Productivity in Apparel Manufacturing: Back to Basics - Apparel Resources India (2024)

The task of a manager of an apparel manufacturing firm, in the new millennium, has become quite challenging. The growing international competition has put a lot of pressure on the apparel manufacturers to produce quality products at competitive prices and deliver them to the customer just-in-time. In this scenario, managers of apparel firms need to lead the factories to the path of continuous improvement. This improvement also needs to be measured continually, so as to understand how much improvement has taken place. Productivity data could be a useful indicator of the improvement rate and the level of performance of the factory.

Though factory managers are aware of the importance of productivity, data on productivity is rarely available. Managers, sometimes, feel that collection of productivity data, its measurement and generation of reports is simply extra paper work. As most managers in apparel factories are busy fire fighting, they seldom have time for so-called ‘paper work’. The managers and their supervisory team often have misconceptions about productivity and lack the knowledge of the true dimension of the benefit they can derive from productivity measurement, and subsequently the productivity improvement.

What is Productivity?

Productivity, in simple words, is the relationship between output and input. The output in garment factories can be pieces of finished garments. The output of sections or departments within the garment factories could be: metres of the fabric inspected in fabric inspection section, cut components in cutting room, number of garments ironed in the ironing section and so on. The examples of input are: man-hours, machine hours, metres of fabric consumed or electricity consumed. Productivity can be calculated as:

Output
Productivity = ————
Input

In simple words, productivity is concerned with the efficient utilization of resources (inputs) in producing goods (output). Quite often productivity is expressed in terms of efficiency. For example if the standard expected output per operator is 25 pieces of jeans per shift and the operator productivity is of 20 jeans per day, the productivity in terms of efficiency becomes 20/25 = 80%. This expression may also be called ‘productive efficiency’.

‘Partial productivity’ is the ratio of output to one class of input. For example, labour productivity (the ratio of output to labour input) is a partial measure. Similarly, material productivity (the ratio of output to material input) and machine productivity (the ratio of output to machine input) are examples of partial productivity.

‘Total productivity’ is the ratio of total output to the sum of all input factors. It is a kind of a higher level of productivity assessment combining several or many partial productivity measures.

Apparel Manufacturers, internationally, prefer to use partial productivity measures like labour or machine productivity. This is mainly because of the fact that data needed for the partial productivity measurement is easily available and the results of productivity computation can be used by the department or the section in-charge to evaluate its performance or to plan improvement.

[bleft]Dr. Rajesh Bheda is a Professor at the GMT Department, NIFT, New Delhi, one of the world’s leading fashion technology institutes. His teaching, consultancy and research interests focus on productivity improvement, quality management, and the social issues in apparel manufacturing. He is a thought-provoking speaker, writer and author and has addressed international conferences besides conducting several management development programmes for leading apparel firms. He holds a Doctorate in Management from the Faculty of Management Studies, University of Delhi. – This is the first of a series of five articles by Dr. Rajesh Bheda on Productivity.[/bleft]

Measuring Output and Input

With respect to measuring inputs, labour input is generally measured in physical units like minutes, hours, days or months. Capital inputs like machines can also be measured in terms of time. In the apparel industry, it is often seen that productivity is communicated in terms of number of garments produced per sewing machine per shift or per operator per shift. Inputs like labour, capital and energy can also be measured in financial terms.

As output and input are primary constituents of productivity, it is essential that while communicating productivity, the output and inputs are explained clearly. It is often seen that productivity communication is incom-plete or vague. In the apparel industry, it is common to hear statements like, ‘productivity of a factory is 15 pieces per operator’. A statement like this cannot be understood or the listener cannot make any useful judgement on the productivity performance as the information provided is insufficient. It is vital to provide the following information in productivity communication:

• The form of input and output
• Quantum of input and output
• Unit of measuring the input and output

A better and easy method of communication can be to state that the productivity of organisation xyz is 15 standard shirts per sewing operator per eight hour shift.

Manufacturers producing a standard product (five pocket jeans or dress shirt) can use the physical unit method for measuring output, i.e. the output is measured in terms of number of items (garments) produced. In case of manufacturers producing closely similar products, the output is converted into ‘standard equivalent product’ for physical measurement. For example, if a manufacturer produces three styles of shirts, each involving direct labour content of 16, 20 and 24 minutes respectively and the shirt style taking 20 minutes is a standard shirt, then the output of shirts with work content of 16 and 24 minutes will be multiplied by 0.8 and 1.2 respectively to arrive at the output in ‘standard shirt equivalent’.

