Title and Content
109
207
246
Dark 1
185
175
164
Accent 3
255
255
255
Light 1
151
75
7
Accent 4
131
56
155
Dark 2
193
187
0
Accent 5
0
99
190
Light 2
255
221
62
Accent 6
85
165
28
Accent 1
255
255
255
Hyperlink
127
203
179
212
255
IIT Mumbai
–
First
and
Last
Leg
Optimization
175
215
149
195
242
221
Tata Blue 50%
229
205
186
CONFIDENTIAL
Brown 50 %
May, 2012
214
73
42
Accent 2
236
137
29
Followed Hyperlink
197
223
171
255
249
213
Purple 50 %
Purple 25 %
Yellow 50 %
Yellow 25 %
248
241
235
180
213
154
214
231
200
241
240
202
251
251
241
Brown 25 %
Green 50 %
Green 25 %
238
Tata Blue 25%
Light Green 50% Light Green 25%
Freight Flow -1
Pickup
Delivery
Freight Flow -2
Seller
CFS
Customers
Origin Port
Destination
Port
CFS/
Destination
Warehouse
Freight Flow - 3
Trucking Industry Level Challenges
 Infrastructure Issues and Challenges
–
–
–
–
–
Congestion
Operational inefficiencies
Non standard trucks
Under utilization of infrastructure available.
Supply demand mismatch
 Institutional Issues
– Highly Fragmented industry
– Manual, non-uniform or discrete processes across the industry
– Non-availability of Quality manpower
 Technological Issues
–
–
–
–
Old technology
Adoption of new technologies is expensive
No clear Return on Investments for New Technologies
Manual processes leading to operational inefficiencies
Solutions and Strategies (Largely Capital intensive)
 Vehicle Size and Delivery Time Regulations
 Load Consolidation and Load Factor Efficiency (Load consolidation, or
co-loading)
 Urban Distribution Centers
 Freight Villages - Different from urban distribution centers, but similar
in concept. Freight villages are planned unit developments specifically
designed for multi-modal freight transfer within a secured perimeter.
 Delivery Tunnels - In Helsinki, freight tunnels for underground
trucking are planned
 Dedicated freight corridors – are they really helping urban areas ?
6
Inefficiencies in the current process
 Pickup driver has to visit the terminal to collect the list of pickups
 Planning for linehaul, cross-docking, resource requirements, delivery
plans etc are not possible till the goods reaches to the terminal
 There is no update on the status of delivery till the driver reports back
to the terminal.
 This process is time consuming and lead to inefficiencies such as
•
•
•
•
•
missed pickups and missed appointments,
excessive waiting times during pickups and deliveries
resulting in additional driver hours and under utilization of
trucks
postponing pickups
additional kilometers operated by drivers thus additional fuel
consumption and choking of traffic
no clue on the traffic situation on the network – no route
guidance
7
Solution Components and Business Model
Solution Components
•
•
•
•
•
•
Vehicle Tracking System - Telematics
Pickup and Delivery Management System – to plan the pickups and
deliveries
Handheld Mobile devices – Scanner, data logger etc
Route Planner to generate optimal routes
Central Server and communication systems
Transportation Management System
•
Platform based solution
Benefits
From Trucking companies Perspective
•
•
•
•
•
•
Trucking company can register with minimum fee
Trucking companies can pay as per use
Opex and No capital investments – Transaction based
Can withdraw when not required
No technology skills required
Improved visibility of shipments, high asset utilisation, less fuel costs and customer satisfaction
From Service Provider perspective
•
•
Multiple trucking companies can be hosted on single software platform.
Other services such as reports, performance indicators can be sold as value added services
From City/Governance perspective
•
•
•
Less Pollution and congestion
Real time and accurate data for traffic alerts
Trustworthy and huge volume of data for / Freight Modelling/ infrastructure planning and real time
decisions
8
Overview – An example for Auto Route Generation
9
As-Is Routes
Features considered
• Routes are planned for a region.
• A truck will be assigned/reserved
for route
• Static route is generated by the
route planner
• Dispatcher assigns new stops to
the route manually as and when
new orders are to be handled
Parameters for comparison
4 Trucks
Deployed
10
Total Truck KM 126
To-Be Routes
Features considered
• No region based routes
• Routes will be developed as per the
order/stop locations
• Algorithm based route generation
• Optimises the number of trucks required
rather than the truck-km
Parameters for comparison
3 Trucks
Deployed
11
Total Truck KM 135
Data for Analysis
Available Data for Analysis
•
•
•
•
•
Driver Data
Equipment Data
Order Data
Trip Data
Stop Data (including Stop to Stop Distance Data)
Output Expected
•
Optimized Route with route parameters
12
Business Benefits
• Reduced P&D Costs (They represent around 30% of total cost in the case of
road based movement)
• Improved Route Planning
• Effective Equipment utilization
• Effective Utilization of Drivers
13
Title and Content
109
207
246
Dark 1
185
175
164
Accent 3
Thank127
You
175
221
255
255
255
Light 1
151
75
7
Accent 4
203
215
238
229
205
186
CONFIDENTIAL
Brown 50 %
May, 2012
Dark 2
193
187
0
Accent 5
0
99
190
Light 2
255
221
62
Accent 6
85
165
28
Accent 1
255
255
255
Hyperlink
214
73
42
Accent 2
236
137
29
Followed Hyperlink
179
149
197
212
195
223
255
242
171
255
249
213
Purple 50 %
Purple 25 %
Yellow 50 %
Yellow 25 %
248
241
235
180
213
154
214
231
200
241
240
202
251
251
241
Brown 25 %
Green 50 %
Green 25 %
http://www.tcs.com
Tata Blue 50%
131
56
155
Tata Blue 25%
Light Green 50% Light Green 25%