This can make good management look bad by not consistently meeting profit goals despite solid decision-making. The problem is that the decisions are not based on the most current information in the most useful form. Minimizing volatility and error in profit forecasts allows more realistic views of the performance of business unit management. If profit goals are better understood, then corporate-wide strategies can be better developed to focus on selling and producing the most profitable products.
Solution. This can be addressed using pricing analytics for aggregation of data across business units and functional silos to arrive at historical summaries. Additionally, pricing analytics ensures that profitability is calculated consistently across all business units. Having consistent data that are summarized in automatic systems minimizes human errors. Because this historical information is more reliable, goals can be established using a more accurate baseline.
Once historical information is assembled into an accurate format, forecasting techniques can bracket reasonable expectations of future profits. Sensitivity studies then can be performed to examine the effect of market conditions. This allows for forecasts based on solid data and sound statistical approaches, not gut feel.
A critical challenge affecting the industry is growing competition from overseas firms. These companies frequently have fundamental advantages such as lower cost of labor, less stringent environmental regulation, advantaged proximity to feedstock and governmental financial support. Because foreign competition is so significant, the bulk chemical industry may follow the path of the pulp and paper industry. Within the past five years, a large number of domestic pulp and paper companies have closed plants or gone out of business because of strong foreign competition. Like chemicals, pulp and paper production is very capital intensive. Only those with the highest margins survive.
Solution. To remain competitive in the global market, U.S. chemical companies must do at least one of three things. First, serve a domestic market out of reach to a foreign competitor, e.g., compressed gases. (It is extremely uneconomical to transport liquid nitrogen or cylinders of carbon dioxide from China.) Second, improve business processes so that margins are higher than competitors. Third, exploit non-economic product differentiators such as quality, customer service, inventory management, etc.
The first point may be difficult to change depending on the core competency of the company. However, pricing analytics can help identify low margin products where a company is not as competitive. Strategic decisions can be made based upon these data about whether to drop these products.
The second point can be addressed using optimization. This technique relies on forecasts and thus comes last. Optimization utilizes mathematical techniques such as linear programming, nonlinear programming, multiple integer programming and dynamic programming. It can improve profitability by: minimizing turnarounds associated with product switches; effectively allocating product manufacturing across multiple locations; giving production priority to higher-margin products; and optimizing product yields based on raw material, production and product prices. This approach does not address any fundamental advantages of foreign competitors but does ensure that domestic facilities operate as profitably — and thus as competitively — as possible.
The third point, non-economic product differentiation, can be tackled using pricing analytics to analyze customer-specific costs on a product-specific basis.
A way forward
Price management allows companies not only to improve their profitability in spite of challenging market conditions but also to create a strategic competitive advantage. When chemical firms become more efficient and better direct their resources, everyone wins, especially the shareholders.
Dr. Jeff Kabin is a senior business consultant with PROS Pricing Solutions, Houston, Texas. E-mail him at email@example.com.