Shantanu Roy is the CIO of Mahindra Logistics since 2015. His academic interest lies in supply chain strategy, and enjoys data modelling, user journey mapping, and network optimization. He is an alumnus of NIT Warangal and UC Berkeley, Haas School of Business.
SARAL (Simulated Analysis of Route and Load) by Mahindra Logistics is a cloud-based route optimization simulation engine developed bespoke using open source frameworks and open source algorithms for planning scheduled (last-mile/first-mile) deliveries. It also focuses on ensuring optimal resource capacity utilization with an ultimate objective of minimizing delivery cost while adhering to SLAs.
SARAL democratizes route modelling and route optimization for MLL users. Off-the-shelf commercial optimization engines with similar capabilities are 10X – 100X more expensive to operate since they are priced on user-licenses procured as well as on number of cores deployed (to run the engine on). Moreover, commercial engines can only optimize one scenario at a time. SARAL can cater to an infinite number of users and can be scaled to run an infinite number of route optimization scenarios in parallel.
SARAL brings the cost of doing route optimization to almost zero. Other than the initial development cost, there is only the cost of hosting and annual API subscription fees. It also doubles up as a BPM engine since one can develop templates, save scenarios and persist master data in it.