Productivity is the efficiency of production of goods or services expressed by some measure. Measurements of productivity are often expressed as a ratio of an aggregate output to a single input or an aggregate input used in a production process, i.e. output per unit of input, typically over a specific period of time.[1] The most common example is the (aggregate) labour productivity measure, one example of which is GDP per worker. There are many different definitions of productivity (including those that are not defined as ratios of output to input) and the choice among them depends on the purpose of the productivity measurement and data availability. The key source of difference between various productivity measures is also usually related (directly or indirectly) to how the outputs and the inputs are aggregated to obtain such a ratio-type measure of productivity.[2]
Productivity is a crucial factor in the production performance of firms and nations. Increasing national productivity can raise living standards because increase in income per capita improves people's ability to purchase goods and services, enjoy leisure, improve housing, and education and contribute to social and environmental programs. Productivity growth can also help businesses to be more profitable.[3]
Productivity measures that use one class of inputs or factors, but not multiple factors, are called partial productivities.[4] In practice, measurement in production means measures of partial productivity. Interpreted correctly, these components are indicative of productivity development, and approximate the efficiency with which inputs are used in an economy to produce goods and services. However, productivity is only measured partially– or approximately. In a way, the measurements are defective because they do not measure everything, but it is possible to interpret correctly the results of partial productivity and to benefit from them in practical situations. At the company level, typical partial productivity measures are such things as worker hours, materials or energy used per unit of production.[4]
Before the widespread use of computer networks, partial productivity was tracked in tabular form and with hand-drawn graphs. Tabulating machines for data processing began being widely used in the 1920s and 1930s and remained in use until mainframe computers became widespread in the late 1960s through the 1970s. By the late 1970s inexpensive computers allowed industrial operations to perform process control and track productivity. Today data collection is largely computerized and almost any variable can be viewed graphically in real time or retrieved for selected time periods.
Labour productivity levels in 2012 in Europe. OECDComparison of average labour productivity levels between the OECD member states. Productivity is measured as GDP per hour worked. Blue bars = higher than OECD-average productivity. Yellow bars = lower than average.
In macroeconomics, a common partial productivity measure is labour productivity. Labour productivity is a revealing indicator of several economic indicators as it offers a dynamic measure of economic growth, competitiveness, and living standards within an economy.[citation needed] It is the measure of labour productivity (and all that this measure takes into account) which helps explain the principal economic foundations that are necessary for both economic growth and social development. In general labour productivity is equal to the ratio between a measure of output volume (gross domestic product or gross value added) and a measure of input use (the total number of hours worked or total employment).[citation needed]
The output measure is typically net output, more specifically the value added by the process under consideration, i.e. the value of outputs minus the value of intermediate inputs. This is done in order to avoid double-counting when an output of one firm is used as an input by another in the same measurement.[5] In macroeconomics the most well-known and used measure of value-added is the gross domestic product or GDP. Increases in it are widely used as a measure of the economic growth of nations and industries. GDP is the income available for paying capital costs, labor compensation, taxes and profits.[6] Some economists instead use gross value added (GVA); there is normally a strong correlation between GDP and GVA.[7]
The measure of input use reflects the time, effort and skills of the workforce. The denominator of the ratio of labour productivity, the input measure is the most important factor that influences the measure of labour productivity. Labour input is measured either by the total number of hours worked of all persons employed or total employment (head count).[7] There are both advantages and disadvantages associated with the different input measures that are used in the calculation of labour productivity. It is generally accepted that the total number of hours worked is the most appropriate measure of labour input because a simple headcount of employed persons can hide changes in average hours worked and has difficulties accounting for variations in work such as a part-time contract, paid leave, overtime, or shifts in normal hours. However, the quality of hours-worked estimates is not always clear. In particular, statistical establishment and household surveys are difficult to use because of their varying quality of hours-worked estimates and their varying degree of international comparability.
