This article was written by Paolo Tatticchi and Giuseppe Stigliano and published in Forbes Mexico on 16 February 2026, with the Spanish title Entre planes y realidad (“Between plans and reality”). 

When I started my first business, I produced a meticulous 40-page plan. It had market sizes, Gantt charts and five-year projections. It also had very little to do with the messy choices I faced within weeks. That was my first encounter with a pervasive corporate myth: that strategy is a plan. In reality, strategy is a living system of choices under uncertainty. The plan was neat; the world was not. 

Below are five myths that quietly sabotage modern management and how to replace them with practices that move organisations from intent to impact.  

Myth 1: “Strategy is a plan.” 

Plans are useful, but they are not strategy. Strategy is direction under uncertainty: a coherent set of where-to-play and how-to-win choices that align decisions and behaviours. It is dynamic by nature and, in today’s environment, must be more agile than ever. Henry Mintzberg’s work on emergent strategy exposed the limits of purely deliberate plans; advantage now accrues to fast-emerging strategies that evolve as evidence arrives. The remedy is to shift from plan-centric governance to decision-centric governance. Establish clear cadences (weekly for operating choices, monthly for portfolio choices, quarterly for strategic bets), force every major decision through a short brief that names the hypothesis, leading indicators and kill-criteria, and hold post-decision reviews to harvest learning. The artefact matters less than the ability to decide, adapt and keep direction. 

Myth 2: “More data means better decisions.” 

In an era of abundant dashboards and AI-generated summaries, many leaders confuse volume with signal. More data can add latency, create spurious correlations and breed false confidence. High-performing teams start with the decision, not the dataset: what choice are we making, what would change our mind, and what is the smallest high-signal evidence we need in the time available. A practical rule is to define a minimum-sufficient dataset for each decision type and stick to it. Use AI to compress time to insight, not to outsource judgment: always generate alternative scenarios, surface disconfirming evidence and test sensitivity to a handful of assumptions. The aim is not exhaustive analysis but decisive action with transparent uncertainty. 

Myth 3: “What gets measured gets managed.” 

Measurement is necessary, but on its own it distorts. As Goodhart’s law warns, when a measure becomes a target, it ceases to be a good measure. KPI theatre follows: activity surrogates outcomes, and teams game the numbers to look green. Replace metric monoculture with a balanced system that pairs numbers with narratives. For each objective, track one outcome metric, one leading indicator and one behaviour indicator that reflects how results are achieved. Complement dashboards with monthly evidence-of-learning notes from teams: what changed in the environment, what we tried, what we learned, and what we will stop. Management attention should flow to anomalies and learning, not just to traffic-light colours. 

Myth 4: “The customer is always right.” 

Customers are diverse, often conflicted and sometimes wrong for your strategy. Winning firms decide which customers are right for them and when to say no. That means segmenting not just by demographics, but also by jobs-to-be-done, lifetime economics, and values compatibility. Create explicit anti-personas to clarify who you will not serve or what requests you will not fulfil. Equip frontline teams with a simple test: does this request advance our chosen positioning, degrade it, or distract us? Saying no can feel uncomfortable in the short term, but it builds clearer propositions, faster roadmaps and healthier margins. Strategy is as much about subtraction as it is about addition. 

Myth 5: “Growth at all costs.” 

Chasing topline without discipline inflates risk and destroys optionality. In my research on organisational dynamics and organic growth, drawing on the Brunello Cucinelli case, we observed a different playbook: patient scaling anchored in product integrity, pricing discipline and craft-based capability building. Growth was paced to protect culture and quality, with capital allocated to deepen know-how, strengthen communities and extend the brand’s meaning before widening distribution. The result was resilient cash flows, pricing power and reputational equity that compounded over time. The broader lesson is that durable growth is an outcome of coherence: unit economics that work without subsidy, a supply chain that can flex without breaking, and a licence-to-operate sustained by genuine stakeholder value. In volatile markets, this slow-is-smooth, smooth-is-fast approach outperforms blitzscalingthat leaves cultural and operational debt. 

Putting it into practice: five shifts