e commerce and freight transport - chasing the last mile, one byte at a time
TRANSCRIPT
E-commerce and freight transport
Chasing the last mile - one byte at a time
Per Olof Arnäs, PhD
Chalmers University of Technology Service Management and Logistics
[email protected] about.me/perolofarnas
Slides: slideshare.net/poar @Dr_PO
OKIMG_5751 by taymtaym on Flickr (CC-BY)
Demographic and social
change
Shift in economic
power
Rapid urbanisation
Technological breakthroughsClimate
change and resource scarcity
5 GLOBAL TRENDS
Source: PWC (google: pwc megatrends 2014)
Process improvement
Servic
e
developm
entInfrastructure
development
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
Servic
e
developm
entInfrastructure
development
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
friendly3PL 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
friendly3PL 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…
RESOURCE UTILISATION LOW
Source: Kent Lumsden
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
RESOURCE UTILISATION LOW
Source: Kent Lumsden
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
January February March April May June July August September October November December
10% Nov 25
When do we start generating profit?
Profit margin = Sales - Cost
Sales
January February March April May June July August September October November December
10% Nov 25
2% Dec 25
When do we start generating profit?
Profit margin = Sales - Cost
Sales
January February March April May June July August September October November December
10% Nov 25
1% Dec 29
2% Dec 25
When do we start generating profit?
Profit margin = Sales - Cost
Sales
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)
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
Things are happening outside the freight industry
(and have been for some time)
Image: Richard Hancock, twitter.com/CanaryWorf
Stage Coach Wheel by arbyreed on Flickr
Development of transportation technology has been
fairly linear
…for the last 5500 years
A new global eco system where new types of, knowledge based,
industries compete with traditional ones
http://jaysimons.deviantart.com/art/Map-of-the-Internet-1-0-427143215
Startups don’t compete with airlines...
by purchasing a bunch of planeshiring a bunch of pilots
and locking up a bunch of terminals at airports.
Quote: bryce.vc/post/18404303850/the-problem-with-innovation Image: Connecting the community, my Twitter strategy, and American Airlines at DFW by Trey Ratcliff on Flickr (CC-BY,NC,SA)
Startups compete with airlines by inventing videoconferencing.
Startups don’t compete with airlines...
by purchasing a bunch of planeshiring a bunch of pilots
and locking up a bunch of terminals at airports.
Quote: bryce.vc/post/18404303850/the-problem-with-innovation Image: Connecting the community, my Twitter strategy, and American Airlines at DFW by Trey Ratcliff on Flickr (CC-BY,NC,SA)
355:365:2015BWH by hermitsmoores on Flickr (CC-BY,NC,SA)
Make analogue information digital
Digitization:
Mob
ile W
orld
Con
gres
s 201
6 by
Kār
lis D
ambrān
s on
Flic
kr (C
C-BY
)
Increased use of digital technology
Digitalization:
Mob
ile W
orld
Con
gres
s 201
6 by
Kār
lis D
ambrān
s on
Flic
kr (C
C-BY
)
Increased use of digital technology
Digitalization:
Make analogue information digital
Digitization:
Both are important! (and interesting)
Ominous Windmill by Conrad Kuiper on Flickr (CC-BY,NC,SA)
Digit(al)ization is not a trend
It is a force of nature
Gartners Hype Cycle for Emerging Technologies
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
Source: Gartner July 2015
Could affect transportation and logistics
Integration of digital and physical worlds
http://www.sygic.com/gps-navigation/addon/head-up-display
”New” modes of transport
https://www.youtube.com/watch?v=50sv4M4rgBMhttps://www.youtube.com/watch?v=HG76DcXySuw
Servitization
Move up in the value chain
Upgrade drop points
Consumer services
Expose data
Mall of Scandinavia
http://www.smartcompany.com.au/growth/innovation/41765-online-retailer-offers-a-courier-that-waits-at-your-door-fashion-advice-not-included.html
https://www.amazon.com/dashbutton
https://www.shyp.com
The Action of New York City by Trey Ratcliff on Flickr (CC-BY,NC,SA)
Real-time (data driven) decision making
Data collection Data processingData exploitation
http://mindconnect.se/http://waze.com
https://mydrive.tomtom.com/
Bitcoin, bitcoin coin, physical bitcoin, bitcoin photo by Antana on Flickr (CC-BY,SA)
Another thing to
keep tabs on
Bitcoin, bitcoin coin, physical bitcoin, bitcoin photo by Antana on Flickr (CC-BY,SA)
Block chain technology
Records transactions and data among actors that do not trust each other
Fully decentralized
https://news.bitcoin.com/nimber-disrupts-logistics-system-blockchain-matters/
http://www.economist.com/news/leaders/21677198-technology-behind-bitcoin-could-transform-how-economy-works-trust-machine
Bitcoin, bitcoin coin, physical bitcoin, bitcoin photo by Antana on Flickr (CC-BY,SA)
