Productivity Concepts and Measures

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Productivity Concepts and Measures

Productivity is an overall measure of the ability to produce a good or service. More specifically, productivity is the measure of how specified resources are managed to accomplish timely objectives as stated in terms of quantity and quality. Productivity may also be defined as an index that measures output (goods and services) relative to the input (labor, materials, energy, etc., used to produce the output). There are two major ways to increase productivity: increase the numerator (output) or decrease the denominator (input). A similar effect would be seen if both input and output increased with output increasing faster than input; or if both input and output decreased with input decreasing faster than output. Productivity can be expressed as:

Organizations can use this formula in many areas: labor productivity, machine productivity, capital productivity, energy productivity, and so on. A productivity ratio can be computed for a single operation, a department, a facility, an organization, or even an entire country.

CONCEPTUAL ASPECTS OF PRODUCTIVITY

Productivity is an objective concept, which can be measured, ideally against a universal standard. As such, organizations can monitor productivity for strategic reasons such as corporate planning, organization improvement, or comparison to competitors. It can also be used for tactical reasons such as project control or controlling performance to budget.

Productivity is also a scientific concept, and hence can be logically defined and empirically observed. It can also be measured in quantitative terms, which qualifies it as a variable. Therefore, it can be defined and measured in absolute or relative terms. However, an absolute definition of productivity is not very useful; it is much more useful as a concept dealing with relative productivity or as a productivity factor.

Productivity is useful as a relative measure of actual output of production compared to the actual input of resources, measured across time or against common entities. As output increases for a level of input, or as the amount of input decreases for a constant level of output, an increase in productivity occurs. Therefore, a productivity measure describes how well the resources of an organization are being used to produce input.

Productivity is often confused with efficiency. Efficiency is generally seen as the ratio of the time needed to perform a task to some predetermined standard time. However, doing unnecessary work efficiently is not exactly being productive. It would be more correct to interpret productivity as a measure of effectiveness (doing the right thing efficiently), which is outcome-oriented rather than output-oriented.

EXPRESSIONS OF PRODUCTIVITY

Productivity is usually expressed in one of three forms: partial-factor productivity, multifactor productivity, and total-factor productivity.

Partial-Factor Productivity. The standard definition of productivity is actually what is known as a partial-factor measure of productivity, in the sense that it only considers a single input in the ratio. The formula then for partial-factor productivity would be the ratio of total output to a single input or:

Managers generally utilize partial-factor productivity measures because the data is readily available. Also, since the total of multifactor measures provides an aggregate perspective, partial-factor productivity measures are easier to relate to specific processes. Labor-based hours (generally, readily available information) is a frequently used input variable in the equation. When this is the case, it would seem that productivity could be increased by substituting machinery for labor. However, that may not necessarily be a

wise decision. Labor-based measures do not include mechanization and automation in the input; thus when automation replaces labor, misinterpretation may occur.

Other partial-factor measure options could appear as output/labor, output/machine, output/capital, or output/energy. Terms applied to some other partial factor measures include capital productivity (using machine hours or dollars invested), energy productivity (using kilowatt hours), and materials productivity (using inventory dollars).

Multifactor Productivity. A multifactor productivity measure utilizes more than a single factor, for example, both labor and capital. Hence, multifactor productivity is the ratio of total output to a subset of inputs:

A subset of inputs might consist of only labor and materials or it could include capital. Examples include:

or

or

Obviously, the different factors must be measured in the same units, for example dollars or standard hours.

Total-Factor Productivity. A broader gauge of productivity, total-factor productivity is measured by combining the effects of all the resources used in the production of goods and services (labor, capital, raw material, energy, etc.) and dividing it into the output. As such the formula would appear as:

or

One example: a ratio computed by adding (1) standard hours of labor actually produced plus (2) the standard machine hours actually produced in a given time period divided by the actual hours available for both labor and machines in the time period.

Total output must be expressed in the same unit of measure and total input must be expressed in the same unit of measure. However, total output and total input need not be expressed in the same unit of measure. Resources are often converted to dollars or standard hours so that a single figure can be used as an aggregate measure of total input or output. For example, total output could be expressed as the number of units produced, and total input could be expressed in dollars, such as tons of steel produced per dollar input. Other varieties of the measure may appear as dollar value of good or service produced per dollar of input, or standard hours of output per actual hours of input.

Total productivity ratios reflect simultaneous changes in outputs and inputs. As such, total productivity ratios provide the most inclusive type of index for measuring productivity and may be preferred in making comparisons of productivity. However, they do not show the interaction between each input and output separately and are thus too broad to be used as a tool for improving specific areas.

