Connecting the industrial supply chain
Namrita Mahindro is the Chief Digital Officer of the Chemical Division at Aditya Birla Group.
This article highlights the supply chain transformation journey of the Birla group in the chemical filaments and insulators sector and the role of technology and APIs and connecting the entire ecosystem.
Over the last two years, we have seen unprecedented challenges. The disruption was on both the demand and supply sides. In the chemical sector, we saw the demand for certain products go up significantly, like chlorine, or certain other chemical products, which went into the making of disinfectants, etc. On the other hand, we had other non-essential products, where the demand collapsed completely as there was a constraint on manufacturing. So while some of our plants had to get into business right away, within a week of the lockdown happening, on the other hand, we had others that had to shut down for long periods. There was an impact on the labor; there were transportation issues with the customers and the distributors. There were challenges, but we also saw an opportunity to see how we could reinvent our supply chain; how could we make sure that these challenges across the entire value chain that we were seeing could become a competitive advantage for us.
Supply Chain Digitization Objective
Some areas that we looked at were, establishing a new SLA for our customers and getting from our suppliers; if the logistics costs were going up, what could we do to use techniques to manage that more effectively. To enable that, we developed internal as well as external capabilities. From a people and process perspective, we had to figure out the organization setup we would need to support our supply chain. We needed to build IT and team capabilities. We needed to study the data assets we had, which we could use to improve our intelligence and insights, and create a better environment, to provide seamless services.
We looked at restating our digitalization objective as we were looking at transforming our entire supply chain function. We were going to look at something which was extremely agile.
If there were logistical delays, we went multimodal. We predominantly used to look at roadways as our key transportation mechanism or logistics partner. When we went multimodal, we started looking at the railways and roadways.
We tried to get more autonomous across the value chain for being connected. While we had a control tower and were already connected, to some extent, with our tier one partners, the need was to go beyond that and see how we could connect from a logistics point of view with the entire ecosystem.
We had a very robust and consistent supply chain. 80% to 90% of our supply was pre-decided and repetitive in the pre-COVID era. From there, we went into a very dynamic situation. That was something that we weren’t geared up for. How we could become far more dynamic was something else that we looked out for as part of our scenario planning and execution.
Accepting failure was the other thing that became mainstream within the organization as a culture. Let’s experiment, let’s innovate, even if it means that we repeatedly fail, which is a very native mindset to a startup but not so native to a large traditional organization; this shift happened by being connected.
We were gathering a lot more data. As we took this journey, we wanted to gather more insights and become more intelligent and resilient. The intent was to increase transparency.
Building Our Competitive Advantage
Innovation – We realized that we would need to be far more innovative than we had been previously. We looked at reimagining our supply chain. So the intent was to go away from a very monolithic structure to a far more modular one. We looked at making our supply chain modules as self-replicating elements, which could then be plugged into different aspects of new plants being set up or existing plants where we didn’t have the agility and robustness we previously had wanted.
Operational Excellence – From an operational excellence point of view, it was about looking at how we look at our inbound and outbound logistics and what are some of the things that we could do over there to drive greater agility and excellence.
Ecosystem Play – We have started building up connectedness,
managing risk a lot better and ensuring transparency across the board. We look at connecting to the nth level of our ecosystem, collecting more data, not just about ourselves, our customers, and our suppliers, but also the larger macro and micro economic factors; looking at putting a lot of other elements into play, which would allow us to have a much better ecosystem play. So if there’s a factor impacting our suppliers or customers, then the roll-on effect on us is something we’re trying to determine.
Capability Building – Building new capabilities, bringing the teams up to speed, to look at doing things differently. It was about working on their mindsets, as well as working on their skill sets. This has been done over the last two odd years or so.
Data – The aspiration became to have a unified view of the data across the entire supply chain, procurement, and logistics space. We are still working on being able to look at data holistically as opposed to in silos.
Infrastructure – We have accelerated our cloud journey significantly. Our key aspect has been the number of connections we are trying to create across the entire ecosystem. We are looking at API gateways and partners and piloting different use cases. A mix of partners works more effectively depending on the use case.
