Measuring productivity

11 Key excerpts on "Measuring productivity"

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  Productivity Analysis

  An Empirical Investigation

  • Doris Yi-Hsin Wang(Author)
  • 2018(Publication Date)
  • Taylor & Francis

    (Publisher)

  Kaplan [1983] suggests using productivity measures as supplements to traditional financial measures of manufacturing performance. In his view, management accountants would separate variances due to relative price changes from those caused by changes in production efficiency. Belcher [1984] also supports integrating productivity measurement into the process of analyzing and interpreting financial data. He recommends using productivity measurement as an important element of the performance evaluation process.

  ALTERNATIVE APPROACHES TO PRODUCTIVITY MEASUREMENT

  In the economics literature productivity is usually defined as the ratio of output to input. Mundel [1983] defines productivity as a ratio of output produced per unit of resources consumed. Kendrick [1984] defines productivity as the ratio of output to inputs of labor and other resources, in real terms, at the company level. Sales revenues are used as this output measure, and all costs relating to the production of output, including inputs of material, labor, capital, and indirect business taxes, are measured as input costs. Productivity increases if the same output requires less input in the production process, or if the same input levels lead to increased output. Two distinct types of productivity ratios have been investigated in the literature, partial productivity ratios and total factor productivity ratios.

  Partial Productivity

  Partial productivity measures are derived by dividing total output by a single input. The early productivity researchers were mainly concerned with the changing status of labor. The partial productivity index of labor, which is a ratio of output divided by labor cost, was one of the first indexes of productivity. Belcher [1984] proposes partial productivity measures for four inputs—material, labor, capital, and energy—because these four factors are the major inputs for producing output. Kendrick [1984] states that a company may use partial productivity ratios if only one or two inputs are the major inputs in its production processes.

  In fact, as noted in the next section where available models are discussed, partial productivity measures are criticized by many researchers. Belcher points out that one partial measure can be improved at the expense of another. For example, improvements in labor productivity may result from increases in capital investments. Mammone [1980a:37] thinks that a labor productivity index is unrealistic , stating that “the ratio of output to labor input may change for reasons unrelated to the quality of labor input.” Craig and Harris [1973] comment that the cost of generating increased labor productivity must be considered in evaluating manufacturing performance. Generally speaking, partial productivity measures are useful in certain circumstances, but they have the serious shortcoming that substitutions among inputs may affect the resulting output measures.

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  Accounting for Construction

  Frameworks, Productivity, Cost and Performance

  • Rick Best, Jim Meikle, Rick Best, Jim Meikle(Authors)
  • 2019(Publication Date)
  • Routledge

    (Publisher)

  7   Measuring capital productivity in construction Michael Regan

  Introduction

  Productivity is the ratio of output to input in the production process and is a measure of the productive efficiency of the economy. Labour productivity measures output generated for each unit of labour input and, like capital productivity, is considered a partial productivity measure because of its reliance on a single input. Labour productivity is calculated for the economy as real gross domestic product (GDP) per hour worked.1 Capital productivity estimates are indicators of real GDP per unit of capital inputs or services used in production. Multifactor productivity (MFP) measures the amount of real output expressed in real value added from inputs of capital and labour.

  The most comprehensive measure of an economy’s productivity is MFP, which is the efficiency with which producers generate additional output from inputs of capital and labour (Productivity Commission 2015: 2). Growth in labour productivity captures improved labour efficiencies as well as the value added from growth in capital productivity through such mechanisms as research and development, technical progress and technology embodied in new plant and equipment. These environmental factors or externalities provide incremental output without the use of additional labour inputs. Investment in technical progress is central to both labour and capital productivity and directly affects MFP. Other externalities on the input side are the pricing of inputs, currency exchange rates (Productivity Commission 2016), public capital expenditures (Pereira and Roca-Sagales 1999; Abiad et al. 2015) and the utilisation of capital (Barnes 2011).

