Demand and Supply Forecasting at Air Products Essay

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Executive Summary
The US Chemicals industry once, one of the largest American industries, is facing an ongoing trade deficit that was aggravated by volatile natural gas prices and a surge in foreign based manufacturing centers. Subsequently, chemical producers doubled the foreign direct investments as compared to ten years earlier. Despite this increase, US chemical industry remained in a trade deficit since 1996.
Air Products, based in Pennsylvania, ranked among the top specialty gas and chemical companies in US. Their high sales are attributed to Worldwide Gases’ sales, derived from specialty chemicals and gases prepared specifically for the electronics industry. Electronics Specialty Materials (ESM), a business unit within Worldwide …show more content…
The numerous SKUs offered by ESM made this tuning process extremely complex, necessitating a focus on high-priority customers and strategically important products.
Role of forecasting in Financial management
Financial forecasting was the foundation for overall ESM global revenue and distribution costs. Following the initial forecast analyses, ESM used the recent history as a guide and estimated the revenue for all the products. The result was a high level statement of anticipated revenue and costs for the following year and was a key input in the projections provided to Wall Street by Air Products’ executive management. However, there were several major challenges, including trying to predict future demand within an inherently cyclical industry. Trying to project customer requirements was also complicated by the product, customer and geographic complexity of the business coupled with a long supply chain.
Forecast process
Exhibit 10 presents the financial forecast that was fairly accurate. It has to be noted that the budget is developed with an eye to the target, but it also factors in judgment about what is achievable given the underlying economic environment. However, exhibit 12, which provided the monthly forecast data, could still be an inaccurate result even with 100% operational correctness. This is due to the difficulty in demonstrating numerically what portion of forecast
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