How technology is driving Innovation in Logistics?

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route optimization in logistics

Increasingly enterprises are deploying Deep Tech solutions to solve complex logistics problems. Technology is enabling businesses to reimagine logistics that is highly efficient, resilient and digitally fit. Key to success in such transformational initiatives is the ability to model real-world logistics problems.

In last couple of years, we have observed increased focus from businesses to reach out to consumers directly. Consumers expect delivery experience to be as superior as buying experience. Logistics planning solutions are expected to offer unprecedented scale.

Striking balance between logistics speed and logistics cost becomes a dauting tasks in absence of smart decision support system. Across different legs of logistics, constraints and optimization levers vary significantly. One thing is certain that Logistics SaaS companies cannot afford to offer black box solutions in such a rapidly changing business environment.

At Mojro, we provide comprehensive set of tools to model real-world scenarios and helps businesses to create logistics digital twin. Our planning algorithms have capability to model constraints and uncertainties and measure impact of BULLWHIP effect on the logistics.

We take pride in offering Best-In-Class logistics planning and optimization solution.
 

Following capabilities help us to deliver significant value to our customers,
 

  • Multi-dimensional optimization capability helps in improving overall asset utilization. We optimize on various parameters like route, truck capacity, number of deliveries, lead time etc. We fuse AI, OR and big data elements and smartly manage trade-offs between logistics efficiency and algorithm performance. We apply Meta-modelling techniques to create an abstraction of the problem before solving optimization problem.
     
  • BYOC model - Build your own constraints - We offer comprehensive set of demand and supply side constraints. Geographic constraints are overlaid on top of business constraints to generate a feasible solution. On top of this, we allow customers to model their own constraints in a self-service way. Our ability to model real-world constraints helps businesses in creating a logistics digital twin to accelerate collaboration among teams.
     
  • What-If modeler - Demand and supply patterns can vary significantly through the month. Ongoing pandemic has made demand patterns nondeterministic. Businesses need "What-If" modeler to carry out scenario testing and experiment on parameters like shipping policies (FTL, LTL), single vs multi leg, fixed fleet vs best fleet mix models etc. We offer recommender system that helps in making apt decisions on logistics network, fleet mix and mechanisms to control returns.
     
  • Hyper scale - Same day/hour delivery models require ability to make complex mathematical decisions at an unprecedented speed. Our algorithms solve mathematically most complex problems (with polynomial time complexity) and recommend best possible solution. These algorithms carry out millions of computations in matter of minutes to recommend highly optimized solution.
     
  • Automate procurement and distribution processes - Complex supply chain involve multiple legs in procurement and distribution. In order to scale business, many decisions need to be automated. For example, we help our FMCG & CEP customers in identifying nearest distribution centre that can serve customer by modelling geographic and territorial complexities with an objective of reducing cost. We help our Dairy customers in automating sourcing decisions for milk procurement involving farms, chillers and processing plants.
     
  • Progressive learning capabilities - We strongly believe in having integrated planning and execution capabilities. This model enables us to identify levers to deliver continuous ongoing value. Insights from execution data is harnessed to tune planning algorithm recommendations and improve accuracy of master data sets. We harness vehicle tracking time series data to make execution proactive and simple.
     

Advancements in big data, data science and operations research techniques have helped us to build "Cognitive Sense & Response" system.
 

In our next blog, we will touch upon how this technology foundation is being leveraged to solve deeper logistics problems for Courier, Parcel and Express (CEP) domain.

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