A Report On Castrol India Ltd. , Mumbai Assignment: Supply Chain Executive Summary Castrol India LTD. Castrol India Limited is a Public Limited Company with 70. 92% of the equity held by Castrol Limited UK (part of BP Group). From a minor oil company, with a share of about 6% in 1991, Castrol India has grown to become the second largest lubricant company in India with a market share of around 28%. Castrol India manufactures and markets a range of automotive and industrial lubricants. It markets its automotive lubricants under two brands - Castrol and BP.
The company has leadership positions in most of the segments in which it operates including passenger car engine oils, premium 2-stroke and 4-stroke oils and multigrade diesel engine oils. Castrol India has the largest manufacturing and marketing network amongst the lubricant companies in India. The company has 5 manufacturing Plants across the country, including a state-of-the-art plant in Silvassa. The company reaches its consumers through a distribution network of 270 distributors, servicing over 70,000. retail outlets.
From a minor oil company, with a share of about 6% in 1991, Castrol India has now grown upto a market share of around 28%. Product and services * Passenger car oil * Gear Oil * Diesel Engine oil * Two wheeler engine oil * Grease * Coolant * Castrol Supply Chain Network Overview * Manufacturing facilities : In India there are 12 production facilities with major ones at Patalganga, Silvassa, Tondiarpet, Paharpur. Each production plant has its own capacity in terms of different packing lines and not SKU. | * Plant and capacity data
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Daily available filling capacities across current locations(in KL) - Single | Shift w/o overtime*Data taken by project Report | | | Distribution: Inbound Logistics: The base oil for Castrol is centrally purchased by British Petroleum. Some of the Indian refineries also provide base oil to Castrol India Limited. The oil is brought to the plants by tankers from offshore tanks. Castrol India Limited has four plants-Patalganga, Silvassa, Paharpur and Tondiarpet and in total 12 filling stations.
Outbound Logistics: Castrol has three tier distributor structure-distributor hubs (CDC/RDC), carrying & Forwarding Agents (CFA) and Distributors. The transportation from manufacturing plant to distributor hub is called Primary Transportation (P0). Transportation from distribution centre to carrying & forwarding agency (CFA) (P1), from warehouse to warehouse (P2) and warehouse to customer and distributors is called Secondary transportation. The entire country is divided into four zones North, East, West and South.
There are 30 CFA,2 DC and 4 Marine warehouses in India. The diagram below shows the supply chain distribution structure at Castrol India. There are five layers - Supplier, Plants, Distribution Hubs, Warehouses and Distributors. Castrol has recently implemented DRM in which demand is generated at the CFA level once the inventory at the distributor level falls below an established norm. * The diagram below shows the supply chain distribution structure at Castrol India. There are five layers - Supplier, Plants, Distribution Hubs, Warehouses and Distributors. Castrol has recently implemented DReaM in which demand is generated at the CFA level once the inventory at the distributor level falls below an established norm. Global Reach: The global reach of British Petroleum is shown in the below mentioned figure. Castrol is a subsidiary of that. Planning Process: Forecasting: Generating production forecasts is a key business process in the oil and gas industry. Production forecasts are used to calculate cash flow using economic models and to assess reserves in the corporate portfolio. These forecasts impact the financial health of the company and its market value.
To generate forecasts, the super majors use in-house reservoir simulators and commercial simulation products, several of which exist on the market. Generally, companies use a variety of methods for production forecasting. Production forecasts for brown fields, i. e. fields currently in production, are regularly updated with production data acquired with off-take volumes. Many production forecasting software products on the market are generally applied on a fit-for-purpose basis. Reservoir simulation is a standard part of the reservoir engineer’s toolkit for generating production forecasts.
The reservoir models have become more sophisticated over the years, due to the increasing computing power available, with the creation of earth models and use of high-technology tools to acquire data for history matching. For brown fields it is common practice to use a reservoir simulation model and history to match the model with new reservoir data on a regular basis and run the model in forward prediction mode to generate forecasts of oil, gas and water production volumes. Use of 3-D seismic data acquisition became widespread in the 1980s and 1990s.
This has allowed construction of detailed reservoir models of the subsurface architecture and identification of additional oil (new zones, bypassed oil, etc. ). Increasing use of geostatistical models during the 1990s has raised the awareness of risk and uncertainty and their impact on decision-making. The driving force has been to reduce the bandwidth of uncertainty, i. e. to narrow the range of uncertainty by using multiple realisations. Systematic application of statistical techniques may be used to understand the predicted reservoir behaviour and the range of production forecasts.
