Using commodity sensitivity to inform financial decision-making

The effects of unpredictability can be felt nearly everywhere you look; Brexit, deteriorating international relations, increasing nationalism, weather events, and cyber-attacks all keep you wondering what’s next. This unpredictability, whether it’s geo-political, technological, environmental, economic, or societal, directly impacts the demand, supply, and prices in commodity markets.

As businesses focus on cost transformation within the supply chain, they need to have the ability to make decisions quickly as commodity prices change. This could include substituting inputs to production, prioritizing and promoting specific product lines, entering or exiting businesses or whole markets, and adjusting pricing.

However, analyzing the impact and timing of these decisions upstream, within their supply chain, and in a multi-currency environment can be a daunting, extensive, and continuous task. In a recent webinar with Marco G. Limito, Senior Manager at Accenture, we explored how organizations can revolutionize financial decision-making through the application of commodity sensitivity modeling in a cloud-based financial planning platform.

As discussed in the webinar, organizations can use a commodity sensitivity model to develop scenarios that can be based on:

• Commodity price fluctuations
• Foreign exchange
• Timing impacts resulting from hedging and supply chain inventory
• Projected consumption of commodities and components

By understanding the impacts of commodity fluctuations on business performance, organizations can evaluate different purchasing and pricing strategies, in addition to the likely impacts on their markets. This allows businesses to continuously understand the implications to their supply chain and deploy the necessary corrective actions to improve outcomes and capitalize on opportunities.

Where are commodities in the supply chain?

The relevant commodities to analyze differ from business to business. Some businesses are impacted by crude oil prices, which may be used in generation of energy to transform or transport their products. Other commodities include metals such as gold, copper, or rare earths, grains, and meats. Soft commodities include cotton, sugar, cocoa, or lumber, and are used in manufactured goods, food, and clothing.

Commodities prices not only impact the cost of input to the production process but also the inventories of suppliers, raw materials, and work in progress. The cycle to manufacture a finished good also varies between businesses so that inventory timing may crystalize in days, months, or years.

As businesses globalize, traditional commodity modeling in the supply chain becomes more complex and can take weeks or months per cycle when using desktop productivity tools, such as spreadsheets. The Anaplan model that Marco demonstrates on the webinar aggregates commodity prices, indices, and associated demand across the business to quickly assess the relevant components in real-time calculations. The impacts and scenarios assessed can be linked to production cost planning and financials to deliver a more holistic view of the business.

How can commodity sensitivity help improve business performance?

Steering business performance through constant waves of market instability can be difficult to accomplish without a structured and holistic strategy. Companies that perform bottom-up forecasting with legacy planning tools or manual environments are prone to lengthy processes producing analyses that are already outdated by the time they are delivered. With such complicated and decentralized processes, it can be difficult to understand if assumptions are universally adopted and where variances in the output have originated.

With the right approach and technology, organizations can improve levels of market and commodity predictability, and react to pricing opportunities faster, which may protect profit or gain market share and effectively manage risk and liquidity. Commodity sensitivity trends can be used to understand shifting profit pools and to inform footprint strategy.

By merging financial, supply chain, and external market data with real-time predictive analytics and forecasting models, organizations can use a commodity sensitivity solution like Accenture’s to optimally analyze and mitigate the impacts of commodity price fluctuations on business performance.