LP can be measured for both the market and non-market sectors of the economy. This is because labour input can be measured in real volume terms as hours worked. MFP is a measure closer to the concept of productive efficiency than LP as it removes the contribution of capital deepening from the residual. Two potential sources of change in measured productivity warrant special attention: unmeasured inputs that affect real costs, and capacity utilisation. There are also a number of measurement problems associated with estimating output and input volumes.
In some industries, inputs other than capital and labour and knowledge can have a strong influence on output. Where these inputs are not purchased in the market, as is the case with some natural resource inputs and volunteer effort, they are not included in the measure of inputs.
If the availability or quality of these inputs is changing then productivity estimates, as the residual, will be affected. Recent Commission research has identified Mining, Utilities, and Agriculture as industries where the MFP estimates are affected by changes in unmeasured inputs.
These industries are all dependent on natural resource inputs. Deterioration in the quality of the natural resource input, or more stringent regulatory restrictions on the uses of such inputs, can reduce measured productivity despite the productive efficiency of the firms in the industry remaining unchanged or even improving.
Business output responds to market demand. As demand rises or falls over time with the business cycle or other influences, firms adjust the output they produce. In the case of cyclical downturn, many firms will reduce output volumes, but cannot easily reduce their capital and labour inputs as they need these inputs ready for when demand recovers.
As a result, firms are likely to underutilise their capital and labour inputs in a downturn and productivity will be lower. When business is booming, firms will fully utilise their capital and labour. Hence, measured productivity tends to be pro-cyclical as utilisation rates of inputs rise in upswings and fall in downswings. Many industries experience cycles in demand that affect capacity utilisation but industries with high levels of fixed capital, such as manufacturing, tend to be more exposed to the business cycle.
This means that annual productivity estimates are likely to under or overstate the underlying trend level of productivity depending on where the industry is in the business cycle. To assist users to interpret measured productivity, the ABS divides time series MFP into productivity cycles for the market sector. Productivity measurement is simply too important to be delegated to productivity specialists.
A set of practical guidelines can help them understand, evaluate, and apply productivity measurement techniques effectively. What is productivity? Productivity is not about wages. High wages can present a problem, not because workers are paid too much but because they produce too little. In deciding how best to measure productivity, managers should focus not on dollars per hour but on labor dollars per product.
That is, on labor content, not labor cost. Workers who are very productive can be paid thousands of dollars more than employees elsewhere and the business can still prosper, as manufacturers like Lincoln Electric have demonstrated. Productivity measurement should focus on overall capabilities, not on one set of costs. How good is your company at taking a pile of raw materials, a bunch of machines, stacks of paperwork, and groups of employees, and turning out useful goods or services?
It is, as much as possible, a relationship between physical inputs and outputs. The formula is disarmingly simple. The company producing more with a given set of inputs capital, labor, and materials or using fewer inputs to produce the same output has an advantage over the company producing less. Lower input costs create an added advantage—but not the principal advantage that productivity measures must identify.
The central mission of a productivity index is to illuminate how a business can get more units of output per labor hour, per machine, or per pound of materials than its competitors. Still, much of U. At the national level, productivity figures do mean labor productivity. The Bureau of Labor Statistics, the primary source of productivity information, logically enough focuses on labor productivity.
Cost accounting also reinforces this bias. The allocation of overhead, for example, is often based exclusively on labor hours. This approach may have been reasonable when labor hours represented a large percentage of total costs, but today, for many businesses, labor is a minor cost element. But there is much more to productivity, and many companies miss opportunities to bolster efficiency in nonlabor areas.
Consider one U. His intuition proved correct, as Exhibit I illustrates. His subordinates are now looking for ways to reduce overhead and make better use of technology. Single-minded attention to direct labor can produce unexpected consequences.
Several years ago, a big New York bank concerned about labor costs in its back office implemented a department-by-department system to measure productivity, defined as transactions per employee. Senior management gave high visibility to the new system and even used it to calculate a large portion of the bonuses it paid to line managers. So the line managers computerized everything in sight.
