Identifying gaps to address through ABG’s intervention:

The leading petroleum and natural gas corporation required support to address its challenges, which included:

• Discrepancy in supply management and business process with variability in response and exports, as per the demand
• Lack of operational efficiency, due to manual process of forecasting to meet the demand

Resolving the concern with ABG Solution

ABG is in the process of implementing SAS Demand-Driven Planning and Optimisation solution to automate demand forecasting system, which will project demand for its domestic liquid hydrocarbon at multiple hierarchy levels—across products, customers and locations. Through this intervention, ABG aims to deliver the target of average forecast accuracy at rolled up levels, which is greater than 90%.

The solution enables forecasting to be done on daily, weekly and monthly intervals at various time horizons. Furthermore, to factor in seasonality, the solution further enables highly accurate and reliable forecast through multiple demand influencing factors, including:

• Variety of internal and external explanatory variables such as price, weather, macro-economic factors, etc.

• Multiple events such as temporary/permanent suspension of plant supplies, holidays, etc.

• Demand diversion and other automated data treatments

The solution’s accurate and reliable forecast improves the oil corporation’s capability to perform scenario analysis. This allows the client to understand the sensitivities and impacts of various demand influencing factors on future demand.

Aiming to achieve scalable business outcomes through ABG solutions

While the implementation of ABG Solution is underway at the petroleum and natural gas corporation, the solution has enabled to foster results as below:

Ensuring cost efficiency through improved supply chain management

• Through streamlining the process, solution enables to improve the accuracy, while forecasting
• Reduction in the inventory’s carrying costs (hauling) through maximised capacity usage
• Reduction in overall supply chain costs, while maintaining service levels and customer satisfaction

Scalable and systemic forecasting process to secure analytical insights through standardising the solutions

• Establishing a systematic process to ensure that the client meets their fast-growing domestic and international commitments through country-level demand forecast across all fuel types
• Creation of robust forecasting process that will enable hierarchical forecasting capturing the impact of causal factors

Building team efficiency on analytical work for qualitative outcomes

• Enabling teams to conduct studies to simulate operational scenarios, such as performance of lower operating levels resulting from pricing or event-based scenarios
• Optimising manpower by minimising the time taken to develop the forecast resulting in more time for scenario analysis and analytical high value-added tasks