This document provides an overview of a research package on big data in the supply chain and logistics industry from eft. It includes: - Interviews and presentations from industry experts on the biggest opportunities in using big data. - A survey of over 200 supply chain executives on their use of big data. - An article on using sensors and the "Internet of Things" to gain insights from real-time supply chain data. The package explores how companies can leverage big data and analytics to improve visibility, flexibility, optimization, collaboration and control across their supply chains and gain competitive advantages. It highlights specific areas like risk management and predictive analytics that big data is enabling.

1. Big Data
Package
2014
In a world where everyone has the capability to leverage machine potential and maximize human
productivity through the use of big data, how can the logistics and supply chain industry take ad-
vantage of this game-changing phenomenon and use it as a competitive advantage? Explore this,
and more, in this comprehensive research package from eft:
 3 exclusive interviews and presentations with the industry experts, exploring the biggest op-
portunities in big data
 Industry analysis from the recent big data survey of over 200 supply chain and logistic execu-
tives
 Snapshot into Lora Cecere’s latest research on supply chain big data
This research was conducted in conjunction with the 5th Annual Chief Supply Chain Officer Fo-
rum, taking place in Amsterdam, November 18-20

2. Table of Contents
I. Introduction
Introductory comments from Jan-Willem Adrian, VP Strategy & Business Development Supply Chain
& Logistics at QuartetFS
II. Interview with Fred Hartung, VP Supply Chain at Jabil on the future of big data, wearable tech and
where you can get your greatest supply chain ROI
III. Presentations
a) The Big Data Opportunity - presentation by Lora Cecere, Founder and CEO of Supply Chain Insights
b) Big Data for Competitive Advantage - presentation by Richard Sharpe, CEO at Competitive Insights
IV. Webinar: Big Data—Using Analytics for Intelligent Decision Making
V. Article by Dr Steve Brady, CEO at Supply Chain Innovations Today: Internet of Things
VI. Big Data in the Supply Chain Infographic
VII. Recent big data research from the global eft survey featuring the responses of over 200 supply chain
and logistics executives
VIII. Conclusion

3. I. Introduction
By Jan-Willem Adrian, VP Strategy & Business Development Supply Chain
& Logistics at QuartetFS
Supply Chain Execution
Getting products to your customers is critical to your organization. Your goods have to be there on time,
in full and you require visibility and control over the entire process.
Nowadays, in fast moving industries, making ‘the right’ decision is not good enough. You have to make the
right decision at the right time. Having near real-time data is key in this process, as it means that source
systems and the operational intelligence platform have the same data.
Envisage knowing the inventory level across your business, the status of orders in process, the latest de-
mand forecast, the exact amount of goods in transit, the latest transport status of a specific container,
whenever you need to know. Instant-decision making and real-time logistics solutions will empower manag-
ers and organizations with accurate information in order to capture a time-sensitive opportunity or avert-
ing a major impact. This will lead to enhanced decision making, improved service levels and a reduction in
overall costs & risk.
Therefore you if you want to create an agile and resilient supply chain your company needs to focus on five
key areas:
Visibility: The ability to monitor supply chain events and patterns as they happen, which lets companies
proactively—and even pre-emptively—address problems. Critical enablers:
 Aggregating data from multiple sources in real time
 Custom user defined dashboards.
 Source system and operational intelligence platform have the same data
Flexibility: Being able to adapt to problems quickly, without significantly increasing operational costs, and
make rapid adjustments that limit or maximize the impact of decisions. Critical enablers:
 Multi-dimensional analysis with drill down & drill through to the lowest level
 Ability to drill down to the lowest level of data to identify root cause.
 Freedom of analysis for the user

4. Optimization: In order to make the supply chain more efficient, companies have to continuously opti-
mize their supply chain by analyzing e.g. costs, efficiency, stock holding, warehouse / transport capacity and
many more based on the latest demand forecast and trends. Critical enablers:
 What-if simulations
 Complex calculations
 Instant decision making
Collaboration: Allow companies to work closely with internal & external supply chain partners & cus-
tomers to identify risks, opportunities and/or avoid disruptions. Critical enablers:
 Multi-dimensional analysis
 Sharing findings across internal and external platforms (unlimited users)
Control: Having policies, monitoring capabilities, and control mechanisms that help ensure that proce-
dures and processes are actually followed. Critical enablers:
 Ability to create KPIs & limits with a real-time alert notification and an escalation workflow when
thresholds are breached across the various levels in the supply chain
 A single platform that can be used across the entire organization; from the lowest operational level all
the way to the highest strategic level.
In summary: Real-time Supply Chain visibility = real time results

