Across all industries, teamwork and strong communication are crucial for long-term business success. However, organisations are facing a new reality, one where collaboration in the workplace is lacking, says Dr Chibeza Agley.

Where ‘quiet quitting’ and ‘quiet firing’ have been the key trends over the past year, the rise of ‘quiet constraint’ (when an employee withholds potentially valuable information from their colleagues) is causing isolation in the workplace.

In our now firmly established age of remote working, it is becoming increasingly more difficult to identify and manage this rising issue. But quashing ‘quiet constraint’ must be a top priority for 2023.

What is the cause of ‘quiet constraint?’

The latest research reveals that over half of corporate workers are retaining information that could benefit their co-workers and employers, with Gen Z employees being the most likely group to do so. Although unsettling, the news that ‘quiet constraint’ is becoming a notable challenge for businesses will not come as much of a surprise to many.

Learning and development (L&D) is a central part of this issue, as executives are now waking up to the fact that conventional approaches to L&D, such as content organisation and internal knowledge sharing, cannot withstand the ever-expanding and rapidly changing global body of knowledge within modern businesses.

The corporate training market is expected to grow to a massive $475Bn by 2027 as companies across all sectors recognise the continual need to keep their workforce up-to-date, relevant, and productive. However, they are currently unable to build, curate, personalise, or analyse the impact of learning programmes and knowledge sharing quickly enough to match the knowledge and skills development needs of the workforce.

With 2023 likely to see the continuation of the economic challenges that businesses have been facing, there is a pressing need for organisations to derive the maximum value from their existing workforce. As many face higher attrition rates than normal due to forced cutbacks, establishing effective processes for knowledge transfer will be a significant factor in mitigating these challenges.

The matter of efficiency

The industry is also facing an issue around efficiency. The time it takes to establish learning programmes, conduct assessments, and launch a platform for knowledge sharing is often more than the business has to give.

What’s more, workers are no longer bringing 10-20 years of institutional knowledge to an organisation or role; they are moving between companies and jobs more than ever before, and though this movement can bring fresh insights, onboarding times are longer and the potential for costly knowledge gaps to creep in is greater.

These inefficiencies mean that, ultimately, businesses are losing money and employees are not receiving the L&D needed to succeed in their roles. Given that human capital costs are almost always one of the highest outgoing expenses in any business, not having a highly trained workforce with the capability to curate, consume, measure and share knowledge in an efficient, effective way, is costing organisations hundreds of millions of dollars a year.

However, HR teams have the opportunity to grab a seat at the top table when it comes to the future of business, by taking on innovative approaches to upskilling and reskilling staff, and ensuring efficient and measurable knowledge sharing is intrinsic at every level in the business.

A changing environment

The empowerment of staff to be more productive, efficient, and successful is moving more towards the forefront of companies’ minds. Without doubt, the Covid-19 pandemic has been a catalyst for moving the work and skills market into the future, highlighting the need for reskilling and retraining on a sizeable scale.

Gartner found recently that three-quarters of CFOs were planning to keep part of their workforce permanently remote. Therefore, it is becoming increasingly apparent that businesses will need to continue to invest heavily in efficient, successful training and knowledge sharing regardless of their workplace setup.

Actions employers can take

Businesses are calling out for innovative new solutions that will help solve their mounting challenges, such as staff turnover, the growing time and resource costs associated with conventional training approaches, extreme skills shortages and a fiercely competitive hiring market.

Business leaders have made productivity and efficiency, as well as the supporting data, one of their main points of focus. The ability to harness the power of AI-driven automation, adaptability and analytics for enterprise learning removes the time-consuming and costly methods, whilst also generating effective tailored learning experiences that show clear ROI.

The world of work is continuing to evolve at a rapid pace, including the ways in which people learn and digest information. Therefore it is vital that the resources required keep pace, ensuring both businesses and their employees are constantly adapting.

The wider industry skills gap is another point of issue for organisations, but due to the ability to digitise and curate information, staff are much more likely to retain essential knowledge throughout their time at their company and beyond.

The integration of AI-powered automation, adaptability and analytics within learning and knowledge-sharing empowers companies, enabling them to become more efficient, capable, and resilient. This ensures that each individual learner is sent on the most tailored journey for them and ultimately holds the key to their success.





Amelia Brand is the Editor for HRreview, and host of the HR in Review podcast series. With a Master’s degree in Legal and Political Theory, her particular interests within HR include employment law, DE&I, and wellbeing within the workplace. Prior to working with HRreview, Amelia was Sub-Editor of a magazine, and Editor of the Environmental Justice Project at University College London, writing and overseeing articles into UCL’s weekly newsletter. Her previous academic work has focused on philosophy, politics and law, with a special focus on how artificial intelligence will feature in the future.