In modern organisations, decision-making has become significantly more complex. Leaders are expected to navigate growing volumes of data, faster execution cycles, AI-driven workflows, and constant uncertainty — often while making high-impact decisions under pressure.

Yet research consistently shows that even experienced teams still make poor strategic decisions. According to Adroiti Product Owner Arminas Kazlauskas, the issue is rarely intelligence alone. More often, the real problem is the absence of a structured decision-making system.

“Even experienced leaders make mistakes, but not because they don’t know enough. The real issue is that the decision-making process is often not disciplined enough,” he says.

Drawing on the bestselling book Decisive: How to Make Better Choices in Life and Work, Arminas highlights the main reasons why organizations make poor decisions and shares practical approaches that help teams avoid common decision-making traps in complex operational environments.

The Biggest Problem: Narrow Framing

According to Arminas, the first mistake happens even before the decision itself — in the way we define the problem.

“In engineering and AI product development, decisions rarely fail because of a lack of information. More often, they fail because teams operate inside narrow assumptions, fragmented workflows, or emotionally driven priorities,” Arminas explains.
“We often make decisions based on what is immediately visible instead of deliberately widening our options. We choose between two projects, two universities, or two strategies, assuming those are the only possibilities. In reality, the frame is often artificially narrow,” he explains.

Another common issue is that people tend to search for information that confirms what they already believe.

“If we already lean toward one option, consciously or unconsciously, we look for arguments that support our thinking. This is known as confirmation bias. In business environments, this often happens when organisations become attached to a product idea, workflow, or strategy before validating it properly,” Arminas points out.

In high-performing organisations, better outcomes usually come from structured challenge processes rather than instinct alone.

Asking the Right Questions Matters

In one study analysing more than a thousand business decisions, companies that followed a clear decision-making process achieved outcomes that were six times better.

“However, even superb analysis is not enough — asking the right questions is just as important,” Arminas emphasises.

He highlights four principles that help decisions become not necessarily perfect, but far more reliable. Over time, that reliability is what separates average outcomes from exceptional ones.

Widen Your Options – Replace “or” with “and”

One of the most common mistakes teams make is framing decisions as either-or choices: cut costs or invest, choose one project or another, hire or save money.
High-performing teams, however, replace “or” with “and”.

“A study of 4,700 companies showed that during recessions, organisations that both reduced costs and invested in growth recovered significantly better than those that chose only one direction. They not only rebounded faster but also outperformed competitors in both sales and profit growth,” Arminas explains.

He notes that one of the simplest ways to expand thinking is to ask a powerful question: “What would you do if none of these options was available?” This question forces people to move beyond the artificial frame of limited choices.

Arminas also stresses the importance of clearly identifying the opportunity cost — what we lose when choosing one option over another.

“Research shows that simply making the opportunity cost explicit can significantly change people’s behaviour,” he says.

Test Your Assumptions in Reality

Even when we widen our options, we can still make mistakes if our decisions rely on untested assumptions.

“Instead of asking ‘Is this a good idea?’, it’s often better to ask: ‘What would have to be true for this decision to succeed?’ This question turns opinions into measurable conditions. For example, if we believe a new product will work, what exactly needs to happen for that to be true? How many customers? At what price? What level of engagement?” Arminas explains.

Arminas notes that this becomes especially relevant in AI initiatives and digital product development, where companies often move too quickly from prototype to execution, without validating assumptions under real operational conditions.

“Modern organisations often over-rely on isolated metrics or dashboards without understanding the broader operational context. Effective decision-making requires both macro-level pattern recognition and the ability to interpret granular signals correctly,” Arminas says.

Whenever possible, he recommends starting with small experiments instead of making large commitments immediately: “Running a small operational test before making a large strategic commitment allows teams to learn faster and reduce execution risk significantly,” he adds.

Create Distance Before Making a Decision

Strong short-term emotions influence our decisions far more than we realise. Sometimes a simple pause can help prevent long-term mistakes.

“We tend to fear losses more strongly than we enjoy gains, and this significantly distorts how we evaluate risk,” Arminas says.

This effect is illustrated by a classic experiment. Students who were given a cup were asked how much they would sell it for — on average, $7.12. Students who did not own the cup were only willing to pay about $2.87 for it.

The moment people own something, they begin valuing it significantly more.
“That’s why it’s important to consciously create distance before making an important decision,” Arminas explains.

One useful technique is asking yourself: ‘If a new CEO came in today, what would they do?’ This question helps detach from past investments of time, money, or reputation.

In everyday work, a simple habit can also help — periodically pausing and asking: “Am I doing the work that actually creates value right now?”

Prepare to Be Wrong

According to Arminas, even well-thought-out decisions can turn out to be wrong because the future is never a single outcome — it is always a range of possibilities.

“Before committing to a decision, it’s important to build safety margins. Instead of relying on a single forecast, consider a range of outcomes and ask: what is the best-case scenario and what is the worst-case scenario? Are we prepared for both?” he advises.

In engineering, such safety factors are standard practice — structures are built to withstand much more than the expected load. The same principle applies in business through financial buffers, time reserves, and alternative plans.

Arminas also highlights the importance of tripwires — clearly defined triggers that prompt action.

“Instead of saying ‘we’ll see how things go’, define clear thresholds. For example: ‘If the market reaches X% adoption, we will change our strategy,’ he explains.

“A decision doesn’t become good just because it was made confidently. What matters is being ready to adjust when reality proves you wrong,” Arminas concludes.

At Adroiti, this approach shapes how teams build AI-powered products and operational systems — through structured validation, iterative testing, and decision-making grounded in real-world execution rather than assumptions alone.

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Adroiti is a Lithuanian technology company building AI-powered systems and running senior engineering teams that deliver real, production-ready results.