the measurement strategy and the information being measured have changed over time, and this complicates the interpretation and understanding of the information. Whereas some trends are easily seen in retrospect, it is unclear whether or not the measures currently in use accurately reflect the state of the overall economy or the manufacturing sector and the trends that are developing.
Because such metrics are routinely used as the basis for federal policies and legislation, it is very important that the measures be well understood in order for them to be useful. For example, measuring direct employment in the manufacturing sector may be misleading. A decrease in employment might indicate a loss of manufacturing production capacity in the United States; however, it might also reflect an increase in productivity, and production might actually be increasing. Such a decrease in employment numbers may also indicate that some jobs once counted as manufacturing (security guards or payroll clerks, for example) may today be outsourced by the manufacturing company and are now counted in the service sector. Many conclude that all three trends are at work, but today’s data are viewed as inadequate to determine their relative importance. In addition, no metrics today look at such factors as wealth generation from manufacturing, for example, which could help policy makers understand the true impact of changes in the manufacturing sector.
Further, the changing operating models in the manufacturing sector make it an interesting challenge to find accurate and useful metrics. Goods are produced in a variety of ways: some are used as raw materials, others with added value from processing techniques, and some as finished products sold to an end user. These different types of products are all tracked by federal agencies, and their levels of production are quantified in systems that are sometimes similar and sometimes orthogonal. In addition, tracking of products is complicated by the fact that the components of a single product may come from a variety of sources and may be processed several times. Each processing step may happen at a different company and/or location, either in the United States or abroad.
As productivity increases, our standard of living could increase even as direct manufacturing employment decreases. As manufacturing grows in the developing world, markets are growing as well. Although it is easy to speculate that these changes will be reflected in the measures the U.S. government gathers and uses, it is difficult to ascertain the extent or dimension of the changes. An additional complication arises because of the growing interdependence between manufacturing and service jobs: The continued loss of manufacturing jobs could have a direct relationship to a corresponding loss of service sector jobs.
Historically, much of the discussion and measurement of manufacturing elements have been in the context of factory floor activities. Also referred to as “little m” manufacturing, this facet is concerned with direct production, or the cutting, grinding, fabrication, and assembling of materials. In a larger context, “big M” manufacturing expands this scope to include many of the decisions, processes, and activities that occur both upstream and downstream of factory floor activities. “Big M” manufacturing includes areas such as e-business, product design, process development, supply chain management, plant design, capacity management, product distribution, product costing, performance measurement, plant scheduling, quality management, workforce organization, equipment maintenance, strategic planning, and interplant coordination, as well as direct production.
The current national debate on manufacturing is sometimes narrowly focused on little m manufacturing. However, all manufacturing organizations must attend not only to little m