City Gas Distribution (CGD) networks are turning out to be the next big downstream expansion in India, after fuel retailing, with investments of as much as ₹1.1 trillion ($13.8 billion) expected over the next decade. CGD is one of the most crucial sectors to push for incremental natural gas demand and achieve the Indian government’s ambition to increase natural gas from 6.2% of the primary energy mix to 15% by 2030.
As per the Petroleum and Natural Gas Regulatory Board (PNGRB), following the recently concluded 11th CGD bidding round, 96% of India’s population and 86% of its geographic area would be covered under the CGD network. The number of CNG stations is estimated to reach 10,000, a 300% increase, by 2030. Likewise, nearly 78 lakh household kitchens are now getting clean fuel with the number projected to reach 5 crores by 2035.
This mammoth of an expansion plan includes penetrating into high urban areas as well as the rural parts of India. The challenges are aplenty for players like ATGL, Torrent Gas, IOCL, AG&P, etc., but the biggest of them is managing the supply chain of the entire expansion with limited workforce, suppliers, infrastructural resources and visibility into their operations.
The financial risks are also significant, as with every incremental delay, the return on these capital-intensive projects diminishes. To add to it, noncompliance in on-time delivery attracts huge penalties as high as 20 lakhs rupees for a shortfall in achieving cumulative work targets for every natural gas station.
A few other challenges that need urgent attention for these CGD players include managing inventory levels throughout the project, building a supplier base for pressure-regulated materials, incorporating technology into master operational visualization and insights, and getting the technology implementation right the first time.
Although companies realize the necessity for an effective supply chain network to deliver on their expansion, few can claim with any certainty that their networks are truly optimized.
An optimized supply chain network configuration offers the lowest total cost and highest total profit considering the operational and financial risks, while achieving targeted service levels. Given the complexities and the number of touchpoints in the modern supply chain, running operations based on assumptions or human intuition is just not feasible.
In a broader sense, AI/ML-based network optimization helps cater to transportation and route planning for the physical flow of goods, provides local intelligence about accurate placement of supply chain nodes and warehouses, improves multi-echelon inventory levels across geographical areas, and strategizes sourcing using data-driven intelligence, with data not captured using traditional planning methods.
Bristlecone provides a transformative digital supply chain approach that results in a strategic foundation, end-to-end visibility, the right technologies and empowered employees.