Expert Knowledge Partners Bring Business Process Optimization to the Process Industry
By Gerry Cleaves, MyPlant.com
In the 1970s, chemical processors and refiners began to view data as an important asset. During the 1980s, companies began to analyze sales, inventory, and manufacturing data in an attempt to create meaningful information and to use it advantageously. DuPont, for example, used the simple concept of balancing supply with demand to help it understand what is most central to its businesses. It has simplified, improved, and reengineered its processes, putting its businesses in position to understand their marketplace and to create reliable partnerships with key customers and expert knowledge partners—enabling companies who can harness decision-support technology and comprehend what is possible. For Du Pont and many other leading chemical companies this resulted in wider application of expert solutions for Business Process Optimization—the use of computers and mathematical models in production planning, scheduling, and decision-making from Expert Knowledge Partners.
It is becoming increasingly important for multinational chemical processors to improve the global integration of their supply chains—from order acceptance to product delivery. Leading chemical companies are reengineering their supply chains to increase speed, efficiency, and product quality. In the near term, decisions center around how to optimally use worldwide production capacity and distribution capabilities to meet projected demands for finished and semifinished goods. Models that consider longer time horizons are used to analyze different potential capacity expansions options and product-mix changes. Having the right decision-support tools for sales and operations planning is critically important for servicing the company's customers reliably, responsively, and at lower cost.
Decision-Support Tools
Over the last decade, state-of-the-art decision-support tools for production planning and scheduling have been implemented by several leading companies. The objectives of these models are to provide business planners and production schedulers with decision-support tools which allow them to consider:
- geographically dispersed manufacturing facilities
- world-wide customer base and demand forecasts
- finished and semifinished inventories
- product distribution requirements and constraints
- customer requirements such as just-in-time delivery
As early as 1995, BASF reported that they had implemented two supply chain decision-support applications prior to 1992, four by year-end 1993 and 15 by year-end 1994. They expected to have approximately 25 by year-end 1996 and a global rollout of these solutions by 2000. DuPont, too, has consistently used state-of-the-art decision-support tools for production planning and scheduling for over a decade. Long-range planning models have been used extensively for the full spectrum of DuPont Polymer's business, from intermediates to the most specialized engineering products. Business planners used these models to develop worldwide production and distribution plans, for time horizons ranging from six months to several years. Already in 1991, the company reported having 14 production planning and scheduling applications in their polymers department alone that resulted in significant reductions in inventory and greatly improved customer service.
While effective at reducing costs and improving operating performance, these efforts alone fall short for improving long-term and strategic planning—a field of complex problems that involve uncertainty, substantial risk, and complex multiple goals. Simplistic applications of operations research and management science magnify the effect of deficiencies in data and forecasts and aggravate the errors.
The petroleum industry, for example, began to apply Linear Programming (LP) almost from the moment of its inception in the late 1940s. Over time, mathematical programming concepts penetrated all facets of the oil business, from supply, distribution, and refinery planning, to product blending and process control. During the energy crisis of the mid-1970's, several oil companies attempted to extend LP technology for developing strategic plans—20-year worldwide petroleum industry models. In 1975, with the price of crude oil at nearly $30 a barrel, industry observers predicted the price would be $100 a barrel by 1980 and $200 by the turn of the century. Considering that the average 2000 price is under $30 a barrel, the plans developed under these erroneous assumptions were of little value, despite the technology employed. In fact, optimization techniques may have even aggravated the errors.
Currently, such complex problems become much more common and frequently occur even in short-term planning. Perhaps some companies believe that by implementing a forecasting system they would begin making better decisions. However, forecasting is merely statistics-based data processing, a desirable but insufficient first step to better planning. The 1990's are different from the post-WWII period because the customer now largely dictates their preferences and priorities for products, quality, quantity, service and price. As a result, uncertainty greatly increases, is a rule rather than exception, and often brings unpleasant surprises. Forecasts become less reliable.
New Planning and Scheduling Technology
Old methods of planning and scheduling need an overhaul and a revolutionary approach to risk management and uncertainty. New methods must consider multiple goals which may be incongruous and ambiguous. Decision-support technologies need to include good old-fashioned common sense for finding strategies and making strategic decisions that meet all these various needs. The objective is to find strategies that are:
- Optimal, or close to optimal, under favorable conditions
- Good under a wide range of conditions
- Acceptable under the most adverse conditions forecast.
Processing companies that will fare best in the new millennium beyond must listen and respond to the voice of the customer. They must transform information into knowledge and make decisions within a risk-protection framework which allows them to make good decisions under great uncertainty. Manufacturing decisions are difficult to make even in a stable environment, since they involve the assimilation of vast amounts of information. When the unexpected occurs—last-minute order changes, interruption of material flow, or equipment failure—the task becomes more difficult. Even the most knowledgeable employees may find the job overwhelming unless they have access to the appropriate current information and decision-support tools.
Business Process Optimization requires integration of data, solution techniques and business practices throughout the sales, manufacturing and logistics supply chain. The first step is to gather pertinent information and make it available to everyone involved in the planning and scheduling function. The data can then be used to optimize the planning and scheduling process, to improve customer service, and to reduce manufacturing costs.
As the experience of leading chemical companies demonstrates, a holistic approach that integrates the key elements of business process reengineering, organizational development and business information, will expand a company's knowledge and improve its performance resulting in both tangible and intangible benefits. Companies that consistently develop good production plans and adapt their schedules as conditions change to meet the growing needs of their customers will be superior competitors. Those that can integrate this information along the supply chain and make good decisions will have the knowledge to be leaders, not followers.
Finding these Expert Knowledge Partners has always been a challenge, but the rise of the Internet and Business-to-Business portal solutions have made the search easier. A community of process industry experts has been formed at MyPlant.com under the banner of MyExpert. MyPlant provides software solutions, new technologies, career guidance, and seminars tailored to the unique needs of the process industry. My Expert vicinities have already been formed for Business Process Optimization, Chemicals, Pharmaceutical Discovery, Planning Under Uncertainty, OPEC and Gasoline Prices and new vicinities are forming every day.
For more information, contact Gerry Cleaves at Gerry.Cleaves@myplant.com or Darron Smith at Darron.Smith@myplant.com.
About the Author
Gerry Cleaves recently joined MyPlant.com as the Director of the Pharmaceuticals and Consumer Packaged Goods vertical and to lead the new MyExpert initiative. Prior to MyPlant.com, he was the founder and CEO of AtlanTec, a company he formed in 1995 to commercialize new disruptive decision-support technologies for pharmaceutical discovery, financial derivative modeling, advanced process control, intelligent data mining for e-business, and longer-range strategic planning under risk and uncertainty. For 10 years he was the Director of Business Development for Chesapeake Decision Sciences and for 2 years an Engagement Director in the process industries for i2 Technologies. Gerry has a B.S. Ch.E. (Lehigh University), an M.S. in Engineering from Princeton, and an M.B.A. from the Harvard Business School. He can be reached at GCleaves@home.com, by phone at 908-654-5534, or at his home office at 603 Tremont Ave., Westfield, NJ 07090.