Untangling the wires between automation and the future of work

New Acas research shows that automation is having a significant impact on the way jobs are done

The research, Mind Over Machines: New technology and employment relations, also highlights how tracking technologies and algorithms are important recent developments, which are beginning to play a significant role in organisational decision-making processes.

It’s not just about robots

Automation is often thought of in relation to robots. In some sectors, particularly manufacturing, robots are already transforming the way jobs are carried out. They often make physical tasks easier and can reduce the number of health and safety incidents at work. The research looks at the experience of Siemens in Congleton, and describes how robotics has enabled significant ergonomic improvements, therefore removing the risk of back injuries to staff when reaching items that are placed too high.

But there is much more to automation than robots. Automation technologies also include data recording and analytics that can be used to track sales and demand levels, or even new forms of surveillance, such as handheld devices and wearable technology that can monitor employee performance.

Our research highlights the example of Jaguar Land Rover, which used new technology to monitor productivity. While this level of tracking was helpful for planning purposes and meeting targets, it was also considered to be a rather blunt tool for managing staff as it failed to account for resourcing issues or problems with the technology. Tracking technologies should not be used in isolation but rather supported with human interaction.

What about algorithms?

Increasingly algorithms are becoming commonplace at work. These are computer programs that use mathematics to make decisions that a business would traditionally have employed a person to do.

Algorithms can be used in a number of ways, from helping to package and label products to working out shift patterns based on customer demand. Percolata is just one example that can generate a number of metrics by combining data sources.

Algorithms often tend to be used in managing staff processes like recruitment, but sometimes this brings unexpected consequences. For instance, they can minimise bias in the recruitment process as potential applicants are selected through meeting objective criteria (such as qualifications) as opposed to more subjective criteria like how a person looks.

The research describes a US company which, incredibly, saw ethnic minority recruits increase by around 25% after it moved towards software-assisted hiring decisions. In this way algorithms can help organisations treat employees fairly.

But who sets the rhythm in a work algorithm?

The research makes clear that new technologies need to be supported with human interaction; to challenge, test and make use of technologies in the right way.

Ultimately it depends on who sets the parameters in an algorithm, and if they reflect personal preferences. This raises interesting questions on how automation technologies are monitored and evaluated so that they operate in a fair manner.

This also has significant implications in terms of how much say employees have in shaping automation processes, and in turn the levels of trust between managers and staff. A case study with an NHS Trust illustrates this point, as staff were cautious about how data about them was used and also the security provisions in place for keeping this personal data safe.

By untangling the wires between automation and the world of work there are strong connections between automation and simplifying processes, making efficiency gains, and new innovative ways of working. However, there are clear challenges too, in relation to how automation can be effective yet empowering to employees, and be used appropriately to support decision-making processes.

Getting this balance right in terms of what automation and employees have to offer is important in how we approach the future world of work. Making use of automation technologies therefore requires human interaction to make them truly effective. Now that is a connection worth strengthening.

Rachel Pinto is a senior research officer at Acas