CogniBalance: a new way to address the cognitive supply - demand challenge
The world of work has fundamentally changed. Yet, how we think about thinking hasn’t.
For much of the twentieth century, organisational performance was built around productivity; improved processes, reduced waste, increased throughput and better use of labour. As economies became more digital, the focus shifted towards information. Organisations invested in technology, analytics and automation to improve how quickly information could be created, shared and acted upon.
This way of thinking about productivity is no longer sufficient. It’s not even applicable from a human productivity perspective. Question is, was it ever?
The primary constraint on organisational performance now is the human capacity to process information, make decisions, solve problems, adapt to change and sustain high-quality thinking in increasingly complex environments.
In other words, competitive advantage is becoming increasingly dependent on the human capability to optimise thinking. To know how to sustainably nurture, energise and utilise the cognitive resources and capacity available will be key as AI make the traditional term of productivity from a human perspective irrelevant.
The era of the Brain Economy
This represents the now rapidly emerging concept around the Brain Economy.
In the brain economy, value is created through the cognitive assets of an organisation e.g. emotional awareness, judgement, interpretation, problem-solving and decision-making ability and capability. These are central, not only to conventional knowledge work such as professional or financial services, but also to control rooms, healthcare, engineering, technology, transport and other complex or high-risk environments.
In fact, across all industries, small cognitive failures can quickly become very costly operational, safety, reputational or commercial failures.
The main challenge is that the cognitive demands placed on people have increased significantly. Work is more information-rich, more interconnected and often more time-pressured. People are expected to shift between tasks, respond to interruptions, process large volumes of information and make decisions in environments that are constantly changing. Artificial intelligence is accelerating this transition. It can reduce routine work, but it also places greater emphasis on evaluation, verification, judgement and oversight.
As a result, organisations are becoming more dependent on the quality of human cognition at the same time as the conditions required to support that cognition are becoming more difficult to maintain.
The cognitive supply - demand issue
Cognitive capacity is limited. Working memory can only hold and manipulate a certain amount of information at one time. Attention is vulnerable to interruption and fragmentation. Decision quality declines when people are mentally fatigued. Sustained stress can reduce concentration, impair emotional regulation and increase the likelihood of errors. When cognitive load exceeds available resources for too long, performance becomes less reliable.
This does not mean that cognitive demand should always be reduced. Moderate demand can support engagement, focus and learning. Challenging work can strengthen capability and create a sense of meaning and progress.
The problem arises when the level or nature of the demand is poorly matched to the resources available to meet it.
At one extreme, excessive demand, intense effort, low clarity, high stress and depleted energy can lead to overload. At the other, insufficient demand and limited stretch can lead to boredom, disengagement and underuse of capability. Between these extremes lies the opportunity to design work that supports both performance and growth.
This is why cognitive performance cannot be understood through workload alone. The same level of demand may be manageable for one person and overwhelming for another. Work may be productive in the morning and unsustainable by the end of a long shift. Work may support learning when clarity and energy are high, but create strain when information is fragmented, priorities are unclear or fatigue is already present.
Why traditional people metrics are therefore no longer enough
Over the past two decades, organisations have invested heavily in understanding the human side of performance:
Employee engagement surveys have become a standard component of organisational management, providing insights into commitment, motivation and organisational culture, yet with little meaningful impact.
Wellbeing initiatives have expanded rapidly, whilst burnout has become an increasingly important measure of organisational health, again with little impact on actual health or performance outcomes.
At the same time, productivity dashboards provide continuous visibility into operational outputs, enabling leaders to monitor efficiency, utilisation and business performance at unprecedented levels, an area where human contribution has been near zero.
These measures have undoubtedly improved organisational decision-making. The challenge is that they were never designed to answer a fundamentally different question that has emerged as work has become increasingly cognitive in nature.
Are people cognitively positioned to perform at their best?
In the next article we will review some of the common tools and frameworks used and introduce a new framework, CogniBalance, tailored to meet the demands of the new world of work.
