Industrial productivity: what it is and how to measure it

In one line

Productivity is the ratio between what is produced and the resources consumed to produce it. It is not a synonym for working faster, or for keeping everyone busy all the time.

What it is

The definition the ILO uses is simple: productivity is the relationship between a measure of output and a measure of the use of inputs. Inputs can be labor hours, invested capital, materials or energy. When people talk about "productivity" without further clarification, they almost always mean one of these three types:

• Labor productivity: output over hours worked or over people employed. It is the most widely used because the data exists in almost any company.
• Capital productivity: output over the volume of installed capital (machinery, equipment, facilities).
• Multifactor productivity (or total factor productivity, TFP): relates output to several combined inputs at once: labor, capital and intermediate inputs. It is usually calculated as a residual: the part of output growth that is not explained by more labor or more capital, but by using them better.

One point the ILO guide explicitly highlights because it is often confused: productivity is not the same as competitiveness. A company can be very productive and still not be competitive if the product does not have the quality, price or timing the market demands. Productivity is a necessary condition for competing, not the only one.

A simple example to visualize the concept

The same ILO guide illustrates labor productivity with a case outside the factory, precisely because you do not need technical jargon to understand it: Lionel Messi and Cristiano Ronaldo in the 2017-2018 season of Spain's La Liga. Messi scored 34 goals in the season against Ronaldo's 26, so he had higher productivity measured in goals per season. But Ronaldo averaged 0.96 goals per match played against Messi's 0.94, because Ronaldo played in fewer matches. Neither measure is "the right one": it depends on which input is used as the denominator (the full season or the hours actually played), just as in a plant, productivity per worker and productivity per hour worked can give different readings of the same process.

What it is for

Measuring productivity is not an academic exercise. The ILO documents the link between productivity and concrete results:

• Company profits and growth: a study of medium-sized textile companies in India (Bloom et al., 2013) found that a 17% increase in productivity translated into USD 300,000 more profit per company in one year, and into a tripling of the number of production plants within three years.
• Wages: a study by Stansbury and Summers (2017) found that a 10% increase in productivity is associated with a 7.4% increase in workers' real compensation in the United States.
• Customer costs: the productivity increase in U.S. telecommunications between 1970 and 2000 reduced the cost of a long-distance call to one sixth of what it cost before.

The pattern repeats at different scales: more productivity not only improves the company's results, it also pushes wages up and prices down. That is why a plant management team that only measures OEE or equipment availability, without looking at labor and capital productivity, is missing half the picture.

How it is measured

A single productivity indicator, for example units per man-hour, tells you whether something improved or got worse, but not why. Leonard Mertens, in work developed by the ILO together with Mexico's CIMO program, proposes measuring productivity in three complementary subsystems:

1. Economic-financial indicators: the highest-level ones: margin, return on assets, labor cost per hour, value added per hour worked. They are useful for strategic planning but do not explain what happens on the plant floor: they are the "black box" of the process.
2. Process management indicators: they open that black box. They are physical-technical in nature: equipment downtime, model changeover time, reworked output, lead time between departments, delivery compliance. They change over time as improvements advance, unlike the financial ones, whose calculation method is more stable.
3. Human resources performance indicators: these are built by the staff themselves, not imposed from outside. They measure commitment to achievable performance goals, defined in a participatory way according to the real technological and organizational context of each work team.

At the level of individual indicators, the ILO guide lists the ones most used in practice:

• Output per hour worked: volume produced ÷ hours worked in the period.
• Output per worker: volume produced ÷ number of people employed.
• Revenue per worker: sales for the period ÷ number of workers.
• Revenue per hour worked: sales for the period ÷ hours worked.
• Capital productivity: production volume ÷ volume of installed capital (equipment, facilities).
• Total factor productivity (TFP): change in output that is not explained by more labor or more capital, but by using them better.

The key point: none of the indicators on this list works on its own. An increase in output per hour worked can be due to the staff working better, or simply to the company buying a faster machine. These are two completely different causes that call for completely different actions, and they can only be told apart by also looking at the process indicators.

How it is applied on the plant floor

The most practical contribution of Mertens' methodology for industrial plants is that it does not require highly trained staff to implement it, and there is a documented case that proves it. At a Mexican sugar mill, the SIMAPRO methodology (Productivity Measurement and Advancement System) was applied for several years with working groups of up to thirty people, mixing operators, supervisors and managers, even though the average educational level of the operating staff did not exceed three years of primary school while the area heads were engineers, some with master's degrees. The process has three stages:

1. Visualizing problems and solutions: each person identifies, through simple exercises (even a drawing of their own workstation), the main problems they see in their area, without needing to know how to read financial indicators.
2. Self-commitment to performance goals: the working group, not management alone, defines what level of performance is achievable given the real context (available technology, training, labor relations).
3. Periodic feedback meetings: the agreed indicators are reviewed and the plan is adjusted. At the sugar mill, in the third year of application the plant put the focus on how these same meetings worked, expanding the indicators to safety and absenteeism in the highest-risk areas, and it set up a supervisor training program of more than 200 hours so that they could sustain the role of process facilitators.

Real example

Medium-sized textile companies in India (Bloom, Eifert, Mahajan, McKenzie and Roberts, 2013, cited in the ILO guide). A group of medium-sized textile plants received consulting on productivity management practices. The documented result: a 17% increase in productivity translated into USD 300,000 of additional profit per company in the first year, and the number of production plants of the participating companies tripled within three years. It is one of the few cases where the whole chain is visible in numbers: better management → more productivity → more profit → more installed capacity.

Sugar mill in Mexico (Mertens / ILO-Cinterfor). The case described above, in the "How it is applied on the plant floor" section, is the same kind of result seen from the plant floor instead of from the financial statements: productivity measurement was not left in the hands of a finance department, but became part of the routine of supervisors and operators with little formal education, sustained over several years.

Benefits

• It gives an objective criterion for deciding where to invest (training, technology or management) instead of deciding by intuition or by the urgency of the day.
• It connects directly with results that matter to management: profit, installed capacity, workers' compensation.
• The three-subsystem approach (financial, process, HR) avoids the mistake of looking only at the final number without understanding what moves it.
• A participatory system like SIMAPRO improves communication between hierarchical levels as a side effect. It is not just a measurement tool, it is also a people management tool.

Limitations to keep in mind

• A productivity indicator can go up for reasons unrelated to staff performance (better machinery, lower staff turnover, a change in product mix), and you have to separate those causes before rewarding or correcting anyone.
• Comparing the productivity of very different companies or lines (different industry, different technology) says little; the value is in comparing the same unit against its own history.
• The three measurement subsystems can become disconnected from each other in practice: it is common for the finance area to have no notion of what is critical in the process, and vice versa. Mertens documents this as the main management challenge, not an exception.
• An indicator system built "from the outside," without the participation of the staff who will use it, tends to lose legitimacy and ends up abandoned. The SIMAPRO experience was effective precisely because the staff helped define their own goals.

In summary

Productivity is output over inputs, and it is measured best with three layers (financial, process and human resources) rather than with a single isolated number. The Indian textile case shows the impact it can have on a company's results (17% more productivity, USD 300,000 more profit in one year), and the Mexican sugar mill case shows that measuring and improving it in a participatory way works even in plants with staff of low formal education, as long as the system is built with the people who will use it every day.