Latest news with #decision making
Irish Times
05-08-2025
- Business
- Irish Times
Shopping for agreement: the truth about financial advice
We seek financial advice to make better, more accurate decisions – don't we? Well, maybe not. Often, we're shopping for agreement, looking for someone to bless the choice we were leaning toward all along. So suggests a recent study, Motivated Advice Seeking: Are Advice Seekers Trying to Be More Accurate?, which says we don't want better advice, but better justification. Across five studies on real-world decision-making, many involving financial trade-offs – from quitting a job to covering medical bills, booking a holiday or renovating a kitchen – researchers found that people seek out advisers they believe will agree with them. They also frame questions in biased ways, emphasising the option they secretly hope to hear endorsed. READ MORE Advisers pick up on these cues, resulting in advice being 'co-created by both motivated advisees and motivated advisers'. Result: a feedback loop where confidence goes up, but decision quality doesn't. In financial terms, that can mean wasted money, missed opportunities or preventable regret. In short, it's less about clarity than comfort. Next time you seek financial advice, ask yourself: am I looking for advice or affirmation?
Forbes
11-07-2025
- Business
- Forbes
How Systems Thinking Helps Leaders Avoid Bad Decisions
Confused businessman staring at complexity. It's remarkable how smart, experienced executives systematically make decisions that backfire. They apply industrial-age logic to a hyperconnected systems-age world. They break down complex problems, optimize individual components, and expect predictable outcomes. They believe that perfect information leads to perfect decisions. There are no shortage of examples illustrating these failures. Boeing's engineers solved a specific aerodynamics problem with elegant precision—yet 346 people died in crashes soon afterwards. Amazon executed a routine system update flawlessly—yet accidentally paralyzed Netflix, Slack, and thousands of their own services for seven hours. And, Uber has optimized urban transportation with ruthless efficiency—yet experienced such strong community backlash that they were barred from some cities. These aren't isolated failures or execution problems. They're the inevitable result of applying analytical thinking to systemic challenges. When everything connects to everything else, traditional decision-making approaches don't just miss the mark—they create the very chaos leaders are desperately trying to prevent. Here are three reasons why smart executives keep making bad decisions, and how systems thinking can break this costly cycle. Reason 1: The Myth of the 'Right Answer' Walk into almost any boardroom and you'll hear the seductive language of certainty: "best practices," "proven solutions," "data-driven decisions." Executives pay hefty fees for consulting firms that peddle definitive answers to complex challenges, which offers an illusion of control. stressed businesswoman pouring over data This pursuit of perfect solutions seduces executives into believing that more data and better analysis will yield the right answer. Yet, most complex problems cannot be solved by simply analyzing more data. Most business problems involve numerous considerations, many of which cannot be seen or measured. Consider Boeing's 737 MAX crisis. When engineers discovered the plane's tendency to pitch upward during extreme maneuvering, they treated this as a pure engineering problem and developed the Maneuvering Characteristics Augmentation System (MCAS). The solution was elegant and precise. It was also catastrophically flawed. Only when two planes crashed within months of each other, killing 346 people and grounding the entire 737 MAX fleet for 20 months, did senior executives recognize that the issue wasn't just bad engineering. They also faced weak backup systems, inadequate training protocols, cultural pressure to compete with Airbus, and overconfidence in technological fixes—all of which interacted in ways that Boeing's optimization-focused approach couldn't anticipate. Build adaptive capacity instead. In interconnected systems, there are no perfect solutions—only better and worse interventions. Every action creates ripple effects that cannot be fully predicted or controlled. The executives winning in today's environment have abandoned the search for perfect answers and instead developed the capacity to sense, experiment, and adapt. Microsoft's transformation under Satya Nadella exemplifies this shift. When Nadella became CEO in 2014, he didn't look for the perfect strategic answer. Instead, he made a series of interconnected bets—cloud computing, artificial intelligence, strategic partnerships with former competitors like Apple. None of these moves had guaranteed returns, but together they positioned Microsoft to thrive in an uncertain future. The result? A 12-fold increase in market capitalization during his tenure as CEO. Reason 2: The Obsession with Control The second myth plaguing modern business is the assumption that complex systems can be controlled through tighter management processes. This industrial-age thinking treats organizations like machines—predictable, controllable, and responsive to top-down commands. Reality is far messier. Tightly integrated systems means that small changes can produce massive, unintended consequences. This is true in technical systems, such as computers, and even more true in systems that involve people, which are even more unpredictable than computers. The 2021 Amazon Web Services outage provides a stark illustration. At 7:30 AM on December 7, Amazon executed a routine system update flawlessly, yet triggered a cascading failure that paralyzed Netflix, Slack, and thousands of unrelated services for seven hours. What seemed like a simple technical adjustment in one part of AWS's system rippled through interconnected networks in ways no amount of planning could have anticipated. Embrace strategic flexibility instead. When leaders respond to complexity by