit from big data. However, as shown in figure 11, the
highest importance is placed on “supply-based initiatives.”

Figure 10. The Big Data Opportunity
Figure11. Importance versus Performance of Current Types of Data

One of the barriers to capturing the big data opportunity is the “definition of supply chain.” When the supply
chain is seen as a “function”—versus an end-to-end process from the customer’s customer to the supplier’s
supplier—the organization is more likely to move forward with big data projects as a functional program.
Recommendations
The term big data is “hot,” and will get “hotter,” as companies realize the opportunity. As companies mobilize
for the future, we offer these recommendations:
Avoid the Hype. If a vendor or a technology consultant comes in and shares a slide on how their solution
helps with big data, ask them, “What do you mean by big data? And how does your solution help to solve the
problems to harvest the big data opportunity?” In parallel, drive change in the organization by facilitating and
elevating discussions on analytics and the use of data. Any time there is an internal discussion on “big data,”
ask for the definition and try to “ground the discussion in reality.” Is it a big data opportunity because the data is
different? Or is it a big data opportunity due to the volume and velocity of data?
Focus End-to-end. Build a Cross-functional Team. Big data offers a wealth of opportunities. It enables
market sensing, consumer listening, test and learn strategies, new forms of visibility and safe and secure
supply chains. It is an opportunity to use new data forms and emerging analytics to build processes outside-in
from the customer back. This can best be accomplished when there is a team of IT and line-of-business
leaders that can work cross-functionally with a focus on end-to-end processes. This team is best led by a line-
of-business leader and is guaranteed a higher level of success if it does the following:
• Sidestep Religion. Do not get entangled in religious arguments of supply chain as a function or an
end-to-end process.
• Start Small and Iterate. Do not get caught up in the ERP-like mindset of big projects with a series
of releases. Focus on small wins and use the learning from the use of analytics to spread to other
functions. For example, the use of in-memory reporting from QlikView and visualization from
Spotfire and Tableau are being used by a number of our clients to improve data usage today to
power organizational support of funding for big data initiatives. Organizations have many
technologies and systems and need to free the decisions for analytics from the decisions being
made on their systems of record implementations (ERP). ERP is only one source of data, and over
time, will become a less significant contributor to the overall response.
• Provide Innovation Funding. Give these teams innovation dollars to innovate for the company.
Some companies have had success with having departments submit requests for consideration for
innovation spending on analytics and the use of different data forms by cross-functional teams
working on big data initiatives.

• Consolidate Business Intelligence Centers of Excellence and Master Data Efforts into Big
Data Initiatives with a Goal to Serve the Business. Organizations that are good at using data will
win in driving big data opportunities. The goal needs to be on solving business problems through
the harnessing of the cross-functional efforts of knowledgeable people working on teams to solve
data and analytical problems and opportunities.
Conclusion
Big data is more of an opportunity than a problem. Companies need to mobilize now to build new processes
and differentiated services. The focus needs to be on what the end-to-end supply chain can be. To do this,
companies need to free themselves from the limited definition of what it is today. As a result, some
organizations are calling it the “digital supply chain.”
It is a great opportunity to build processes outside-in and harness new channel opportunities. It is also critical
to meet new supply chain challenges for safe and secure and temperature compliant supply chains. It is
foundational for digital manufacturing and solving the tough issues of Corporate Social Responsibility (CSR).
The possibilities are endless. It starts with thinking about how to use different data in a differentiated way.

Appendix
In this section, we share the demographic information of survey respondents. The respondents answered the
survey questions of their own free will. There was no exchange of currency. The only offer made to stimulate a
response was to share the survey results in the form of Open Content research at the end of the study.
The names of those that completed the surveys are held in confidence, but the demographics are shared to
help the readers of this report gain perspective on the respondents. The demographics supporting these
figures are found below in Figures A-L.
Figure A. Survey Respondents by Type of Company

Figure B. Breakout of Respondents by Industry
Figure C. Survey Respondent Demographic Data on Company Size

Figure D: Geographic Respondent Information
Figure E: Respondent Demographic Information by Role

Figure F: Respondent Leadership of Big Data and Master Data Management Initiatives
Figure G: Supply Chain Trends

Figure H: Companies with a Master Data Program are Three Times More Likely to have a Big Data Initiative
Figure I: Big Data Initiative Leader

Figure J: Size of Largest ERP Live Instance and Number of Unique IT Software Systems
Figure K: Current State of Master Data Management Programs

Figure L: Master Data Management Program Leader
Other Related Reports
The Art of the Possible: Actionable Analytics for Value Networks
Big Data – Go Big or Go Home?

About Supply Chain Insights LLC
Founded in February, 2012 by Lora Cecere, Supply Chain Insights LLC is focused on delivering independent,
actionable and objective advice for supply chain leaders. If you need to know which practices and
technologies make the biggest difference to corporate performance, turn to us. We are a company dedicated to
this research. We help you understand supply chain trends, evolving technologies and which metrics matter.
About Lora Cecere
Lora Cecere (twitter ID @lcecere) is the Founder of Supply Chain Insights LLC and the
author of popular enterprise software blog Supply Chain Shaman currently read by 5,000
supply chain professionals. Her book, Bricks Matter, (co-authored with Charlie Chase)
published on December 26th
, 2012, and her second book, Metrics That Matter, will publish
in 2014.
With over nine years as a research analyst with AMR Research, Altimeter Group, and
Gartner Group and now as a Founder of Supply Chain Insights, Lora understands supply
chain. She has worked with over 600 companies on their supply chain strategy and speaks at over 50
conferences a year on the evolution of supply chain processes and technologies. Her research is designed for
the early adopter seeking first mover advantage.
i
How Much is a Petabyte of Data? Mozy Blog, http://mozy.com/blog/misc/how-much-is-a-petabyte/

Big Data Handbook - 8 Juy 2013

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