Big Data and Analytics in M2M

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1 Big Data and Analytics in M2M May 2014 Dan Shey Practice Director M2M, Enterprise and Verticals

2 M2M/IoT Value Chain Value Chain Hardware* Connectivity** Value-Added Services 2012 $1.4 $0.3 $10 $2.5 $30 - $50 $8 - $12 Worldwide North America Worldwide North America Worldwide North America 2018 $4 $1.3 $25 $6 $80 - $120 $20 - $30 Worldwide North America Worldwide North America Worldwide North America Value- Added Services Connected Device Platform Device Management Device Connectivity Device Cloud Application Development System Integration Analytics Professional Services Application Enablement Platform * Chipsets and modules ** Cellular, Fixed, Satellite

3 Customer Evolution Hardware Connection Connection Management Device Intelligence Device Cloud Applications Services M2M Value Chain Gateways, Routers, Modules CDP Platform (cellular) Agents Scripts Protocol Conversion Data Mngmt Basic Analytics Device Mngt Development System Integration APIs Consulting Project Mngmt Analytics Data Needs Low Volume Event Alerts High Volume Predictive and Prescriptive Analytics Stakeholders Partners Business Unit Device OEM Multiple Stakeholders Internal, External Market Segment B2B B2C B2B2C Services and Offers Enhanced Support Services SLAs, Warranty Management, Product-AAS, New Services

4 M2M/IoT Big Data and Analytics Three phases of analytics: Descriptive and Diagnostic Predictive Prescriptive Five leading use cases: Predictive Maintenance Product/Service Development Usage Behavior Tracking Operational Analysis Revenues $1.9 $14 Contextual Awareness

5 Big Data and Analytics Suppliers: White Space Data Integration & Data Visualization First-Stage Predictive Analytics Machine Learning ALL COMPANIES Hedge funds pricing optimization Credit card providers customer rating Real estate portfolio-risk management Pharmaceuticals drug research Transport fuel-cost reduction Agriculture yield optimization Oil and gas field exploration Energy distribution smart-grid operation Manufacturing predictive maintenance Construction building-site safety and so on and so forth

6 Big Data and Analytics Supplier Demographics Data Storage Supplier Segmentation Data Visualization Data Integration Predictive Analytics Machine Learning Established Suppliers Start-ups Industries and Applications Finance Hedge funds pricing optimization E-commerce Credit card industry customer risk scoring Media Social media activity matching to transaction and web-clicks Oil and gas field exploration Energy Cloud and Data Center Leaders Energy distribution smart grid operation Real estate portfolio risk management Pharmaceuticals drug research Transport fuel cost reduction Agriculture yield optimization Energy distribution smart grid operation Data centers cooling system predictive maintenance Manufacturing predictive maintenance Manufacturing - yield optimization Distribution inventory management Healthcare heart disease onset predictions Fast Followers and Laggards

7 M2M Big Data and Analytics Revenue Sources Data Integration Aggregation and integration of the collected data streams in a manner that makes them suitable for analysis; integration with other possible data sources is included in this component. Data Storage Implementation and management of the data store holding the data sets that have been integrated for the analytics process. Data Analytics Processing of the data by an analytics engine and the subsequent delivery of insights; all three forms of analysis (descriptive, predictive, and prescriptive) are included in this component. Data Presentation Further presentation of the delivered analytical insights to the end-user in the form of reports, visualizations, or dashboard mash-ups. Professional Services

8 Supplier Products and Services Coverage Data Storage Data Integration Analytics Data Presentation Mnubo TempoDB Mtell Rapid Miner Platfora Software AG Cirro Skytree Ayata Splunk Datawatch Cloudera Tableau

9 Analytics Phases Descriptive and Diagnostic Predictive Prescriptive Why After Event or Failure When and How Before Event or Failure Analytics built into Decision Management If This Then That Simple statistical tools Data management Presentation Technologies Statistical modeling methods Statistical programming skills Inter-departmental acumen IT, OT and Engineering Statistical modeling methods Statistical programming skills Inter-departmental acumen IT, OT and Engineering Systems integration Machine learning

10 M2M Analytics Revenues 1% 14% 9% 85% 38% 53% Descriptive and Diagnostic Predictive Prescriptive

11 Product/Service Development Product Descriptive/ Diagnostic Evolving Products and Services Predictive Prescriptive Service

12 Usage Behavior Tracking Smart Metering/ Smart Grid Descriptive/ Diagnostic Derive pricing and offers to incent usage behaviors Predictive Usage-based Insurance Prescriptive

13 Operational Analysis Descriptive/ Diagnostic Predictive Prescriptive

14 Contextual Awareness Descriptive/ Diagnostic PASSIVE Traditional Telematics: ecall, bcall, diagnostics, SVT, UBI Cellular (2G) ACTIVE Obstacle detection and collision avoidance ADAS: Radar, machine vision, sonar Predictive COOPERATIVE V2V and V2I DSRC (4G LTE, long-range BT, RFID) AUTONOMOUS Driverless vehicles Cellular + V2X + ADAS sensors + Lidar Prescriptive

15 Maintenance and Repair Segments and Spend Predictive Maintenance Condition Monitoring 1,400 1,200 1,000 Condition-based Maintenance Planned Maintenance (US$ Billions) Preventive Maintenance Corrective Maintenance Enablement Execution

16 Maintenance Analytics Infrastructure Industrial Vehicles Other

17 M2M/IoT Tip of the Iceberg Citizen Empowered Cities New Business Models Equipment Replacement Services Expansion Micro- Markets Market Expansion

18 Thank you Dan Shey Practice Director M2M, Enterprise and Verticals

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