Production forecasts can also be generated using traditional methods, such as decline curves. Classical reservoir engineering methods, such as material balance, should also be in the reservoir engineer’s toolbox. It is important to recognise that the reservoir simulator should not be used as a ‘black box’. For history matching, the production data has to be quality-checked to ensure good quality control and validity. The forecasts generated by a reservoir simulator should be consistent with other reservoir engineering methods that are used, for example, in gas field P/Z plots (i. . the visual image of the gas material balance, where the original gas volume equals the remaining gas volume plus the volume of gas produced). Future trends in real time production forecasting with automatic history matching will include production data and 4-D seismic data, the creation of geo statistical models and multi-realization simulation models for forward prediction. This will still require reservoir engineering intervention to assure and control the quality of the output.
With the advent of the e-field, an executive might be directly linked to the same computer as the reservoir engineer and can view, on a screen at his desk, the corporate production forecasts and the corporate reserves being updated in real time. Oil industry (Castrol) forecasts are generated using the best-practice techniques of time-series modeling. The precise form of time-series model used varies from industry to industry, in each case being determined, as per standard practice, by the prevailing features of the industry data being examined.
For example, data for some industries may be particularly prone to seasonality, i. e. seasonal trends. In other industries, there may be pronounced non-linearity, whereby large recessions, for example, may occur more frequently than cyclical booms. Approach varies from industry to industry. Common to analysis of every industry, however, is the use of vector auto regressions. Vector auto regressions allow us to forecast a variable using more than the variable’s own history as explanatory information. For example, when forecasting oil prices, we can include information about oil consumption, supply and capacity.
When forecasting for some of our industry sub-component variables, however, using a variable’s own history is often the most desirable method of analysis. Such single-variable analysis is called univariate modeling. We use the most common and versatile form of univariate models: the autoregressive moving average model (ARMA). In some cases, ARMA techniques are inappropriate because there is insufficient historic data or data quality is poor. In such cases, we use either traditional decomposition methods or smoothing methods as a basis for analysis and forecasting.
It must be remembered that human intervention plays a necessary and desirable part in all our industry forecasting techniques. Intimate knowledge of the data and industry ensures we spot structural breaks, anomalous data, turning points and seasonal features where a purely mechanical forecasting process would not. Inventory Planning: The company recently had implemented an inventory optimization application from Tools Group, Amsterdam, called DPM (formerly, Distribution Planning Model). But Tenaglia knew that technology was only part of the solution.
After gaining some experience with the software to understand its capabilities, the European division of Castrol undertook the hard work of organizational change, creating a supply-chain planning department that was totally separate from execution functions. Aggregate Planning Methodology: Castrol initiated a program to improve their Sales and Operations Planning (S&OP) processes. The team was faced with reactive supply chains caused by forecasts that were inaccurate, unreliable and incomplete. The forecast did not extend to all SKUs and calculations required intensive manual work.
The supply chain was still widely order-driven and structured to be reactive, rather than proactive. The demand forecast was carried out by sales and marketing, so the supply chain people reworked the forecast in order to trigger replenishments. We had a lot of uncertainty due to poor forecast practices. ” The inventory side was also challenging. Most slow moving products had excess inventory. Fast moving products were often out-of-stock. Safety stocks had been set manually, based largely on personal experience. In the calculations, there was little formal sense of supply and demand uncertainty.
Safety stocks were infrequently adjusted, and when they were, it was often in reaction to a single event. For instance, an under stock situation would often trigger an increase in safety stock levels. addition, planners were expediting to constantly to overcome the poorly derived inventory targets. This expediting was triggering production reschedules and urgent deliveries, increasing costs and amplifying supply chain noise. “We’ve seen dramatic increases in our service level with significant reductions In inventory across Europe”.
