This document discusses the challenges and opportunities of real-time data in freight transport. It identifies three "mountaintops" that must be climbed: 1) collecting data in real-time from vehicles, cargo, drivers, companies and infrastructure; 2) processing this real-time data; and 3) exploiting the real-time data. Real-time data could improve efficiency and decision making but challenges include integrating different data sources, organizational adoption of new technologies, and ensuring benefits increase with supply chain complexity.

1. CC-BY PER OLOF ARNÄS
UNSOLVED PROBLEMS IN
FREIGHT TRANSPORT
CLIMBING THE THREE
MOUNTAINTOPS OF
REAL-TIME DATA
Per Olof Arnäs
Chalmers University of Technology
@Dr_PO
per-olof.arnas@chalmers.se
about.me/perolofarnas
Slides: slideshare.net/poar
En la cima! by Alejandro Juárez on Flickr (CC-BY)

2. Northern LEAD
Logistics Research Centre
Founded by:
Chalmers University of Technology
University of Gothenburg
Logistics and Transport Society LTS

3. Tomorrow’s logistics. We are finding the answers.
Around 70 researchers
Research centre for
sustainable logistics
solutions
Five core research
groups Organises, facilitates,
disseminates highly
relevant logistics
researchCollaboration between
Chalmers and University
of Gothenburg

4. Physical
Distribution
Production
Logistics
Industrial marketing
& purchasing
Logistics &
Transport
Optimization
Professors 10
Visiting Professors 6
Associate Professors 5
Post docs 6
Faculty 14
PhD students 32
Total 73
Five core
research groups

5. Thought leadership
through
high quality
research and
innovation
Challenges
and trends
Outcomes for
policy and
business
Volatility and risk
Demographic
changes
Complexity and
structural
flexibility
Resource
limitations
Manufacturing
and retail
revolution
Environmental
impact
Focused areas
Urban Transport
Long Distance Transport
Purchasing of
transport
Logistics and Production Networks
Information,
planning and
control
Measurements
and measuring
Service
development in
networks
Resource
utilisation
Intermodality

6. Per Olof Arnäs
The Transport
industry
3 things:
Carbon-free transport by Stéfan on Flickr

7. …physical
3d boxes by crystaljingsr on Flickr

8. Technology
Management
and
Economics
Logis4kcs
and
Transporta4onCC-­‐BY
Per
Olof
Arnäs
…public
Traffic Jam by Giorgio Minguzzi on Flickr

9. Technology
Management
and
Economics
Logis4kcs
and
Transporta4onCC-­‐BY
Per
Olof
Arnäs
…analogue
542 miles by Jason on Flickr

11. Per Olof Arnäs Stage Coach Wheel by arbyreed on Flickr
Development of transportation
technology has been
fairly linear
…for the last 5500 years

12. We are in the middle of a gigantic
exponential development curve
beginning

13. A new global eco system where new
types of, knowledge based, industries
compete with traditional ones

14. http://bryce.vc/post/18404303850/the-problem-with-innovation
Startups don’t compete with airlines...
by purchasing a bunch of planes
hiring a bunch of pilots
and locking up a bunch of terminals at airports.
Miniature Airport by disparkys on Flickr

15. Startups compete with airlines by
inventing videoconferencing.
http://bryce.vc/post/18404303850/the-problem-with-innovation
Startups don’t compete with airlines...
Miniature Airport by disparkys on Flickr (CC-BY,SA)
by purchasing a bunch of planes
hiring a bunch of pilots
and locking up a bunch of terminals at airports.

17. RESOURCE UTILISATION LOW

18. Safety imbalance
Variation in resource demand
Chain imbalance
Caused by the chain
Technological imbalance
E.g. mismatch in equipment
Operational imbalance
Goods and resource flow not compatible
Structural imbalance
Uneven transport demand

19. Safety imbalance
Variation in resource demand
Chain imbalance
Caused by the chain
Technological imbalance
E.g. mismatch in equipment
Operational imbalance
Goods and resource flow not compatible
Structural imbalance
Uneven transport demand
Several of these
imbalances can be
reduced by reducing
uncertainties

20. InSearchOfLostTimebybogenfreundonFlickr
But the biggest problem
in transportation is time.
There is not enough of it.
Ever.

21. The transport industry
does not like real-time
decisions.
At all.
DSC_9073.jpg by James England on Flickr (CC-BY)

22. The transport industry
does not like real-time
decisions.
At all.
Batch-handling
Zip codes
Zones
Time-tables
DSC_9073.jpg by James England on Flickr (CC-BY)

23. Image: Alain Delorme, alaindelorme.com
The current model is
focused on economy of
scale and standardization

24. Image: Alain Delorme, alaindelorme.com
The current model is
focused on economy of
scale and standardization

25. The current paradigm

26. So…
What are we
doing about
all this?

27. http://www.gartner.com/newsroom/id/2575515
Source: Gartner August 2013
Augmenting
humans with
technology
Machines
replacing
humans
Humans and
machines
working
alongside each
other
Machines
better
understanding
humans and
the
environment
Humans better
understanding
machines
Machines and
humans
becoming
smarter
Gartners Hype Cycle for Emerging Technologies

28. http://www.gartner.com/newsroom/id/2575515
Source: Gartner August 2013
Gartners Hype Cycle for Emerging Technologies

29. http://www.gartner.com/newsroom/id/2575515
?
Source: Gartner August 2013
Gartners Hype Cycle for Emerging Technologies
Transportation/
logistics?