5. II. The Future of Big Data; Wearable Tech and Where You Can Get Your Greatest Supply Chain ROI
Fred Hartung is responsible for events planning, capacity planning, production planning, inventory con-
trol, supply chain solution & tool development, along with logistics and trade compliance, for Jabil.
At eft, we’ve conducted research and found that 40% of participants were not implement-
ing big data analytics to enhance their supply chain operations and 30% were looking into it.
Any surprises there to you?
Not surprised at all, we personally are well along the path. We actually set up business intelligence tools
about three or four years ago off our dashboard, which we actually called an ‘amp metric’ (actual meas-
urable proactive). We would go through our data and automatically identify the opportunities or issues
and we would quantify how to solve them. Then with the advent of big data in the last couple years it’s
been much more feasible to really do across the whole enterprise, as well as extend that to suppliers
and our customers. We’ve actually developed our control tower platform (which is really a platform
with a lot of different applications for risk, operations, manufacturing) and it’s a competitive differentia-
tor for us.
Most companies don’t really know how to get started, one of the ways we feel was successful is that we
didn’t go through IT. Instead we hired business people that were interested in solving issues and they
also happened to be programmers. We put them with functional experts to get a quick, rapid develop-
ment. What we use IT for is to understand the architecture that we should use, ensure we have the
right security in place, as well as staying on top of technology. Technology is really moving into a com-
modity space and there are so many different applications that are going out of this. The key thing is to
be able to keep putting things out there but making sure that your infrastructure and architecture allows
you to move in multiple directions.
With big data, it’s easier to make a tenfold improvement than 10% improvement. With big data, you can
make disruptive changes to your supply chain and from that standpoint I’m very confident of the benefits
we will get moving forward.
What key supply chain areas do you think the focus should be in?
Certain risk management identifications and proactive minimization of risk. We now have visibility of all
parts of the supply chain, through data you can manage and understand what your exposures are and get
them before they turn to smoke, let alone a fire. A big aspect that we’re also looking at is in terms of
‘instruction data’, using tweets for product introduction and market feedback.
What is your take on wearable tech, where do you see its future?
Wearable tech is big for a lot of customers but there are different applications for wearable tech. The
best example is with the health & fitness bands, so you can monitor what your heart rate is, what your
blood pressure is etc but the next step is through telemetry, which is very cheap now. You can now
monitor whole populations and understand what health trends are and what’s actually going on with
people. That was impossible in studies before.

6. III. Big Data Presentations
At last year’s Big Data in the Supply Chain event Lora Cecere, Founder and CEO of Supply Chain In-
sights gave an interesting presentation defining key concepts and sharing insights to help leaders better
understand how big data strategies can help solve problems in today's supply chain.
See the full presentation here

7. III. Big Data Presentations
How do you establish efficient ways to use "big data" to drive fact-based decisions that continually impact
financial performance? Richard Sharpe, CEO at Competitive Insights shares his unique insights as to how
supply chain industry leaders are tackling this problem cross-functionally and how having this capability is
providing an ongoing competitive advantage.
See the full presentation here

8. IV. Webinar: Big Data—Using Analytics for Intelligent Decision Making
Lora Cecere, Founder and CEO of Supply Chain Insights reveals her latest findings on supply chain big
data in this 10 minute webinar.
Lora discusses:
 The top 3 areas of supply chain management pain in big data terms
 Definitions of structured data, unstructured data, sensor data and new data types and what these
terms mean for your operations
 Big data plans and expectations of supply chain executives
 The state of current IT operation systems
See the full webinar here