  On the output side, externalities in the case of commodity exports include exchange rate or commodity price volatility, shifts in demand or a downturn in the business cycle. If investment continues in order to complete projects commenced several years earlier and the value of output diminishes, productivity will decline. Other matters that may affect productivity on the output side include externalities such as mismatch of business and investment cycles (KPMG 2016) and change in the terms of trade (Productivity Commission 2014a, 2016).

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  The Economics of Firm Productivity

  Concepts, Tools and Evidence

  • Carlo Altomonte, Filippo di Mauro(Authors)
  • 2022(Publication Date)
  • Cambridge University Press

    (Publisher)

  2 Basic Concepts 2.1 Productivity In recent decades, the topic of firm productivity has increasingly gained attention from academics and in the policy debate. Macro- economists find that productivity growth is the source of almost all per capita income differences across countries, and so a new strand of research has emerged, dedicated to understanding the drivers of this growth (Syverson, 2011). Trade economists identify firm productivity as the most important determinant of export activity (Melitz, 2003) and foreign direct investment of multinational enterprises (Helpman et al., 2004). Labour economists are exploring the impact of workers’ human capital on productivity differences (Bloom and Van Reenen, 2007). Micro-economists are developing new methods to correctly measure productivity to improve our understanding of firm behaviour and market efficiency. In this chapter, we try to explain what productivity is and how it can be estimated. We will also provide some practical examples and computing codes. Let’s start with one definition (of the many possible definitions) of productivity. Productivity is the effectiveness of productive effort, especially in industry, as measured in terms of the rate of output per unit of input. (Oxford Dictionary) In other words, productivity measures how efficiently production inputs such as intermediates, energy, labour or capital are bundled together to produce an output. A typical (economic) measure of this efficiency is the ability of the production process to generate value added, that is, the increase in value in the final output of production compared to the value of the materials used in the production process by a firm. 8 2.2 Factor Productivity 9 In this sense, it is necessary to distinguish the productivity of a single production factor such as labour (this is what we call “factor productivity”) from the ability of a firm to combine the bundle of inputs at its disposal to create new value.

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  Cost Management

  • Don Hansen, Maryanne Mowen, Dan Heitger, , Don Hansen, Maryanne Mowen, Dan Heitger(Authors)
  • 2021(Publication Date)
  • Cengage Learning EMEA

    (Publisher)

  Only by looking at the total productivity effect of all inputs can managers accurately draw any conclusions about overall productivity performance. Second, because of the possi-bility of trade-offs, a total measure of productivity must assess the aggregate financial conse-quences and, therefore, should be a financial measure. TOTAL PRODUCTIVITY MEASUREMENT Measuring productivity for all inputs at once is called total productivity measurement . In practice, it may not be necessary to measure the effect of all inputs. Many firms measure the productivity of only those factors that are thought to be relevant indicators of organiza-tional performance and success. Thus, in practical terms, total productivity measurement can be defined as focusing on a limited number of inputs, which, in total, indicates organizational success. In either case, total productivity measurement requires the development of a multi-factor measurement approach. A common multifactor approach suggested in the productivity literature (but rarely found in practice) is the use of aggregate productivity indexes. Aggre-gate indexes are complex and difficult to interpret and have not been generally accepted. Two approaches that have gained some acceptance are profile measurement and profit-linked produc-tivity measurement . Profile Productivity Measurement Producing a product involves numerous critical inputs such as labor, materials, capital, and energy. Profile measurement provides a series or vector of separate and distinct partial operational measures. Profiles (vectors or series of measures) can be compared over time to provide information about productivity changes. When the partial productivity ratios move in the same direction when compared with the base period ratios, some definitive statements about productivity changes can be made. However, if the ratios move in opposite directions, a trade-off exists and the comparison of profiles provides a mixed signal about productivity changes.

