Background Economists and managers have long recognized the importance of productivity in determining an organizations success. Productivity is the relation between the firms output of goods and services and the inputs necessary to produce that output. If a firm is able to produce more output with the same inputs, we say it has improved its productivity. Likewise, if two firms produce the same quantity of goods and services but one firm uses less input, that firm is called more productive. Countries that produce more output per person generate more consumable wealth. Economists keep productivity statistics, and these numbers are reported in the financial press as measuring the competitiveness and well-being of that country. In the 1970s, many of the largest U.S. firms became interested in productivity and better ways to measure and improve their firms productivity. Largely driven by foreign competition, these American firms were losing market share to Japanese and European rivals. Japanese auto companies were producing cars with fewer employee hours per car than American companies, thus offering lower-priced and often higher-quality cars than U.S. automakers. Foreign steel producers were more productive than their U.S. counterparts. Concerned about their declining relative productivity in 1977, large U.S. firms financed the formation of the American Productivity Center (later the American Productivity and Quality Center). To become more productive, some firms experimented with various productivity measures. In its most basic form, productivity is defined as:

If the firm uses a single input (steel) to produce a single homogeneous product (horseshoes) that never changes over time, then the measure of productivity is the units of output per quantity of input, or the number of horseshoes per pound of steel. If steel waste is reduced, more horseshoes can be produced with the same amount of steel. One measure of productivity is the ratio of horseshoes to steel, in terms of physical volume. Steel is not the only input to making horseshoes. Labor is also an input, and labor is usually the input of most interest to managers. Productivity is usually thought of as the amount of output per unit of labor. Most managers want to know the number of horseshoes produced per person and how this number changes over time and compares to the competition. Proponents of productivity measurement systems argue that managers should focus on productivity instead of accounting profits. A firm can appear profitable but can be experiencing declining productivity if selling prices are rising faster than input prices. Productivity measures help identify these cases. Managers control the physical aspects of the manufacturing process, such as the amount of steel scrap in making horseshoes, but they cannot control the price of steel or the price of horseshoes. For the most part, managers cannot influence prices but must take them as a given and try to produce more output from a given physical input or the same output using less physical input. Proponents of productivity measures argue that basing managerial performance on productivity, which does not include uncontrollable price changes, yields a better indicator of the managers performance. They argue that traditional accounting measures, such as net income, include many factors that managers cannot control and do not focus enough attention on factors that managers can control such as labor productivity. The following example illustrates productivity measurement systems in more detail. Measuring productivity If the firm produces several types of outputs (large and small horseshoes) and the mix of output varies over time, then the productivity measure must somehow aggregate the quantities of outputs into a single aggregate quantity. Likewise, several inputs must be aggregated to derive a homogeneous page 641input measure. The measure of productivity (outputs/inputs) must aggregate the multiple inputs and the multiple outputs. To measure firmwide productivity when multiple inputs and outputs exist, prices are used as the weighting factors. The productivity measure with two outputs and three inputs becomes:

Outputi (i = 1 or 2) and inputj ( j = 1, 2, or 3) denote the physical quantities of the ith output and the jth input. Pricei and costj are the corresponding output prices and input costs. If one then compares how productivity changes over time, this aggregate measure of productivity will vary with changes in both physical quantities and relative prices. But productivity measures should exclude noncontrollable price and cost changes, thereby focusing managers attention on physical quantities. To exclude price and cost changes from the performance measure, yet still have a way to aggregate multiple inputs and outputs, the following scheme is used: Choose a base period year and use that years prices and costs as the weights for future years. The base year should be one of high production, and a new base year should be chosen about every five years as the structures of production and prices change. Weight the physical quantity of each input and output using the base period cost or price for that input or output. Divide the weighted outputs by weighted inputs to compute the productivity index for the year. Divide this years productivity index by last years to get the change in productivity.16 A simple example with two inputs (steel and labor) and two outputs (small and large horseshoes) illustrates the mechanics of the computations.17 Table 1 summarizes operations for the last two years: TABLE 1 Physical Quantities Inputs/Outputs Base Year Prices Last Year This Year Outputs: Small horseshoes $2 500 600 Large horseshoes $3 500 550 Inputs: Steel $1 1,000 300 Labor $4 300 320 page 642

Based on these data, the productivity measures are calculated as shown in Table 2: TABLE 2 Inputs/Outputs Last Year This Year Outputs: Small horseshoes $1,000 $1,200 Large horseshoes 1,500 1,650 Total outputs $2,500 $2,850 Inputs: Steel $1,000 $1,200 Labor 1,200 1,280 Total inputs $2,200 $2,480 $2,500 $2,850 Productivity $2,200 $2,480 = 1.136 = 1.149

Total productivity increased from 1.136 last year to 1.149 this year, or a 1.1 percent increase. Using base period prices, the productivity measure indicates that more output was produced using relatively less input. In a study of productivity systems in Canada, few firms were found to measure aggregate firmwide productivity as the ratio of firm outputs to firm inputs.18 Instead, firms develop a few distinct nonfinancial measures that capture the essential strategic elements of their business. For example, a steel company tracks tons of steel shipped divided by tons of iron purchased and tons of steel shipped divided by number of employees. In an insurance company, the number of policies processed per employee in a particular department is reported. Other companies measure yield rates, defect rates, and production rates. The study concludes (p. 132), We believe that productivity measures are operational aids in the strategic process that helps organization members keep track of what is required for the organization to achieve its long-run goals. Required: Critically analyze the productivity calculations in Table 2. Did the managers of the firm perform better this year compared with last year, as the productivity measures indicate? Discuss some plausible reasons why comprehensive productivity systems have not been widely adopted by organizations. Consider the situation of Burk Wheels. Burk Wheels manufactures aluminum automobile wheels (onto which rubber tires are mounted). The owner, Gerry Burk, is worried about increased competition from foreign countries (with lower labor costs) and is seeking to increase the productivity of her workers. She decides to implement a bonus system for direct line supervisors and department managers to reward them for improving labor productivity. In particular, supervisors will receive bonuses if they improve their departments page 643labor productivity, defined as Output Labor hours. The casting department is the primary production process whereby molten aluminum is poured into molds, cooled, and then removed to form the wheels. Operating data for the casting department for the last two months prior to announcing the labor productivity incentive program are: March April Wheels cast 1,680 1,710 Direct labor hours 722 701 Aluminum used (pounds) 14,616 15,219 Direct labor wages/hour $23.10 $23.75 Price of aluminum/pound $ 0.92 $ 0.91