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Change management is a multibillion-dollar industry built on the fundamental claim that most people dislike change, and that someone needs to manage that resistance. But after decades of organizational theories and billions in consulting fees, the industry does not work as promised: change management projects have a failure rate of around 70%. Theres a reason no one asked McKinsey or any other leading consulting firm to run DOGE. As enterprises large and small grapple with the wholesale transformation that will be wrought by the rise of artificial intelligence, its time to face an uncomfortable truth: Change, especially today, doesn’t happen in neat phases. It’s cyclical, unpredictable, and requires constant adaptation. The Old Model Never WorkedBut It Especially Doesnt Now Traditional change management follows a predictable model. Under investor scrutinyor to avoid itthe CEO announces a transformation is coming. Consultants conduct surveys, present slides at workshops, and create communication plans to deal with signs of revolt. Success gets measured by stakeholder-focused metrics like adoption rates, and KPIs like number of training programs deployed. It’s an industry that prioritizes rationality at the expense of inspiration and serendipity. AI will be the force that kills this episodic approach. First, the tech is already moving too quickly for rigid approaches to be relevant. Second,AI requires significant amounts of training and customization to be effective in most organizations, rendering a one-size-fits-most approach obsolete. And finally, the human side of AI-driven change is more complicated than a standard reorganizationbecause AI anxiety strikes at the heart of what is human, and what sort of careers we and our children will have. A Tale of Two Companies In our recent work inside companies that are adopting new AI tools and workflows, weve seen the potential for a new way of working. Instead of a traditional change management approach, smart leaders today are understandingand embracingthat change in the era of AI is often organically driven by shifts brought about by AI eureka moments. Competitive advantage is built not by how quickly you move humans through a change program, but how seamlessly your organizations source codethe unique combination of people, process, and technologyrewrites itself in real time. A Tale of Two Companies Consider a recent tale of two companies. First, fintech company Klarnas recent initiative to automate its customer service operations using generative AI. The company publicly claimed that its AI tools were performing the work of 700 full-time agents, leading to a dramatic reduction in hiring and headcount. The rollout was managed through a centralized, top-down approach: executive-led messaging, internal dashboards to track AI performance, and a focus on cost savings and productivity metrics. But the transition sparked internal unease and external criticism, and Klarna quietly began rehiring human agents within the year. The AI may have delivered efficiency on paper, but the rigid implementation and lack of human-centered change management eroded trust, both inside and outside the company. Contrast that with one of our clientsa multinational pharmaceutical organization that took a radically different approach. Rather than relying on static KPIs and sequential rollouts, they used using AI to surface real-time insights from employee sentiment, social media behavior, and internal feedback loops. These insights continue to inform tailored interventions across roles and geographies. AI-powered chatbots enable employees to access personalized resources on demand, while leaders use behavioral analytics to trigger timely nudges and adapt strategies instantly. The result has been a more agile, inclusive transformationwhere change has been continuously shaped by how employees are actually working. How Organizations Can Stay Ahead In this new world, best practice changes from week to week. But the most important trends we see in recent, successful transformations are: First, build a nonlinear approach. When it comes to generative and agentic AI, you often dont know your best use cases until you experiment. Embrace the 3-D problem solving that comes with transformation by moving to organized but flexible processes that account for two-way feedback. Second, create pilots. Understand that new processes, technologies, and workflows will work differently for each organization and team. Select specific organizational areas for focused experimentation and training. Give them deadlines and establish feedback loops between pilot participants and the transformation team. Then, scale successful approaches across the organization using champions as advocates for the technology and its impact. Third, work to understand and activate teams with precision. Identify specific employee categories to play a role in championing change. Every organization has a group of early adoptersthe weekend warriors who explore AI on their own time. And every organization also has laggardsthose who will require structured protocols and personalized training plans to implement new systems. Focus your communicationsand your expectationsby identifying each group and understanding the different needs it requires. Finally, empower leaders. Measure success not by who attended the meeting or did the training, but by whos actually creating new pathways in process or technology. Encourage those leaders, from the CEO down, to show how they use AI tools, and arm with appropriate nudges for staff. According to the Boston Consulting Group, the small minority of companies already operating at this level are realizing 1.5× revenue growth, 1.6× shareholder returns, and 1.4× ROI. The goal is improving organizational metabolism so your organization stays healthy, instead of contracting a disease that needs treatment. The business model for change management consulting may shift to something far more organic: Enabling leaders to role model and guide, designing teams built for experimentation and imbuing organizational culture with a growth mindset. Adaptability counts most Corporate America rewards risk-taking and stories about explosive growth, rapid innovation, and bottom-line-enhancing layofs. But it’s adaptability that will count most in the AI era, and continuous improvement is what will deliver it. Organizations that continue to rely on traditional change management consultancies are not just wasting moneythey’re actively handicapping their ability to compete in an increasingly dynamic business environment.Consultants can either changethe irony!or go down with their ship.
