To measure productivity you divide outputs by inputs over a set period of time. As a formula that’s productivity = output ÷ input. It’s a simple equation – yet measuring productivity in the real world is never so straightforward; nor is making any meaningful improvement.
In this article we’ll look at ways to measure productivity in the workplace – including how to measure labour productivity, and how to measure multifactor productivity – then explain some practical metrics and KPIs that help managers lift productivity in the workplace.
To keep things simple we'll be looking mostly at measuring manufacturing productivity. Most of what we'll touch on, though, will be equally relevant to wholesalers and retailers, who each have outputs and inputs that can be tracked and optimised. We’ll also look at how to measure knowledge worker productivity (and improve it), as part of measuring multifactor productivity.
In this article:
- How to measure productivity
- How to measure labour productivity
- What does measuring labour productivity tell you?
- What does measuring labour productivity NOT tell you?
- How do you improve labour productivity?
- How to measure multifactor productivity
- An example of multifactor productivity in practice
- How to improve multifactor productivity
- Measuring knowledge worker productivity
- 6 practical productivity KPIs
How to measure productivity
There are two main approaches to measuring productivity: measuring labour productivity, and measuring multifactor productivity. We’ll look at the difference later in the article – and at the pros and cons of both – but first let’s take a moment to look at the core components of the productivity equation, ‘inputs’ and ‘outputs’. Let’s say a toy making company decides they want to lift their productivity. Their first task is to work out a standard way to measure this in their business that’s relevant to what they do – and that gives them a meaningful metric by which they can chart their progress.How to measure productivity: Deciding on an output
The management team decides that the output measure will simply be ‘individual toys produced’. That’s a relatively blunt measure – after all they sell lots of different kinds of toy, some of which take more time and money to create. But they figure that over a long enough time-frame – say three months – this variability will cease to matter, compared to the convenience of having such a simple unit to measure.How to measure productivity: Deciding on an input
Our toy maker decides that they want to keep things similarly simple at the input end, and choose ‘number of direct labour hours’ as their measure of input. By ‘direct labour’ they mean ‘staff directly involved in running the toy-making production-line’. This will include the assembly line workers, the machinists, the parts handlers who keep the assembly lines stocked, plus the shift supervisor – but, for example, not the cleaners, nor the toy design team that comes up with each season’s new range – nor the management team themselves. They decide on a quarterly measurement period.How to measure labour productivity
Our toy makers, therefore, will be dividing the number of toys produced by the number of direct hours of labour, to reach a number. What that number is isn’t relevant – what’s relevant is how much it changes quarter by quarter. Here’s how Q1 pans out: The toy factory has 25 ‘direct’ staff on per shift, working a conventional 8 hours, for 5 days a week. In Q1 therefore their inputs are:- 25 staff x 8 hours = 200 labour hours per shift
- 5 shifts per week = 1000 labour hours week
- 12 weeks per quarter = 12,000 labour hours per quarter
- So their Q1 productivity is 20,000/12,000 = 1.6
- Then in Q2 they produce 22,000 toys: their productivity is 22,000/12,000 = 1.8
- And in Q3 they’re struck by a bout of illnesses. They run the same number of shifts, and by pulling through on reduced staff numbers produce 20,000 toys – but with only 11,000 labour hours. Their productivity in Q3 is therefore 20,000/11,000 = 1.8
What does measuring labour productivity tell you?
Our toy makers now have a valuable manufacturing KPI for understanding productivity in their factory. By choosing to focus on labour inputs alone they avoid getting bogged down in the details of measuring all sorts of other, less tangible, factors. From here they can make practical steps towards addressing productivity What happened in Q2, for example? What motivated staff to produce more? Can it be replicated? And why was output down in Q1? As for Q3 – is that ‘let pull through this together’ attitude something that could be expanded on, or would it just exhaust their staff and lead to higher turnover? This is where a good management team will think beyond the obvious to build a manufacturing business that’s more productive – and therefore more valuable and competitive.What does measuring labour productivity NOT tell you?
Equally relevant – and equally important to think about before leaping into a new course of action – is what measuring labour productivity doesn’t tell you. By focusing on the simplest element of the productivity equation – labour – managers can miss many other harder-to-measure, yet highly relevant inputs that affect productivity. These can include:- The effectiveness of management
- The suitability of machinery used
- The suitability of the working space
- How well capital in the company is being used
- And much more
How do you improve labour productivity?
