Knowing When to Pull the Plug
Many organisations fall into the trap of persisting with a failing tech rollout simply because those behind it can’t admit it’s a dud. Picture a heavily customised system, touted as the ultimate solution to streamline operations, but in practice, it’s riddled with glitches, escalating expenses, and subpar results. Rather than switching to reliable, proven alternatives, decision-makers keep funnelling resources into it, all to dodge the sting of failure.
At the heart of this is escalation of commitment – a psychological pattern where people stick with a poor decision despite clear evidence it’s wrong, driven by the need to justify past choices and protect their ego. It’s not just stubbornness; it’s a defence against the discomfort of admitting error, which threatens self-esteem and perceived competence.
This ties into cognitive dissonance, the mental tension from holding conflicting beliefs – like knowing the system is broken but insisting it’s salvageable. To ease this, individuals distort facts or downplay issues, rationalising setbacks as minor blips rather than fatal flaws. Rationalisation itself is a key mechanism here: creating post-hoc excuses to make the bad choice seem logical, such as blaming external factors or claiming unforeseen complexities.
Then there’s the sunk cost fallacy, where the investment already made – time, money, effort – becomes the rationale for continuing, even when logic screams to stop. “We’ve come this far; we can’t quit now.” It’s irrational, but it shields the ego from the regret of wasted resources.
Denial plays a role too, with leaders outright ignoring data or feedback that contradicts their view, preserving a bubble where the project still has merit. Add self-serving bias, where successes are owned but failures are attributed to outside forces, and you have a cocktail of biases that prioritises personal image over organisational health.
These psychological forces explain why killing a pet project feels impossible: it’s not about the tech; it’s about avoiding the ego bruise of being wrong.
In sectors like mining, where the MRO (Maintenance, Repair, and Operations) supply chain is critical, this persistence wreaks havoc on the bottom line. A system that’s simply not working in reality leads to stock-outs of essential parts, forcing unplanned downtime on heavy equipment – think excavators or haul trucks grinding to a halt, costing thousands per hour in lost production. Excessive inventory ties up capital in unused spares, inflating carrying costs and risking obsolescence, while integration failures exacerbate reactive maintenance over predictive strategies. Inventory management errors alone can eat into annual profits significantly, amplified in mining by volatile commodity prices and remote operations. Failed tech rollouts compound this, with hidden productivity losses and ballooning expenses eroding margins – turning operational inefficiencies into multimillion-dollar hits.
Worse still, this behaviour teaches users – the frontline employees relying on these systems – all the wrong lessons. When leaders ignore data and feedback, it fosters a culture of scepticism towards evidence, where gut feelings trump analytics. Staff learn to game the flawed system rather than trust it, perpetuating errors and discouraging innovation. Over time, this erodes confidence in data-driven processes, making it harder to implement future improvements.
But true leadership demands overriding these impulses. Spot the red flags early, confront the evidence head-on, and scrap the failure without delay. Trust data to drive better decision-making: analyse metrics rigorously, weigh proven options objectively, and pivot decisively. Clinging on only amplifies the damage – lost productivity, eroded team morale, and opportunities squandered. The smart move? Admit the mistake, pivot to what works, and learn from it. Hesitation is the real killer.