Open Innovation Partner Ecosystem
We have 300 plus partners; the product companies and research firms we work with; whether it is the academia, which goes hugely into our startup ecosystem or industry.
The Intelligence Hub
From an intelligence point of view, while we are looking at data, there is a complete platform that we’re building up as an intelligence hub, which takes data from internal and external sources. Some of it is manual, and some of it is through APIs. We pick up some data from social media and other industry bodies, e.g., Bloomberg. The intent is to have that single view of all of the data from an operational point of view.
Striving for operational excellence
We’ve looked at the space in the three procurement and supply chain logistics areas.
Procurement – We realized we had complete automation from the PO process perspective, but the automation was missing prior to that. We would be able to gather all of the information about the various responses we get from RFQs. Earlier, we sent out RFQs manually. We will now have a system whereby the various vendors invited from the ecosystem for a particular RFQ can come onto this platform and submit their responses. Once those responses are submitted, we can judge them on their relevance, product, and requirement fit.
All these decisions are in the system, available to everyone authorized, as opposed to individuals. We are moving from a people-centric to a process-centric approach.
Supply Chain – We have a platform in place which was set up over the last four or five years back. But, it was highly inadequate for us during the pandemic. The need to upgrade that to the next level became important.
Logistics – There’s a lot of work that we’ve been doing for logistics. We automated our entire inbound logistics and created transporter portals. The information flow was two-way, transparent, and available in real-time.
We use RFID tags for our tonners to keep track of their positions. We look at creating more visibility by tying in customs and shipping companies and ensuring complete visibility across the board.
Supply Chain Planning
If we look at a bottom-up approach, we can understand what kind of data is available in the markets. Before COVID, the data we were studying was internal and people-centric. So, we tried to get data points related to the market, customers, and competition.
We’re still in the process of building up a third-party platform. But the ability to bring all of this data together to do far better demand forecasting, demand sensing, and demand planning is what the intent is over here.
Similarly, with the supply side, once we have all the data, we study it and understand our networks, products, placements, optimal plant locations, etc. Because of the uncertainties, first with the pandemic and now with the war, it becomes important to understand the huge impact on our sourcing and production. This is governed by the demand which is created in the market. This end-to-end perspective enables us to plan both demand and supply and will eventually allow all of this to contribute back to maximizing our margins, which is our end goal.
Inbound Logistics Automation
Similarly, with our inbound logistics automation, the amount of time the transport spent coming to the plant, waiting, getting their payments, and their exit has become more streamlined. The cycle time went down by 80%. Weigh-bridge operations have also been automated. To make all of this happen, the interconnectedness across the transporter ecosystems, the transport portal, and internal ecosystems has been key to the success of this particular project. We started with one plant and are now rolling to other plants.
The transport scorecard tracks transporters and their drivers. It has been a huge benefit for our transporter ecosystem. It helps transporters understand how their drivers perform from a safety point of view, a compliance point of view, and a performance perspective. That allows them to incentivize their truckers and optimize who they would provide on which routes far more effectively. We are enhancing this scorecard further, bringing in safety, compliance, and performance data.
Supplier risk across the partner ecosystem
In the early stages of COVID, we realized that many of our raw materials were single-source. This implied that we were at risk. We had to ensure that those single-source suppliers were not at risk of going out of business. We had to ensure that we supported these suppliers financially or otherwise. This is to enable them to continue to be in business and to help them take up their performance levels. We are looking at building a predictive scorecard to bring in far more intelligence than before.
Innovation across the value chain, AI, Metaverse, and Web 3
We have established a new risk management framework. The key aspect over here is the secondary and the tertiary intelligence networks we’ve started building up, which helps us predict risk a lot better and manage risk far more efficiently when things don’t go as planned. The second aspect is a new supply-constrained playbook that we are looking at building up. The intent here is to bring agility and transparency to ensure we can limit disruptive events’ impact on our supply chain.
From a blockchain point of view, we have a couple of early-stage use cases, like invoice discounting or connecting the entire ecosystem from a logistics point of view. We are looking at greater transparency and agility.