Digital transformation was expected to bring relief: less paperwork, faster decisions, fewer mistakes, and reduced staff burden.

Yet in many high-pressure environments, the opposite quietly happened.

Despite significant investment, teams remain mentally stretched, frequently interrupted, and consistently behind schedule. Alerts ping incessantly, fracturing concentration every few minutes and causing workflow disruptions. Work takes longer, errors increase, and staff rely on memory, notes, and workarounds to complete tasks.

This is not emotional burnout, a motivation issue, or a result of inadequate coping skills. Instead, it is cognitive load, which has become one of the most costly and least visible forms of digital inefficiency.

The Pressure Has Always Existed; Digital Changed Its Form

Healthcare has lived with cognitive load for decades.

The same is true for construction, logistics, utilities, emergency services, and any environment where decisions are critical, time is limited, and information is incomplete.

Before digital systems, the burden appeared as paperwork, phone calls, clipboards, and whiteboards. Staff members would juggle a physical flurry of charts, notes, and memos, moving across desks, pinboards, and filing cabinets. Each document had its place, each call had its timing, and the rhythm of clipboard choreography was as visible as the daily routines it dictated. The workload was significant but visible.

Digital tools were intended to simplify this reality. Instead, they often shifted the effort from physical tasks to mental tasks.

  • Clinicians now switch between multiple systems per shift.
  • Site managers juggle apps, spreadsheets, and email chains.
  • Operations teams track progress across dashboards that are not designed to integrate.

In healthcare, studies indicate that clinicians spend 40 to 50 per cent of their working day interacting with digital systems, often navigating interfaces, re-entering data, or searching for information instead of providing care. (Interaction Time with Electronic Health Records: A Systematic Review, 2021) Each interface switch forces users into slower, effortful ‘System 2’ thinking, thereby compounding fatigue and contributing to System 2 fatigue. In the construction industry, workers typically lose nearly two full working days every week addressing conflicts, resolving preventable problems, and searching for project information across different systems, according to Construction Executive. (Williams, 2021)

To help leaders contextualise these benchmarks and evaluate their own teams’ inefficiencies, they could conduct internal assessments to compare their current digital workload with these industry standards. This might involve monitoring the average time spent on system navigation per employee, analysing incident reports related to digital inefficiencies, or conducting staff surveys to gather qualitative insights into system-related challenges.

The increased pressure was not due to declining job performance. It increased because systems require more mental effort than necessary. While training is essential, no amount of training offsets poor cognitive ergonomics. This shift in understanding reframes the challenge as one of design, rather than diligence, liberating teams from blame and pivoting attention to systemic fixes.

What Cognitive Load Really Looks Like on the Ground

Cognitive load is the mental effort required to complete a task. It is not the task itself, but all the surrounding requirements and considerations. Such as:

  • Remembering which system to use.
  • Recalling the correct sequence of steps.
  • Interpreting unclear information.
  • Recovering after interruptions.
  • Double-checking work because the system doesn’t reassure you it’s right.

In high-pressure environments, these factors accumulate rapidly.

Research across safety-critical industries shows that increased cognitive load is directly linked to slower decision-making, higher error rates, and reduced situational awareness. (Salinas-Navarro, 2024) Consider, for instance, a healthcare scenario where a nurse faces a delay in accessing a patient’s electronic health record. Even a ten-second delay could mean missing a critical piece of information, potentially leading to life-altering consequences for the patient. Similarly, in construction, cognitive overload can lead to safety breaches. A momentary lapse in situational awareness due to information overload might result in a preventable accident or delay. Each cognitive strain adds to risks that could have tangible, significant outcomes.

This is a crucial perspective: when capable, experienced individuals struggle, it is rarely due to a lack of knowledge. Instead, the system requires them to manage excessive mental demands.

How Digital Systems Quietly Make the Problem Worse

Most digital systems are not “bad”.

They’re technically sound.

They meet requirements.

They capture the correct data.

However, they are often designed around processes, departments, or compliance rather than how work actually unfolds under pressure. This is where cognitive load increases.

A single workflow may span multiple tools. Information is entered once, then re-entered elsewhere for redundancy. Interfaces are optimised for completeness rather than clarity. Alerts interrupt without aiding recovery, and screens display all information except what is immediately relevant.

Individually, these are minor inefficiencies. Together, they create an environment where staff must constantly switch contexts, remember details, translate information, and compensate for system shortcomings.

Industry research suggests that context switching alone can reduce productivity by 20-40 per cent in complex roles. (Kohl et al., 2020) This loss is rarely reflected in reports, but leaders notice it when timelines slip, and teams appear busy without making progress. To begin measuring this impact, leaders can track the frequency and duration of task switches throughout the day using simple time-tracking tools or software that logs application usage. Doing so provides data-driven insights, allowing managers to quantify these interruptions and devise strategies to minimise them.

Why Leaders Should Treat This as a Strategic Risk

Cognitive load doesn’t show up neatly on a balance sheet.