Category:
E-Commerce
Labubu, the bug-eyed elves from Beijing, might just be the unlikeliest face of global brand disruption. But the viral figurines, sold in blind boxes across Asia, Europe, and the Americas, are helping rewrite the rules of consumer engagement and revealing what the future of global brands might look like. Their success isnt really about toys; its about building a new kind of consumer community. Pop Mart, the brand behind Labubu, has built a business on orchestrating demand, emotion, and engagement at scale. In the first half of 2024, the company posted RMB 6.65 billion in revenue (roughly $920 million), tripled its profits year-on-year, and reached a $40 billion market capitalization, more than double that of U.S. toy giants Hasbro and Mattel combined. It recently told investors to expect a 350% year-on-year profit surge for the first half of 2025. What makes Labubu exceptional is that it represents one of Chinas first truly organic cultural exports. Its a phenomenon driven by its community of fans, rather than top-down orchestration. A TikTok moment Born from the imagination of Hong Kong-based illustrator Kasing Lung, the ugly-cute dolls were catapulted into the spotlight after Blackpinks Lisa was spotted carrying a plush version. That moment triggered a viral TikTok surge and helped drive a 726.6% increase in Labubu-related revenue, now accounting for 25% of Pop Marts total. What were seeing isnt a one-off success, its a structural shift in how cultural IP is created, scaled, and consumed globally. Chinese consumer innovation is entering a new phase, moving from platforms and hardware to emotionally resonant, creator-led IP. These fandom-driven communities bypass traditional media gatekeepers entirely. Other Chinese firms are accelerating this shift. Xiaomi, Miniso, and Heytea are part of a new generation of brands not competing on price or scale, but by building fan communities, embedding emotion, and turning cultural resonance into business strategy. The orchestration of desire Labubus rise is no accident. Sold in blind boxessealed packaging that hides the variant insideits more than clever merchandising. Its behavioral design. The randomized reward system mirrors gaming mechanics, tapping into dopamine loops and repeat engagement. Over 1.7 million TikTok videos tagged #Labubu feature unboxings. Limited editions, like the Rainbow Labubu, have fetched over $150,000 at auction. Instead of relying on loyalty programs or sales funnels, the brand creates micro-moments of surprise that make shopping feel like play. Its 66.8% gross margin reflects not just operational efficiency, but emotional value. The retail strategyvending machines, roboshops, and immersive flagshipsis designed for experience, not efficiency. In New York, teens queue outside Pop Marts SoHo flagship not to shop, but to swap figurines, livestream unboxings, or hunt for rare Labubu variantsmimicking sneaker culture. From product to platform This emotional engagement mirrors moves by other Chinese innovators. Xiaomi, once a low-cost smartphone player, has evolved into a lifestyle platform spanning wearables, TVs, EVs, and smart home devices. Its loyal Mi Fan community is central to its success by participating in product development. This two-way relationship cuts marketing costs and builds loyalty. Online forums, feedback channels, and fan