Connect with us

Business

Harvard researcher: Three-hour flight delays now four times more common than in 1990

Published

on



On one sweltering summer afternoon in June, thunderstorms rolled over Boston Logan International Airport. It was the kind of brief, predictable summer squall that East Coasters have learned to ignore, but within hours, the airport completely shut down. Every departure was grounded, and flyers waited hours before they could get on their scheduled flights.

Among those stranded were Maxwell Tabarrok’s parents, in town to help move him into Harvard Business School, where he is completing an economics PhD. Tabarrok told Fortune he was fascinated by how an entire airport could grind to a halt, not because of some catastrophic event, but due to a predictable hiccup rippling through an overstretched system. 

So, he did what any good statistician would: dive into the data. After analyzing over 30 years—and 100 gigabytes—of Bureau of Transportation Statistics data, he found out his parents’ situation wasn’t bad luck: Long delays of three hours or more are now four times more common than they were 30 years ago. 

Not only that, but Tabarrok found airlines are trying to hide the delays by “padding” the flight times—adding, on average, 20 extra minutes to schedules so a flight that hasn’t gotten any faster still counts as “on time.” Thus, on paper, the on-time performance metrics have improved since 1987, even as actual travel times have gotten longer. 

“For 15 years, from 1987 to 2000, the actual and scheduled times stayed very close together,” Tabarrok said. “Then, starting right around 2000, they started diverging—a pretty clear sign airlines made a decision to start padding their schedules to avoid shorter delays.”

The padding carries a hidden economic cost. Using average U.S. wage data, the extra minutes built into flights add up to roughly $6 billion in lost passenger time annually, the researcher calculated. 

There are far more users in the National Airspace system today than there were decades ago, industry sources say. U.S. Department of Transportation data shows weather is the most common cause of non-airline delays.  An ongoing shortage of air traffic controllers, combined with recent FAA equipment outages, has also disrupted operations worldwide. 

A structurally unsound system

For Tabarrok, the root of the problem isn’t just bad weather, outdated infrastructure, or even airline strategy: It’s incentives. He argues the FAA has little reason to respond quickly to rising delays because the agency doesn’t bear the cost of stranded passengers, nor are they rewarded when airports run smoothly.

“I think the costs of delays can double, triple, quadruple over the next 10 years. But is anyone’s career negatively affected at the FAA? Probably not,” Tabarrok said.

He pointed to the shortage of air traffic controllers as an example. Hiring and training more staff would ease congestion and reduce cascading delays—a very simple solution that many people have called for. However, doing so requires sustained effort and leadership that is actually willing to push through bureaucratic inertia.

“You need somebody at the FAA who really cares about improving service. That’s not so easy to do because there’s really no incentive for somebody at the FAA to care a lot about this… they don’t get paid more,” Tabarrok said. “They don’t really get rewarded at all.” 

A FAA spokesperson told Fortune the organization prioritizes safety, which sometimes necessitates delays. They pointed to a chart showing the top five causes of delays—with weather being “by far” the largest cause. They declined to answer questions about airlines padding schedules and incentives to improve airport quality.  

Expanding airport capacity, for Tabarrok, is the most obvious long-term solution to reduce the cascading delays. But the U.S. hasn’t opened a major commercial airport since Denver International in 1995, and runway construction at existing hubs has been minimal, he said. Passenger traffic, meanwhile, has grown by about 50% since 2000, meaning more travelers are concentrated in the same physical space.

While we have built larger aircrafts to help carriers move more people, that’s also created new bottlenecks, he added. Bigger planes take longer to fly at every turn. They take longer to board, unload, and turn around at the gate, so the disruption continues to ripple into the schedule.

“The infrastructure at airports is fixed, especially season to season,” Tabarrok said. “So when you have more demand with fixed infrastructure, there’s going to be more delays.”

‘Pessimistic story’

Further, Tabarrok argued big-ticket fixes like building a new airport or runways face environmental reviews and legal challenges that can drag on for a decade. 

That leaves staffing as the most realistic solution, but even that will require changing how the FAA recruits, licenses, and trains controllers.

“It’s kind of a pessimistic story,” Tabarrok said. “We have these two constraints that aren’t that responsive to the market pressures of people’s demand for more reliable travel, and they’ve been around for a long time.” 