GDP per capita is a rough measure of average living standards or economic well-being and is one of the core indicators of economic performance.[8] GDP is, for this purpose, only a very rough measure. Maximizing GDP, in principle, also allows maximizing capital usage. For this reason, GDP is systematically biased in favour of capital intensive production at the expense of knowledge and labour-intensive production. The use of capital in the GDP-measure is considered to be as valuable as the production's ability to pay taxes, profits and labor compensation. The bias of the GDP is actually the difference between the GDP and the producer income.[9]
Another labour productivity measure, output per worker, is often seen as a proper measure of labour productivity, as here: "Productivity isn't everything, but in the long run it is almost everything. A country's ability to improve its standard of living over time depends almost entirely on its ability to raise its output per worker."[10] This measure (output per worker) is, however, more problematic than the GDP or even invalid because this measure allows maximizing all supplied inputs, i.e. materials, services, energy and capital at the expense of producer income.[citation needed]
Trends in U.S. productivity from labor, capital and multi-factor sources over the 1987–2014 period
When multiple inputs are considered, the measure is called multi-factor productivity or MFP.[5] Multi-factor productivity is typically estimated using growth accounting. If the inputs specifically are labor and capital, and the outputs are value added intermediate outputs, the measure is called total factor productivity (TFP].[11] TFP measures the residual growth that cannot be explained by the rate of change in the services of labour and capital. MFP replaced the term TFP used in the earlier literature, and both terms continue in use (usually interchangeably).[12]
TFP is often interpreted as a rough average measure of productivity, more specifically the contribution to economic growth made by factors such as technical and organisational innovation.[6] The most famous description is that of Robert Solow's (1957): "I am using the phrase 'technical change' as a shorthand expression for any kind of shift in the production function. Thus slowdowns, speed ups, improvements in the education of the labor force and all sorts of things will appear as 'technical change'." The original MFP model[13] involves several assumptions: that there is a stable functional relation between inputs and output at the economy-wide level of aggregation, that this function has neoclassical smoothness and curvature properties, that inputs are paid the value of their marginal product, that the function exhibits constant returns to scale, and that technical change has the Hicks’n neutral form.[14] In practice, TFP is "a measure of our ignorance", as Abramovitz (1956) put it, precisely because it is a residual. This ignorance covers many components, some wanted (like the effects of technical and organizational innovation), others unwanted (measurement error, omitted variables, aggregation bias, model misspecification)[15] Hence the relationship between TFP and productivity remains unclear.[2]
When all outputs and inputs are included in the productivity measure it is called total productivity. A valid measurement of total productivity necessitates considering all production inputs. If we omit an input in productivity (or income accounting) this means that the omitted input can be used unlimitedly in production without any impact on accounting results. Because total productivity includes all production inputs, it is used as an integrated variable when we want to explain income formation of the production process.
Davis has considered[16] the phenomenon of productivity, measurement of productivity, distribution of productivity gains, and how to measure such gains. He refers to an article[17] suggesting that the measurement of productivity shall be developed so that it ”will indicate increases or decreases in the productivity of the company and also the distribution of the ’fruits of production’ among all parties at interest”. According to Davis, the price system is a mechanism through which productivity gains are distributed, and besides the business enterprise, receiving parties may consist of its customers, staff and the suppliers of production inputs.
In the main article is presented the role of total productivity as a variable when explaining how income formation of production is always a balance between income generation and income distribution. The income change created by production function is always distributed to the stakeholders as economic values within the review period.
Benefits of productivity growth
Labour productivity growth in Australia since 1978, measured by GDP per hour worked (indexed)
Productivity growth is a crucial source of growth in living standards. Productivity growth means more value is added in production and this means more income is available to be distributed.
At a firm or industry level, the benefits of productivity growth can be distributed in a number of different ways:
to the workforce through better wages and conditions;
to shareholders and superannuation funds through increased profits and dividend distributions;
to customers through lower prices;
to the environment through more stringent environmental protection; and
to governments through increases in tax payments (which can be used to fund social and environmental programs).
Productivity growth is important to the firm because it means that it can meet its (perhaps growing) obligations to workers, shareholders, and governments (taxes and regulation), and still remain competitive or even improve its competitiveness in the market place. Adding more inputs will not increase the income earned per unit of input (unless there are increasing returns to scale). In fact, it is likely to mean lower average wages and lower rates of profit. But, when there is productivity growth, even the existing commitment of resources generates more output and income. Income generated per unit of input increases. Additional resources are also attracted into production and can be profitably employed.
In the most immediate sense, productivity is determined by the available technology or know-how for converting resources into outputs, and the way in which resources are organized to produce goods and services. Historically, productivity has improved through evolution as processes with poor productivity performance are abandoned and newer forms are exploited. Process improvements may include organizational structures (e.g. core functions and supplier relationships), management systems, work arrangements, manufacturing techniques, and changing market structure. A famous example is the assembly line and the process of mass production that appeared in the decade following commercial introduction of the automobile.[18]
Mass production dramatically reduced the labor in producing parts for and assembling the automobile, but after its widespread adoption productivity gains in automobile production were much lower. A similar pattern was observed with electrification, which saw the highest productivity gains in the early decades after introduction. Many other industries show similar patterns. The pattern was again followed by the computer, information and communications industries in the late 1990s when much of the national productivity gains occurred in these industries.[19]
There is a general understanding of the main determinants or drivers of productivity growth. Certain factors are critical for determining productivity growth. The Office for National Statistics (UK) identifies five drivers that interact to underlie long-term productivity performance: investment, innovation, skills, enterprise and competition.[20]
Investment is in physical capital— machinery, equipment and buildings. The more capital workers have at their disposal, generally the better they are able to do their jobs, producing more and better quality output.