events make Xiaomi feel less like a company and more like a community. Miniso, too, has leaned into aesthetic curation and scarcity. Its co-branded collections with Sanrio, Marvel, and Coca-Cola go viral on social platforms, while its treasure-hunt store layout fuels impulse discovery. Despite affordable price points, it achieves performance that rivals luxury retailersproving emotional design can scale. At the center of this shift is aesthetic fluency. Pop Marts roboshops now span 25 countries, including the U.S., France, and Australia. Flagship stores in New York and Los Angeles draw Gen Z crowds reminiscent of Supreme drops. The design of Labubuquirky, ironic, expressivetaps directly into Gen Zs appetite for memeable, imperfect symbols of self-expression. This isnt imitation. China is exporting design-native communities that speak to youth culture through visual language. Monetizing emotion at scale Chinese brands are also redefining how emotion scales. While legacy Western players rely on storytelling and identity marketing, their Chinese counterparts are building infrastructure for emotional engagement. Heytea treats each product launchwhether a limited-edition cheese tea or a regional collaborationas an event, amplified through influencers, teaser campaigns, and fan buzz. Its minimalist, Instagrammable stores are designed for social interaction, turning queues into part of the experience. Co-branded drops with luxury names like Fendi and seasonal exclusives fuel emotional attachment. This isnt just clever marketingits a system that turns a beverage into a lifestyle, and a brand into a community. That same emotional infrastructure powers Labubus rise into fandom. Rare figurines flip for 5 to 30 times their retail value on Xianyu, Alibabas resale platform, some with blockchain verification. Police raids on counterfeit Lafufu dolls signal Labubus ascent to luxury-like status, making it a new asset class: IP with emotional and economic value, validated in real time. What Western brands can learn Some Western executives may dismiss blind boxes and roboshops as quirky or culturally niche. But under the surface lies a global truth: Consumers crave emotion, novelty, and community. Labubus rise shows how brands can scale through visual culture that travels without translation. No slogan, no storyline, just design. It spreads like a physical meme, interpreted across cultures from Seoul to Paris. The core question is no longer Whats the story? Its Whats the emotion were scaling? Chinese brands are showing that strategy today is built from small, orchestrated moments that add up to immersive communities. Theyre blurring the lines between product and platform, commerce and culture. The old playbookposition, promote, pushwas built for mass marketing and one-way messaging. Todays leading brands thrive on feedback loops, cocreation, and community-driven agility. The next wave of global brands? Its tempting to view Pop Mart as a regional curiosity. That would be a mistake. Labubu may look like a viral toy, but its also a case study in how design, emotion, and communities converge into strategic advantage. What ties these brands together is not just design or digital presenceits the way they build and sustain fan communities. Labubu isnt a preview, its proof. And for global brands still running on legacy logic, its time to catch up.
