Today’s organizations generate too much cognitive noise for the people who work within them.
This is a widespread phenomenon. It unfolds gradually and often goes unnoticed: more tools to use, more metrics to monitor, more communications to process, more documents to read, write, digest. Paradoxically, as the volume of information increases, clarity decreases.
Complexity grows faster than our ability to metabolize what we produce.
As a result, people become the bottleneck of a system that, ironically, thanks to technology was supposed, though, to become faster and more efficient.
This dynamic has a direct and significant impact on decision-making. The issue is not, as is often assumed, that leaders are unable to make smart decisions. On the contrary, leaders are increasingly placed in the worst possible conditions to make decisions effectively and quickly.
Many strategic decisions, especially in areas such as product and portfolio management, are made while attempting to process an excessive number of inputs simultaneously.
The truth? The human mind is simply not designed to sustain this kind of pressure.
Cognitive Load Theory: Knowing the Limits of the Mind
To better understand this phenomenon, Cognitive Load Theory (CLT) – John Sweller – provides a critical lens; one that every leader should master to escape this trap and become a better decision-maker.
According to CLT, every cognitive task is influenced by three types of cognitive load:
- Intrinsic load: determined by the inherent complexity of the decision itself
- Extraneous load: generated by anything that makes information unnecessarily difficult to process
- Germane load: the useful mental effort necessary for understanding, learning, and deciding well
The implication is clear:
> Intrinsic Load should be reduced as much as possible
> Extraneous Load should be eliminated entirely
> Germane load is where cognitive energy should be primarily invested
Decision quality does not depend only on a leader’s intelligence, but on how much extraneous cognitive load is removed from the system.
In today’s organizations, however, extraneous load tends to dominate everything else. Overly long documents, unfiltered metrics, options presented without a comparable structure, information scattered across too many channels: these are all sources that create friction in our minds and that consume mental energy before strategic thinking even begins.
Extraneous cognitive load increases task difficulty even when the content itself is largely within the individual’s capabilities.
Neuroscience confirms how critical this is. Research by Nelson Cowan (2001) shows that working memory can hold only 3 to 5 meaningful elements at a time.
The working memory, being a system with finite capacity, is highly sensitive to overload. Those studies show how excessive information distorts attention, reduces decision quality, and increases the probability of “cognitive deadlock”.
Once this threshold is exceeded, reasoning quality rapidly deteriorates: we become slower, less organized, and more vulnerable to cognitive biases and ultimately leading to suboptimal decisions.
Other researches highlight how much learning suffers when essential information is scattered across separate sources (like text and diagrams); this forces the brain to juggle and mentally combine them. The results? The Split-attention effect, which overloads working memory and hinders understanding.
The figure on the left side of the image produces the split-attention effect, while the figure on the right enhances learning because it guides the learner’s attention through the integrated example.
Recognizing these limits does not mean lowering ambition.
It means acknowledging that decision quality does not depend solely on a leader’s intelligence, but on how much extraneous load is removed and how effectively the system simplifies intrinsic complexity, and finally freeing space for germane (pertinent) cognitive effort.
Designing for Clarity
A decision process can be complex without being confusing. The difference is design.
If we accept that the brain has measurable limits, we are then ready to face the real challenge that is not to “think or concentrate more”, but to create conditions that allow people to think better.
During daily work leadership teams and product organizations, we consistently observe that informational noise does not originate from problem complexity, but from how problems are presented. A decision process can be complex without being confusing.
What makes the difference? Design. Designing for Clarity.
Below are three practical principles that can help decision-makers improve the quality of their decisions.
1. Reduce the Number of Simultaneous Inputs
This is not about simplifying content, but about “modulating the pace” at which information is presented; e.g. when a review includes ten initiatives at once, there is no realistic chance that each will be evaluated with equal depth.
The brain responds defensively: it literally discards information, catches what appears first, or bigger, or interprets random signals as priorities. Limiting inputs is everything but a stylistic choice: it is neuro-designing.
2. Isolate What’s Truly Relevant
The second principle concerns relevance. One of the most effective ways to reduce extraneous load is to eliminate information that does not materially affect the decision.
Simply filtering out what is marginal immediately improves the quality of discussion, because it frees mental space for real reasoning.
3. Separate Cognitive Moments
Most decisions unfold across three distinct phases: exploration, synthesis, and decision. These phases require different levels of focus and cognitive resources—and they should not happen simultaneously.
When, instead, we mix those moments, attention fragments and extraneous load increases. Research on multitasking, for example, consistently shows that even brief interruptions significantly impair evaluative capacity.
These principles do not make decisions simpler. They make minds freer to engage with real complexity, without being weighed down by unnecessary information and fatigue.