Innovation is the successful exploitation of new ideas. New ideas can take the form of new technologies, new products or new corporate structures and ways of working. Speeding up the diffusion of innovations can boost productivity.
Skills are defined as the quantity and quality of labour of different types available in an economy. Skills complement physical capital, and are needed to take advantage of investment in new technologies and organisational structures.
Enterprise is defined as the seizing of new business opportunities by both start-ups and existing firms. New enterprises compete with existing firms by new ideas and technologies increasing competition. Entrepreneurs are able to combine factors of production and new technologies forcing existing firms to adapt or exit the market.
Competition improves productivity by creating incentives to innovate and ensures that resources are allocated to the most efficient firms. It also forces existing firms to organise work more effectively through imitations of organisational structures and technology.
Research and development (R&D) tends to increase productivity growth,[21] with public R&D showing larger spillovers and smaller firms experiencing larger productivity gains from public R&D.[22]
Technology has enabled massive personal productivity gains—computers, spreadsheets, email, and other advances have made it possible for a knowledge worker to seemingly produce more in a day than was previously possible in a year.[23] Environmental factors such as sleep and leisure play a significant role in work productivity and received wage.[24] Drivers of productivity growth for creative and knowledge workers include improved or intensified exchange with peers or co-workers, as more productive peers have a stimulating effect on one's own productivity.[25][26] Productivity is influenced by effective supervision and job satisfaction. An effective or knowledgeable supervisor (for example a supervisor who uses the Management by objectives method) has an easier time motivating their employees to produce more in quantity and quality. An employee who has an effective supervisor, motivating them to be more productive is likely to experience a new level of job satisfaction thereby becoming a driver of productivity itself.[27] There is also considerable evidence to support improved productivity through operant conditioning reinforcement,[28] successful gamification engagement,[29] and research-based recommendations on principles and implementation guidelines for using monetary rewards effectively.[30]
Detrimental impact of bullying, incivility, toxicity and psychopathy
Workplace bullying results in a loss of productivity, as measured by self-rated job performance.[31] Over time, targets of bullying will spend more time protecting themselves against harassment by bullies and less time fulfilling their duties.[32]Workplace incivility has also been associated with diminished productivity in terms of quality and quantity of work.[33]
A toxic workplace is a workplace that is marked by significant drama and infighting, where personal battles often harm productivity.[34] While employees are distracted by this, they cannot devote time and attention to the achievement of business goals.[35] When toxic employees leave the workplace, it can improve the culture overall because the remaining staff become more engaged and productive.[36] The presence of a workplace psychopath may have a serious detrimental impact on productivity in an organisation.[37]
In companies where the traditional hierarchy has been removed in favor of an egalitarian, team-based setup, the employees are often happier, and individual productivity is improved (as they themselves are better placed to increase the efficiency of the workfloor). Companies that have these hierarchies removed and have their employees work more in teams are called liberated companies or "Freedom Inc.'s".[38][39][40][41][42] The Kaizen system of bottom-up, continuous improvement was first practiced by Japanese manufacturers after World War II, most notably as part of The Toyota Way.
Business productivity
Productivity is one of the main concerns of business management and engineering. Many companies have formal programs for continuously improving productivity, such as a production assurance program. Whether they have a formal program or not, companies are constantly looking for ways to improve quality, reduce downtime and inputs of labor, materials, energy and purchased services. Often simple changes to operating methods or processes increase productivity, but the biggest gains are normally from adopting new technologies, which may require capital expenditures for new equipment, computers or software. Modern productivity science owes much to formal investigations that are associated with scientific management.[43] Although from an individual management perspective, employees may be doing their jobs well and with high levels of individual productivity, from an organizational perspective their productivity may in fact be zero or effectively negative if they are dedicated to redundant or value destroying activities.[23] In office buildings and service-centred companies, productivity is largely influenced and affected by operational byproducts—meetings.[44] The past few years have seen a positive uptick in the number of software solutions focused on improving office productivity.[45] In truth, proper planning and procedures are more likely to help than anything else.[46]
Overall productivity growth was relatively slow from the 1970s through the early 1990s,[47] and again from the 2000s to 2020s. Although several possible causes for the slowdown have been proposed there is no consensus. The matter is subject to a continuing debate that has grown beyond questioning whether just computers can significantly increase productivity to whether the potential to increase productivity is becoming exhausted.[48]
National productivity
In order to measure the productivity of a nation or an industry, it is necessary to operationalize the same concept of productivity as in a production unit or a company, yet, the object of modelling is substantially wider and the information more aggregate. The calculations of productivity of a nation or an industry are based on the time series of the SNA, System of National Accounts. National accounting is a system based on the recommendations of the UN (SNA 93) to measure the total production and total income of a nation and how they are used.[49]
International or national productivity growth stems from a complex interaction of factors. Some of the most important immediate factors include technological change, organizational change, industry restructuring and resource reallocation, as well as economies of scale and scope. A nation's average productivity level can also be affected by the movement of resources from low-productivity to high-productivity industries and activities. Over time, other factors such as research and development and innovative effort, the development of human capital through education, and incentives from stronger competition promote the search for productivity improvements and the ability to achieve them. Ultimately, many policy, institutional and cultural factors determine a nation's success in improving productivity.