Without those changes, Tabarrok predicts the U.S. will be locked into a cycle where every summer thunderstorm or mechanical hiccup crashes airports and wastes millions of hours of Americans’ lives.

“If you just do some rough estimation of the value of people’s time, multiplied by how much time they’re spending waiting around in airports or waiting around for delays, you can easily get billions of dollars lost every year.” Tabarrok said. “And that cost will keep growing.”



Source link

Continue Reading

Business

Fortune Brainstorm AI San Francisco starts today, with Databricks, OpenAI, Cursor, and more on deck

Published

on



It’s been a crazy few weeks in AI.

Granted, it feels like it’s always been a crazy few weeks in AI. But this cycle has been especially notable: Reports that Sam Altman has declared a “code red” around improving ChatGPT have made waves, while Databricks is reportedly in talks to raise at a jaw-dropping $134 billion valuation. Anthropic is reportedly looking at a real-life IPO, and everyone’s always watching for news from perhaps the biggest ascent of the year: Cursor, the AI coding juggernaut that’s now valued at more than $29 billion. 

And today, Brainstorm AI starts, and so many of these key players will be with us live in San Francisco, including Databricks CEO Ali Ghodsi, OpenAI COO Brad Lightcap, Cursor CEO Michael Truell, San Francisco Mayor Daniel Lurie, Google Cloud CEO Thomas Kurian, and Rivian CEO RJ Scaringe, plus some starpower from Joseph Gordon-Levitt and Natasha Lyonne. 

If you’re attending the conference, come find me! I’ll realistically be the one running around in a bright pantsuit. And if you can’t make it, we’ll be livestreaming the show, too – tune in here.

See you soon,

See you tomorrow,

Allie Garfinkle
X:
@agarfinks
Email:alexandra.garfinkle@fortune.com
Submit a deal for the Term Sheet newsletter here.

Joey Abrams curated the deals section of today’s newsletter.Subscribe here.

Venture Deals

Antithesis, a Tysons Corner, Va.-based platform designed to validate that software works before it launches, raised $105 million in Series A funding. JaneStreet led the round and was joined by AmplifyVenturePartners, SparkCapital, and others.

ParadigmHealth, a Columbus, Ohio-based clinical research platform, raised $78 million in Series B funding. ARCHVenturePartners led the round and was joined by DFJGrowth and existing investors.

Oxzo, a Santiago, Chile-based provider of oxygenation services for aquaculture, raised $25 million in funding from S2GInvestments.

Quanta, a San Francisco-based accounting platform, raised $15 million in Series A funding. Accel led the round and was joined by OperatorCollective, NavalRavikant, DesignerFund, and others.

LizzyAI, a New York City-based AI-powered talent interviewing company, raised $5 million in seed funding. NEA led the round and was joined by Speedinvest and ZeroPrimeVentures

PvX, a Singapore-based provider of user-acquisition financing for gaming companies, raised $4.7 million in a seed extension from Z Venture Capital, DrivebyDraftKings, and existing investors.

Corma, a Paris, France-based developer of a copilot for AI teams, raised €3.5 million ($4.1 million) in seed funding. XTXVentures led the round and was joined by TuesdayCapital, KimaVentures, 50Partners, OlympeCapital, and angel investors.

Private Equity

NITEOProducts, a portfolio company of HighlanderPartners, acquired Folexport, a Tualatin, Ore.-based manufacturer of carpet, fabric, and hard surface cleaning products. Financial terms were not disclosed.



Source link

Continue Reading

Business

Why the worst leaders sometimes rise the fastest

Published

on



History is crowded with CEOs who have flamed out in very public ways. Yet when the reckoning arrives, the same question often lingers: How did this person keep getting promoted? In corporate America, the phenomenon is known as “failing up,” the steady rise of executives whose performance rarely matches their trajectory. Organizational psychologists say it’s not an anomaly. It’s a feature of how many companies evaluate leadership.

At the core is a well-documented bias toward confidence over competence. Studies consistently show that people who speak decisively, project certainty, and take credit for wins—whether earned or not—are more likely to be perceived as leadership material. In ambiguous environments, boards and senior managers often mistake boldness for ability. As long as a leader can narrate failure convincingly—blaming market headwinds, legacy systems, or uncooperative teams—their upward momentum may continue.