The result was increased productivity in every department but one—data processing. While staff was shrinking in the rest of the bank, data processing came under incredible pressure. It boosted its staff as well as its spending on hardware and software. If that expansion in overhead was best for the bank, executives could never say for sure; their measurement system focused only on the productivity of direct labor.
The trouble with single-factor productivity measures whether output per labor hour, output per machine, or output per ton of material is that it is easy to increase the productivity of one factor by replacing it with another. Labor, capital, and materials are all potential substitutes for each other. Effective productivity measurement requires the development of an index that identifies the contribution of each factor of production and then tracks and combines them.
Take a hypothetical plant that machines purchased castings as one step in its production of motors. Now the company decides to purchase this component premachined. What happens to productivity? Output has remained constant, but the number of workers has fallen, so labor productivity is up.
So too is capital productivity, by virtue of the lower asset base. But with top management pushing hard for identifiable productivity increases, there is a real risk that defining productivity too narrowly will lead to unsound decisions by subordinates. A multifactor view of productivity is important, therefore, but it is difficult for one index to encompass all inputs.
Using several different single-factor measures can also yield a multifactor perspective. Indeed, even if a plant uses one aggregate measure, it still makes sense to use single-factor measures because they help identify the sources of aggregate productivity trends. A big change in a multifactor productivity measurement raises obvious questions: Is the change due to simultaneous shifts in the productivity of labor, capital, and materials, or has only one dimension changed? Economists and productivity specialists like to use sophisticated functional forms when they combine labor, materials, and capital into one index.
Rather than simply adding everything up or averaging inputs, they prefer logarithmic and multiplicative techniques. When the chief goal is to study productivity behavior, as in statistical research, these approaches have theoretical advantages. Within Northern Telecom, some divisions make sure managers and workers understand multifactor productivity by including them in the design of department-specific indexes and by keeping the indexes simple.
Petra Jahchan Writer, Formative Content. Take action on UpLink. Image: conference-board. Average weekly hours per worker, G7 countries.
Image: Office of National Statistics. Does innovation improve productivity? License and Republishing. Written by. More on Inclusive Growth Framework View all. How to finance digital inclusion so universal access to the internet drives sustainable growth While COVID has accelerated a global transition towards a digital economy, the crisis has also shed even more light on the digital divide.
Derek O'Halloran 11 Oct Of course, this requires having a clear understanding of what your goals are. Knowing what matters to your company will ensure you avoid measuring aspects of productivity that have little relevance to your business.
Measuring near-term targets is an excellent way to track your progress toward larger goals. For instance, you can track and compare different types of week-by-week productivity. When you have regular productivity measures in place, you can make changes to your operation and check if the adjustment has a positive or negative effect.
In fact, you can continue to make constant tweaks to optimize the results. You want your employees to be productive and they want to do the best job possible. Provide feedback to individuals by turning productivity measurements into a rating scale. This will help you track growth and will tell your employees where they need to improve. Too often, employers are worried about seeing a drop in productivity. As a result, they quash innovation — but this ultimately means that growth stagnates.
By using productivity measures, you can encourage workers to try innovative ideas and test if these tactics work. Many factors that impact productivity at the workplace are out of your control, but there are plenty of aspects you do influence. For instance, whereas you may be unable to prevent competition and you have no sway over the wider economy, you can have a direct influence over your employees.
By measuring productivity, you can see how your business reacts to factors both in and out of your control, which can guide your efforts in the future. The next step is to improve those factors that are under your control. Share it with your team! Laura Holton. Laura is a professional writer specializing in content aimed at small businesses and entrepreneurs.
She has helped countless startups find the information they needed to take their ventures to the next level. Receive a notification whenever we publish a new post.
Be the first to read our tips and tricks for business owners and other professionals. Types of Productivity Measures Within an organization, there are four main types of productivity. Capital Productivity Capital productivity tells you the ratio of products or services to physical capital.
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