adding more tightly monitored and controlling processes, they actually make systems more brittle and fragile. The harder they squeeze, the more likely the system will break under pressure. Instead of controlling outcomes, effective leaders create conditions for better solutions to emerge. They give people authority, tools, and resources to adapt to their situations. These executives foster coordination, not close monitoring. They empower people to make their own decisions and the time and resources to do so. This managerial slack, so that unexpected events do not completely unravel the business. When Danish energy firm Ørsted (formerly DONG Energy) decided to transform from a coal-intensive utility to an offshore wind leader. Executives set a bold ambition. In 2008, the company generated 85% of its energy from coal. In 2009, they committed to flip this ratio, generating 85% from renewable sources by 2040. Rather than creating a precise and rigid 30-year plan, they built flexibility and learning into the system. They allowed leaders to respond to changes in the environment. For example, they made a massive upfront investment in 500 wind turbines—more than were operating offshore globally—to build supply chain capabilities. They also sold oil and gas assets to create financial slack. They also brought in institutional investors for long-term financing, giving more strategic flexibility. The result: a 350% increase in valuation and an 86% reduction in carbon emissions by 2023—hitting their target 17 years ahead of schedule. Reason 3: Short-Term Thinking Perhaps the most dangerous myth is the relentless pursuit of quarterly results and operational efficiency. This doctrine, enshrined in business schools and reinforced by capital markets, creates a vicious cycle where leaders sacrifice innovation, resilience, and competitive positioning for the illusion of predictable returns. My research consistently demonstrates this dynamic. In one study with Caroline Flammer, we found that firms adopting long-term incentive plans invested more heavily in R&D and stakeholder engagement, financially outperforming their peers after two years across multiple metrics. Another study with Natalia Ortiz de-Mandojana shows that firms with a long-term orientation experienced higher revenues and better survival rates. Adopt dual time horizons instead. Short-term thinking is important as executives can respond to immediate threats and opportunities. Long-term thinking is important as it contextualizes these pressing events within the firm's strategic context. In interconnected systems, businesses face a constant barrage of information and must decide when the signals are vital and or when they are simply a distraction from their long-term ambitions. Sustainable competitive advantage comes from understanding and investing in relationships that create value over time. Consider how Patagonia has built a $1 billion outdoor apparel business by explicitly rejecting short-term optimization. The company's "Don't Buy This Jacket" campaign and commitment to environmental activism seem antithetical to growth, yet they've created fierce customer loyalty and premium pricing power that traditional marketing could never achieve. The companies thriving today are those that that can maintain dual time horizons. They keep one eye on the short term, so they know which short-term events require their attention and which ones to ignore. The other eye is focused on the long term, so they are not derailed by short-term distractions. Maintaining a dual time horizon paradoxically build stronger organizations that deliver consistently higher short-term and long-term returns. Such an approach requires fundamentally different mental models, metrics, and governance structures than those designed for industrial-era business. Embracing Systems Thinking Seeing patterns in simplicity Uber's meteoric rise from a $5 million startup to a $3.5 billion juggernaut in just four years appeared to validate Silicon Valley's favorite playbook: identify a problem, build a solution, scale fast, and let the market sort out the details. To executives watching from the sidelines, Uber's success looked like a masterclass in disruptive innovation. But beneath the headlines of exponential growth lay a different story—one that reveals why our most trusted approaches to business decision-making are dangerously obsolete in today's hyperconnected world. The ride-hailing giant that promised to reduce traffic actually increased congestion by 50% in San Francisco from 2010 and 2016. The platform designed to create opportunity for drivers instead trapped them in a gig economy with no safety net. The innovation meant to complement urban mobility ended up cannibalizing public transportation, particularly harming low-income communities removing their access to affordable transit options. After years of regulatory battles, driver protests, and public relations disasters, the company began adapting to local conditions, integrating with public transit, and addressing worker concerns. These changes may have slowed expansion in the short term, but they've created a more sustainable, profitable business model that contributes to more resilient systems—for both the company and its communities. The executives who will succeed in this systems age are not those who apply industrial-age logic, seeking simple cause-and-effect relationships. Instead, they seek to understand the deeper patterns that shape business outcomes. They've shifted from the traditional plan-do-check-act approach to business to one that is agile and adaptive. This requires governance structures that distribute decisions throughout the organization, build flexibility to adapt, and foster experimentation for long-term gains without losing sight of short-term realities. Systems thinking isn't a management fad—these ideas have been around for decades. What's new is the urgent need to respond to a fundamentally different business environment that's more interconnected than ever before. Systems thinking isn't merely about altruism—it's essential for survival.
