Join NTT Data Enterprise Services, Inc.for a discussion on the Internet of Things (IoT), wearables, augmented reality, predictive analytics, and a strategy for using Big Data effectively in your enterprise. Presented at the Barcoding, Inc. Executive Forum 2014

1. To know or not to know, that - is no
longer an option!

2. Agenda
• Innovation
• Technology Solutions
– How Mobile Changed Everything!
– Wearables and Augmented Reality
– Big Data and Predictive Analytics
• Big Data Maturity Model and The Journey
• Actionable Strategy

3. Agenda
• Innovation
• Technology Solutions
– How Mobile Changed Everything!
– Wearables and Augmented Reality
– Big Data and Predictive Analytics
• Big Data Maturity Model and The Journey
• Actionable Strategy

4. The Data Explosion

5. Megatrends Driving Significant
Profile Shifts

6. Growth of Everything

7. Agenda
• Innovation
• Technology Solutions
– How Mobile Changed Everything!
– Wearables – Augmented Reality
– Big Data and Predictive Analytics
• Big Data Maturity Model and The Journey
• Actionable Strategy

8. How Mobile Changed….
Everything
• Asset intensive industries were out in
front of the mobile curve
• The process was cumbersome as any
analysis or additional information
required connection to the back
office
• In certain industries, this extended
cycle produced longer downtimes
and lowered the return on
investment (ROI) on those very
expensive assets
Source: Fieldconnect

9. How Mobile Changed….
Everything
• Smart devices and Mobile technology
provides right real time information to the
field service technician
• Technician can visualize the work
instructions in 3D and can perform the job
• If the job requires new part technician can
research the options and initiate purchase
request
• Mobile access to analytical data provides
technicians knowledge of what is going on
at the shop-floor level so they can assess it
against historical or benchmark data and
optimize asset performance

10. Wearables – Augmented
Reality
• “The market for company-provided wearables
will be larger than the consumer market within
the next five years, as wearables represent the
next phase of the mobile revolution.” –
Forrester
• Within Wearables smart glasses, has huge
potential for any workforce that could
benefit from access to hands free
computing.
• The next wave is having the right analytics
presented to the right user instantly, rather
than requiring a query. This is the thinking
behind the concept of “augmented reality.”

11. Wearables – Augmented
Reality
• A service technician can scan an item and
instantly know all of its technical data,
including the equipment number, the status
of the asset, and more. The technician can
be simply guided there by a system that
uses both facility and GPS data
• The key to the effectiveness of augmented
reality is the presentation of data. With so
much data available, important analytics
and its presentation is critical
• Handsfree actionable insight will help make
better business decisions and improve
worker productivity

12. Big Data – Predictive Analytics
• The explosive growth of social media,
mobile devices, and machine sensors is
generating a wealth of data that either
didn't exist or wasn’t accessible a few years
ago
• Until now analytics was used to simply
access huge sets of data that might have
been aggregated for reporting purposes
• New Analytics applications based on in-memory
computing, advanced models and
predictive algorithm can facilitate instant
access to actionable knowledge in seconds

13. Big Data – Predictive Analytics
• Asset-intensive industries can employ
predictive maintenance strategies that
increase uptime and speed ROI on assets
and equipment
• Sensors track a machine’s performance,
provide an alert when the machine’s
performance dips below a threshold
• But predictive analytics can forecast the
machine’s condition, which reduces
downtime and improves safety
• Analysis on the machine’s uptime and
performance quality can then be integrated
into the product design to improve the
next generation of machines

14. Agenda
• Innovation
• Technology Solutions
– How Mobile Changed Everything!
– Wearables and Augmented Reality
– Big Data and Predictive Analytics
• Big Data Maturity Model and The Journey
• Actionable Strategy

15. Big Data – Maturity Model
Source: SAP Big Data Maturity Model

16. Big Data – Journey
Niche Intentional Strategic
Business Impact
Lighthouse
Champion
Change Agent
Big Data Maven
Strategy emerging from experience
- Silo’d stages: No Big Data
business programs, seen only
as technology programs
- No specific skills, executive
audience,
- Big Data projects across
business
- Understanding and
managing Big Data insights
- Emerging coherence in Big
Data architecture
Competency Center. Big
Data Governance.
- Integrated stages: Data
drives continuous
Business innovation
- Analytic insight optimizes
processes and is often
automated
- Rapid capability enabled
by centralized platform,
uniform standards and
procedures

17. Agenda
• Innovation
• Technology Solutions
– How Mobile Changed Everything!
– Wearables and Augmented Reality
– Big Data and Predictive Analytics
• Big Data Maturity Model and The Journey
• Actionable Strategy

18. Key Considerations
• Involve Business upfront
– What tangible benefits can big data initiatives provide my organization?
– What is the ROI for a big data initiative?
• Fire Bullets not Cannons.
– Pick something that's manageable. Start on a small scale to prove your
hypothesis.
• Useful Data can come from anywhere (and Everywhere)
– What data should you consider?
– How is data captured?
• You will need new expertise for Big Data.
– Big Data relies on data modeling and data science

19. Big Data Strategy
Purpose Opportunity Assessment Strategy Definition
q Understand current state
Ø Where is Big Data
Analytics being used
today?
Ø What technology,
application and providers
are being used?
Ø How is Big Data evaluated
for productivity and cost
effectiveness?
q Rethink and Re-engineer Business
Model
Ø What jobs can be done more
efficiently with Big Data
Analytics?
Ø What standard applications are
available from vendors?
Ø How are competitors using Big
Data Analytics?
Ø What are quick wins for the
new applications?
Ø How will the data driven
organization look and work?
q Standards and Technology
Provisioning
q Security Practices
q Data Management System