Thousands of Australian companies are measuring the performance of workers in real time and relying less and less on human intuition to make decisions about who to hire and fire.
While this dive into big data is seen by some as more objective, faster and scientific than human decision-making, others worry it can also be inaccurate and far less nuanced.
New research from the University of Sydney Business School challenges the wisdom of using data analytics such as words combinations used on social media, images clicked and time spent on job-seeking site LinkedIn to measure and even predict workplace performance.
The service industry including consulting companies, Google, Amazon, design companies and hospitals are among those using big data to make day to day decisions on staff management.
Associate Professor Uri Gal, from the Discipline of Business Information Systems at the University of Sydney Business School said companies are not only tracking social media posts, they are also monitoring social conversations in the office.
"Despite the allure of scientific rationality, there is little evidence to suggest that the use of workplace analytics results in actual business benefits," he said.
"There is no empirical research to rigorously examine their impact on manager, employee and organisational performance."
The move towards ultra-transparency where online and offline activities are tracked and analysed raises ethical and practical questions.
Associate Professor Gal said managers were often uncritical in their adoption of algorithms and analytics to measure performance. Little thought is given to how they can curb independent thinking, creativity, freedom and privacy.
"Privacy is a myth. It doesn't exist anymore," he said.
"I think most people would be more comfortable having a decision about them made by a human being than by an algorithm.
"When your boss makes a decision you can have a conversation and reason with them."
Human beings are extraneous to the decision-making process.
Associate Professor Uri Gal, University of Sydney Business School.
But when an algorithm is used as the basis for a decision it is done in a semi-automatic way, and the employee has no recourse to reason.
"Human beings are extraneous to the decision-making process," he said.
Associate Professor Gal has researched how some employees game workplace analytics systems by entering inaccurate data on their productivity or using spreadsheets that paint a particular picture of their performance. Social media can also be manipulated in opportunistic ways to create a false impression.
"Algorithms are not accurate because inherently what they try to do is to build a simplified model of complex human behaviour," he said.
"It is just not accurate enough to replace human decision-making."
And the less active people become in decision making, the less skilled they become as managers. Analytics cannot capture what is involved in managing people or showing someone how to master a skill.
Breaking a worker's performance down into a few singular measures is as ineffective as trying to understand the success of a sports team by looking at its individual players. This fails to take account of team culture or how well or badly players interact with each other.
Similarly, analysing the sense of smell or taste cannot provide an impression of consciousness involving the interaction of all five senses – sight, smell, hearing, taste, and touch.
Despite the many flaws involved in using analytics, many companies are uncritical in embracing big data to measure workplace productivity.
"It's unavoidable. This is where we are going in the age of algorithmic management," Associate Professor Gal said.
"But we need to have a frank conversation about the consequences of going there".
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