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Meeting the future - Big data in freight transport

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From a talk at the conference SJÖLOG 2015 showing how Big data can be applied in freight transport. The freight industry has a large potential for improvement here.

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Meeting the future - Big data in freight transport

  1. 1. Meeting the future Big data in freight transport SJÖLOG 2015 Per Olof Arnäs Chalmers @Dr_PO per-olof.arnas@chalmers.se Slides on slideshare.net/poar Film by Foursquare. Google: checkins foursquare
  2. 2. Things are happening outside the freight industry (and have been for some time)
  3. 3. 892 by benmschmidt on Flickr (C)19th century shipping visualized through the logs of Matthew Fontaine Maury (1806-1873), US Navy Shipping movements in the 19th century
  4. 4. Process improvement Service developm entInfrastructure developm ent Customer controls last mile Faster and better returns Better delivery experience Secure identification on pickup/delivery Distribution of food Home delivery Support companies that want to add E- commerce to their business Collect-in-store Local same-day delivery Improved delivery note Delivery and pickup during weekends Marketing of the E-channel Sustainable and climate friendly 3PL targeted at E- commerce Faster, more reliable and secure deliveries in Europe Better infrastructure on consumer side Better security Source: Svensk Digital Handel 2014 Bo Zetterqvist Areas of development for logistics companies in relation to e-commerce
  5. 5. Process improvement Service developm entInfrastructure developm ent Customer controls last mile Faster and better returns Better delivery experience Secure identification on pickup/delivery Distribution of food Home delivery Support companies that want to add E- commerce to their business Collect-in-store Local same-day delivery Improved delivery note Delivery and pickup during weekends Marketing of the E-channel Sustainable and climate friendly 3PL targeted at E-commerce Faster, more reliable and secure deliveries in Europe Better infrastructure on consumer side Better security Source: Svensk Digital Handel 2014 Bo Zetterqvist Areas of development for logistics companies in relation to e-commerce Digital development needed in freight transport
  6. 6. Customer controls last mile Faster and better returns Better delivery experience Secure identification on pickup/ delivery Collect-in- store Improved delivery note Sustainable and climate friendly 3PL targeted at E-commerce Faster, more reliable and secure deliveries in Europe Better security Source: Svensk Digital Handel 2014 Bo Zetterqvist Digital development needed in freight transport Process improvement Use ICT to make the system more efficient Real-time decision making, footprinting, better digital interaction between stakeholders Service development Use ICT to create new services Digital information enables new business models Infrastructure development Use ICT to interact with infrastructure Location Based Intelligence etc.
  7. 7. Customer controls last mile Faster and better returns Better delivery experience Secure identification on pickup/ delivery Collect-in- store Improved delivery note Sustainable and climate friendly 3PL targeted at E-commerce Faster, more reliable and secure deliveries in Europe Better security Source: Svensk Digital Handel 2014 Bo Zetterqvist Digital development needed in freight transport Process improvement Use ICT to make the system more efficient Real-time decision making, footprinting, better digital interaction between stakeholders Service development Use ICT to create new services Digital information enables new business models Infrastructure development Use ICT to interact with infrastructure Location Based Intelligence etc. The freight industry has work to do…
  8. 8. We are in the middle of a gigantic exponential development curve beginning
  9. 9. Jawbone measures sleep interruption during earthquake https://jawbone.com/blog/napa-earthquake-effect-on-sleep/
  10. 10. So… What IS Big data?
  11. 11. 2011 2013 2015 ”Big data is an all- encompassing term for any collection of data sets so large and complex that it becomes difficult to process using on-hand data management tools or traditional data processing applications.” - Wikipedia 2015
  12. 12. Not statistics Exhausted by Adrian Sampson on Flickr (CC-BY) just
  13. 13. Not Business Intelligence Basingstoke Office Staff Desk "No computer" by John Sheldon on Flickr (CC-BY,NC,SA) just
  14. 14. http://dashburst.com/infographic/big-data-volume-variety-velocity/
  15. 15. Strategic Tactical Operational Predictive Time horizons Freight industry Most (preferably all) decisions in the transportation industry are made here. At the latest. Uninformed, ad-hoc, and probably non optimal, decisions Science fiction
  16. 16. Strategic Tactical Operational Predictive But with technology, we are approaching this boundary …and we are starting to move past it! Real-time! Time horizons Freight industry
  17. 17. Goods Vehicle Business process Infra- structure Barcodes   RFID   Sensors ERP systems   TMS systems   E-invoices   Cloudbased services Order handling   Driver support   Vehicle economics RDS-TMC   Road taxes   Active traffic support Digitization fronts
  18. 18. En la cima! by Alejandro Juárez on Flickr (CC-BY) 3 mountaintops to climb…
  19. 19. Length
 Weight
 Width
 Height Capacity
 + other PBS-criteria Emissions
 Fuel consumption
 Route Position
 Speed
 Direction Weight
 Origin
 Destination Accepted ETA Temperature
 + other state variables Temperature + other state variables Education/training Speed (ISA)
 Rest/break schedule
 Traffic behaviour Belt usage
 Alco lock history Schedule status (time to next break etc.) Contracts/ agreements Previous interactions Backoffice support Fixed Historical Snapshot Vehicle Cargo Driver Company Infrastructure /facility Map + fixed data layers Traffic history Current traffic Queue Availability DATA MATRIX
