2021 has been described as the year of the ‘Great Resignation’ – a year in which employees across the world quit their jobs at historic rates. And it looks like the trend is continuing into 2022. According to consumer data company Statista, the number of workers quitting in the U.S. has now exceeded pre-pandemic highs for more than eight straight months. It’s a similar situation in the UK, where a recent report from Deutsche Bank has found that workers are resigning at the highest rate since 2009.
The trend has been driven by a mixture of factors. The pandemic has fundamentally changed the way that many people think about their work. While some look for greater flexibility, others have made the decision to switch industries or pursue passion projects. According to data from Harvard Business Review, employees between the ages of 30 and 45 have had the greatest increase in resignation rates.
So What Can Employers Do to Fill the ‘Great Resignation’ Gap?
While companies worldwide struggle to recruit and do the same – or more – with fewer employees, many have turned to automation software as an answer to resourcing issues. In the case of document-heavy processes, such software can reduce the size of the team needed to manage it. But while some organizations have seen initial business process automation wins, others have failed to effectively operationalize and scale their initiatives to unlock true digital transformation.
Traditional, rules-based process automation approaches lack the flexibility and intelligence needed to handle the increasing complexity of many use cases. While they yield some efficiencies through the automation of individual tasks, which were previously manual, they fail to drive measurable gains at the organizational level. Few of them have the capability to ask whether the underlying process that they’re running makes sense, or learn from the inputs that they receive.
They certainly don’t hold the answer to how to future-proof business processes and to elevate employee potential in a market deeply affected by labor shortages. There’s a key element of the equation that’s missing – human input and feedback.
The Value of Human Centered Automation
Most business processes, particularly those still involving paper documents, are slow and error-prone, often leading to data inaccuracies and poor decisions. These clerical errors and processing delays have negative real-life repercussions, such as the rejection of a mortgage or loan application, or the denial of a disability claim.
Hyperscience’s human centered approach to automation combines Machine Learning with human supervision to enable a new era of human and machine collaboration. The software automatically flags up edge cases for review, where a human is needed for review, and then uses the results to finetune the underlying models. Not only does it reduce manual burden and error rates, but it also enables employees to focus on higher-value tasks.
Millenials Believe Humans & Machines Can Work Well Together
Hyperscience’s survey found that 63% of millennials (the largest group behind The Great Resignation) believe automation in the workplace is good, especially if used to alleviate certain work burdens.
Further, the survey found that the employee experience is front and center when it comes to technological advancement. Nearly half (43%) of respondents said that how the employee interacts with technology, and how it impacts employee experience is of the highest importance. The customer experience was a close second, with more than a third (34%) of respondents selecting it as the most important factor.
Automation Software That Evolves with Your Org
Hyperscience enables humans to provide feedback to the machine through an intuitive, easy-to-use exception-handling platform, helping to customize and train ML models according to their organization’s specific needs. For the companies facing a skills shortage, it offers the potential to complete higher-value work with fewer resources. Crucially, it also drives business agility, enabling workforces to evolve and better meet future market needs. For the end customer, it offers the benefit of far fewer clerical errors, faster decision-making, greater transparency, and a much improved overall customer experience.
One example is The U.S. Air Force Special Operations Command (AFSOC) which was looking to simplify and expedite their audit readiness process and in doing so, reduce the workload of Wing Resource Document Control Officers (WRDCOs)—enabling them to focus on higher value work. The Hyperscience Platform transformed the lengthy, manual audit readiness process into an efficient digital assembly line, in which a ML software collaborates seamlessly with WRDCOs—eliminating cumbersome manual entry and upgrading them with more time and better quality data.