At the national level, productivity growth raises living standards because more real income improves people's ability to purchase goods and services (whether they are necessities or luxuries), enjoy leisure, improve housing and education and contribute to social and environmental programs. Some have suggested that the UK's 'productivity puzzle' is an urgent issue for policy makers and businesses to address in order to sustain growth.[50] Over long periods of time, small differences in rates of productivity growth compound, like interest in a bank account, and can make an enormous difference to a society's prosperity. Nothing contributes more to reduction of poverty, to increases in leisure, and to the country's ability to finance education, public health, environment and the arts’.[51]
Productivity is considered basic statistical information for many international comparisons and country performance assessments and there is strong interest in comparing them internationally. The OECD[52] publishes an annual Compendium of Productivity Indicators[53] that includes both labor and multi-factor measures of productivity.
Gross domestic product (GDP) is a monetary measure of the market value of all the final goods and services produced and rendered in a specific time period by a country or countries. GDP is often used to measure the economic health of a country or region. Definitions of GDP are maintained by several national and international economic organizations, such as the OECD and the International Monetary Fund.
Growth accounting is a procedure used in economics to measure the contribution of different factors to economic growth and to indirectly compute the rate of technological progress, measured as a residual, in an economy. Growth accounting decomposes the growth rate of an economy's total output into that which is due to increases in the contributing amount of the factors used—usually the increase in the amount of capital and labor—and that which cannot be accounted for by observable changes in factor utilization. The unexplained part of growth in GDP is then taken to represent increases in productivity or a measure of broadly defined technological progress.
Agricultural productivity is measured as the ratio of agricultural outputs to inputs. While individual products are usually measured by weight, which is known as crop yield, varying products make measuring overall agricultural output difficult. Therefore, agricultural productivity is usually measured as the market value of the final output. This productivity can be compared to many different types of inputs such as labour or land. Such comparisons are called partial measures of productivity.
Capital intensity is the amount of fixed or real capital present in relation to other factors of production, especially labor. At the level of either a production process or the aggregate economy, it may be estimated by the capital to labor ratio, such as from the points along a capital/labor isoquant. The inverse of capital intensity is labor intensity. Capital intensity is sometimes associated with industrialism, while labor intensity is sometimes associated with agrarianism.
In economics, a production function gives the technological relation between quantities of physical inputs and quantities of output of goods. The production function is one of the key concepts of mainstream neoclassical theories, used to define marginal product and to distinguish allocative efficiency, a key focus of economics. One important purpose of the production function is to address allocative efficiency in the use of factor inputs in production and the resulting distribution of income to those factors, while abstracting away from the technological problems of achieving technical efficiency, as an engineer or professional manager might understand it.
In economics, diminishing returns are the decrease in marginal (incremental) output of a production process as the amount of a single factor of production is incrementally increased, holding all other factors of production equal. The law of diminishing returns states that in productive processes, increasing a factor of production by one unit, while holding all other production factors constant, will at some point return a lower unit of output per incremental unit of input. The law of diminishing returns does not cause a decrease in overall production capabilities, rather it defines a point on a production curve whereby producing an additional unit of output will result in a loss and is known as negative returns. Under diminishing returns, output remains positive, but productivity and efficiency decrease.
In economics, the concept of returns to scale arises in the context of a firm's production function. It explains the long-run linkage of increase in output (production) relative to associated increases in the inputs.