9. V. Internet of Things by Dr Steve Brady, CEO at Supply Chain Innovations Today
The “Internet of Things” has been a topic of discussion for several years now and, like so many of the innovative
topics this column will discuss, can mean different things to different people.
We have heard how your refrigerator will “tell” you when you need to buy more milk, or how using the NEST
Thermostat will save you money and improve the comfort of your home. Or, for those more interested in “big”
ideas, sensors embedded in the road help find parking spaces or as part of a network designed to measure traffic
along the highways. In fact, this NPR story highlights one city in Europe that has installed sensors to
“measure everything from air pollution to where there are free parking spaces. They can even tell garbage collec-
tors which dumpsters are full, and automatically dim street lights when no one is around.”
The central theme throughout the discussion though hinges on the two key points: the interconnectedness of the
sensors, and the ability of the sensors to provide data that can be used to inform decision making.
As supply chain experts we have already been engaged in the use of sensors as central to our decision making pro-
cess. Over the past 20 years or so we have applied cameras and weight sensors to the manufacturing process for
quality control, used bar-code readers tied to automated systems for package sorting, and hand-held readers for
package delivery. Sensors give us “in transit visibility” throughout the shipping process, and provide early detec-
tion of maintenance problems on many of our most expensive MHE and transportation assets. Of course, the
implementation of each of these technologies requires extensive capital investment and generally provides data
through stove-piped, proprietary systems. The “big dogs” can play--and no one else.
We are about to see an explosion of innovation in sensor technology that, when applied judiciously, can be truly
disruptive and move us another step towards a more level playing field between small, medium and large business-
es.
New startups are developing and selling sensors that are priced not in the tens, or hundreds of thousands of dol-
lars, but are instead only a few hundred dollars. Wunderbar is a start-up with the novel approach of “breaking
off” sensors as you would candy off a candy bar. The sensors use BlueTooth technology to talk to one another
and to the “main” board which then uses wifi to move information up to “the cloud.: They will be selling these
“suites” of sensors for less than $200, making them quite attractive for small businesses. Other tools are following
in their wake that can open up the discussion for just what can be measured, what should be measured, and what
can we do with the data?
Of course, they come with one essential trade-off: these tools come without solid “off the shelf” applica-
tions. Over the next few columns I will be exploring the possibilities that open up with these sensors, and seek to
not only answer the questions of what can and should be measured, but also point to ways that with a little elbow
-grease smaller players in the market can start to gain leverage by collecting the data they are already creating--
and then using that leverage to gain efficiencies and market parity, if not leverage.
Internet of Things, and connected processes need no longer be the playground of only the big dogs.
As mentioned, the “internet of things” (IoT) is more than just having “smart” devices. There are many devices
and appliances that have intelligence built into them. Take the iRobot’s line of products, including the Room-
ba. This is a robot that learns about your house and vacuums your floor. This is an “intelligent” device, but isn’t
(at least not at this writing) connected to the outside world. What makes the “internet of things” truly revolu-
tionary is the connection of the device to the larger world through wifi, or bluetooth, or other connectivity ap-
proaches.
How can small businesses begin to leverage these technologies? I propose that we begin to “think differently”
about how we manage our businesses, and look to see what questions we have always wanted to have answered,
but never seemed to have the data to answer the question. Sometimes answering the question would be too ex-
pensive, and as a friend would say “the juice isn’t worth the squeeze.” But often, if one could answer the ques-
tion, it could lead to significant benefits and competitive advantage.

