How do you measure the productivity of temporary staff?

Measuring productivity, especially in terms of temporary staff is traditionally based upon monitoring outputs produced. However, this isn’t the only way they provide value to an organisation.

There are many other index models that we can consider utilising that will account for the wider positive impact that temporary staff can have on a business and in turn, provide a truer representation of their productivity.

By turning single factor output vs input models such as labour productivity, into a multi-factor output vs input model, we can better understand how well a system uses its resources to achieve a goal. In this way, not only can we understand but we can also protect quality of output, customer services levels and overall staff morale, boosting productivity even further.

Why is only measuring a single output vs input factor ineffective?

Using a single-factor output vs input measure such as labour productivity can lead to decisions being made, or targets being set, that jeopardise quality of output, customer satisfaction performance & overarching corporate culture.

Understanding labour productivity is useful if we want to know how much our products or services cost us to produce. However, because it only measures one aspect, (production vs time), it does not help us to understand why, or identify where improvements can be made.

For example, suppose we only measure the time it takes to produce a product from concept to completion, against the total number of products made. In that case, we could surmise that working faster will increase productivity - risking the final quality of the product and staff wellbeing - in favour of increased quantity.

Additionally, a labour productivity index, an annual indicator conveying the growth rates of labour productivity, will ignore the distinction between quantifiable & unquantifiable tasks.

For example, in a Call Centre, if we only track the number of sales calls (quantifiable tasks) our staff make against the number of hours they work, we ignore the unquantifiable tasks, such as a call that resolves a query from an unhappy customer. A call of this type could be worth a lot more in the long run than a new sales call, but under a single factor productivity index, this type of call would not be measured, placing a high value on sales and ignoring the importance of customer service.

Measure the productivity of temporary staff with a multi-factor output vs input model

Our main aim is to track employee productivity to gain a better understanding of how effectively skills are utilised and time is applied but there are many factors that can influence these. Things that are measured get managed and improved, so our metrics need to account for and place value on all aspects of a temporary worker’s role.

While no productivity index is flawless, a multi-factor output vs input model that encompasses many different indicators will provide a broader overview of productivity, upon which effective decisions and improvements can be made.

Choose a range of indicators

Consider all factors that may impact productivity including quality, quantity, presenteeism, absenteeism, happiness, job satisfaction, distraction, customer satisfaction and financial turnover.

Group vs individual output

While it may not be possible to measure some factors on an individual level, solely focusing on group productivity leaves you blind to individual strengths and weaknesses, so try to drill down further wherever possible.

Use an integrated approach

Despite their apparent segregation within an organisational structure, departments do not work in isolation. It is thanks to the efforts of all departments combined that an organisation can operate, so set meaningful indicators for individuals, groups, and departments as well as for the organisation as a whole.

Align quantity with quality

Quantity measures should be aligned with a respective quality standard.

Advocate clarity and transparency

Ensuring that temporary employees are involved in the decisions that affect them, quickly provides a sense of involvement, ownership and accountability.

Seek usable, meaningful insights

Data is only beneficial if it is usable and understandable. A multi-factor measurement process should be able to help you find out why things are, the way they are, the causation behind the effect. For example, is productivity down due to a lack of training, or is it due to distractions in the workplace?

Review data regularly

Set weekly and monthly reviews for individuals and groups. Utilise quarterly, and yearly reviews for departmental trend analysis and the organisation as a whole.