30. Opportunities
Digitization Increasinggoods volumes
New
technology
Political
interest
Quad Aces by fitzsean on Flickr

31. ICT Maturity
App
"Multi-Touch" by DaveLawler on Flickr (CC-BY)

32. smile! by Judy van der Velden (CC-BY,NC,SA)
Speculative
shipping
http://www.scdigest.com/ontarget/
14-01-21-1.php?cid=7767

33. smile! by Judy van der Velden (CC-BY,NC,SA)
Speculative
shipping
http://www.scdigest.com/ontarget/
14-01-21-1.php?cid=7767
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

34. smile! by Judy van der Velden (CC-BY,NC,SA)
Speculative
shipping
http://www.scdigest.com/ontarget/
14-01-21-1.php?cid=7767
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

35. CC-BY PER OLOF ARNÄS
Strategic Tactical Operational Predictive
Time horizons
We are approaching
this boundary
…and we are
starting to
move past it!
Real-time!

36. Digitization fronts
Goods Vehicle
Business
process
Infra-
structure

37. 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

38. CC-BY PER OLOF ARNÄS
Business
processes
Infra-
structure
Paperbased
Phone
Papers
Road
signs
A
nalogue
tools
R
D
S
M
onitorfuel
cosnum
ption
Digitization version 0 0.5 1.0 1.5 2.0
E-mail
Fax
TMS-
systems
Excel
Route
planning
G
PS
fornavigation
Electronically
generated
freight docum
ents
Barcodes
RFID-tags
Simple order
handling
Advanced order
handling
Openinterface
W
eb
based
UI
Platform
based
system
s
Hardware-
oriented
Datacollection
systems
(proprietary)
Communication
withvehicles
E-invoice
W
eb
based
booking
Route
optimisation
ThesocialwebOpenconnectivity
Integrated
prognosis
Data
collection
system
s
(open)
Tolling
system
s
Webservices
with traffic data
Dynamic
routing
systems
Performance
BasedaccessPerformanceBasedaccess
Mashups
Multipledata
sources
Probedata
Individual
routing
inform
ation
Platooning
Platooning
Exceptions
handling
Smartgoods
Manual
Computers
Software
Functions
Distributed
decision
making
G
oods
as
bi-
directional
hyperlink
Paperbased
CC-BY Per Olof Arnäs, Chalmers
Goods Vehicle

39. Goods
Vehicles
Business
processes
Infrastructure
Stra-
tegic
Tac-
tical
Opera-
tional
Pre-
dictiveWhat happens
when access to
real-time data
increases?
not quite clear on the concept by woodleywonderworks on Flickr (CC-BY)

40. The Action of New York City by
Trey Ratcliff on Flickr (CC-BY,NC,SA)
Need for speed

41. The Action of New York City by
Trey Ratcliff on Flickr (CC-BY,NC,SA)
Need for speed
Data collection
Dataprocessing Data
exploitation

42. CC-BY PER OLOF ARNÄS En la cima! by Alejandro Juárez on Flickr (CC-BY)
3 mountaintops to climb…

43. CC-BY PER OLOF ARNÄS En la cima! by Alejandro Juárez on Flickr (CC-BY)
Fixed Historical
3 data types
Mountaintop #1
Collection of data in real-time
Snapshot

44. CC-BY PER OLOF ARNÄS En la cima! by Alejandro Juárez on Flickr (CC-BY)
5 data domains
Vehicle CargoDriver Company
Infrastructure/
facility
at least…
Mountaintop #1
Collection of data in real-time

45. 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

46. CC-BY PER OLOF ARNÄS En la cima! by Alejandro Juárez on Flickr (CC-BY)
Mountaintop #2
Processing of data in real-time
Locals and Tourists #1 (GTWA #2): London by Eric Fischer on Flickr

47. CC-BY PER OLOF ARNÄS En la cima! by Alejandro Juárez on Flickr (CC-BY)
Mountaintop #2
Processing of data in real-time

48. CC-BY PER OLOF ARNÄS En la cima! by Alejandro Juárez on Flickr (CC-BY)
Mountaintop #3
Exploiting data in real-time
Connected. 362/365 by AndYaDontStop
on Flickr (CC-BY)
Lisa for I/O Keynote by Max Braun on
Flickr (CC-BY)
Fulham-Manchester
United 24-02-2007 by
vuhlser on Flickr (CC-BY)

49. CC-BY PER OLOF ARNÄS En la cima! by Alejandro Juárez on Flickr (CC-BY)
Mountaintop #3
Exploiting data in real-time
Boeing-KC-97 Stratotanker by x-ray delta one on Flickr (CC-BY)

50. CASES
(MANY)

51. CASES
(MANY MORE)

52. Challenges
The Challenger by Martín Vinacur on Flickr (CC-BY)

53. Company
Difficulties increase with scale
The Challenger by Martín Vinacur on Flickr (CC-BY)

54. Company
Supply chain,
simple
The Challenger by Martín Vinacur on Flickr (CC-BY)

55. Company
Supply chain,
simple
Supply chain,
complex
The Challenger by Martín Vinacur on Flickr (CC-BY)

56. Company
Supply chain,
simple
Supply chain,
complex
Eco system
The Challenger by Martín Vinacur on Flickr (CC-BY)

57. The Challenger by Martín Vinacur on Flickr (CC-BY)
Not all ideas age with grace

58. The Challenger by Martín Vinacur on Flickr (CC-BY)
Someone must do the work

59. The Challenger by Martín Vinacur on Flickr (CC-BY)
Not everyone will want to
adopt new things…

61. CC-BY PER OLOF ARNÄS
UNSOLVED PROBLEMS IN
FREIGHT TRANSPORT
CLIMBING THE THREE
MOUNTAINTOPS OF
REAL-TIME DATA
Per Olof Arnäs
Chalmers University of Technology
@Dr_PO
per-olof.arnas@chalmers.se
about.me/perolofarnas
Slides: slideshare.net/poar
En la cima! by Alejandro Juárez on Flickr (CC-BY)