10. For example, let’s consider a florist. Perhaps the most important and costly single expense for a florist is the walk
in cooler. Properly controlled temperatures can extend the useful life of fresh-cut flowers significantly. In fact,
the range of acceptable temperatures is actually quite narrow (ideally 33-35 degrees F.) The impacts of higher
than normal temperatures lead to a higher respiration rate, and faster water consumption shortening the life of
the cut flowers.
The impact of shorter lifespans of flowers are obvious:
 increased cost of spoilage to ensure a sufficiently wide assortment
 carrying less inventory to reduce spoilage risking lost sales by not having what the customer wants
 customer dissatisfaction from a significantly shorter life of the flowers and arrangement delivered.
Imagine if the florist could exercise tighter control over the environmental controls--the longer lived flowers, cou-
pled with the ability to offer a wider selection with greater life-spans of floral bouquets certainly could provide an
advantage in business. So here is where the “internet of things” steps in. Of course coolers have always had ther-
mometers inside them. I worked at a local florist to earn extra cash during the holidays while in high school, and
we were regularly checking the temperature in the cooler. But imagine…
Imagine a sensing system that once installed will notify the florist (by email, text, or even a robocall) when the
temperature is “out of specification” for a set period of time, and during specific times. The system could be set
to text the owner any time during non-business hours when the temperature is too warm or too cold. Perhaps
this is an indication of a door left open, compressor failure, or a power outage--assuming the IoT system is on a
battery backup. That could mean the difference between a significantly shortened life of the product or continued
business success.
But wait--there’s more! The coolers should also maintain a high relative humidity, in the range of 90-95%. a Hy-
grometer sensor can notify the owner when the humidity falls out of specifications.
Now, perhaps the problem is simple--the door was left open and the cool (and damp) air has been escaping. Then
a proximity sensor to detect the status of the door would be helpful allowing the owner to quickly assess the
problem. On the other hand the problem could be more complicated, and could include a failure of the compres-
sor motor.
This is where this moves from simply interesting to being quite useful when sensors are applied in other locations
as well. For instance, vibration and temperature sensors could be placed on the the cooling compressor mo-
tor. The data being provided by these sensors, combined with the performance measures of temperature and
humidity, can provide insights into the health of the cooling system itself.
The vibration sensor can not only track the operating of the compressor, but also the duration it is running and
any change in the performance (increased vibrations, or decreased.) In this way, the sensor data can begin to
track changes in performance before the potential catastrophic outcomes of poor temperature control.
This example, while limited to one type of small business, serves to show the ways sensors can be used to moni-
tor crucial aspects of a business that perhaps were unable to be closely monitored before, usually because of a
lack of technology, or because of the high costs associated with implementing the technology. Both of the barriers
to problem solving are disappearing quite quickly.
Having sensors throughout the establishment reporting on the critical measurements in real-time can lead to sig-
nificant dollar savings, potential improvements in product offerings, and avoidance of possible catastrophic
events. A well designed dashboard integrating the measures, with appropriate heuristics in place to provide the
“expert analysis” that traditional small business owners normally would be unable to perform, can really enhance
their operations.
But this is not the limit.

11. It’s not a big step to realize then that, once data is being collected on systems and used to drive decisions at a lo-
cal, or retail, level, the data may actually prove beneficial to others as well.
In the example of the florist, the cooler has sensors in place and software designed to report any deviation from
performance (temperature, humidity) that might shorten the life of their flowers. Additionally, the sensors can be
placed to help diagnose the cause of the deviation (door, compressor failure). The sensors, internetworked and
providing analysis, allows the owner to correct the problem. The owner can now also determine the projected
life of the flowers and adjust pricing and sales to ensure the product moves. This is not much different than they
do now (as do bakeries, or any other business with a perishable commodity.) The additional data simply adds a
level of intelligence to their decision to reduce spoilage.
The next step is to share that data. First, it makes sense to share performance data with the manufacturer of the
cooler. As a manufacturer that data can prove quite useful for diagnosing problems long distance before sending a
technician out. Based on the sensors discussed in the last article, it is possible to know whether the problem is a
compressor, or perhaps a seal, or simply that the door was left open. Remote diagnostics, and the ability to plan a
maintenance event before arriving on site, can bring significant benefits to operations and the bottom line.
Perhaps even more beneficial is the idea of “prognostics” or, predicting the future.
Imagine the manufacturer having sensors on not one, but perhaps 50, or 100 compressors and coolers in a re-
gion. If the sensors are reporting back the performance of the coolers the manufacturer can, over time, start to
track the performance characteristics of their products. As failures are reported, they can pore over the data pri-
or to the events and, as more data is aggregated, discover trends.
This aggregated data supports what is known as “Prognostics” or using data to identify key indicators that precede
a failure. Many firms in the transportation industry, from trucking to rail to aviation, already makes extensive use
of sensors to monitor the health of their fleet. Prognostics (the ability to forecast future failures and avert them)
plays a key role in “Preventative maintenance.” Of course, the transportation systems all require significant up-
front investments either by designing in the sensors from the start or retrofitting existing fleets at substantial
costs.
The manufacturer can now identify potential failures, reach out, and schedule maintenance before a catastrophic
failure can potentially wipe out the whole inventory of a small business.
We are discussing something different. In this “brave new world” of empowered small businesses, the local retail-
er or small business can implement sensors that can make a direct improvement on their operations. They can,
through sharing their data, improve not only their system’s operations but can contribute to a stream of data that
lets their manufacturer improve service and improve their product.
But wait--there’s more! What happens when these affordable sensors, that are sharing data, are embedded
throughout the value chain? That is the next issue...

