Presentation at the October Scope Event on Internet of Things
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How do we do we make decisions at the speed of business? Traditional supply chain processes are batch, and out of cadence with business. How do we rethink these processes to have the right data available when we need it. In this presentation, we discuss the inclusion of streaming data in supply chain visibility. It is not sufficient to ask the question of "Where is my stuff?" without the opportunity to use the data in better decision making.
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Presentation at the October Scope Event on Internet of Things
- 1. Global Supply Chain Visibility from IoT and Machine Learning Solutions SCOPE SUPPLY CHAIN CONFERENCE OCTOBER 9-11, 2016 MARRIOTT MARQUIS SAN DIEGO MARINA
- 2. Jim Hayden Senior Vice President Savi Technology Lora Cecere Founder and CEO Supply Chain Insights
- 3. Can Your Supply Chain Operate at the Speed of Business? LORA CECERE FOUNDER AND CEO SUPPLY CHAIN INSIGHTS
- 8. What Makes a Difference?
- 10. Looking Forward
- 11. New Forms of Analytics
- 12. The Learning Supply Chain Supply But, what if they could? Supply Chains don’t Play by the Rules…
- 13. Barriers
- 14. The Innovators: Not a Normal Distribution
- 15. Global Supply Chain Visibility from IoT and Machine Learning Solutions JIM HAYDEN SENIOR VICE PRESIDENT SAVI TECHNOLOGY
- 16. Internet of Things “IoT” Sources: Cisco, IBM, IDC Unstructured data from sensors is a much more salient feature of what is being called big data The “sensorization” of society is unlocking for the first time in human history, the potential to gather in real time enormous amounts of data and details about almost everything. With the added complexities introduced by new data sources (such as real-time events and sensors) and new types of analysis new opportunities will emerge to build business value. SENSORS BANDWIDTH PROCESSING IoT Enabler: Average Costs Over 10 Years IBM to Invest $3 Billion in Sensor-Data Unit New business to help customers gather and analyze the flood of data from sensor-equipped devices 90% of data generated by connected devices is never analyzed
- 17. Who Cares? Do any of the following matter to you?
- 18. Which vessel is my container on? How long has my shipment been sitting at the port? Are my raw materials going to get here in time? What temperature and humidity are my products at right now?
- 19. This is the real value of IoT for Supply Chain.
- 20. Leveraging All Data Sources … IoT Unstructured Data Sensors Mobile Device Apps Fleet GPS Data, Telematics
- 21. Ocean Visibility – A Particular Challenge Sensors using terrestrial mobile network ◦ Typically transmitting infrequently ◦ Time, location, environmental measures ◦ Only reliable close to land Sensors using satellite network ◦ Typically transmitting frequently ◦ Time, location, environmental measures ◦ More expense, only reliable if container is in line of sight AIS data for tracking vessel MMSI="413811000" TIME="2011-04-12 10:40:27 GMT" LONGITUDE="118.44586666667" LATITUDE="38.87483333333 3" COG="356" SOG="0.1" HEADING="116" NAVSTAT="1" IMO=" 9118824" NAME="JIN HAI XIANG" CALLSIGN="BVKU" TYPE="70" A="197" B="27" C="20" D="12" DRAUGHT="7.5" DEST="CAOFEIDIAN" ETA="04-10 07:00" AIS data feeds using satellite network ◦ Typically transmitting every 6 minutes ◦ Time, location, destination ◦ Most reliable, sometimes turned off (avoiding piracy)
- 22. Shipment End-to-End Visibility Shipment data required: • Who? • What? • When? • Where? • How? Shipment data sources: • Contract/plan • Milestone messages • Location messages Action/alerting data required: • Why? • Who? • How?
- 23. IoT Platform – Core Capabilities Sensor Communication and Management Data Storage/ Cleansing and Mapping Presentation/ Business Connectivity Open Source Data Enterprise Data Data Analytics/ Deep Learning structured data semi-structured/ unstructured unstructured data “things” thing connectivity data management machine learning presentation
- 24. Customer Export Savi Sensor Data Mobile Apps Enterprise Data Open Data Partner APIs Non-Savi Sensor Data INTEGRATION LAYERAMQP CoAP FTP HTTP MQTT SOAP TCP UDP XMPP SERVING LAYER BATCH LAYER SPEED LAYER Savi IoT Adapter Batch Processing Application Views Domain Specific CEP Sensor Agnostic CEP Modeling, Machine Learning RS-232 USB pRFID Bluetooth ZigBee 802.11 6LoWPAN aRFID GSM GPRS 3G 4G/LTE SATCOM Analytics Serving Layer Views Customer Apps Partner Apps Immutable Data Store Savi Insight Savi Apps SECURITY LAYER Structured and unstructured data Real-time Streaming analytics ScalableFastmachine learning Batch IoT Architectures: Real-time and Batch Built from open source technologies including:
- 25. Machine Learning on IoT Data In 1959 Arthur Samuel defined machine learning as a “Field of study that gives computers the ability to learn without explicitly being programmed.” Requires Data Scientists
- 26. Models for Predicting Arrival Time ETA Late confirmed Shipment on time ETA Late warning Machine Learning generates most accurate ETA forecasts
- 27. Modeling Carrier Performance by Lane
- 28. Models Optimize Intermodal Routes Telematics data Sensor data EDI data AIS data
- 29. Why Should You Care? Category Benefits Detention and Demurrage Costs Cost reduction due to ability to capture actual time at a location Cross-Docking Costs Improvement due to more accurate ETA of inbound shipments Late Fees and Expediting Fees Decrease due to improvements in estimating shipment times Carrier Performance Decrease in lane holding time and improve carrier compliance through accurate data and analytics Inventory Value of inventory on hand reduction due to decreased lead time and variability Lost Sales Percent reduction of lost sales due to stock outs because of fewer missed and late deliveries Theft and Damage Percent reduction in theft, loss and damaged goods due to real-time visibility Logistic Planning Percent reduction of logistics planning and forecasting personnel due to automated modeling
- 30. Savi Supply Chain Innovator revolutionary technology delivered as purpose-built applications that solve strategic supply chain challenges Industry awards and recognition Supply Chain Analytics Pioneer leveraging M2M data & the Internet of Things to provide provide logistics insight World's Largest Asset Tracking System powered by Savi RF-ITV award-winning solutions track more than in goods annually Driving supply chain success with leading Global 1000 organizations IP portfolio currently hold more than 60 patents related to logistics, IoT, and in-transit visibility
- 31. Questions ?
- 32. Lora Cecere Founder, Supply Chain Insights [email protected]
- 33. Jim Hayden Senior Vice President, Data Science Solutions [email protected]