With revenue of Rs 17,563 crore and 125,000 vehicles sold in FY20, Ashok Leyland is India’s commercial vehicles behemoth. The company is the world’s largest supplier of defence logistics vehicles. It is the fourth largest manufacturer of buses and the tenth-largest manufacturer of trucks globally.While the company is expanding its business, AI-led digital transformation is supporting its business growth.
According to Venkatesh Natrajan, the company’s CDO, Ashok Leyland was an AI-supported organization, then it transformed into an AI-enabled organisation and now, the company is aiming to become an AI-led one by building a lot of capabilities.
Natarajan also believes that the outputs of using AI must also align with the business objectives. “This is a very important filter that we have so that we don’t take any digital or AI initiatives just for the sake of it and we have clear cut business goals which we have achieved through each of the use cases,” he said.
The commercial vehicles manufacturer has established a separate group focusing on business analytics called the Analytics Center of Excellence. The group has been trained in data science and is focusing on driving AI within the organization.
In Ashok Leyland’s data science team, folks from the business side are also a part of it who act as analytic evangelists. Their role in this team is to identify challenges that their respective business functions are currently facing and how AI-enabled analytics can really play a role.
Ashok Leyland’s tech team is a combination of in-house and outsourced where more than a hundred people lie in the former category.
While the company started its digital transformation journey a decade ago, in 2016, the company started looking at digital not only for improving efficiencies or building digital for business optimization but also for generating new revenues and building new business models.
This was done with the launch of four digital platforms—iAlert, a connected vehicles platform; Service Mandi; LeyKart, a digital commerce platform for selling genuine Ashok Leyland spare parts; and e-Diagnostics.
In 2019, Natarajan came out with the ABCD strategy (each letter denoting a technology of focus–artificial intelligence, blockchain, conversational platforms, and digital twins, respectively).
“While building digital assets will continue, the ABCD strategy was established to further turbocharge the existing assets.”
Now the company is connecting all the digital dots i.e. integrating digital assets, products and platforms to gain business value.
“Earlier, we were doing analytics, then we started prognostics and we are moving towards cognitive services. With analytics, we were identifying patterns with the data, with predictive capabilities, we started forecasting what could happen in the near future and now with cognitive, we’re going to the next level of AI where we can enable human-led decisions using the same data.”
Using AI for saving costs
The company’s AI-led digital initiatives have helped customers in preventing numerous cases of vehicle breakdowns and also helped customers avoid additional costs.
iAlert enables real-time fleet monitoring across various vehicle parameters. It brings together advanced Vehicle Health Monitoring Diagnostics and Reports & analytics capabilities to provide valuable data on vehicle’s performance, predict service requirements, helps customers plan maintenance schedules.
When a vehicle comes for servicing, the service engineer already knows how it is performing. Leveraging AI-driven prognostics, the company is able to identify potential areas which could lead to vehicle breakdown in the future and get it corrected even before a complaint is raised.
“This has been beneficial for all stakeholders. For us, it reduces our warranty costs, for the dealerships, it enhances revenue, and for customers, it guarantees uptime for the next 4-5 months till the next service is due,”
Another example of cost savings is a solution for fuel pilferage which is helping customers avoid the excessive cost of fitting an additional fuel sensor (costs around Rs 10,000 to 12,000) to identify the amount of fuel lost.
“This was done by using data-driven insights. Based on our onboard engine control system, ECU (Electonic Control Unit) data and our fuel sensor data, we were able to build AI logic appropriately and we are now offering that service to our customers.”
AI is also being used in pattern recognition and predictive analysis. The company has around 18 variants of ECU (Electonic Control Unit) in BS-6 and more than 1500 error codes. The automaker uses its own proprietary algorithms to predict which error codes can occur in the vehicles based on past history.
If a customer’s vehicle has encountered an error ABC on the vehicle and visited the service outlet for the same, the company is able to predict whether other errors (DEF for instance) can happen on the vehicle in the future or not.
ML algorithms are also being used for cross-selling parts. A tool recommends additional parts to retailers through a cross-selling approach to enhance the parts revenue.
With the gigantic availability of data, the automaker has been able to create a live breathing digital model of vehicles–digital twin.
Digital twins are fuelled by the integration of data from multiple sources–manufacturing data, servicing data, vehicle operational data.
“Digital twin uses data related to vehicles after they are produced and used by customers. These are continuously evolving models that can rapidly reduce the time between designing to production, production to service, and repeat services, repeat issues.”