12. VI. Big Data in the Supply Chain Infographic

13. VII. eft Research
Recent eft research surveyed over 200 supply chain and logistics executives, exploring the use of big data
and its potential for the industry. One primary area of the study was to gain understanding on where
companies can find the greatest supply chain big data ROI and which functional supply chain areas they
are currently applying it to. Over 3/4 of those surveyed revealed that they were using big data to in-
crease visibility internally, as well as with their suppliers and customers. There is no question that with
more transparency companies are better positioned for real time decision making and superior overall
operational performance. The executives also highlighted the use of analytics in their supply chain risk
strategy, taking advantage of such information to anticipate issues and enable early intervention.

14. When questioned which areas they expected to yield the greatest ROI, executives highlighted ‘to in-
crease visibility’ and ‘to enhance demand planning capabilities’ as their top choices. Making the move
from historical to predictive analytics in terms of planning structures allows for an extra layer of insight
into supply chain.

15. The survey went on to explore the greatest challenges related to supply chain big data implementation,
with ‘integrating big data solutions with current systems’ emerging as the biggest pain point. Further-
more, over half of those surveyed indicated that it was understanding which data they should be collect-
ing and interpreting posed significant problems. The development of data analytics teams has aided com-
prehension but it is clear that the availability of so much data needs adequate tools, people and process-
es to be effectively ‘cleaned’ and utilised.

16. VIII. Conclusion
In a world where everyone has the capability to leverage machine potential and maximise human produc-
tivity through the use of big data, how can the logistics and supply chain industry take advantage of this
game-changing phenomenon and use it as a competitive advantage?
Big data initiatives, like other disruptive technologies, require a cultural shift within your business. Hiring
the right people is crucial but what type of professionals do you need? Should the overall strategy of big
data in the supply chain be left to statisticians, IT executives and data scientists? Although they are an
essential component, it seems imperative that supply chain takes responsibility and drives this change.
Once the right people are in place, the next key steps centre around which of the latest big data technol-
ogies you should be investing in. Should a cloud based infrastructure, open source software framework,
vertical application or massively parallel-processing (MPP) database be the priority? Do you already have
platforms in place that you can take advantage of?
As highlighted throughout the pack, using predictive analytics to increase supply chain visibility was the
number one application of big data for supply chain executives. There are clear advantages from work-
ing with your suppliers to promote big data initiatives on a collaborative level. It is crucial to engage
your partners by demonstrating the customer service and flexibility benefits of data collection pro-
grammes with an overall goal to mutually increase supply chain efficiency. Determining which data you
should be collecting and prioritising in light of the operational and strategic challenges you are facing can
change the face of the way you (and your partners) do business.
Despite all these evident advantages, is investment in big data initiatives and high-level, expensive analyt-
ics tools a waste of money? Can big data provide the true value it promises? Companies need to ensure
that they have the foundations in place to embark on such a transformation, as well as a true sense of
the results that big data is going to deliver.
Big data is becoming everybody’s business, but is it yours?

17. It’s clear that big data can transform your supply chain through streamlining processes, improving end-to-
end visibility and accelerating performance. However is investment in big data initiatives and high-level, ex-
pensive analytics tools a waste of money? With this in mind, the Chief Supply Chain Officer Forum, taking
place in Amsterdam on November 18-20, will be exploring the power of big data and it’s impact on the
supply chain.
The forum brings together around 300 senior supply chain and logistics executives from the logistics and
supply chain industry. The event will explore the impact of disruptive technologies, but that’s not all. Omni-
channel retail, advanced planning and S&OP, supply chain transformation and doing business in SE Asia and
the Middle East are some of the other topics on the table for discussion. Just take a look at some of the
executives who are sharing their knowledge on these subjects:
 John Allan, Chairman, Dixons Carphone plc
 Chris Tyas, Group Head of Supply Chain, Nestle
 Ivanka Janssen, Director Global Route to Consumer, Diageo
 Mick Jones, VP Global Supply Chain, Lenovo
 Patrick Rainforth, VP Distribution, Johnson & Johnson
Join the discussion! Senior supply chain executives working at a manufacturer or retailer can join the
event with a complimentary pass. Contact Sophie Farrow (sfarrow@eft.com) or head online to
www.cscoforum.com/eu for more details.