Castrol identified the need to build an effective S&OP planning process which they would implement in one country and then roll out across Europe. The resulting system would coordinate ten independent systems into one global and unified coherent planning process, encompassing the “downstream” portion of Castrol’s supply chain, from blended oils and packaging through to the end user customer. The system would insure high service levels to customers, reduce stock-outs and cut back on manual expediting. BP Castrol quickly came to the conclusion that to accomplish the above, they needed to include nventory in their S&OP process. Improving the forecasting process was clearly required, but alone it would not achieve the high customer-service levels they wanted. A Castrol uses software that analyzes demand history across multiple dimensions so you can obtain the best possible forecasts and inventory targets for driving your supply chain. Innovative and advanced technologies enable Castrol to improve and automate planning processes. Solutions p key supply chain planning areas such as Demand Planning, Demand Sensing, Promotion forecasting and Inventory Optimization.
BP Castrol’s resulting system delivered the target service levels, reduced out of stocks, and largely eliminated the expediting. Over a two year period, KPIs improved dramatically. Aggregate forecast accuracy improved by 15% on average and channel forecast accuracy* improved to 90% for retail. (* % of SKUs demand within 20% of a 2 months aged forecast) Total network inventories were reduced by 35%, 20% in the first year after implementation and then 20% again in the following year. Despite the lower inventories, service levels to customers, as defined by “line fill rates”, were up by 9% overall.
The system has become a unique company standard for excellence in forecasting, customer service level planning and inventory optimization. The system now ps 29 installations, 25 countries and has been expanded to two continents. The Payoff: Reduced Inventory and Higher Service Levels The replenishment flows had to be synchronized with the demand signal through optimized inventories. They improved demand sensing by generating more robust and reliable forecasts. They implemented an improved and standardized monthly demand forecast process cycle.
A single point of accountability was instituted. Promotion planning and monitoring was also improved. They improved demand response by improving safety stocks using a solution provided by Tools Group. Reliable statistical modeling accurately measured demand and supply chain volatility. Reliable inventory modeling and mix optimization techniques accommodated this volatility and accurately set the inventory targets required to achieve a responsive inventory mix. The Payoff: Reduced Inventory and Higher Service Levels BP Castrol’s resulting system delivered the target service levels, reduced ut of stocks, and largely eliminated the expediting. Over a two year period, KPIs improved dramatically. Aggregate forecast accuracy improved by 15% on average and channel forecast accuracy* improved to 90% for retail. (* % of SKUs demand within 20% of a 2 months aged forecast) Total network inventories were reduced by 35%, 20% in the first year after implementation and then 20% again in the following year. Despite the lower inventories, service levels to customers, as defined by “line fill rates”, were up by 9% overall.
The system has become a unique company standard for excellence in forecasting, customer service level planning and inventory optimization. The system now ps 29 installations, 25 countries and has been expanded to two continents. Pricing: The rising crude prices caused severe Base-oil supply imbalances. The shortage of raw material also severely impacted many of the small-scale players in the Indian lubricant market. (Castrol) Further, the supply uncertainty triggered rapid Base oil price increases. This in turn caused most lubricant players, including Castrol, to take multiple price increases during the year. . Economic slowdown the global financial crisis in the second half of 2008 severely impacted the Indian stock market and caused the rupee to depreciate by about 20% with respect to the US Dollar. The rupee depreciation offset benefits of softening Base-oil prices during the latter half of the year. The lower overall economic activity level and restricted availability of finance also impacted automotive sales and trucking activity in the second half of 2008. a slow-down in the construction sector earlier in the year due to the high interest rate regime was further affected by lack of credit in the second half.
This has caused an overall slackening of demand in the lubricant market, particularly in the industrial, mining, off-road and fleet-operators segment, in the last quarter of the year. The lubricant channel partners reacted to this period of uncertainty by tightening their inventory levels, causing a one-off impact on lubricant volume in the second half of 2008. 2. Crude oil Crude prices continued to remain an important cost input element to Base-oil in addition to supply demand economics. In 2008, crude prices rapidly increased and crossed US$145 a barrel in July.
This triggered steep increases on various crude derivatives including Base-oils across the globe. In the second half of the year the crude prices collapsed but the depreciation of the rupee against the US Dollar offset some of the increases. Refiners also carried inventory of high priced crude procured earlier and as a result, the benefits of the falling crude prices were not passed on by refiners to industrial customers in tandem with the crude prices. The following graph indicates the trend of crude prices 3. Base-Oils and Additives
The steep rise in crude prices severely impacted the Base-oil prices with multiple price increases charged by the Base-oil refiners. At its peak, the Base-oil price touched uS$1800 per ton in the second half of the year, almost doubling from 2007 exit levels. The increases were regular and quick until September 2008. Supply situation had further deteriorated due to refinery closures, production issues and turnaround at domestic and international sources. Due to limited availability, customers were put on allocation by major refineries.
