The recent conflict in Iraq is just one of the variables affecting energy prices in the U.S. Supply and demand, seasonal weather fluctuations, and economic conditions can all influence petroleum, natural gas, and electricity prices.
Spikes in energy prices can play havoc for companies in heavy industries such as chemical plants, refining, iron and steel, etc., as they are among the biggest global consumers of energy.
For instance, companies in heavy industry are expected to increase their global energy consumption from 200 quadrillion Btu in 2010 to 307 quadrillion Btu by 2040, according to the U.S. Energy Information Administration.
Corporate decision makers for companies in heavy industries can use analytics to evaluate different factors that can affect energy costs over the short term and then use these insights to hedge against volatile oil, natural gas, and electricity prices.
For example, a CFO for a chemical manufacturer can use data discovery and analytics tools to identify and scrutinize key factors that are leading to volatility in electricity prices for plants it operates in different regions. These components can include local energy demand, availability of different generation sources, and changes in distribution costs.
From there, the CFO can use analytics and data visualization tools to estimate how electricity prices for plants in different locales are expected to change over the short term and use these insights to try to lock in favorable price caps with electricity suppliers. Meanwhile, the chemical manufacturer that deals with a multi-state energy provider might lock in a fixed price for all of its locations.
Companies in manufacturing and transportation that rely heavily on oil can use analytics to gauge the impact that market sentiment, trading activity, and supply/demand fundamentals are projecting over the short term (one-month, three-month, six-month increments) and where market prices are headed. They can then use these insights to lock in prices for particular grades of crude oil for the desired periods of time.
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