Manufacturing Strategy Paradigm The late 1970s and early 1980s saw the development of the manufacturing strategy paradigm by researchers at Harvard Business School. This work by professors William Abernathy, Kim Clark, Robert Hayes, and Steven Wheelwright (built on earlier efforts by Wickham Skinner) emphasized how manufacturing executives could use their factories’ capabilities as strategic competitive weapons. Central to their thinking was the notion of factory focus and manufacturing trade-offs. They argued that because a factory cannot excel on all performance measures, its management must devise a focused strategy, creating a focused factory that performs a limited set of tasks extremely well. This requires trade-offs among such performance measures as low cost, high quality, and high flexibility in designing and managing factories. Ford seems to have realized this about 60 years before the Harvard professors.
Lean Manufacturing, JIT, and TQC The 1980s saw a revolution in the management philosophies and technologies by which production is carried out. Just-in-time (JIT) production was the major breakthrough in manufacturing philosophy. Pioneered by the Japanese, JIT is an integrated set of activities designed to achieve high-volume production using minimal inventories of parts that arrive at the workstation exactly when they are needed. The philosophy—coupled with total quality control (TQC), which aggressively seeks to eliminate causes of production defects—is now a cornerstone in many manufacturers’ production practices, and the term lean manufacturing is used to refer to the set of concepts.
Of course, the Japanese were not the first to develop a highly integrated, efficient production system. In 1913, Henry Ford developed an assembly line to make the Model-T automobile. Ford developed a system for making the Model-T that was constrained only by the capabilities of the workforce and existing technology. Quality was a critical prerequisite for Ford: The line could not run steadily at speed without consistently good components. On-time delivery was also critical for Ford; the desire to keep workers and machines busy with materials flowing constantly made scheduling critical. Product, processes, materials, logistics, and people were well integrated and balanced in the design and operation of the plant.1
Service Quality and Productivity The great diversity of service industries—ranging from airlines to zoos, with many different types in between—precludes identifying any single pioneer or developer that has made a major impact in these areas. However, McDonald’s unique approach to quality and productivity has been so successful that it stands as a reference point in thinking about how to deliver high-volume standardized services.
Total Quality Management and Quality Certification Another major development was the focus on total quality management (TQM) in the late 1980s and 1990s. All operations executives are aware of the quality message put forth by the so-called quality gurus: W. Edwards Deming, Joseph M. Juran, and Philip Crosby. It’s interesting that these individuals were students of Shewhart, Dodge, and Romig in the 1930s (sometimes it takes a generation for things to catch on). Helping the quality movement along is the Baldrige National Quality Award, which was started in 1987 under the direction of the National Institute of Standards and Technology. The Baldrige Award recognizes companies each year for outstanding quality management systems.
The ISO 9000 certification standards, created by the International Organization for Standardization, now play a major role in setting quality standards for global manufacturers. Many companies require that their vendors meet these standards as a condition for obtaining contracts.
Business Process Reengineering The need to become lean to remain competitive in the global economic recession in the 1990s pushed companies to seek innovations in the processes by which they run their operations. The theme of business process reengineering (BPR) is conveyed in the title of Michael Hammer’s influential article in Harvard Business Review: “Reengineering Work: Don’t Automate, Obliterate.” The approach seeks to make revolutionary changes as opposed to evolutionary changes (which are commonly advocated in TQM). It does this by taking a fresh look at what the organization is trying to do in all its business processes, and then eliminating non–value-added steps and computerizing the remaining ones to achieve the desired outcome.
Hammer actually was not the first consultant to advocate eliminating non–value-added steps and reengineering processes. In the early 1900s, Frederick W. Taylor developed principles of scientific management that applied scientific analysis to eliminating wasted effort from manual labor. Around the same time, Frank and Lillian Gilbreth used the new technology of the time, motion pictures, to analyze such diverse operations as bricklaying and medical surgery procedures. Many of the innovations this husband-and-wife team developed, such as time and motion study, are widely used today.
Six Sigma Quality Originally developed in the 1980s as part of total quality management, Six Sigma quality in the 1990s saw a dramatic expansion as an extensive set of diagnostic tools was developed. These tools have been taught to managers as part of Green and Black Belt Programs at many corporations. The tools are now applied not only to the well-known manufacturing applications, but also to nonmanufacturing processes such as accounts
receivable, sales, and research and development. Six Sigma has been applied to environmental, health, and safety services at companies and is now being applied to research and development, finance, information systems, legal, marketing, public affairs, and human resources processes.
Supply Chain Management The central idea of supply chain management is to apply a total system approach to managing the flow of information, materials, and services from raw material suppliers through factories and warehouses to the end customer. Trends such as outsourcing and mass customization are forcing companies to find flexible ways to meet customer demand. The focus is on optimizing core activities to maximize the speed of response to changes in customer expectations.
The ability to produce a unique product exactly to a particular customer’s requirements.
Electronic Commerce The quick adoption of the Internet and the World Wide Web during the late 1990s was remarkable. The term electronic commerce refers to the use of the Internet as an essential element of business activity. The Internet is an outgrowth of a government network called ARPANET, which was created in 1969 by the Defense Department of the U.S. government. The use of web pages, forms, and interactive search engines has changed the way people collect information, shop, and communicate. It has changed the way operations managers coordinate and execute production and distribution functions.
Service Science A direct response to the growth of services is the development of a major industry and university program called Service Science Management and Engineering (SSME). SSME aims to apply the latest concepts in information technology to continue to improve service productivity of technology-based organizations. An interesting question raised by Jim Spohrer, leader of the IBM team that started the effort, is where will the labor go once productivity improves in the service sector? “The short answer is new service sector industries and business—recall the service sector is very diverse and becoming more so every day. Consider the growth of retail (franchises, ecommerce, Amazon, eBay), communication (telephones, T-Mobile, Skype), transportation (airlines, FedEx), financial (discount e-brokers, Schwab), as well as information (television, CNN, Google) services, not to mention all the new services in developing nations of the world. The creative capacity of the service sector for new industries and business has scarcely been tapped.”2
The use of current business data to solve business problems using mathematical analysis.
Business Analytics Business analytics involves the analysis of data to better solve business problems. Not that this is something new: Data has always been used to solve business problems. What is new is the reality that so much more data is now captured and available for decision-making analysis than was available in the past. In addition, mathematical tools are now readily available that can be used to support the decision-making process.
In the past, most analysis involved the generation of standard and ad hoc reports that summarized the current state of the firm. Software allowed querying and “drill down” analysis to the level of the individual transaction, useful features for understanding what happened in the past. Decision making was typically left to the decision maker based on judgment or simple alerting rules. The new “analytics” movement takes this to a new level using statistical analysis, forecasting to extrapolate what to expect in the future, and even optimization, possibly in real time, to support decisions. These mathematical results can be used either to support the decision maker or to automate decision making.
Take, for example, an airline manager presented with the task of setting price points for tickets on a flight. Real-time demand data, historic demand patterns, and powerful mathematical models can now be applied to setting price points for different classes of tickets. As it is closer to the time of departure for a particular flight, these price points can be adjusted based on how sales are going. These decisions have a major impact on the utilization of aircraft capacity, which impacts both revenue and costs for the airlines. These decisions can even be made using criteria related to weather conditions, fuel prices, crew schedules, and other flights to maximize the profit of the firm.
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