Post the crude prices falling from the high of over uS$145 a barrel and the economic slowdown, the availability of Base-oils witnessed strong improvement. However, there was very little reduction in prices till the last quarter due to the depreciation of the rupee against the US Dollar and the high inventory of Base oils held by refiners in anticipation of demand. Input costs of additive manufacturers witnessed a rapid increase and with the expectation of higher demand, the pricing balance tilted in favor of additive manufacturing companies.
Additive prices witnessed an increase of circa 25% over the 2007 levels. However, Castrol has managed the volatile input prices by ensuring effective procurement and inventory management. Productivity of purchasing spends and working capital management has been an area of focus. Tight control of Base-oils and additives inventory has ensured higher inventory turnaround and release of cash in a timely manner for the business. EXCECUTION: Checking and Controlling of Inventory Plan: The management conducts physical verification of inventory at reasonable intervals during the year. b) The procedures of physical verification of inventory followed by the management are reasonable and adequate in relation to the size of the Company and the nature of its business. (c) The Company is maintaining proper records of inventory and no material discrepancies were Noticed on physical verification. Performance Evaluation Parameters: • Facilitate planning, execution, and management • Enhance visibility • Reduced inventory and demurrage cost • Improve productivity and operational efficiency • Respond quickly and synchronize changes • Reduced costs • Improve decision making Increase customer satisfaction • Build strategic relationships • Improve agility, competitiveness, and business performance Information Technology : In the oil and gas industry, knowing where and what product is being produced or delivered is essential to an efficient and effective organization. The use of IT to offer possible remote control of equipment and facilities, transaction services monitoring, and even transportation management service is important. Firms like British Petroleum have developed new systems to aid in their business operations by using these technologies.
Past and present methods of communication in the oil and gas industry have included satellite communications (on a limited basis), Cellular and Specialized Mobile Radio, fiber-optics, and general offshore telephone service using radio frequencies consisted of a radiotelephone based antenna/transmitter that would allow communications between any offshore oil platforms and land-based telephone networks. These systems required a team of employees to monitor and report to management on a continuing basis.
Currently, cellular and specialized mobile radio services are in the process of providing better services to the offshore drilling platforms and are generally expected to replace the older offshore radiotelephone systems found primarily in the Gulf of Mexico region. Such systems make use of these technologies to reduce and/or eliminate on site monitoring by a team of employees. With respect to labor costs, the organization could save substantial amounts of money because there is no need to have personnel continuously on location to inspect, monitor, maintain, and/or report conditions.
Wireless data provided by implemented wireless technology would automatically produce reports on processes. Adjustments could be made at appropriate times reducing any overtime payments. The benefits of IT integration to the Castrol as a whole could be substantial. Supply Chain Collaborations, Coordination, And Cooperation Supply-chain management requires an oil and gas company to integrate its decisions with those made within its chain of customers and suppliers. This process involves relationship management by the company. Both customer relations and supplier relations are key to effective coordination of supply-chains.
Often, the interaction between suppliers and their customers are adversarial in nature, based on a negotiated contract that spells out all the terms and conditions by which all parties are required to comply. Instead, a firm can create long-term strategic relationships with their suppliers. In most cases, it is a collaboration process between the oil and gas operating company and its suppliers. One of the weaknesses of a supply-chain is that each company is likely to act in its best interests to optimize its profit.
The goal of satisfying the ultimate customer is easily lost and opportunities that could arise from some coordination of decisions across stages of the supply-chain could also be lost. If suppliers could be made more reliable, there would be less need for inventories of raw materials, quality inspection systems, rework, and other non-value adding activities, resulting in lean production. Coordination from the perspective of British Petroleum Company involves the following issues: * ensuring supplier effectiveness n cost, timeliness and quality * setting appropriate targets for inventory, capacity, and lead time * monitoring demand and supply conditions * Communicating market and performance results to customers and suppliers. A typical challenge in the petroleum industry supply chain is the attitude and anxiety regarding collaboration and information sharing between supply chain partners. While collaboration and information sharing rep-resent a crucial factor for supply chain efficiency. Improved supply chain efficiency in the petroleum industry, therefore, needs a new philosophy in collaboration, even if this means working with competitors.
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