Quantzig’s Oil & Gas Sales Cycle Insights: Demand Forecasting Solution
Highlights of the Case Study:
Game-Changing Solutions for the Energy, Oil, and Gas Sector
The global oil and gas industry is facing specific complex challenges, including upstream volatility, midstream constraints, industry consolidation, and shifting customer demands. Demand forecasting has become an important issue related to national energy security and economic development. The outbreak of COVID-19 in 2020 resulted in a dramatic slowdown in energy consumption, leading to significant price fluctuations on a global scale. Therefore, accurate prediction of oil demand is imperative to fulfilling the customers’ orders in time.
How does demand forecasting work?
1. Data-Driven Analysis:
It involves a meticulous data-driven analysis of various factors impacting consumer behavior, sales history, and market trends. Utilizing AI solutions and machine learning algorithms, businesses can sift through vast datasets to identify patterns, correlations, and anomalies critical for accurate predictions.
2. AI-Powered Forecasting Algorithms:
AI-based demand forecasting software employs advanced algorithms and machine learning models to generate precise predictions. These AI-powered solutions analyze historical data, current market trends, and external factors like seasonality or marketing campaigns to provide forecasts that are adaptable, accurate, and can support strategic decision-making in areas such as inventory alignment and capacity planning.
3. Integration with Supply Chain Optimization:
This tool seamlessly integrates with supply chain management, enabling businesses to optimize their supply planning processes. By automating retail business processes, demand sensing, and replenishment, companies can achieve perfect inventory levels, reduce excess stock, and cut costs while ensuring customer satisfaction and loyalty.
4. Strategic Planning for Future Growth:
Beyond short-term and long-term forecasting, this tool contributes to strategic planning. Businesses can use accurate predictions to align inventory, plan after-sales services, and make informed decisions on marketing campaigns. This forward-thinking approach not only ensures adaptability to demand fluctuations but also provides a foundation for future planning and growth.
Types of demand forecasting
Short-Term Forecasting:
Short-term demand forecasting focuses on immediate needs, typically covering a few weeks or months. It’s crucial for day-to-day operational management, ensuring that businesses meet current demands efficiently. AI-powered forecasting tools excel in providing accurate short-term predictions, enhancing businesses’ ability to manage inventory and adapt to dynamic market conditions.
Long-Term Forecasting:
Long-term demand forecast extends its horizon to cover several months or years, aiding businesses in making strategic decisions for future growth. This type of forecasting is invaluable for capacity planning, integration capabilities, and strategic planning. It involves a combination of statistical forecasting, consensus forecasts, and deep analytics to provide insights into future market trends.
Consumer Goods Brands Forecasting:
It is particularly crucial for consumer goods brands. AI-powered solutions and automated forecasting processes are tailored to adapt to the ever-changing consumer preferences and market trends. Accurate forecasts not only ensure perfect inventory levels but also contribute to cost-cutting and maintaining customer loyalty in the competitive consumer goods market.
Business Effect and Flexibility:
An important facet of demand forecast is its effect on business operations. Businesses can monitor forecasting effectiveness through data integration, storage, and analysis, providing insights into sales history and marketing campaign impact. A flexible pricing strategy, coupled with high-quality support, enables businesses to adapt their business strategies based on real-time data, solving problems efficiently and maintaining operational excellence.
The Challenges of the Oil and Gas Company
A global oil giant approached Quantzig to help optimize its demand forecasting systems. The client had huge sales and inventory data volumes but lacked the necessary tools to forecast demand accurately and generate actionable insights. The implications of its inaccurate demand forecasting resulted in either overstocking or understocking of the inventory, leading to reduced margins.
Owing to incorrect planning, the client was also facing issues resulting from a high number of unfulfilled orders and high inventory and finished goods holding costs. This resulted in reduced margin and increased customer dissatisfaction levels. The client approached Quantzig to leverage its data-driven analytical approach and deploy a robust solution to accurately forecast demand and ensure that oil is produced at the right time and delivered seamlessly to reduce inventory holding costs and inconsistencies in the supply chain.
Aiming to develop a superior oil demand forecasting function, the client approach Quantzig to forecast demand accurately.
Demand Forecasting Analytics for the Oil and Gas Industry
Quantzig’s demand forecasting analytics experts helped the client revamp its demand forecasting strategy by delineating reliable data from the data sources to characterize inventories, sales, promotions, customer contracts, etc. Quantzig engineered an automated data pipeline to collect and cleanse the data. It used this data set to forecast demand on a weekly and monthly basis for all the client’s products. This was accomplished with the use of advanced machine learning models.
Our experts also put in place a process of feature selection, model analysis, and outlier analysis to develop a set of time series models that decomposed changing trends and volatility of our client’s historic sales demand. Quantzig experts also implemented a reclassification of products/SKU based on the client’s sales revenues to set up a comprehensive oil and gas demand forecast incorporating seasonality, lead times, and event-based forecast.
Impact Analysis of Quantzig’s Demand Forecasting Solutions
The solutions provided by Quantzig enabled the client to redefine its production and distribution processes, which ultimately resulted in improved margins and satisfied customers. Our oil and gas demand forecast solutions also helped the client topredict futuresalesby using historicalsalesdata to make informed business decisions.The other specific areas of impact on the client’s business were as follows:
- Reduced inventory and finished goods holding costs by 7%
- Reduced operating costs by 6.5%
- Streamlined the order management process
- Increased the profit margins by 15%
- Achieved a 24% reduction in unfulfilled orders
- Gave insights into the sales cycle
- Improved the accuracy of demand forecasting by up to 85%
Key Outcomes
Quantzig’s oil and gas demand forecast solutions were able to resolve all the major pain points of the client. The client was able to derive an analytics-based demand-supply plan that helped optimize its business to a significant extent and set it on the path to further growth. The client improved demand forecast by up to 85%, which helped streamline the production and delivery of finished goods. This also helped to check overheads, such as inventory management and finished goods holding costs, leading to growth in profit margins.
Broad Perspective on the role of Demand Forecasting Solutions in the Oil and Gas Industry
Companies operating in the oil and gas industry need to reduce waste, improve resource allocation, and increase sales and revenue. Quantzig’s solutions can help predict demand, which streamlines production and delivery while reducing wastage of products and resources. Our insights can also be used to minimize inefficiency arising from uncertainty, monitor price fluctuations, and understand the future growth trajectory of the business.
Key Takeaways
- Are imperative to projecting demand accurately
- Help reduce uncertainty and cater to consumer demand efficiently
- Reduce stockpiling of inventory and finished goods
- Improve supply chain management
- Increase profit margins
- Provide insights into sales cycles
Related articles:
Connect with us