Sticking with the simple toy factory example above – and considering only the labour productivity elements being measured, we can see several ways to improve productivity; some obvious, others less so. Consider these scenarios, for example.Increasing targets
Looking at Q2’s results, management decides that staff are fully capable of working at a faster rate. The conveyor belt in the production line is marginally sped up – and a team member hosts a pre-shift stretch-and-exercise routine, followed by coffee. Staff begin working at the faster rate as part of the new normal, with no complaints, thereby lifting labour productivity.Decreasing staff levels
Looking at Q3’s results, management decides they can get by with only one parts handler per shift, rather than two. They go through a redundancy process and one of the handlers opts to go part-time to pursue university study. Labour inputs drop with no reduction in output, lifting labour productivity.Managing shifts
Looking at Q1’s results, management realise the lower output was due to decreased demand for toys. Yet with staff on full-time fixed-hour contracts, labour hours had remained the same. They decide to move staff on to rostered hours, so that in future input hours can be matched to output, with no reduction in productivity. Taking a blunt approach to lifting labour productivity can have unintended consequences.A caveat about measuring labour productivity
Experienced managers are well aware of most of the basic approaches above. Naturally they need to be in the back of every manager or owner's mind, as resets are sometimes required. However relying on rudimentary ‘work faster with fewer staff’ approaches to productivity improvements can have unintended consequences – and risks overlooking some of the most potent ways to increase productivity. Which is where multifactor productivity comes in.How to measure multifactor productivity
Multifactor productivity (MFP) looks beyond labour to include other inputs, such as capital and materials. All of these are added together, with the basic MFP formula looking like this: Multifactor Productivity = units of output ÷ (units of labour + units of capital + units of materials) In order to compare apples with apples, labour, capital and materials are often all reduced to their dollar value. It’s possible to not simplify things in this way – indeed a whole industry of productivity consultants makes a living from creating complex weighted models for measuring the relative productivity value of all sorts of hard-to-quantify inputs. However this approach almost always sacrifices practicality in the name of accuracy. For the purposes of practicality, let’s go back to our hypothetical toy maker and see how they could measure productivity with the MFP approach using dollar values – and make potentially radical improvements.An example of multifactor productivity in practice
Our happy toy-making company has a successful first experiment with measuring productivity and decides to move to a more sophisticated MFP approach. While their outputs are still measured in toys (they make another 22,000 in Q4), their inputs now consist of:- 12,000 direct labour hours per quarter, @ $20 per hour = $240,000
- 5 managers working 2400 hours per quarter @ $40 per hour = $96,000
- Plant, insurance, other labour and machinery costs per quarter = $30,000
How to improve multifactor productivity
With our toy makers now considering far more factors in their productivity, they can now make more sophisticated and effective changes to improve their productivity. Consider the following scenarios.Staff capitalisation
Are they middle-management heavy? Or are they spending too little on employees that can make a disproportionate impact on performance? Should they splash out on that expensive productivity consultant (no – they can just read this article instead), or should they hire an HR team so that future hires are more effective – and valuable current staff are kept content? (probably).Design
Looking at their data, management realise the value of smart design. They invest in their innovation team and tools and start designing toys that not only sell well, but are faster to assemble.Sales
Making more sales doesn’t raise productivity in and of itself. But selling more effectively can. Management decides that their on-the-road sales teams will work better with a mobile sales app, and sees sales improve per agent. That’s a better use of their labour capital expenditure (i.e. their wage spend on salespeople has a better return). But more importantly, the improved sales pipeline means the factory is sitting idle less often. Factory overhead relative to output improves, meaning better productivity.Technology
Similarly, investing in technology can have dramatic effects on productivity. For example our toy makers could:- Deploy inventory management software: to reduce stock loss and wastage, reduce admin time, and prevent production stoppages thanks to automated low stock alerts.
- Invest in robotics: with output lifting, the warehouse manager needs more help. Instead of employing three new staff however, he buys a stock-picking robot and employs one new staff member – a robotics technician. It’s a more productive long-term use of capital, because fixed wages are down relative to output.
- Invest in RFID sensors and GPS: by tracking their delivery fleet, plus movement around their factory and warehouses, the firm can design more efficient layouts for their assembly lines – and reduce their fuel costs too.