big data - modelling world 2015, london
TRANSCRIPT
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
Stage Coach Wheel by arbyreed on Flickr
<<<<<<<<<
Development of transportation technology has been
fairly linear
…for the last 5500 years
Manage complex systems
Image from: http://www.as-coa.org/watchlisten/ascoa-visits-rios-operations-center
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
Human resources
Reduction in driver turnover, driver
assignment, using sentiment data
analysis
Real-time capacity availability
Inventory management
Examples of applications 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
Jawbone measures sleep interruption during earthquake
https://jawbone.com/blog/napa-earthquake-effect-on-sleep/
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
smile! by Judy van der Velden (CC-BY,NC,SA)
Predictive shipping
Image: Alain Delorme, alaindelorme.com
The current model is focused on economy of scale and standardization
But the biggest problem in transportation is time.
There is not enough of it. Ever.
In S
ea
rch
Of
Lo
st T
ime
by
bo
ge
nfr
eu
nd
on
Flic
kr
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)
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
Multicolour Jelly Belly beans in Sugar! by MsSaraKelly on Flickr (CC-BY)
Requirements on Big data specific to
freight transport
Geocoded data
Decentralised data Flows
Goods Resources
Value
Information
Products
Multiple perspectives
Strategic Tactical
Operative Predictive
En la cima! by Alejandro Juárez on Flickr (CC-BY)
3 data types
Mountaintop #1
Collection of data in real-time
Fixed Historical Snapshot
En la cima! by Alejandro Juárez on Flickr (CC-BY)
Mountaintop #1
Collecting data in real-time
5 data domains Vehicle Cargo Driver Company
Infrastructure/facility
at lea
st…
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
(Freight) companies want to share as little data as possible,
with as little friction as possible, to get the highest utility possible
Private Property by Nathan O'Nions on Flickr (CC-BY)
Mountaintop #2
Processing data in real-time
En la cima! by Alejandro Juárez on Flickr (CC-BY)
Locals and Tourists #1 (GTWA #2): London by Eric Fischer on Flickr
Requirement
Fixed Historical Snapshot
Transport 1
Fixed Historical Snapshot
Transport 2
Fixed Historical Snapshot
Requirement
Fixed Historical Snapshot
Transport 1
Fixed Historical Snapshot
Transport 2
Fixed Historical Snapshot
No access!
Full access!
Fixed
Historic
al
Snapshot
Fixed
Historic
al
Snapshot
Requirements. Different.
Fixed
Historic
al
Snapshot
Port area
City centre
Freight terminal
Bridge
Challenges
The Challenger by Martín Vinacur on Flickr (CC-BY)
Cross-disciplinary
Cross-industries
Cross-borders
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)