Innovation drives efficiency… But is time saved being used effectively?

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Earlier this year, Sarah O’Connor at the FT proposed a modern phenomenon called the suitcase principle of white collar work – the theory that just as we fill up our suitcases regardless of the length of our trip, work seems to expand to fill the time available, even when tasks are made more efficient with AI.

This issue has been exacerbated by the global shift to remote working post-pandemic. In particular, rightly or wrongly, we’ve all been so quick to fill up the few hours previously dedicated to daily commutes.

According to People Management, 53% of Brits worked longer hours working from home than before the pandemic – with 41% stating they worked an extra 5-10 hours a week. When AI and other innovative tools are adopted to streamline processes and save time, why is it that employees are working more hours?

Essentially, workers are almost hardwired to fill up empty time, whether they need to or not.

This brings into question a wider issue across the corporate world – the perception that quantity equates to quality. There appears to be a belief that the more hours you put in, the better. But this is generally not the case.

Organisations strive for a quality over-quantity approach, yet we still see cases of people caught in the trap of unnecessarily filling every single hour in the day. As a collective, we need to break the habit of measuring output and success by the number of hours worked.

One area that is in desperate need of this revolution is corporate learning. Currently, so many training programs are measured based on hours completed rather than the quality of learners’ output. So what’s the alternative?

The efficiency evolution in corporate learning

Corporate training is a critical element of modern business as we navigate the sharp twists and turns of the changing market around us. The knowledge that was relevant five years ago is now vastly outdated, and learning programs need to be able to match pace.

Unfortunately, existing training schemes fall short in their delivery of effective learning. As mentioned above, the way in which training is measured is issue number one, but we also need to address the fact that courses usually adhere to a one size fits all approach – which subsequently leads to wasted hours.

For example, when it comes to industry accreditations, individuals are often required to complete a specific course for their role or aspiring role, but the training process can be laborious and inconvenient. Competent learners are often forced to revisit old topics, spending hours on training when half that time would suffice.

This is where AI comes in

Armed with the tools to make training adaptive, where each individual’s unique learning needs are met, organisations can streamline the process to focus more on the quality of learning than the number of hours completed.

Beginners can spend the necessary hours being guided through the content while competent learners are only required to cover the areas where they lack confidence. With this approach, some individuals may spend three hours on a training course whereas others may be done in half that time.

Ultimately, O’Connor’s suitcase principle draws attention to this very real issue across the corporate landscape, and we need to drive an industry-wide understanding that the number of hours you commit to a task is not necessarily reflective of the result.

We need a true quality over quantity approach; that is the future of work.

OBRIZUM is the AI learning technology & data analytics company for enterprise businesses.

We leverage automation, adaptability and analytics to deliver adaptive learning experiences at scale.

Find out how OBRIZUM can help unlock the potential of your business by speaking to our team.

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