KEMBAR78
Mobile, Wearables, Big Data and A Strategy to Move Forward (with NTT Data Enterprise Services, Inc.) #BarcodingEF4 | PDF
To know or not to know, that - is no 
longer an option!
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
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
The Data Explosion
Megatrends Driving Significant 
Profile Shifts
Growth of Everything
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
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
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
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.”
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
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
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
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
Big Data – Maturity Model 
Source: SAP Big Data Maturity Model
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
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
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
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

Mobile, Wearables, Big Data and A Strategy to Move Forward (with NTT Data Enterprise Services, Inc.) #BarcodingEF4

  • 1.
    To know ornot 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.
  • 5.
  • 6.
  • 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