The Solow residual is a number describing empirical productivity growth in an economy from year to year and decade to decade. Robert Solow, the Nobel Memorial Prize in Economic Sciences-winning economist, defined rising productivity as rising output with constant capital and labor input. It is a "residual" because it is the part of growth that is not accounted for by measures of capital accumulation or increased labor input. Increased physical throughput – i.e. environmental resources – is specifically excluded from the calculation; thus some portion of the residual can be ascribed to increased physical throughput. The example used is for the intracapital substitution of aluminium fixtures for steel during which the inputs do not alter. This differs in almost every other economic circumstance in which there are many other variables. The Solow residual is procyclical and measures of it are now called the rate of growth of multifactor productivity or total factor productivity, though Solow (1957) did not use these terms.
In economics, total-factor productivity (TFP), also called multi-factor productivity, is usually measured as the ratio of aggregate output to aggregate inputs. Under some simplifying assumptions about the production technology, growth in TFP becomes the portion of growth in output not explained by growth in traditionally measured inputs of labour and capital used in production. TFP is calculated by dividing output by the weighted geometric average of labour and capital input, with the standard weighting of 0.7 for labour and 0.3 for capital. Total factor productivity is a measure of productive efficiency in that it measures how much output can be produced from a certain amount of inputs. It accounts for part of the differences in cross-country per-capita income. For relatively small percentage changes, the rate of TFP growth can be estimated by subtracting growth rates of labor and capital inputs from the growth rate of output.
The Solow–Swan model or exogenous growth model is an economic model of long-run economic growth. It attempts to explain long-run economic growth by looking at capital accumulation, labor or population growth, and increases in productivity largely driven by technological progress. At its core, it is an aggregate production function, often specified to be of Cobb–Douglas type, which enables the model "to make contact with microeconomics". The model was developed independently by Robert Solow and Trevor Swan in 1956, and superseded the Keynesian Harrod–Domar model.
The productivity paradox refers to the slowdown in productivity growth in the United States in the 1970s and 1980s despite rapid development in the field of information technology (IT) over the same period. The term was coined by Erik Brynjolfsson in a 1993 paper inspired by a quip by Nobel Laureate Robert Solow "You can see the computer age everywhere but in the productivity statistics." For this reason, it is also sometimes also referred to as the Solow paradox.
Compensation of employees (CE) is a statistical term used in national accounts, balance of payments statistics and sometimes in corporate accounts as well. It refers basically to the total gross (pre-tax) wages paid by employers to employees for work done in an accounting period, such as a quarter or a year.
In microeconomic theory, productive efficiency is a situation in which the economy or an economic system operating within the constraints of current industrial technology cannot increase production of one good without sacrificing production of another good. In simple terms, the concept is illustrated on a production possibility frontier (PPF), where all points on the curve are points of productive efficiency. An equilibrium may be productively efficient without being allocatively efficient — i.e. it may result in a distribution of goods where social welfare is not maximized.
In economics, the wage share or laborshare is the part of national income, or the income of a particular economic sector, allocated to wages (labor). It is related to the capital or profit share, the part of income going to capital, which is also known as the K–Y ratio. The labor share is a key indicator for the distribution of income.
Workforce productivity is the amount of goods and services that a group of workers produce in a given amount of time. It is one of several types of productivity that economists measure. Workforce productivity, often referred to as labor productivity, is a measure for an organisation or company, a process, an industry, or a country.
In economics, gross value added (GVA) is the measure of the value of goods and services produced in an area, industry or sector of an economy. "Gross value added is the value of output minus the value of intermediate consumption; it is a measure of the contribution to GDP made by an individual producer, industry or sector; gross value added is the source from which the primary incomes of the System of National Accounts (SNA) are generated and is therefore carried forward into the primary distribution of income account."
Production is the process of combining various inputs, both material and immaterial in order to create output. Ideally this output will be a good or service which has value and contributes to the utility of individuals. The area of economics that focuses on production is called production theory, and it is closely related to the consumption(or consumer) theory of economics.
Productivity in economics is usually measured as the ratio of what is produced to what is used in producing it. Productivity is closely related to the measure of production efficiency. A productivity model is a measurement method which is used in practice for measuring productivity. A productivity model must be able to compute Output / Input when there are many different outputs and inputs.
Research and development intensity is generally defined as expenditures by a firm on its research and development (R&D) divided by the firm's sales. There are two types of R&D intensity: direct and indirect. R&D intensity varies, in general, according to a firm's industry sector, product knowledge, manufacturing, and technology, and is a metric that can be used to gauge the level of a company's investment to spur innovation in and through basic and applied research. A further aim of R&D spending, ultimately, is to increase productivity as well as an organization's salable output.
Profit, in accounting, is an income distributed to the owner in a profitable market production process (business). Profit is a measure of profitability which is the owner's major interest in the income-formation process of market production. There are several profit measures in common use.
References
Citations
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