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  Cornerstones of Cost Management

  • Don Hansen, Maryanne Mowen(Authors)
  • 2017(Publication Date)
  • Cengage Learning EMEA

    (Publisher)

  Productivity measurement can be actual or prospective. Actual productivity measurement allows managers to assess, monitor, and control changes. Prospective measurement is for-ward looking, and it serves as input for strategic decision making. Speci fi cally, prospective measurement allows managers to compare relative bene fi ts of different input combina-tions, choosing the inputs and input mix that provide the greatest bene fi t. Productivity measures can be developed for each input separately or for all inputs jointly. Measuring productivity for one input at a time is called partial productivity measurement . Productivity of a single input is typically measured by calculating the ratio of the output to the input as follows: Productivity ratio ¼ Output/Input Because the productivity of only one input is being measured, the measure is called a partial productivity measure . If both output and input are measured in physical quanti-ties, then we have an operational productivity measure . If output or input is expressed in dollars, then we have a fi nancial productivity measure . Cornerstone 15.3 illustrates par-tial productivity measurement. Assume, for example, that in 20x1, Nevada Company produced 240,000 frames for snowmobiles and used 60,000 hours of labor. The labor productivity ratio is four frames per hour (240,000/60,000). This is an operational measure, since the units are expressed in physical terms. If the selling price of each frame is $30 and the cost of labor is $15 per hour, then output and input can be expressed in dollars. The labor productivity ratio, expressed in fi nancial terms, is $8 of revenue per dollar of labor cost ($7,200,000/$900,000). Partial Measures and Measuring Changes in Productive Ef fi ciency The labor productivity ratio of four frames per hour measures the 20x1 productivity experience of Nevada.

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  Management Science in Hospitality and Tourism

  Theory, Practice, and Applications

  • Muzaffer Uysal, Zvi Schwartz, Ercan Sirakaya-Turk, Muzaffer Uysal, Zvi Schwartz, Ercan Sirakaya-Turk(Authors)
  • 2017(Publication Date)
  • Apple Academic Press

    (Publisher)

  Within for-profit industries, an overriding organizational goal is the maximization of output while simultaneously minimizing the associated inputs without sacrificing the organization’s established quality standards. In spite of the seeming sim- plicity and widespread acceptance of this definition of productivity, attempts at measurement continue to present a challenge for researchers and practi- tioners alike. Existing measures of productivity range from highly quantita- tive financial computations to more conceptual qualitative ones; they may be aggregated to include multifactor elements or represented by a single factor (Hu & Cai, 2004). It appears that different people perceive produc- tivity differently based upon their “backgrounds, positions of responsibility and goals,” (Sigala, 2004) so it makes sense that no single measure serves equally well across all contexts. While some approaches to measuring pro- ductivity are effective at identifying relative productivity among industries or businesses, other measures provide a more accurate picture of the specific levels of productivity achieved by a business, by an individual, or by a work unit. In reviewing the broadly based literature on productivity measurement, it is clear that over time the understanding of productivity has evolved and it has become increasingly clear that many of the elements contributing to productivity are tucked away in a “black box” and can only be guessed at. Given that labor expenditures are often an organization’s single greatest ex- pense category and also one of the most difficult to control, the importance of this issue cannot be overstated (Combs et al., 2006). For labor-intensive industries such as hospitality and retailing the issue is paramount. The present chapter draws from across disciplines to present an evolu- tionary perspective on productivity and issues related to its measurement in management and hospitality studies.

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  Selected Papers Of Lawrence R Klein: Theoretical Reflections And Econometric Applications

  • Kanta Marwah(Author)
  • 1997(Publication Date)
  • World Scientific

    (Publisher)