Another driver is asymmetric accountability. Senior executives typically oversee vast, complex systems where outcomes are hard to tie directly to individual decisions. When results are good, credit flows upward. When results are bad, blame diffuses downward, and middle managers, project leads, and market conditions become convenient shock absorbers. This allows underperforming leaders to survive long enough to secure their next promotion.

Then there’s the mobility illusion. In many industries, frequent job changes are read as ambition and momentum rather than warning signs. An executive who leaves after short, uneven tenures can reframe each exit as a “growth opportunity” or a strategic pivot. Recruiters and boards, under pressure to fill top roles quickly, often rely on résumé signals, like brand-name firms, inflated titles, and elite networks, rather than deep performance audits.

Ironically, early visibility can also accelerate failure upward. High-profile roles magnify both success and failure, but they also increase name recognition. An executive who runs a troubled division at a global firm may preside over mediocre results, yet emerge with a reputation as a “big-company leader,” making them attractive for a CEO role elsewhere.

The reckoning usually comes only at the top. As CEO, the buffers disappear. There is no one left to blame, and performance is judged in the blunt language of earnings, stock price, profitability, or layoffs. The traits that once fueled ascent, such as overconfidence, risk-shifting, and narrative control, become liabilities under full scrutiny.

The central lesson for aspiring CEOs is that the very system that rewards confidence, visibility, and narrative control on the way up often masks weak execution until the top job strips those protections away. Future leaders who want to avoid “failing upward” must deliberately build careers grounded in verifiable results and direct ownership of outcomes because at the CEO level, there is no narrative strong enough to substitute for performance.

Ruth Umoh
ruth.umoh@fortune.com

Smarter in seconds

Big biz buy-in. Anthropic is all in on ‘AI safety’—and that’s helping the $183 billion startup win over big business

Old guard upgrade. How the bank founded by Alexander Hamilton is transforming for the future of finance

Pressure test. Inside the Fortune 500 CEO pressure cooker: surviving is harder than ever and requires an ‘odd combination’ of traits

Rank racing. The one-upmanship driving CEOs

Leadership lesson

Anthropic’s Dario Amodei on when a startup gets too big to know all employees: “It’s an inevitable part of growth.”

News to know

Investors are questioning OpenAI’s profitability amid its massive spending while increasingly viewing Alphabet as the deeper-pocketed winner in the AI race. Fortune

Trump warned that Netflix’s $72 billion bid for Warner Bros. Discovery could face antitrust scrutiny, suggesting it would create an overly dominant force in streaming. Fortune

An etiquette camp is trying to help Silicon Valley shed its sloppy image by teaching tech elites how to dress and behave as their influence grows. WaPo

IBM is reportedly in advanced talks to buy data-infrastructure firm Confluent for about $11 billion, bolstering its AI data capabilities. WSJ

Even as women reach top roles in politics and business at record levels, public confidence in their leadership is stagnating or declining. Bloomberg

Terence “Bud” Crawford, the undefeated 38-year-old boxing champion, has earned more than $100 million and even turned Warren Buffett into a fan. Forbes

Big Tech leaders now warn that artificial intelligence is advancing to the point where it could begin replacing even CEOs, reshaping the very top of corporate leadership. WSJ

This is the web version of the Fortune Next to Lead newsletter, which offers strategies on how to make it to the corner office. Sign up for free.



Source link

Continue Reading

Business

The workforce is becoming AI-native. Leadership has to evolve

Published

on



One of the most insightful conversations I have had recently about artificial intelligence was not with policymakers or peers. It was with a group of Nokia early-careers talents in their early 20s. What stood out was their impatience. They wanted to move faster in using AI to strengthen their innovation capabilities. 

That makes perfect sense. This generation began university when ChatGPT launched in 2022. They now account for roughly half of all ChatGPT usage, applying it to everything from research to better decision-making in knowledge-intensive work. 

Some people worry that AI-driven hiring slowdowns are disproportionately impacting younger workers. Yet the greater opportunity lies in a new generation of AI-native professionals entering the workforce equipped for how technology is transforming roles, teams, and leadership.

