Who is responsible for productivity in an organisation

The price of coffee beans in dollars is therefore an enormous monetary risk for the company because resource scarcity could raise its expenses exponentially. Its controllers must hedge against these risks. Privacy Policy. Skip to main content.

Search for:. Managing Productivity. Defining Productivity In control management productivity is defined as the overall efficiency and output of a given operational system. Learning Objectives Define productivity in the context of management and control. Key Takeaways Key Points Productivity is defined as a total output per one unit of a total input.

In control management, productivity is a measure of how efficiently a process runs and how effectively it uses resources. Managing production levels is part of the control process.

Productivity growth is important to a business because it controls the real income means needed to meet obligations to customers, suppliers, workers, shareholders, and governments taxes and regulation. Key Terms input : Something fed into a process with the intention of it shaping or affecting the outputs of that process.

The Importance of Productivity Productivity is the ratio of total output to one unit of total input; high productivity means larger capital gains. At the very least, the research study should clearly delineate. At the organizational level, a firm may be highly productive but fail because of its inability to manage prices, costs, cash flows, and debt.

A firm, therefore, will track many aspects of performance besides total firm productivity. At the individual level, however, the emphasis usually is on productivity and cost per unit produced. Currently, a major thrust in cost accounting research is attempting to revise methods for assigning overhead costs to products and services produced Cooper and Kaplan, These efforts may make the connection between productivity and cost more compatible and more meaningful at the individual level of analysis.

Productivity researchers, however, should continue their efforts to develop individual-level productivity measurement systems that can be integrated with these new developments in unit cost analysis. No measurement system is perfect; a variance between actual and measured results will likely always exist.

The variance can be reduced, however, by reducing simple errors not counting correctly , reducing conceptual errors not counting the right things , checking the reliability and validity of surrogate measures, and verifying the logic of using pseudoproductivity measures such as measuring activities as an indicator of results. Two dangers arise in attempting to reduce measurement errors, however.

First, by trying to meet all criteria, the measurement system may become so complex that it loses its practicality. Second, the nearperfect measurement system may generate such high demands for data gathering and analysis that the cost of the system is not justified and the results are not timely enough to be useful.

Although reducing measurement error should be a continuing goal, a compromise between this goal and the usability of the measure is generally in order. Much has been written about developing systems for measuring individual productivity; less has been said about how the results of the measures are to be used.

A number of the considerations raised in this section imply misuses of productivity data, such as measuring a worker. Other common misuses include using the results as a whip to speed the pace of work or to place blame on a worker for poor performance.

Unfair comparisons, such as using the same measure under vastly different circumstances, can also cause problems. Research into the development of a system for measuring individual productivity should not stop when the system is implemented. The integration of productivity measures with other measures of performance should be documented, and the effective and ineffective uses of productivity data should be explored.

The challenge before researchers and practitioners is to develop internally consistent and comprehensive productivity measurement systems that account for the productivity of individual workers, work groups, business units, and organizations.

The degree to which this goal can be achieved will determine the ability of organizations to manage resources effectively and direct human effort toward organizational goals. It may help them regain the industrial leadership they have lost and understand the apparent paradoxes that ensue when expected productivity gains are not realized.

Consistent productivity measurement systems will enable researchers and practitioners to speak a common language as they each play their role in solving the problems associated with poor productivity growth. The difficulty in developing a comprehensive productivity measurement system stems from a number of factors, in particular the following:. The concept of productivity is still often misunderstood; discussions of the relationship of productivity to effectiveness, efficiency, quality, innovation, and financial or behavioral measures of performance take the form of debates.

A common definition of productivity, at all levels of organizational analysis, is a prerequisite for the development of a comprehensive measurement system. Attempts to aggregate individual productivity measures or to disaggregate organizational measures are thwarted by the dissimilarity in measures of output. At the individual level, output is often counted in physical units of product produced or service provided.

At higher levels of analysis, different outputs from different sources are combined in some form of weighting scheme, sometimes using cost or price data that are incompatible with financial measures at the individual level, given current cost accounting methods.

On the input side of the productivity ratio, individual productivity is often measured only against labor input, and labor may be counted in a number of different, but acceptable, ways. At the organizational level, a total factor approach is often used, that is, inputs consist of labor, materials, capital, and energy.

In most organizations today, the amount of indirect or managerial work far exceeds the direct labor associated with producing products and services.

The productivity of indirect labor and, to a lesser extent, managerial efforts can be measured in terms of results achieved and resources consumed. Often, however, the contribution of these activities to the productivity of the organization is unclear. If the organization was evaluated strictly by the value of products produced relative to inputs, it would have, for example, no training function; but such myopic views would never be accepted by the enlightened manager.

Current productivity measurement systems suffer from an inability to capture and integrate the contribution of indirect functions, such as training, into the productivity equation for the organization. When individuals are formed into work groups or teams, linkages are formed between the effort of the individual and the output of the group.

