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It is not a separate unit in the hospital - patients are treated in whatever ward or facility is best suited to their needs. Referrals come into the administration office. Prospective patients are sent a form which asks whether their treatment is urgent or routine, and when the patient is available for an appointment. This is very important as seafarers are often away at sea and are unable to cancel appointments. Due to the distances travelled by seafarers from home and from ships around the world, accommodation is also arranged for them.

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No-Nonsense Guide to Measuring Productivity

A few years ago, a major manufacturing-based conglomerate asked a gifted mathematician to join its corporate staff. He devoted many months to the assignment and also tapped the knowledge of […].

Some productivity indexes boast technical elegance and statistical precision—but have little to do with daily management decision making, or even, for that matter, the bottom line. What you need is enough good information to enable you to determine how well your company is taking a pile of raw materials, a bunch of machines, stacks of paperwork, and groups of employees, and turning out useful goods or services.

As long as you stay mindful of how the perfect can get in the way of the good, a few basic guidelines can help you design a system that meets your needs. What is productivity anyway? Rather, productivity is output divided by input. So the job of productivity measurement is to highlight how to get more units of output goods produced or services rendered for each unit of input materials, labor hours, machine time than your competitors are able to deliver. One U. Effective productivity measurement, therefore, takes a multifactor perspective: it identifies the contribution of each factor in production, and then combines the factors to create an understanding of productivity trends.

Keep your measurement system simple—not because people are stupid, but because they need an intuitive grasp of a measurement in order for it to affect their decisions and priorities. Then, too, the effort required to get a slightly more precise measurement may not be worth it. He devoted many months to the assignment and also tapped the knowledge of several academic experts.

The result was a truly sophisticated model that combined historical performance data with economic forecasts to set target productivity levels for each business unit.

So headquarters asked the obvious question—Why? Why was an organization that was generating handsome profits and cash flows showing such disappointing productivity? The expert could not answer the question, nor was his model designed to do so. Not surprisingly, executives saw little value in the new system and scrapped it. Staff specialists or outside consultants—experts in cost accounting, statistics, and economics—usually play an important role in designing these systems.

But specialists are often trained to focus on the technical elegance and statistical accuracy of productivity indexes. All too often, they introduce methods that are very precise but ignore the real challenges managers face.

While collecting information on productivity measurement systems and interviewing managers at plants across the United States during the last several years, I have seen many examples of effective productivity measurement—systems that have led to big strides in operating efficiency. But more frequently I have encountered frustration and confusion.

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. A department develops several performance ratios no fewer than three, no more than seven that it believes capture the essence of its mission. For example, one design engineering team proposes six ratios, among which are: reworked drawings as a percentage of total drawings, overdue drawings as a percentage of total drawings, and overtime hours as a percentage of total hours.

Next the department identifies current performance, long-term goals, and interim goals for each ratio. Finally, managers assign weights to the ratios to reflect their relative importance, with the sum totaling This approach is not analytically perfect; there is no statistical reason to limit the number of ratios to seven, for example, and the weighting scheme is undeniably subjective.

But Northern Telecom follows a basic principle that many other companies fail to appreciate: when deciding whether you need greater measurement precision, ask first whether greater precision will make a real difference in subsequent actions to improve productivity. Executives should seek the measure that promises the greatest impact, not the measure boasting the greatest accuracy or technical elegance.

The same principle applies to data collection. There are real costs associated with developing and implementing elaborate productivity systems. My research suggests that the point comes—sometimes very early on—where increased accuracy is not worth additional cost.

For example, the mismatch between the information provided by some accounting systems and what is needed for productivity analysis often means that bypassing the accounting data and developing data specifically for the productivity index will raise accuracy.

But it is seldom worth the cost. The costs can go even higher if you consider another factor: the time it takes to develop and implement a productivity measurement system. But the challenge goes further. Conventional systems to measure productivity often overlook two aspects of the production process that are becoming very important in determining international competitiveness: production time and the role of employees other than shop-floor workers.

Since neither lends itself well to direct measurement, productivity technicians often prefer to look the other way. Managers do so at their peril.

The first oversight, time, is not purchased, so it is usually ignored. If two businesses use identical machines, the same number of people, and equivalent materials to produce identical products, most productivity indexes would produce identical scores. But suppose one business ships orders within three days of receiving them and the other takes three weeks. Is their productivity the same? Obviously not. This is not an exaggerated example.

Increasingly, companies are discovering the competitive power of shortening their production cycles—or the dangers of not doing so. But unless a productivity index assigns some value to the amount of time consumed, it is unrealistic to expect managers to focus on shortening turnaround times.

Assigning inventory carrying costs is a step in the right direction, although most companies record carrying charges far below their true competitive costs.

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News reporter SkyRussHope1. One east London brewer has taken the idea of serving pints to a whole new level by bringing them to his customers stuck at home because of the coronavirus pandemic. It's nearly two months since the government ordered Britain's pubs and bars to close to help slow the spread of the coronavirus pandemic. Under lockdown rules, food and drink suppliers can still offer delivery services, but though many firms have started delivering cans, the trade has taken a huge hit.


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A few years ago, a major manufacturing-based conglomerate asked a gifted mathematician to join its corporate staff.

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