Better human connectivity 

One of the first tangible benefits of generative AI is that it allows individual contributors to take on tasks once handled by managers. Research by Harvard Business School found that access to Copilot increased employee productivity by 5% in core tasks. As productivity rises and hierarchies flatten, early-career employees using AI are empowered to focus on outcomes, learn faster, and contribute at a higher level.

Yet personal productivity is not the real measure of progress. What matters most is how well teams perform together. Individual AI gains only create business impact when they align with team goals and that requires greater transparency, alignment, and accountability.

At Nokia, we ensure that everyone has clear, measurable goals that support their teams’ objectives. Leaders need to be open about their goals to their managers and to their reports. And everyone means everyone. Me included. That way goals are not only about recognition and reward. They become an ongoing dialogue between leaders and their teams. It’s how we’re building a continuous learning culture that thrives on feedback and agility, both essential in the AI era. 

Humans empowered with AI, not humans versus AI

AI’s true power lies in augmenting human skills. Every role has a core purpose – whether in strategy, creativity, or technical problem-solving – and AI helps people focus on that. 

During the COVID-19 pandemic, more than 60 chatbots were deployed in 30 countries to handle routine public health queries, freeing up healthcare workers to focus on critical patient care. Most health services never looked back. 

The same pattern applies inside companies. Some of the routine tasks given to new hires are drudge work and not a learning experience. AI gives us a chance to rethink the onboarding, training, and career development process.

Take an early-career engineer. Onboarding can be a slow process of documentation and waiting for reviews. AI can act as an always-on coach that gives quick guidance and helps people ramp up. Mentors then spend less time on the basics and more time helping engineers solve real problems. Engineers can also have smart agents testing their designs, ideas, and simulating potential outcomes. In this way, AI strengthens, rather than substitutes, the human connection between junior engineers and their mentors and helps unlock potential faster.

Encourage experimentation and entrepreneurship 

During two decades of the Internet Supercycle (1998-2018), start-ups created trillions of dollars in economic value and roughly half of all new jobs in OECD countries

As AI lowers the barriers to launching and scaling ventures, established companies must find new ways to encourage experimentation, nurture innovation through rapid iterations, and give employees the chance to commercialize and scale their ideas.

There is a generational shift that increases the urgency: more than 60% of Gen Z Europeans hope to start their own businesses within five years, according to one survey. To secure this talent, large organizations must provide the attributes that make entrepreneurship attractive. Empowering people with agility, autonomy, and faster decision-making creates an edge in attracting and keeping top talent.

At Nokia, our Technology and AI Organization is designed to strengthen innovation capabilities, encourage entrepreneurial thinking, and give teams the support to turn ideas into real outcomes.

More coaching, less managing 

Sporting analogies are often overused in business as the two worlds don’t perfectly align, yet the evolution of leadership in elite football offers useful lessons. Traditionally, managers oversaw everything on and off the pitch. Today, head coaches focus on building the right team and culture to win. 

Luis Enrique, the manager of Paris-St. Germain football club, last season’s UEFA Champion’s League winner, exemplifies this shift. He transformed a team of stars into a star team, while also evolving his coaching style, elevating both individual and collective potential.

Of course, CEOs must switch between both roles (as I said, the worlds don’t perfectly align) – setting vision and strategy while also cultivating the right team and culture to succeed. AI can help leaders do both with more focus. It gives us quicker insight into what is working, what is not, and where teams need support.

I have been testing these tools with my own leadership team. We are using generative AI to help us evaluate our decisions and to understand how we work together. It has revealed patterns we might have missed, and it has helped us get to the real issues faster. It does not replace judgment or experience. It supports them.

Yet the core of leadership does not change. AI cannot build trust. It cannot set expectations. It cannot create a culture that learns, improves, and takes responsibility. That still comes from people. And in a world shaped by AI, the leaders who succeed will be the ones who coach, who listen, and who help teams move faster with confidence.

Nokia’s technology connects intelligence around the world. Inside the company, connecting intelligence is about how people work together. It means giving teams the tools, support and culture they need to grow and perform with confidence. Connecting intelligence is how teams win.

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.



Source link

Continue Reading

Trending

Copyright © Miami Select.