Forbes
11-07-2025
- Business
- Forbes
Three Reasons Why Smart Executives Make Bad Decisions — And How Systems Thinking Fixes Them
Confused businessman staring at complexity. It's remarkable how smart, experienced executives systematically make decisions that backfire. They apply industrial-age logic to a hyperconnected systems-age world. They break down complex problems, optimize individual components, and expect predictable outcomes. They believe that perfect information leads to perfect decisions. There are no shortage of examples illustrating these failures. Boeing's engineers solved a specific aerodynamics problem with elegant precision—yet 346 people died in crashes soon afterwards. Amazon executed a routine system update flawlessly—yet accidentally paralyzed Netflix, Slack, and thousands of their own services for seven hours. And, Uber has optimized urban transportation with ruthless efficiency—yet experienced such strong community backlash that they were barred from some cities. These aren't isolated failures or execution problems. They're the inevitable result of applying analytical thinking to systemic challenges. When everything connects to everything else, traditional decision-making approaches don't just miss the mark—they create the very chaos leaders are desperately trying to prevent. Here are three reasons why smart executives keep making bad decisions, and how systems thinking can break this costly cycle. Reason 1: The Myth of the 'Right Answer' Walk into almost any boardroom and you'll hear the seductive language of certainty: "best practices," "proven solutions," "data-driven decisions." Executives pay hefty fees for consulting firms that peddle definitive answers to complex challenges, which offers an illusion of control. stressed businesswoman pouring over data This pursuit of perfect solutions seduces executives into believing that more data and better analysis will yield the right answer. Yet, most complex problems cannot be solved by simply analyzing more data. Most business problems involve numerous considerations, many of which cannot be seen or measured. Consider Boeing's 737 MAX crisis. When engineers discovered the plane's tendency to pitch upward during extreme maneuvering, they treated this as a pure engineering problem and developed the Maneuvering Characteristics Augmentation System (MCAS). The solution was elegant and precise. It was also catastrophically flawed. Only when two planes crashed within months of each other, killing 346 people and grounding the entire 737 MAX fleet for 20 months, did senior executives recognize that the issue wasn't just bad engineering. They also faced weak backup systems, inadequate training protocols, cultural pressure to compete with Airbus, and overconfidence in technological fixes—all of which interacted in ways that Boeing's optimization-focused approach couldn't anticipate. Build adaptive capacity instead. In interconnected systems, there are no perfect solutions—only better and worse interventions. Every action creates ripple effects that cannot be fully predicted or controlled. The executives winning in today's environment have abandoned the search for perfect answers and instead developed the capacity to sense, experiment, and adapt. Microsoft's transformation under Satya Nadella exemplifies this shift. When Nadella became CEO in 2014, he didn't look for the perfect strategic answer. Instead, he made a series of interconnected bets—cloud computing, artificial intelligence, strategic partnerships with former competitors like Apple. None of these moves had guaranteed returns, but together they positioned Microsoft to thrive in an uncertain future. The result? A 12-fold increase in market capitalization during his tenure as CEO. Reason 2: The Obsession with Control The second myth plaguing modern business is the assumption that complex systems can be controlled through tighter management processes. This industrial-age thinking treats organizations like machines—predictable, controllable, and responsive to top-down commands. Reality is far messier. Tightly integrated systems means that small changes can produce massive, unintended consequences. This is true in technical systems, such as computers, and even more true in systems that involve people, which are even more unpredictable than computers. The 2021 Amazon Web Services outage provides a stark illustration. At 7:30 AM on December 7, Amazon executed a routine system update flawlessly, yet triggered a cascading failure that paralyzed Netflix, Slack, and thousands of unrelated services for seven hours. What seemed like a simple technical adjustment in one part of AWS's system rippled through interconnected networks in ways no amount of planning could have anticipated. Embrace strategic flexibility instead. When leaders respond to complexity by adding more tightly monitored and controlling processes, they actually make systems more brittle and fragile. The harder they squeeze, the more likely the system will break under pressure. Instead of controlling outcomes, effective leaders create conditions for better solutions to emerge. They give people authority, tools, and resources to adapt to their situations. These executives foster coordination, not close monitoring. They empower people to make their own decisions and the time and resources to do so. This managerial slack, so that unexpected events do not completely unravel the business. When Danish energy firm Ørsted (formerly DONG Energy) decided to transform from a coal-intensive utility to an offshore wind leader. Executives set a bold