How Mahindra Logistics is aiming to improve efficiencies using ML and cloudWith 17,800+ employees and 475+ corporate customers across India, Mahindra Logistics Limited (MLL) pursues an asset-light business model, providing customized and technology enabled solutions that span the entire supply chain and people transport operations.

The company has created a warehouse management system that has end to end visibility of the warehouse operations using paperless hand-held terminals (HHT) based operations. With real time visibility of inbound operations (Gate-In, goods received note a.k.a. GRN, a system guided Put away) and real time order processing (Order status, system guided HHT based picking, loading) Real-time inventory information (days of inventory, ageing).

In the transportation space, Mahindra Logistics is trying to transform the entire transportation platform by first connecting all its vendor partners who provide the firm transportation as a service (TaaS).

How Mahindra Logistics is aiming to improve efficiencies using ML and cloud“We have created a platform where customers can connect and provide these services online. We are additionally optimizing the customers’ transportation by finding the right transport management system [Oracle Transport Management (OTM), ShipX, Mpodd (created in-house) TMS)], where we are trying to optimize transport requirements in terms of the cost reduction and minimize truck requirement,” said, Shailesh Sultania, CIO, Mahindra Logistics.

The organization has a team of over hundred tech professionals and the digital platforms used are a mix of in-house and third-party developers.

Becoming a data-driven organization

MLL wants to become a fully data-driven company, and according to Sultania, advanced data analytics will play a key role in helping the company get there.

For example, MLL uses analytics to identify the ‘Backhaul’ opportunities for its transportation services. This is helping cut costs and improve asset (Truck) utilization.

The 3PL services provider also does Dynamic ETA (estimated time of arrival) using machine learning of past data of similar trips in the same lane. The machine learning model calculates a dynamic ETA, which predicts very accurately that when that vehicle reaches a particular destination or when the goods will be delivered to the customer.

In the coming months, Sultania will also be focusing on creating a centralized data lake and get deeper into more advanced analytics across the board.

Additionally, facial recognition-based attendance systems have also been implemented for all warehouse and production line workforce. It gives real-time info of resources available at each site, their total working hours etc.

Moving apps on the cloud

MLL is transforming into a cloud-first business, moving all its IT applications to the cloud.

Currently, Mahindra Logistics has a hybrid IT setup, including a mix of applications/workloads running in the company’s own data center as well as on the cloud.

Sultania believes that cloud is a more scalable, more flexible and more accessible model. And that is why MLL relies on strategic cloud partners such as Oracle to run its business smoothly.

“This will give us the flexibility of onboarding a customer or integrating with any customer faster, whereby our services are available on the cloud or on the web-accessible from any part of the world,” he said.

The company’s customers come with their own unique requirements and their own set of systems which needs to be integrated.

“From a technology standpoint, Oracle Cloud Infrastructure provides a platform where we can interface or connect to any system very easily because they come with pre-built APIs with most of the standard ERPs and other key systems. And the monitoring of the message between MLL and the customer is also seamless and can be monitored real time and action can be automated,” added Sultania.

Source link