Total-factor productivity is a measure favored by the Japanese, whereas labor productivity is the measure favored by the United States. As such, the individual productivity of the American employee tends to be the best in the world, in that an American employee can purchase more eggs per one hour of work than anyone else in the world. But as a measure of national productivity, the Japanese have, in the past, tended to be better performers.

PRODUCTIVITY MEASURES

It has been said that the challenge of productivity has become a challenge of measurement. Productivity is difficult to measure and can only be measured indirectly, that is, by measuring other variables and then calculating productivity from them. This difficulty in measurement stems from the fact that inputs and outputs are not only difficult to define but are also difficult to quantify.

Any productivity measurement system should produce some sort of overall index of productivity. A smart measurement program combines productivity measurements into an overall rating of performance. This type of system should be flexible in order to accommodate changes in goals and policies over time. It should also have the ability to aggregate the measurement systems of different units into a single system and be able to compare productivity across different units.

The ways in which input and output are measured can provide different productivity measures. Disadvantages of productivity measures have been the distortion of the measure by fixed expenses and also the inability of productivity measures to consider quality changes (e.g., output per hour might increase, but it may cause the defect rate to skyrocket). It is easier to conceive of outputs as tangible units such as number of items produced, but other factors such as quality should be considered.

Experts have cited a need for a measurement program that gives an equal weight to quality as well as quantity (productivity). If quality is included in the ratio, output may have to be defined as something like the number of defect-free units of production or the number of units that meet customer expectations or requirements.

The determination of when productivity measures are appropriate performance measures depends on two criteria. The first is the independence of the transformation process from other processes within the organization. Second is the correspondence between the inputs and outputs in the productivity measurement process.

USE OF PRODUCTIVITY MEASURES

Productivity is a required tool in evaluating and monitoring the performance of an organization, especially a business organization. When directed at specific issues and problems, productivity measures can be very powerful. In essence, productivity measures are the yardsticks of effective resource use.

Managers are concerned with productivity as it relates to making improvements in their firm. Proper use of productivity measures can give the manager an indication of how to improve productivity: either increase the numerator of the measure, decrease the denominator, or both.

Managers are also concerned with how productivity measures relate to competitiveness. If two firms have the same level of output, but one requires less input thanks to a higher level of productivity, that firm will be able to charge a lower price and increase its market share or charge the same price as the competitor and enjoy a larger profit margin.

Within a time period, productivity measures can be used to compare the firm's performance against industry-wide data, compare its performance with similar firms and competitors, compare performance among different departments within the firm, or compare the performance of the firm or individual departments within the firm with the measures obtained at an earlier time (i.e., is performance improving or decreasing over time?).

Productivity measures can also be used to evaluate the performance of an entire industry or the productivity of a country as a whole. These are aggregate measures determined by combining productivity measures of various companies, industries, or segments of the economy.

PRODUCTIVITY INDEX

Since productivity is a relative measure, for it to be meaningful or useful it must be compared to something. For example, businesses can compare their productivity values to that of similar firms, other departments within the same firm, or against past productivity data for the same firm or department (or even one machine).This allows firms to measure productivity improvement over time, or measure the impact of certain decisions such as the introduction on new processes, equipment, and worker motivation techniques.

In order to have a value for comparison purposes, organizations compute their productivity index. A productivity index is the ratio of productivity measured in some time period to the productivity measured in a base period. For example, if the base period's productivity is calculated to be 1.75 and the following period's productivity is calculated to 1.93, the resulting productivity index would be 1.93/1.75 = 1.10. This would indicate that the firm's productivity had increased 10 percent. If the following period's productivity measurement fell to 1.66 the productivity index of 1.66/1.75 = 0.95 it would indicate that the organization's productivity has fallen to 95 percent of the productivity of the base period. By tracking productivity indexes over time, managers can evaluate the success, or lack thereof, of projects and decisions.

FACTORS AFFECTING PRODUCTIVITY

There is quite a variety of factors that can affect productivity, both positively and negatively. These include:

  1. Capital investments in production
  2. Capital investments in technology
  3. Capital investments in equipment
  4. Capital investments in facilities
  5. Economies of scale
  6. Workforce knowledge and skill resulting from training and experience
  7. Technological changes
  8. Work methods
  9. Procedures
  10. Systems
  11. Quality of products
  12. Quality of processes
  13. Quality of management
  14. Legislative and regulatory environment
  15. General levels of education
  16. Social environment
  17. Geographic factors

The first 12 factors are highly controllable at the company or project level. Numbers 13 and 14 are marginally controllable, at best. Numbers 15 and 16 are controllable only at the national level, and 17 is uncontrollable.