ambition. In 2008, the company generated 85% of its energy from coal. In 2009, they committed to flip this ratio, generating 85% from renewable sources by 2040. Rather than creating a precise and rigid 30-year plan, they built flexibility and learning into the system. They allowed leaders to respond to changes in the environment. For example, they made a massive upfront investment in 500 wind turbines—more than were operating offshore globally—to build supply chain capabilities. They also sold oil and gas assets to create financial slack. They also brought in institutional investors for long-term financing, giving more strategic flexibility. The result: a 350% increase in valuation and an 86% reduction in carbon emissions by 2023—hitting their target 17 years ahead of schedule. Reason 3: Short-Term Thinking Perhaps the most dangerous myth is the relentless pursuit of quarterly results and operational efficiency. This doctrine, enshrined in business schools and reinforced by capital markets, creates a vicious cycle where leaders sacrifice innovation, resilience, and competitive positioning for the illusion of predictable returns. My research consistently demonstrates this dynamic. In one study with Caroline Flammer, we found that firms adopting long-term incentive plans invested more heavily in R&D and stakeholder engagement, financially outperforming their peers after two years across multiple metrics. Another study with Natalia Ortiz de-Mandojana shows that firms with a long-term orientation experienced higher revenues and better survival rates. Adopt dual time horizons instead. Short-term thinking is important as executives can respond to immediate threats and opportunities. Long-term thinking is important as it contextualizes these pressing events within the firm's strategic context. In interconnected systems, businesses face a constant barrage of information and must decide when the signals are vital and or when they are simply a distraction from their long-term ambitions. Sustainable competitive advantage comes from understanding and investing in relationships that create value over time. Consider how Patagonia has built a $1 billion outdoor apparel business by explicitly rejecting short-term optimization. The company's "Don't Buy This Jacket" campaign and commitment to environmental activism seem antithetical to growth, yet they've created fierce customer loyalty and premium pricing power that traditional marketing could never achieve. The companies thriving today are those that that can maintain dual time horizons. They keep one eye on the short term, so they know which short-term events require their attention and which ones to ignore. The other eye is focused on the long term, so they are not derailed by short-term distractions. Maintaining a dual time horizon paradoxically build stronger organizations that deliver consistently higher short-term and long-term returns. Such an approach requires fundamentally different mental models, metrics, and governance structures than those designed for industrial-era business. Embracing Systems Thinking Seeing patterns in simplicity Uber's meteoric rise from a $5 million startup to a $3.5 billion juggernaut in just four years appeared to validate Silicon Valley's favorite playbook: identify a problem, build a solution, scale fast, and let the market sort out the details. To executives watching from the sidelines, Uber's success looked like a masterclass in disruptive innovation. But beneath the headlines of exponential growth lay a different story—one that reveals why our most trusted approaches to business decision-making are dangerously obsolete in today's hyperconnected world. The ride-hailing giant that promised to reduce traffic actually increased congestion by 50% in San Francisco from 2010 and 2016. The platform designed to create opportunity for drivers instead trapped them in a gig economy with no safety net. The innovation meant to complement urban mobility ended up cannibalizing public transportation, particularly harming low-income communities removing their access to affordable transit options. After years of regulatory battles, driver protests, and public relations disasters, the company began adapting to local conditions, integrating with public transit, and addressing worker concerns. These changes may have slowed expansion in the short term, but they've created a more sustainable, profitable business model that contributes to more resilient systems—for both the company and its communities. The executives who will succeed in this systems age are not those who apply industrial-age logic, seeking simple cause-and-effect relationships. Instead, they seek to understand the deeper patterns that shape business outcomes. They've shifted from the traditional plan-do-check-act approach to business to one that is agile and adaptive. This requires governance structures that distribute decisions throughout the organization, build flexibility to adapt, and foster experimentation for long-term gains without losing sight of short-term realities. Systems thinking isn't a management fad—these ideas have been around for decades. What's new is the urgent need to respond to a fundamentally different business environment that's more interconnected than ever before. Systems thinking isn't merely about altruism—it's essential for survival. This is the first in a series exploring how systems thinking can transform business decision-making. In future articles, I'll examine practical frameworks for developing systems intelligence and real-world applications across industries.
