Classically, productivity is defined as Output divided by Input.

-or-

Some say productivity is the same as profit, selling price minus all costs

-or-

Toyota sees Profit = (Price – Cost) x Volume, assuming that the manufacturer cannot dictate the sales price.

Different mathematics, same theory:

JPR offers the complimentary summary below, of productivity viewed from the industrial context, because we have found that any theoretical measurement must be carefully interpreted to yield meaningful results. You are welcome to apply the following insights within your organization.

Just because there are complicating factors to productivity measurement, do not stop the effort to measure. Recognize that answers may not be perfectly accurate, but still can be a good indicator of productivity change. And you can fine tune the initial mechanism to yield ever better results.

This summary is academic in nature. For specific ways to improve business productivity, please click on the Improve Productivity link to the left.

Generally when "Productivity" is discussed, we really mean "Labor", the people side of the manufacturing enterprise. But if we measure only labor we get information that is useless at best and misleading at worst. One company may be highly automated, so their labor productivity is very good compared to a more manual company. But the automated company may be unprofitable because it has so much money invested in equipment, or runs higher expense to maintain equipment. Delphi in 2005 sought bankruptcy protection at the same time that many of its factories were winning Lean Manufacturing awards.

Measure total productivity in an organization to capture the comprehensive effect of labor, executive prowess, waste, equipment utilization, effective automation, employee input, sales and marketing, new products, product quality, customer service. See how the result tracks with the bottom line of the P&L over a period of time. Since corporate results do not indicate where a problem may be, measure smaller entities as well, both line and staff.

Many financial measurements are in use already for management to monitor some portion of overall productivity. Accounts receivable days outstanding, and inventory turns, and return on investment, and net profit to name a few.

Is it possible to look at one productivity number and learn if it represents an acceptable rate or not? No. There is not one magic number because are too many variables involved. One can at best measure productivity over a period of time and determine how much it changes. Even then, a result does not indicate what actions caused the change.

You will probably need to apply different units of measure, because the groups being measured are different, and their output is expressed differently. If possible, relate units to the business of the entity, tractors produced, insurance policies written, ads sold, packages delivered.

Measure a factory by units of tractors produced, but the sales organization by tractors sold, and the customer service group by tractors maintained.

Some departments are organized to produce a service for the organization. State the mission of such a department, define expected results, and measure their productivity as they perform the mission.

Some departments, usually of a general management nature, have much to do with overall productivity but department output is not easily defined. Include these people in overall division or corporate measurements. The key to meaningful results is to incorporate all functions into one or more productivity measures.

The preferred productivity units for large or small entities should be dollars spent per unit of output generated, because measuring man-hours alone does not account for capital investment and overhead expense, which are both major factors in productivity.

A productivity value as stated has no meaning alone. Measure again in a month using exactly the same procedures, or last year, and the values start to have significance.

Use a productivity measurement in conjunction with other performance data such as profitability or return on investment or cash flow. If a company is profitable but has a lower productivity than another, that indicates an opportunity but not a cause for alarm. Different companies have different automation levels, or inventory strategy, or vertical integration, or training levels, or employee / contractor levels, or regulatory requirements. All of those factors affect productivity measurement.

For meaningful insights, measure within the organization. Define a measurement system, make calculations for a particular time frame, then another calculation for a different time frame. How do they compare? Internal comparisons between entities may show differences in productivity that reflect operating conditions, perhaps a newer facility is more productive, or one with a more stable work force, or an automated one. Overhead allocation must be correct for accurate internal comparisons.

A Regulatory Affairs group is absolutely necessary in some industries. Including its costs in a productivity measure can make comparison with a non-regulated industry meaningless. A major Research and Development group also is difficult to measure, as costs are extensive yet benefits usually affect future years more than immediate results. If these groups have proven management techniques to plan and control their effectiveness, they may well be excluded from corporate productivity measures.

Other plant, division, and corporate functions should however be included in productivity results. Groups such as sales, marketing, quality, HR, IT may also be hard to measure but that is all the more reason to include them in productivity calculations based on corporate sales and profit values. These particular groups often incur or cause capital and expense costs in the expectation of increased productivity in an operating department, so an overall measurement "before" and "after" can be an effective way to monitor result against intentions.

Comparisons tend to be inaccurate unless they are "apples to apples", or they assure that all factors are the same from one comparison to another. Yet comparisons over time seldom involve purely identical sets of variables.

One significant variable in productivity measurement is sales volume. Sales volume will always affect productivity measurement; incrementally more volume will cause more direct cost of materials and labor, but usually no more plant managers or corporate aircraft or receptionists. Most companies will therefore convert added sales to better productivity as well as better overhead absorption and better profits. Incrementally less volume will have the opposite effect.

The net effect of variables is that comparisons will be usually require some interpretation.

A group may be busy but not productive. If output is measurable but has no value to the business entity, then the group that generates such output may have 100% busy-ness but zero productivity.

Another group may not be always busy but at the same time contribute extensively to the productivity of their overall organization. Examples are maintenance people who keep their equipment in good repair so that they can stand by while operators produce. A busy maintenance person usually means the equipment is not at work and that is bad. Other groups who should be idle for good overall productivity are security guards, police and firemen.

Preventive maintenance hours may take the place of demand maintenance, and crime prevention and better building codes may take the place of emergency reactions. Costs may be shifted but still be present.

Be advised that the results of any measurement, productivity or otherwise, can report only part of the story, the final result; it does not report what caused the result. For instance, the much emulated Toyota Production System emphasizes personal development of line workers and supervisors, which is usually accomplished by training. In a productivity measurement result, training will appear to be unproductive but would shortly lead to even higher productivity.