This set of practice, could help cut down the value loss across the chain. However the question that arises is that how would uncertainties like natural disasters, or law enforcement related to reduction in carbon footprint be incorporated in this model to reduce its negative effects.
Monday, September 22, 2014
Fuel Management: Securing value across India's coal supply chain by AT Kearney
Coal is the primary source of energy in the country. In spite of being the third largest global coal producer, India is also ranked third for highest consumption and import of coal. Although production of coal increased by 4% since 2007, an annual growth in the demand of nearly 7% has been observed. This has significantly increased the import demand from nearly nil in 1990 to 23% in 2012.
Coal accounts for nearly 60- 70% input cost in a thermal power plant. Hence managing coal is very crucial to control value loss. As per AT Kearny; managing coal is complex, with an array of issues across the supply chain—from sourcing to logistics management, bulk handling, yard management, and overall quality management. In India, which has an emerging market, the addressable value loss can reach 7 to 12 percent of the total cost of coal across the entire chain.
Value is lost generally in coal sourcing. The thermal plants have a long term contract with domestic sources of coal. But they are unable to fulfill the requirements; hence the plants are relying on alternative options like spot and short term contracts and imports. However, this leads to logistical issues like capacity constraints (including storage and transportation) and quantity losses due to poor external infrastructure. Also improper quality measurement and inefficient yard and stockpile management leads to loss of quality across the supply chain.
AT Kearny has helped numerous plants to plug the value loss by adopting a comprehensive set of best practices across three dimensions-
1) Planning and sourcing-
Identifying the most cost efficient source and most optimal blend is very essential to plant profitability. Determining and comparing the total cost of coal delivered, port costs, logistics and indirect costs like quality losses is important. Also an in depth study and understanding of the global coal market is necessary to make the appropriate decision, while importing. For example, the small and mid-size coal mines in Indonesia with low cash flow and high sulfur content are a good bet for India, on the basis of cost. Also potential ban on import of low grade coal in China will open up opportunities in other countries in Asia to source cheap and low calorific value coal.
While sourcing, the plants must also consider an optimal blend of the coal types to be fed into the boilers, such that its cost efficient as well as sustainable.
2) Coal Quality-
Quality losses can account to 3-6% of the total value loss. Hence it is very important to track and measure, sample and test accurately and implement the right yard and stockpile management practices.
3) Logistics and inventory-
Coal logistics and inventory planning can be complex, costly and unreliable. As per AT Kearny, many companies rely on experience based logistics planning, which can lead to sub-optimal decision making. Further, significant losses can occur across the supply chain due to handling losses, losses due to wind and pilferage. Considering these issues, AT Kearny has devised 3 solutions -
i. Scientific modeling of the supply chain which includes indirect costs like penalties,vessel demurrages, dead freight and handling losses need to be accurately factored.
ii. Optimal infrastructure to reduce losses during handling.
iii. The inventory targets need to be synced in with the optimized logistics plan. The right inventory level at each node is determined by allowing for expected lead times and supply chain variations while ensuring acceptable service levels that prevent stock-outs. Reduction in safety stock is essential for optimal inventory levels, which can be achieved by reducing demand variation and lead times. Demand variation can be reduced by accurate forecasting while faster shipping and minimizing pre-berthing delays can reduce the lead times.
Inventory levels can be further reduced by employing a multi-nodal network with parallel inventory stock points. Safety stock should be maximized at the node that has minimum quality and quantity losses to reduce value loss.