http://www.coindesk.com/how-bitcoins-technology-could-make-supply-chains-more-transparent/
https://news.bitcoin.com/future-use-cases-blockchain-technology-parcel-tracking-regardless-courier/
Block chain technology
Records transactions and data among actors that do not trust each other
Fully decentralized
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
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
Jawbone measures sleep interruption during earthquake
https://jawbone.com/blog/napa-earthquake-effect-on-sleep/
Not Business
Intelligence
Basingstoke Office Staff Desk "No computer" by John Sheldon on Flickr (CC-BY,NC,SA)
just
Multicolour Jelly Belly beans in Sugar! by MsSaraKelly on Flickr (CC-BY)
Requirements on Big data specific to
freight transport
Geocoded data
Decentralised data
FlowsGoods
Resources
Value
Information
Products
Multiple perspectives
StrategicTactical
Operative Predictive
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
smile! by Judy van der Velden (CC-BY,NC,SA)
Anticipatory shipping
http://www.scdigest.com/ontarget/14-01-21-1.php?cid=7767
http://www.scdigest.com/ontarget/14-01-21-1.php?cid=7767
Anticipatory 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)
7Big Data Best Practice Across Industries
Usage of data in order to:Increase Level of TransparencyOptimize ResourceConsumption Improve Process Qualityand Performance
Increase customersloyalty and retentionPerforming precisecustomer segmentationand targetingOptimize customerinteraction and service
Expanding revenuestreams from existingproductsCreating new revenuestreams from entirelynew (data) products
Exploit data for: Capitalize on data by:
New Business Models
Customer Experience
OperationalEfficiency
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
2.1 Operational Efficiency
For metropolitan police departments, the task of tracking down criminals to preserve public safety can sometimes be tedious. With many siloed information repositories, casework often involves making manual connection of many data points. This takes times and dramatically slows case resolution. Moreover, road policing resources are deployed reactively, making it very difficult to catch criminals in the act. In most cases, it is not possible to resolve these challenges by increasing police staffing, as government budgets are limited.
One authority that is leveraging its various data sources is the New York Police Department (NYPD). By capturing and connecting pieces of crime-related information, it hopes to stay one step ahead of the perpetrators of crime.6 Long before the term Big Data was coined, the NYPD made an effort to break up the compartmentalization of its data ingests (e.g., data from 911 calls, investigation reports, and more). With a single view of all the informa-
tion related to one particular crime, officers achieve a more coherent, real-time picture of their cases. This shift has significantly sped up retrospective analysis and allows the NYPD to take action earlier in tracking down individual criminals.
The steadily decreasing rates of violent crime in New York7 have been attributed not only to this more effective streamlining of the many data items required to perform casework but also to a fundamental change in policing practice.8 By introducing statistical analysis and georaphical mapping of crime spots, the NYPD has been able to create a “bigger picture” to guide resource deployment and patrol practice.
Now the department can recognize crime patterns using computational analysis, and this delivers insights enabling each commanding officer to proactively identify hot spots of criminal activity.
6 “NYPD changes the crime control equation by the way it uses information”, IBM; cf. https://www-01.ibm.com/software/success/cssdb.nsf/CS/JSTS-6PFJAZ7 “Index Crimes By Region”, New York State Division of Criminal Justice Services, May 2013, cf. http://www.criminaljustice.ny.gov/crimnet/ojsa/stats.htm8 “Compstat and Organizational Change in the Lowell Police Department”, Willis et. al., Police Foundation, 2004; cf. http://www.policefoundation.org/
content/compstat-and-organizational-change-lowell-police-department
2.1.1 Utilizing data to predict crime hotspots
DHL 2013: ”Big Data in Logistics”
http://blog.digital.telefonica.com/?press-release=telefonica-dynamic-insights-launches-smart-steps-in-the-uk
Vizualisation
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
Create teams
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
friendly3PL 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
friendly3PL 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…
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)
OKIMG_5751 by taymtaym on Flickr (CC-BY)
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E-commerce and freight transport
Chasing the last mile - one byte at a time
Per Olof Arnäs, PhD
Chalmers University of Technology Service Management and Logistics
[email protected] about.me/perolofarnas
Slides: slideshare.net/poar @Dr_PO