  27 INTERNATIONAL PRODUCTIVITY COMPARISONS (A REVIEW) t Meaning of Productivity According to the Oxford English Dictionary (1971), productivity is equated to productiveness, 1 which, in turn, is defined as ... fruitfulness; abundance or rich-ness in output. Solomon Fabricant, writing in the Encyclopedia of the Social Sci-ences (Fabricant, 1968), states, ... productivity measures the fruitfulness of human labor . . . . In another sense, productivity measures the efficiency with which re-sources as a whole including capital as well as manpower are employed in produc-tion. In these general terms, productivity carries a meaning that is fairly well known, in an intuitive sense, to most people and is, by and large, a good thing, something to be encouraged and desired. There are those, however, who fear productivity to the extent that it might lead to displacement from work. This is the case in which productivity enhancement comes about through technological progress. Nonparametric measurement. Productivity, as I shall use the term in this essay, has a technical meaning that is obviously tied to the dictionary meaning. I shall look at productivity in two ways, nonparametrically and parametrically. In a nonparametric sense, I shall define productivity as some simple ratio, but with common-sense meaning: X/L = labor productivity, where X = output and L = labor input, and X/TF = total factor productivity, where TF = L + (r/w)K, r = capital rental, w = wage rate, and K = capital stock. These two key ratios for labor and for total factor productivity seem to be simple enough, but in careful measurement for quantitative economics each numerator and denominator requires precise specification. If an economic establishment — firm, plant, enterprise — produces a single output, X is best measured as the physical number of units produced in a given + From Proceedings of the National Academy of Sciences, Vol.

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  Improving Public Sector Productivity

  Concepts and Practice

  • Ellen D. Rosen(Author)
  • 1993(Publication Date)
  • SAGE Publications, Inc

    (Publisher)

  The importance of output quality gained in recognition, even when it was not yet included in practice: The report recognizes problems with the nature and scope of the current measurement system which is based on a definition of productivity which compares outputs to inputs. This is expressly an efficiency measure. . . . Productivity measurement must take into consideration the quality and effectiveness of the goods and services that are delivered as well as the irresponsiveness to public needs (Measuring Federal Productivity, 1980, p. v). Hatry and co-workers did more than exhort. They began to develop methods for measuring the quality of services. They identified criteria (such as cleanliness, comfort, timeliness, and accessibility) that could be used as quality indicators, and they proposed methods for collecting this kind of data for substantive fields (Hatry, Blair, Fisk, Greiner, Hall, & Schaenmar, 1977). Today, as a result of two developments, output quality has taken on new and greater importance. One factor has been the influence of the private sector's emphasis on quality (for which the Japanese success had been a goad and a model). Quality-centered management requires an ability to 95 Measuring productivity measure quality because, as the brochure describing the award-winning total quality management initiative of the U.S. Air Force's 1926th Communications-Computer Systems Group says, in large letters: You cannot manage what you do not measure! (Federal Quality Institute, 1991, p. 10). The second source of contemporary interest in quality comes by default from the current fiscal crisis and popular dissatisfaction with government. Efficiencies are already happening, not so much by managerial design as by the reality of having to maintain services in the face of severe budget cuts. Managers can still maneuver with regard to quality, however.

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  Human Performance and Productivity

  Volumes 1, 2, and 3

  • Marvin D. Dunnette, Edwin A. Fleishman(Authors)
  • 2014(Publication Date)
  • Psychology Press

    (Publisher)

  7. It may well be that a technical productivity index that concentrates on labor inputs and work outputs is not feasible. This is reflected in equation (7) that recognizes that output is a function of more than labor input. This is a recognition that, in modem technology, output is rarely, in either goods or services, a simple and direct result of what people do.

  Causation and Uses

  Productivity measures are not collected just for the sake of collecting numbers. Like all measures, they must serve some purpose. Two issues are of importance here: (1) productivity measures as an indication of the causes of productivity decline or increase; and (2) productivity measures as tools for increasing employee productivity.

  1. Where productivity shows an increase or a decline one immediate question is: Why? Why is it, as shown in Tabie 2.1, that some industrial groups are showing marked increases in productivity, whereas others are in marked decline? One purpose of productivity assessment might weil be diagnostic; that is, the measurement should provide some indication of the reasons for productivity change. Unfortunately, all the available evidence points to a remarkable complexity in the specific determinants of labor productivity. In the most detailed analysis to date, Sutermeister (1976) has suggested some 33 possible determinants that may affect job productivity. These are roughly divided into such general categories as individual needs, physical conditions, social conditions, organizational variables, leadership, and so forth. And, it is very probable that for every real-life situation, many of these determinants are acting together in some unknown amounts.