However, its effects are widespread. Cognitive load quietly erodes productivity, increases operational risk, undermines digital ROI, makes capable staff appear inefficient, and limits an organisation’s capacity for change. (Awad & Martín-Rojas, 2024) Imagine a construction crane operator whose dashboard is cluttered with unnecessary alerts and information. As a result, he misses a critical warning signal, potentially leading to a devastating on-site accident. This vivid scenario exemplifies how the strategic hazard posed by digital inefficiency can manifest in real-world situations with tangible consequences.

In healthcare, this shows up as delayed decisions, workarounds, and staff frustration. In construction, there are risks of rework, miscommunication, and exposure to safety hazards. In any high-pressure environment, it reduces resilience. (Awad & Martín-Rojas, 2024)

Every unnecessary decision your system requires is a performance tax. Unlike financial costs, this burden accumulates without visibility.

The Early Warning Signs Are Already There

Most organisations do not require new analytics to identify cognitive load. They need to listen to their teams. Leaders can use the following “Cognitive Load Pulse Check” to assess their organisational environment. After collecting pulse check results, leaders should prioritise addressing the areas with the highest cognitive load. This may include redesigning workflows, creating more user-friendly interfaces, or refining current systems to better suit team needs. Initiating in-depth, focused discussions with staff can yield invaluable insights and guide decision-making, enabling targeted improvements that enhance overall efficiency.

Cognitive Load Pulse Check:

1. Are people keeping personal notes, spreadsheets, or cheat sheets to get their work done?

2. Are tasks requiring frequent refresher training to complete?

3. Does success rely more on memory than on system guidance?

4. Is work often interrupted without a straightforward way to resume?

5. Are systems avoided unless necessary?

6. Does feedback often start with phrases like: “It works, but…”?

These are not behavioural issues. They are indicators of design problems, showing that the system now demands effort rather than providing support. (Cheng et al., 2025)

If this pulse check feels uncomfortably familiar, the most valuable next step is not another platform, rollout, or transformation programme.

It is taking a structured look at where your systems are increasing cognitive load, where mental effort is being wasted, and where clarity breaks down in real workflows.

This is often the moment organisations choose to bring in an external partner, not to build something new immediately, but to help them see their existing systems through a different lens. One that focuses on reducing mental effort, improving flow, and designing around how work actually happens under pressure.

That understanding is what gets teams most of the way there.

Everything else builds on top of it.

What Reducing Cognitive Load Actually Means in Practice

Reducing cognitive load does not mean oversimplifying work. It means respecting the complexity of real tasks.

In practice, that looks like:

  • Designing workflows based on actual work practices, not solely on documentation.
  • Eliminating unnecessary steps rather than simply digitising them.
  • Making priorities and following actions clearly.
  • Supporting users in managing interruptions and recovery.
  • Automating decisions where consistency matters
  • Reducing the need for users to remember, re-check, or second-guess information.

This is not about more attractive interfaces or advanced features. It is about shifting effort from users to the product. The most effective digital systems reduce mental effort when it is most costly, ensuring that reducing clicks or processes translates into tangible cognitive relief. This allows users to allocate their mental bandwidth to higher-level tasks and decision-making, thus reinforcing the design-over-feature stance. By explicitly linking these reductions to reclaimed cognitive capacity, the systems sharpen the benefit and provide a strategic advantage. (Sivaraman, 2016)

The Importance of Addressing Cognitive Load and Choosing the Right Partner

Many leaders recognise this issue, even if they lack the terminology: “Everything technically works, but it feels harder than it should.” This perception is an important signal.

According to Jonas Müller and Sarah Weber, organisations undergoing digital transformation often benefit most by first identifying sources of employee stress and wasted effort, rather than immediately building new solutions. By understanding where mental effort is unnecessarily high and clarity is lacking in current workflows, companies can reduce risks and improve performance. This understanding enables all subsequent improvements.

In the following section, we will examine practical examples of how organisations, including those in traditional industries such as telecoms and financial services, have used digital technologies such as artificial intelligence and cloud computing to turn the challenge of cognitive load into a potential advantage, as noted in a ScienceDirect report.

In high-pressure environments, the most effective systems are those that use digital tools to make work feel easier, rather than demanding more mental effort from employees.

This is where the right partner matters.

Reducing cognitive load is not a tooling exercise. It requires understanding how people work under pressure, how systems interact in the real world, and where digital decisions quietly create risk, waste, or friction.

At Sonin, this is the space we specialise in. We work with organisations operating in complex, high-pressure environments to uncover where cognitive load is being created, redesign workflows around real behaviour, and build digital products that reduce mental effort rather than add to it.

We do not start with features or platforms.

We start by making the invisible visible.

If you are responsible for systems where accuracy matters, time is constrained, and people cannot afford to think harder than necessary, then this problem is already costing you more than it should.

The next step is not committing to a build.

It is having the right conversation.