  20. 20. http://www.scdigest.com/ontarget/ 14-01-21-1.php?cid=7767 Speculative shipping Package item(s) as a package for eventual shipment to a delivery address Associate unique ID with package Select destination geographic area for package Ship package to selected distribution geographic area without completely specifying delivery address Orders satisfied by item(s) received? Package redirected? Determine package location Convey delivery address, package ID to delivery location Assign delivery address to package Deliver package to delivery address Convey indication of new destination geographic area and package ID to current location Yes Yes No No smile! by Judy van der Velden (CC-BY,NC,SA)
  21. 21. Multicolour Jelly Belly beans in Sugar! by MsSaraKelly on Flickr (CC-BY) Requirements on Big data specific to freight transport Geocoded data Decentraliseddata Flows Goods Resources Value Information Products Multiple perspectives Strategic Tactical Operative Predictive
  22. 22. Human resources Reduction in driver turnover, driver assignment, using sentiment data analysis Real-time capacity availability Inventory management Examples of applications of Big data in freight (Waller and Fawcett, 2013) Transportation management Optimal routing, taking into account weather, traffic congestion, and driver characteristics Time of delivery, factoring in weather, driver characteristics, time of day and date Forecasting Waller, M. A. and Fawcett, S. E. (2013), Data Science, Predictive Analytics, and Big Data: A Revolution That Will Transform Supply Chain Design and Management. JOURNAL OF BUSINESS LOGISTICS, 34: 77–84
  23. 23. 7Big Data Best Practice Across Industries Usage of data in order to: Increase Level of Transparency Optimize Resource Consumption Improve Process Quality and Performance Increase customers loyalty and retention Performing precise customer segmentation and targeting Optimize customer interaction and service Expanding revenue streams from existing products Creating new revenue streams from entirely new (data) products Exploit data for: Capitalize on data by: New Business Models Customer Experience Operational Efficiency Use data to: • Increase level of transparency • Optimize resource consumption • Improve process quality and performance Exploit data to: • Increase customer loyalty and retention • Perform precise customer segmentation and targeting • Optimize customer interaction and service Capitalize on data by: • Expanding revenue streams from existing products • Creating new revenue streams from entirely new (data) products New Business ModelsCustomer ExperienceOperational Efficiency Figure 4: Value dimensions for Big Data use cases; Source: DPDHL / Detecon DHL 2013: ”Big Data in Logistics”
  24. 24. Measure real-time system behaviour Emil Johansson - EJOH.SE
  25. 25. Predict future events
  26. 26. http://blog.digital.telefonica.com/?press-release=telefonica-dynamic-insights-launches-smart-steps-in-the-uk Vizualisation
  27. 27. Created by Oliver O'Brien (UCL Geography/UCL CASA) Vizualisation
  28. 28. Locals and Tourists #1 (GTWA #2): London by Eric Fischer on Flickr Vizualisation
  29. 29. Vizualisation/combination
  30. 30. Vizualisation/combination
  31. 31. Manage complex systems Image from: http://www.as-coa.org/watchlisten/ascoa-visits-rios-operations-center
  32. 32. Avoid unpleasant surprises
  33. 33. Domain knowledge critical! See for instance: Waller, M. A. and Fawcett, S. E. (2013), Data Science, Predictive Analytics, and Big Data: A Revolution That Will Transform Supply Chain Design and Management. JOURNAL OF BUSINESS LOGISTICS, 34: 77–84 Data scientists - the new superstars "Data Science Venn Diagram" by Drew Conway - Own work. Licensed under Creative Commons Attribution- Share Alike 3.0 via Wikimedia Commons - http://commons.wikimedia.org/wiki/ File:Data_Science_Venn_Diagram.png#mediaviewer/File:Data_Science_Venn_Diagram.png
  34. 34. Challenges The Challenger by Martín Vinacur on Flickr (CC-BY) Cross-disciplinary Cross-industries Cross-borders
  35. 35. Customer controls last mile Faster and better returns Better delivery experience Secure identification on pickup/ delivery Collect-in- store Improved delivery note Sustainable and climate friendly 3PL targeted at E-commerce Faster, more reliable and secure deliveries in Europe Better security Source: Svensk Digital Handel 2014 Bo Zetterqvist Digital development needed in freight transport Process improvement Use ICT to make the system more efficient Real-time decision making, footprinting, better digital interaction between stakeholders Service development Use ICT to create new services Digital information enables new business models Infrastructure development Use ICT to interact with infrastructure Location Based Intelligence etc.
  36. 36. Customer controls last mile Faster and better returns Better delivery experience Secure identification on pickup/ delivery Collect-in- store Improved delivery note Sustainable and climate friendly 3PL targeted at E-commerce Faster, more reliable and secure deliveries in Europe Better security Source: Svensk Digital Handel 2014 Bo Zetterqvist Digital development needed in freight transport Process improvement Use ICT to make the system more efficient Real-time decision making, footprinting, better digital interaction between stakeholders Service development Use ICT to create new services Digital information enables new business models Infrastructure development Use ICT to interact with infrastructure Location Based Intelligence etc. The freight industry has work to do…
  37. 37. Even if it hurts.
  38. 38. Even if it hurts. Although… Indiana Jones
  39. 39. It’s not business as usual. This is the internet happening to freight transport. There is no ’usual’ anymore. Hello Kitty Darth Vader by JD Hancock on Flickr (CC-BY)
  40. 40. It’s not business as usual. Get used to it. This is the internet happening to freight transport. There is no ’usual’ anymore. Hello Kitty Darth Vader by JD Hancock on Flickr (CC-BY)
  41. 41. Meeting the future Big data in freight transport SJÖLOG 2015 Per Olof Arnäs Chalmers @Dr_PO per-olof.arnas@chalmers.se Slides on slideshare.net/poar Film by Foursquare. Google: checkins foursquare

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