Category:
E-Commerce
Its summer, and its been hot, even in northern cities such as Boston. But not everyone is hit with the heat in the same way, even within the same neighborhood. Take two streets in Boston at 4:30 p.m. on a recent day, as an example. Standing in the sun on Lewis Place, the temperature was 94 degrees Fahrenheit (34.6 degrees Celsius). On Dudley Common, it was 103 F. Both streets were hot, but the temperature on one was much more dangerous for peoples health and well-being. The kicker is that those two streets are only a few blocks apart. The difference epitomizes the urban heat island effect, created as pavement and buildings absorb and trap heat, making some parts of the city hotter. A closer look at the two streets shows some key differences: Dudley Common is public open space sandwiched between two thoroughfares that create a wide expanse of pavement lined with storefronts. There arent many trees to be found. Lewis Place is a residential cul-de-sac with two-story homes accompanied by lots of trees. This comparison of two places within a few minutes walk of each other puts the urban heat island effect under a microscope. It also shows the limits of todays strategies for managing and responding to heat and its effects on public health, which are generally attuned to neighborhood or citywide conditions. Even within the same neighborhood, some places are much hotter than others owing to their design and infrastructure. You could think of these as urban heat islets in the broader landscape of a community. Sensing urban heat islets Emerging technologies are making it easier to find urban heat islets, opening the door to new strategies for improving health in our communities. While the idea of reducing heat across an entire city or neighborhood is daunting, targeting specific blocks that need assistance the most can be faster and a much more efficient use of resources. Doing that starts with making urban heat islets visible. In Boston, Im part of a team that has installed more than three dozen sensors across the Roxbury neighborhood to measure temperature every minute for a better picture of the communitys heat risks, and were in the process of installing 25 more. The Common SENSES project is a collaboration of community-based organizations, including the Dudley Street Neighborhood Initiative and Project Right Inc.; university researchers like me who are affiliated with Northeastern Universitys Boston Area Research Initiative; and Boston city officials. It was created to pursue data-driven, community-led solutions for improving the local environment. Data from those sensors generate a real-time map of the conditions in the neighborhood, from urban heat islets like Dudley Common to cooler urban oases, such as Lewis Place. These technologies are becoming increasingly affordable and are being deployed in communities around the world to pinpoint heat risks, including Miami, Baltimore, Singapore, and Barcelona. There are also alternatives when long-term installations prove too expensive, such as the U.S.s National Oceanic and Atmospheric Administration volunteer science campaign, which has used mobile sensors to generate onetime heat maps for more than 50 cities. Making cooler communities, block by block Although detailed knowledge of urban heat islets is becoming more available, we have barely scratched the surface of how they can be used to enhance peoples health and well-being. The sources of urban heat islets are rooted in developmentmore buildings, more pavement, and fewer trees result in hotter spaces. Many projects using community-based sensors aspire to use the data to counteract these effects by identifying places where it would be most helpful to plant trees for shade or install cool roofs or cool pavement that reflect the heat. However, these current efforts do not fully capitalize on the precision of sensors. For example, Los Angeless massive investment in cool pavement has focused on the city broadly rather than overheated neighborhoods. New York Citys tree planting efforts in some areas failed to anticipate where trees could be successfully planted. Most other efforts compare neighborhood to neighborhood, as if every street within a neighborhood experiences the same temperature. London, for example, uses satellite data to locate heat islands, but the resolution isnt precise enough to see differences block by block. In contrast, data pinpointing the highest-risk areas enables urban planners to strategically place small pocket parks, cool roofs, and street trees to help cool the hottest spaces. Cities could incentivize or require developers to incorporate greenery into their plans to mitigate existing urban heat islets or prevent new ones. These targeted interventions are cost-effective and have the greatest potential to help the most people. But this could go further by using the data to create more sophisticated alert systems. For example, the National Weather Services Boston office released a heat advisory for July 25, 2025, the day I measured the heat in Dudley Common and Lewis Place, but the advisory showed nearly the entirety of the state of Massachusetts at the same warning level. What if warnings were more locally precise? On certain days, some streets cross a crucial thresholdsay, 90 Fwhereas others do not. Sensor data capturing these hyperlocal variations could be communicated directly to residents or through local organizations. Advisories could share maps of the hottest streets r suggest cool paths through neighborhoods. There is increasing evidence of urban heat islets in many urban communities and even suburban ones. With data showing these hyperlocal risks, policymakers and project coordinators can collaborate with communities to help address areas that many community members know from experience tend to be much hotter than surrounding areas in summer. As one of my colleagues, Nicole Flynt of Project Right Inc., likes to say, Data + Stories = Truth. If communities act upon both the temperature data and the stories their residents share, they can help their residents keep coolbecause its hot out there. Dan O’Brien is a professor of public policy and urban affairs and director of the Boston Area Research Initiative at Northeastern University. This article is republished from The Conversation under a Creative Commons license. Read the original article.
Category:
E-Commerce
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