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
Things are happening outside the
freight industry
(and have been for some time)
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
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
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
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.
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…
We are in the middle of a gigantic
exponential development curve
beginning
Jawbone measures sleep
interruption during earthquake
https://jawbone.com/blog/napa-earthquake-effect-on-sleep/
So…
What IS
Big data?
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
Not statistics
Exhausted by Adrian Sampson on Flickr (CC-BY)
just
Not
Business
Intelligence
Basingstoke Office Staff Desk "No computer" by John Sheldon on Flickr (CC-BY,NC,SA)
just
http://dashburst.com/infographic/big-data-volume-variety-velocity/
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
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
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
En la cima! by Alejandro Juárez on Flickr (CC-BY)
3 mountaintops to climb…
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
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)
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
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
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”
Measure
real-time
system
behaviour
Emil Johansson - EJOH.SE
Predict future events
http://blog.digital.telefonica.com/?press-release=telefonica-dynamic-insights-launches-smart-steps-in-the-uk
Vizualisation
Created by Oliver O'Brien (UCL Geography/UCL CASA)
Vizualisation
Locals and Tourists #1 (GTWA #2): London by Eric Fischer on Flickr
Vizualisation
Vizualisation/combination
Vizualisation/combination
Manage complex systems
Image from: http://www.as-coa.org/watchlisten/ascoa-visits-rios-operations-center
Avoid unpleasant surprises
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
Challenges
The Challenger by Martín Vinacur on Flickr (CC-BY)
Cross-disciplinary
Cross-industries
Cross-borders
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.
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…
Even if it hurts.
Even if it hurts. Although…
Indiana Jones
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)
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)
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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Meeting the future - Big data in freight transport

  • 1. Meeting the future Big data in freight transport SJÖLOG 2015 Per Olof Arnäs Chalmers @Dr_PO [email protected] Slides on slideshare.net/poar Film by Foursquare. Google: checkins foursquare
  • 2. Things are happening outside the freight industry (and have been for some time)
  • 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. 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. 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. 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. 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. We are in the middle of a gigantic exponential development curve beginning
  • 9. Jawbone measures sleep interruption during earthquake https://jawbone.com/blog/napa-earthquake-effect-on-sleep/
  • 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. Not statistics Exhausted by Adrian Sampson on Flickr (CC-BY) just
  • 13. Not Business Intelligence Basingstoke Office Staff Desk "No computer" by John Sheldon on Flickr (CC-BY,NC,SA) just
  • 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. 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. 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. En la cima! by Alejandro Juárez on Flickr (CC-BY) 3 mountaintops to climb…
  • 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. 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. 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. 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. 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”
  • 27. Created by Oliver O'Brien (UCL Geography/UCL CASA) Vizualisation
  • 28. Locals and Tourists #1 (GTWA #2): London by Eric Fischer on Flickr Vizualisation
  • 31. Manage complex systems Image from: http://www.as-coa.org/watchlisten/ascoa-visits-rios-operations-center
  • 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. Challenges The Challenger by Martín Vinacur on Flickr (CC-BY) Cross-disciplinary Cross-industries Cross-borders
  • 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. 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. Even if it hurts.
  • 38. Even if it hurts. Although… Indiana Jones
  • 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. 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. Meeting the future Big data in freight transport SJÖLOG 2015 Per Olof Arnäs Chalmers @Dr_PO [email protected] Slides on slideshare.net/poar Film by Foursquare. Google: checkins foursquare