The problem is not a lack of data. It is the lack of a structure that makes data comparable.
The 3×3×1 Decision Matrix
To facilitate decision making one good approach is to proceed with a “minimalist” comparative synthesis: transforming heterogeneous information into a simple, uniform representation aligned with Cognitive Load Theory.
A practical tool for this purpose is the 3×3×1 Decision Matrix: 3 decision options, 3 comparison dimensions, 1 single page or view
Each option is evaluated along three dimensions:
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Expected impact: What difference does this option make if it works?
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Main risk: What could realistically go wrong?
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Required effort: How much time, energy, and attention does it consume?
A Concrete Example
Consider a situation like this:
A B2B digital product is live for over a year. The initial business case was strong, but after launch momentum has stalled. Adoption is uneven, growth is slower than expected, and despite continuous feature delivery, overall traction has plateaued.
Now it’s the moment to engage the leadership team to make a decision; let’s see how the matrix can help.
| Option | Impact | Risk | Effort |
|---|---|---|---|
| Persevere (continue investing) | Medium – incremental improvement on current outcomes; optimization of existing traction | Stagnation – continued investment without a breakthrough in adoption or growth | Medium – ongoing roadmap execution, team continuity |
| Pivot (validate real user interest and refocus) |
Potentially High – meaningful change in trajectory if a new value proposition gains traction | Uncertain validation – no guarantee the new focus will scale or convert | High – strategic reset, experimentation, team and roadmap realignment |
| Cancel (halt development and reallocate budget) |
Resource liberation – capital, talent, and attention freed for higher-impact initiatives | Customer impact – loss of users, reputational or political cost | Low – operationally simple, though emotionally and organizationally difficult |
This approach, by standardizing comparison, naturally reduces cognitive load. Decision making process gets enhanced because a shared basis for discussion is now available to every stakeholder, preventing any personalization and bias in framing the problem,.
How AI Can Help
AI is often seen as a generator of additional analyses, documents, or insights. But as we have seen, adding information does not improve decision-making. In this context,
AI is useful only when it reduces extraneous cognitive load.
As we know, AI can analyze large volumes of data, extract relevant metrics, and identify inconsistencies, ambiguities, and contradictions. It can rapidly synthesize feedback, detect patterns, and surface risks.
In doing so, AI removes much of the cognitive burden associated with digesting large datasets. Its output can then be a clean 3×3×1 decision matrix.
Ah, one final thing on this, do not forget to explicit the right reasoning and prompt to avoid hallucinations or opaque options and data. Here below an off-the-shelf LLM prompt you can use for one of your critical scenarios.
ROLE: You are a senior strategy analyst supporting executive-level decisions under uncertainty. TASK: Transform the scenario into a 3×3 decision matrix that makes trade-offs explicit without recommending a choice. INPUT: You will receive a short scenario describing a decision context, constraints, and what matters most. OUTPUT REQUIREMENTS 1) Define exactly THREE decision options (mutually exclusive) - Each option must represent a distinct strategic posture. - Keep options at the same level of abstraction. - Avoid overlap (no “Option A + some of Option B”). - Title each option with a short, executive-friendly label. 2) Evaluate each option using exactly THREE dimensions (use the same ones for all options) - Expected Impact: the meaningful difference if it succeeds. - Primary Risk: the single most material risk that could undermine it. - Required Effort: time, attention, energy, and organizational disruption. 3) Language constraints - Use qualitative, comparative terms only (e.g., Low / Medium / High / Potentially High). - No numbers, no forecasts, no financial calculations. - Each cell must be ONE short sentence or compact phrase. - No explanations, no justification, no extra commentary. 4) Format constraints - Produce ONE table only. - Rows = the three options. - Columns = Expected Impact | Primary Risk | Required Effort. - Do not add any text before or after the table. QUALITY CHECK (silent, do not output) - Options are clearly different and mutually exclusive. - Impact, risk, and effort are not conflated. - An executive can scan and understand it in under 30 seconds. SCENARIO <<<PASTE SCENARIO HERE>>>
Conclusion
Leadership is no longer about accumulating information…it hasn’t been for over 30 years now.
It is about creating the right conditions to understand it.
In a world that naturally trends toward hyper-complexity, the ability to design clarity is a strategic responsibility. Reducing extraneous load does not mean oversimplifying analysis; it means understanding and setting the stage for the very physiology of human thinking.
Every important decision requires mental space, order, and focused attention. It requires an ecosystem that protects thinking instead of obstructing it.
The leadership of the future won’t be a solitary effort in trying to manage uncertainty.
It will be the capability to build information systems that allow people to think better, together.