IMPROVING PRODUCTIVITY

Productivity improvement can be achieved in a number of ways. If the level of output is increased faster than that of input, productivity will increase. Conversely, productivity will be increased if the level of input is decreased faster than that of output. Also, an organization may realize a productivity increase from producing more output with the same level of input. Finally, producing more output with a reduced level of input will result in increased productivity.

Any of these scenarios may be realized through improved methods, investment in machinery and technology, improved quality, and improvement techniques and philosophies such as just-in-time, total quality management, lean production, supply chain management principles, and theory of constraints.

A firm or department may undertake a number of key steps toward improving productivity:

  • Develop productivity measures for all operations; measurement is the first step in managing and controlling an organization.
  • Look at the system as a whole in deciding which operations are most critical, it is overall productivity that is important.
  • Develop methods for achieving productivity improvement, such as soliciting ideas from workers (perhaps organizing teams of workers, engineers, and managers), studying how other firms have increased productivity, and reexamining the way work is done.
  • Establish reasonable goals for improvement.
  • Make it clear that management supports and encourages productivity improvement. Consider incentives to reward workers for contributions.
  • Measure improvements and publicize them.
  • Don't confuse productivity with efficiency. Efficiency is a narrower concept that pertains to getting the most out of a given set of resources; productivity is a broader concept that pertains to use of overall resources. For example, an efficiency perspective on mowing the lawn given a hand mower would focus on the best way to use the hand mower; a productivity perspective would include the possibility of using a power mower.

As a cautionary word, organizations must be careful not to focus solely on productivity as the driver for the organization. Organizations must consider overall competitive ability. Firm success is categorized by quality, cycle time, reasonable lead time, innovation, and a host of other factors directed at improving customer service and satisfaction.

PRODUCTIVITY AT THE NATIONAL LEVEL

Since productivity is one of the basic variables governing economic production activity some mention of national productivity concerns would be appropriate. As a matter of fact, productivity may be the most important variable governing economic production activity. It is the fundamental controllable factor in wealth production. Since other economic variables depend on it, increasing productivity tends to have a beneficial multiplying effect on other economic variables. This is generally true at every level of economic aggregation.

During the 1970s and 1980s, productivity growth in the United States lagged behind that of other leading industrial countries. Although U.S. productivity was still the world's highest, the fact that it was losing ground to other nationsmost notably Japan, Korea, the United Kingdom, and West Germanycaused concern among government officials and business leaders. The United States reversed this trend beginning in the mid-1990s with a shift from a reliance on manufacturing and agriculture to the new economy focus on service and high-technology. Since then, the United States has witnessed a sustained productivity growth from the late-1990s through the mid-2000s.

Although economists and business analysts disagree about the specific causes of this reversal, most point to successful investments in information and communication technology as well as increased automation and productivity-enhancing organizational innovations. The contribution of technology to U.S. productivity is nothing new. It has been estimated that technology was responsible for at least half of the growth in productivity in the United States between 1948 and 1966. Technology continues to be seen as the key to sustaining increases in productivity.

Improving productivity is of national importance because, for a society to increase its standard of living, it must first increase productivity. Overall productivity for individual countries is calculated by dividing output, as measured by Gross Domestic Product (GDP) or Gross National Product (GNP), by the country's total population. Thus, productivity is measured as the dollar value per capita outputs. An increase in this measure of productivity means that each person in the country, on average, produced more goods and services. Also if productivity increases, then profits increase. The resulting profits can then be used to pay for wage increases

(inherent in inflation) without having to raise prices. In this way, productivity gains actually help curb inflation.

SEE ALSO Economies of Scale and Economies of Scope; Effectiveness and Efficiency; Experience and Learning Curves; Financial Issues for Managers; Financial Ratios

BIBLIOGRAPHY

Bloom, Nicholas, Raffaella Sadun, and John Van Reenen. Americans Do I.T. Better: U.S. Multinationals and the Productivity Miracle. Available from: emlab.berkeley.edu/users/webfac/gorodnichenko/e237_s08/bloom.pdf.

Coelli, Timothy J., D.S. Prasada Rao, Christopher O'Donnell, and George Battese. An Introduction to Efficiency and Productivity Analysis. 2nd ed. New York: Springer 2005.

The eManager: Value Chain Management in an eCommerce World. Dublin, Ireland: Blackhall Publishing, 2001.

Lynch, Lisa M. Organizational innovation and U.S. productivity. Vox 6 December 2007. Available from: http://www.voxeu.org/index.php?q=node/775.

Stevenson, William J. Operations Management. 8th ed. Boston,MA: Irwin McGraw-Hill, 2006.

Vora, Jay A. Productivity and Performance Measures: Who Uses Them. Production and Inventory Management Journal 33, no. 1 (1992): 4649.

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