  Trends in the literature appear to concentrate on single variables or small clusters of variables. For some years, there has been substantial interest in such items as: (1) job satisfaction and productivity (Dunn & Stephens, 1972); (2) quality of working life (Herrick, 1975); (3) consumer behavior and productivity [Lovelock & Young, 1979); (4) job redesign (Pritchard, Montagno, & Moore, 1978); (5) team pressures (Pepinsky, Pepinsky, & Pavlik, 1960); (6) environmental variables and productivity (Young & Berry, 1979), and so forth. What all these studies seem to indicate is that individual and team productivity is a very implicated matter.

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  The Industrial Study of Economic Progress

  • Hiram Simmons Davis(Author)
  • 2016(Publication Date)
  • University of Pennsylvania Press Anniversary Collection

    (Publisher)

  CHAPTER IV T H E M E A S U R E M E N T O F P R O D U C T I V E E F F I C I E N C Y BEFORE research can be undertaken on the conditions which affect productive efficiency, some procedure has to be devised for measuring efficiency itself. Without the expression of efficiency in some definite statistical form, the study of conditions would yield only confusion. Even one lone investigator could not effec-tively demonstrate that he was using the same concept of efficiency in two different situations unless he gave concrete expression to his concept. Because of these considerations, this entire chapter is devoted to the methods that are being used, or have been suggested, for the measurement of productive efficiency, and to the kind of measures which would appear to be most useful in the industrial study of economic progress. A. CURRENT YARDSTICKS It is easy to think of productive efficiency as the ratio of physical output to physical input, but very difficult to arrive at actual measures which are generally satisfactory, particularly on the input side. Some understanding of these difficulties can readily be obtained by turning to the comments which have been made about ratios both in use and proposed. I. FACTORY MAN-HOURS In nearly all studies bearing on physical productivity, output per man-hour or per wage earner 1 has been the key measure of efficiency. But its wide use is not to be interpreted as meaning that it is generally accepted as a completely satisfactory yard-stick. As F. C. Mills points out, 2 it is even an incomplete measure 1 Generally when the ratio of output to number of wage earners is used it is only because man-hour data are not available. Even in such cases, some adjustment may be made for differences in scheduled hours. 2 Industrial Productivity and Prices, Journal of the American Statistical Association, June 1937, pp. 247-262. 16

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  The New Economy in Development

  ICT Challenges and Opportunities

  • A. D'Costa(Author)
  • 2006(Publication Date)
  • Palgrave Macmillan

    (Publisher)

  Today we have e-business transactions between ‘brick’ firms, ‘click’ firms and ‘brick and click’ firms. The measurement challenge here is to account for the increased volumes in transactions, to identify the business players and their roles and their respective industries and to avoid double counting the value of related transactions. While comprehensive measures of e-business may be useful to profile all of these transactions, such detailed business statistics coverage would be unprecedented if not unrealistic. 2.4 Input measurements in services In this section the specific components of productivity inputs are discussed: labour, capital and intermediates. 28 The New Economy in Development 2.4.1 Labour force (L) measurements in services The measure of labour used in the estimation of productivity is generally quantified in terms of either total hours worked (H) of all employed (E), if one wants to measure output (Y) per hour worked; or total number of employed persons (E), if one wants to measure output per person employed: Output per hour worked (LPH) Y / (E * H) Output per employed (LPE) Y / E This methodology for valuing labour in productivity measurement is not adequate to capture the particular characteristics of labour in the service sector; therefore productivity indicators for services are often miscalculated. 2.4.1.1 The impact of the ICT revolution on patterns of work The ICT revolution in digital technology has increased opportunities for new such ways of working, particularly in knowledge-intensive business services (KIBS), which account for about one-third of the workforce. It is well known that many service employees are working more hours than are documented in the official numbers. It can be argued that actual ‘hours worked’ should include work performed after hours – work at home, work during travel as well as usage of cell phone for working activity – all of which are activities directly associated with work.

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