In the case of manufacturers with great amount of product variation, the measurement of output in physical unit terms may not be useful, as the products are not comparable. In such cases, the output is measured in financial terms.

Example of Productivity Calculation

The calculation of productivity in apparel industry is further explained by the following example of a shirt manufacturing factory. The data on the output and various inputs is shown in Table-1.

The calculation of productivity based on above data can be done as shown in Section A of Figure-1.

Labour or machine productivity can also be communicated in terms of volume of labour/machine input consumed per unit of output. In such cases, productivity will be calculated as shown in Section B of Figure-1.

Interpretation of Productivity Data

Having discussed what productivity is and how to measure it, it is equally important to understand how to interpret and analyse the productivity data. Many a times, productivity communication can lead to wrong interpretations or conclusions. For example, lets assume that the labour productivity of a T-shirt manufacturing unit is only 50% (225 standard minutes produced per 450 minutes consumed per operator). It may seem that the productivity of the operators of the plant is only 50%. But, it is not necessary that it is only the operators who are at fault. Actually, this productivity performance could be reflective of the collective impact of various inputs like labour, machine, supervision, raw material, power, etc.

Productivity data, if not fully analysed, may lead to costly mistakes. It is also possible that people may wrongly use the productivity data for their personal or departmental gain. These problems arise when productivity measurement is not an organisation-wide activity. For example, the in-charge of cutting department may not carry out a few important tasks like notching or drill holes in the cut components.

This may give an impression of increased productivity in terms of number of garments cut per worker or per machine. However, such an act will reduce the productivity of the sewing department, as the operators will take more time to sew due to incomplete cutting. Another example could be that by using a highly skilled (high wage) sewing operators for a particular job, the labour productivity measured in physical units produced per shift may go up. But when the input of labour is measured in relation to the cost of labour in place of the time of labour inputs, the story may be quite different.

Levels of Productivity Measurement

It is important to understand which productivity measure to use at a particular level of productivity measurement in an organisation. Productivity measurement can be done at macro as well as micro level. Figure-1 explains various levels of possible productivity measurement in the apparel industry.

Organisations with the presence of productivity measurement system do undertake regular productivity measurements, starting from the plant level up to the operator/ staff/ machine level. It must be noted that, depending on the prevalent situation in the organisation in terms of relative importance, different productivity measures may be favoured. Manufacturers in the developed world may give more importance to labour productivity over machine productivity, whereas in a developing country with lower wage cost, machine productivity may gain much more prominence.

How is Productivity Lost?

When one hears a statement that labour productivity of a factory is only 50% or 60%, it comes as a shock. However, it is important to know that the 50% or 40% performance that is lost, is contributed by various factors that individually may seem quite insignificant. However, their collective impact can be disastrous for the productivity performance of a manufacturer. The factors that could cause productivity losses and their assumed occurrence level are given in Table-2.

A factory with one hundred workers can have 4000 standard hours of productive time a week at the rate of 40 hours x 100 workers. When all the factors mentioned above are applied, the total output lost comes to 1960 hours, which makes it 49% of the potential. It is important to understand these factors and control them so that productivity is not lost to such a level.

The top management of an apparel factory, if so desired, can make or break productivity performance. It is often seen that productivity performance of factories producing the same garments is substantially different. The chart on the next page is based on valuable inputs from Alan Chandler, a management consultant with rich experience in apparel operations, demonstrates how productivity performance could change between a poorly managed and a well-managed apparel manufacturing unit. This change is mainly caused by factors like absenteeism, hours and performance ‘on and off incentive’ (see box) and rejection level. From a workforce of 140 bodies working at 48 hours a week, the well-managed factory could produce 21,522 garments as compared to 14,636 garments only by a poorly managed factory. The resultant productivity works out to be 25.62 garments per operator per shift in the former case and 17.42 garments per operator per shift in the latter case.

Conclusion

To conclude, I would like to suggest the following DOs and Don’ts.

Dos

• It is a must for every apparel producer in India to start measuring productivity on a continuous basis.

• Productivity must be measured at various levels starting from operator/ machine level, going up to plant level.

• Measure productivity in physical as well as value terms against all the quantifiable inputs.

• Monitor productivity performance to track improvement over a period of time. Do not accept claims of people without clearly spelt out evidence on productivity improvement.

Don’ts

• Ignore productivity measurement as unnecessary paperwork.

• Assume your team understands what productivity is, its true importance and the amount of value productivity improvement can add to your organization.

• Leave productivity improvement initiatives to your people thinking that it is common sense. You
would need to show commitment to productivity improvement and lead the team; after all ‘Common-sense is not common’ and you cannot run away from your responsibility of leading by example.