The nature of the linkage is dependent on the structure of the group, characteristics of the individuals, psychological factors, sociological factors, technological variables, and system variables. The complex interactions that take place in cooperative productive behavior, however, are seldom captured in common productivity measurement systems.

In their efforts to understand and control work group behavior, managers and researchers alike are hampered by inadequate measurement systems.

Progress toward the goal of developing internally consistent and comprehensive productivity measurement systems will require a joint effort between practitioners and researchers. Greater understanding of the concept of productivity, common definitions of terms, and the building of conceptual models of productivity provide the requisite framework to develop and refine productivity measures.

Better productivity measurement will help to organize and unify the building of a common body of knowledge on productive behavior. Cooper, R. Profit priorities from activity-based costing. Harvard Business Review — Forrester, J. Industrial Dynamics. Cambridge, Mass. Hershauer, J. A worker productivity model and its use at Lincoln Electric. Interfaces — Lawler, E. New York: McGraw-Hill. McGrath, J. Groups: Interaction and Performance. Englewood Cliffs, N.

Ruch, W. Factors Affecting Worker Productivity. Tempe: Arizona State University. Steiner, I. Models for inferring relationships between group size and potential group productivity. Behavioral Science Evils of research—or what my mother didn't tell me about sins of academia. American Psychologist Sutermeister, R. People and Productivity , 2nd ed. Werther, W. Ruch, and L. Productivity Through People.

Paul, Minn. By one analysis, a 12 percent annual increase in data processing budgets for U. This timely book provides some insights by exploring the linkages among individual, group, and organizational productivity. The authors examine how to translate workers' productivity increases into gains for the entire organization, and discuss why huge investments in automation and other innovations have failed to boost productivity. Leading experts explore how processes such as problem solving prompt changes in productivity and how inertia and other characteristics of organizations stall productivity.

The book examines problems in productivity measurement and presents solutions. Also examined in this useful book are linkage issues in the fields of software engineering and computer-aided design and why organizational downsizing has not resulted in commensurate productivity gains.

Important theoretical and practical implications contribute to this volume's usefulness to business and technology managers, human resources specialists, policymakers, and researchers. Based on feedback from you, our users, we've made some improvements that make it easier than ever to read thousands of publications on our website. Jump up to the previous page or down to the next one.

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Organizational Linkages: Understanding the Productivity Paradox. Page Share Cite. A Conceptual Productivity Model. The Productivity Servosystem Model. Elements of the Model. Input Factors. Types of Work Group Structures.

Several conclusions follow from these examples: Many alternative structures exist for the accomplishment of a given group task. Types of Productivity Linkages. Determining the Unit of Output. Determining the Unit of Input. Companies can make work easier for people if they specified channels for urgent and non-urgent issues. A medical device manufacturer I worked with set up the following communication protocol to clarify what tool to use in each situation.

The benefit was dramatic, as they were liberated from the need to check all incoming emails for urgent issues. They could focus on work requiring deep, uninterrupted thought, secure in the knowledge that they only needed to pay attention to text messages or phone calls. This misalignment leads to frustration, stress, and overburden.

He diverted a container that was en route to the U. The rule is simple: if an employee is responsible for an outcome, they should have the authority to make the necessary decisions, without being forced into an endless string of emails, meetings, or presentations. The manufacturing company W. Gore has spent decades developing and refining the culture, systems, and processes to support their unique organizational structure, so it might be difficult for another company to copy their model.

You have 1 free article s left this month. You are reading your last free article for this month. However, knowing this and actually being able to do something about it are two different things. In recent years, productivity has suffered a turn for the worst in countries like the UK where the economic downturn of caused employee output to take a deep dive. But not all is lost, as it has been increasing slowly but steadily.

Last year, it was at its highest with an increase of 0. Technology has advanced and the economy somewhat improved, yet productivity remains a hard nut to crack when it comes to increasing it. So it is time we take a deeper look into it and answer the questions:. What causes employee productivity to increase and how can we apply it to our organizations? There are several things that can affect productivity, such as engagement, good people management practices, workplace environment, appropriate tools, use of technology as an advantage, etc.

Each of these factors influence our employees and affect their productivity, and whether this is a negative or a positive effect is completely up to us. Productivity today is highly linked to everything else, so what can we do to improve the conditions that help it increase? In our article The Real ROI of Learning and Development , we briefly discuss the findings of Maia Josebachvili, who exposes the positive consequences of investing in proper people practices in her article How to understand the ROI of investing in People.

Her findings clearly show the advantages of not only investing in your people but doing it right. It does not help to invest without the knowledge of what you want to achieve with said investment and without a strategy to get there. Moreover, in our following article Using Learning and Development to increase Employee Engagement , we explain how engagement is the fuel which keeps employees improving and thus keeps the organisation on top of their industry. In other words, an organisation with high levels of employee engagement is at least twice as productive as its counterparts with lower employee engagement.

This means that not only are employees disengaged but also looking for new jobs which,, will bring associated costs in: recruitment, training and one precious but often underlooked resource, time. So how can you stop this from happening? Something as simple as investing in your people will take you a long way.