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IIT Mumbai – First and Last Leg Optimization

IIT Mumbai – First and Last Leg Optimization. CONFIDENTIAL May, 2012. Freight Flow -1 . Pickup. Delivery. CFS/ Destination Warehouse. Destination Port. Customers. Freight Flow -2. Seller. CFS. Origin Port. Freight Flow - 3. Trucking Industry Level Challenges.

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IIT Mumbai – First and Last Leg Optimization

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  1. IIT Mumbai –First and Last Leg Optimization CONFIDENTIAL May, 2012

  2. Freight Flow -1 Pickup Delivery

  3. CFS/ Destination Warehouse Destination Port Customers Freight Flow -2 Seller CFS Origin Port

  4. Freight Flow - 3

  5. 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

  6. 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 ?

  7. 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

  8. 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

  9. Overview – An example for Auto Route Generation 9

  10. 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 10

  11. 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 11

  12. 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

  13. 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

  14. Thank You http://www.tcs.com CONFIDENTIAL May, 2012

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