When you have your customer’s confidence, the opportunity to create an excellent customer experience dramatically improves. That confidence comes from consistency. The customer knows what to expect, even if any problems or issues arise. They know you’ll take care of them.
This is a follow-up to my article that covered the Customer Service Recovery Paradox, in which a customer’s perception of the company is higher after a problem or complaint is resolved than if the problem had never happened at all. One of our subscribers, Sean Crichton-Browne of Market Culture, shared a great comment. The short version is that when you have the customer’s confidence, especially in potentially tenuous situations, customers work with you rather than against you.
Sean’s insight is spot-on and worth diving into further. Think about the last time you had a problem with a company you trusted versus one that you didn’t. By the way, that lack of trust could be because you haven’t yet experienced how they handle a problem, not because of any inconsistencies or problems in the past. With the trusted company, you most likely approached the conversation differently. You were more patient as you explained the situation, and you were more open to their suggestions and solutions.
Contrast that with a company you don’t yet trust. You go into the conversation with your guard up, wondering if you’ll get the response and answers you hope for. You may even be prepared to fight for what you believe is right.
When customers trust you, they:
Give you the benefit of the doubt when mistakes happen.
Share more information about what went wrong, making it easier to fix.
Accept reasonable solutions rather than demanding unrealistic ones.
Remain calm and respectful, making it much easier to help them without having to first de-escalate the customer’s anger.
As mentioned, and worth mentioning again, confidence comes from consistency. Even if the customer has only done business with you once or twice, it can be earned through all of the positive touchpoints of those interactions. Every interaction, big or small, builds confidence. Every time you answer the phone, return a call promptly, respond to email quickly, keep your promises, and more, you’re building trust. When something does go wrong, not if something goes wrong, you will have those past interactions working for you.
Yes, we need to react to complaints and problems when they happen, but remember that your ability to resolve those issues successfully may have been determined long before the problem ever occurred. It’s determined by how you treat customers and manage every interaction, the small ones and the big ones. Every touchpoint is an opportunity to build the confidence that will make future problems easier to resolve. When you have their trust, customers work with you rather than against you.
Image credits: Flickr Mary Jane, Shep Hyken
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Private Equity is Ruining Everything from Sandwiches to Pet Ownership
LAST UPDATED: January 20, 2026 at 3:59 PM
GUEST POST from Art Inteligencia
I have always maintained that innovation is a byproduct of human curiosity meeting competitive necessity. It is a biological process of sorts; a marketplace needs diversity, mutation, and the survival of the fittest ideas to stay healthy. However, we are currently witnessing a systemic threat to this ecology: the massive concentration of wealth in the hands of a dwindling few. This financial gravity is creating a “Consolidation Gravity Well” that is sucking the life out of industries, raising prices, and — most crucially — killing the very spirit of innovation, community and entrepreneurship.
When wealth is widely distributed, it acts as seed corn for a thousand different experiments. But when wealth is concentrated, it becomes a weapon of market stabilization. For those at the top, innovation is often viewed as a threat to be managed rather than an opportunity to be seized. The result is a rapid consolidation across industries — from digital platforms to healthcare to agriculture — that leaves consumers with fewer choices and higher bills.
“When wealth concentrates, the marketplace loses its heartbeat. We trade the vibrant pulse of human-centered discovery for the sterile, predictable hum of a monopoly’s balance sheet.” — Braden Kelley
The Erosion of Value for Money
The standard economic argument for consolidation is “efficiency.” Larger firms, we are told, can leverage economies of scale to lower costs. Yet, in practice, we see the opposite. When three or four firms control 80% of a market, they stop competing on value creation and start competing on extraction. Without the threat of a nimble competitor stealing their lunch, these giants engage in “shadow pricing” and “feature stripping.”
The consumer feels this as a decrease in value for money. You pay more for a subscription that offers less; you buy food that is more processed but more expensive; you use software that hasn’t seen a meaningful update in five years because there is nowhere else to go. This is a direct consequence of wealth concentration allowing incumbents to buy their way out of the need to innovate.
How Financial Gravity Sucks Wealth Upwards
Concentrated wealth creates a financial gravity that funnels massive pools of capital — from sovereign wealth funds and ultra-high-net-worth individuals — directly into private equity (PE) vehicles seeking high-return alternatives to public markets. This capital is deployed through aggressive “roll-up” or “buy-and-build” strategies, where a PE firm identifies a stable “platform” company in a fragmented industry — like plumbing, dental services, HVAC, or veterinary care — and systematically gobbles up smaller independent competitors as “bolt-on” acquisitions. By centralizing control, these firms often shift the focus from organic, empathy-driven innovation to “multiple arbitrage” and operational extraction, where value is manufactured by selling the consolidated giant at a higher valuation multiple than the individual pieces were originally purchased for. The ultimate cost is a landscape where consumer prices often spike by 7% to 20%, competition is silenced, and the marketplace loses the healthy diversity required for genuine, breakthrough human-centered innovation.
Case Study 1: The “Kill Zone” in Digital Platforms
In the technology sector, the concentration of wealth has created what venture capitalists call the “Kill Zone.” This is the space around a dominant platform (like Google, Amazon, or Meta) where any startup that shows true innovative potential is either acquired or crushed. Because these giants have nearly infinite cash reserves, they don’t have to wait to see if a startup’s idea is better. They simply buy the team and the patents, often “sunsetting” the product to protect their existing revenue streams. This has led to a stagnation in social media and search innovation, where the goal for founders is no longer to “build a great company,” but to “get bought by the monopoly.” The human-centered focus on solving user problems is replaced by the financial focus of an exit strategy.
The Innovation Debt of Oligopolies
Consolidated industries suffer from what I call Innovation Debt. Because they face no external pressure to reinvent themselves, they continue to polish old, inefficient systems while ignoring the fundamental shifts in human needs. They become brittle. When a shock hits the system—be it a pandemic or a supply chain crisis—these consolidated giants often fail to adapt because they have spent decades optimizing for profit extraction rather than resilient innovation.
Case Study 2: The Consolidation of American Meatpacking
In the mid-20th century, the meatpacking industry was relatively diverse. Today, just four companies control the vast majority of the market. This concentration of wealth and power has allowed these firms to keep prices high for consumers while keeping payments to farmers low. From an innovation standpoint, the industry has stagnated. Instead of investing in more sustainable, humane, or efficient farming practices, the focus has been on process consolidation and political lobbying to prevent regulation. When the supply chain was tested recently, the lack of innovative, decentralized alternatives led to massive price spikes and shortages. The lack of competition meant there was no “Plan B” being developed by a smaller, hungrier innovator.
Case Study 3: Consumer Goods and Shrinkflation Innovation
In consumer packaged goods, consolidation has produced a different form of innovation failure. Fewer parent companies control hundreds of brands. Price increases are disguised through shrinkflation, packaging changes, and marketing narratives.
Instead of innovating on nutrition, sustainability, or affordability, companies innovate on perception management. Value erodes while margins grow.
This is not innovation in service of humans—it is innovation in service of financial engineering.
Case Study 4: How Private Equity is Redefining the Price of Pet Companionship
For decades, the local veterinarian was a staple of the community—an independent practitioner who knew your dog’s name and your family’s budget. Today, that landscape has been fundamentally reshaped. As of early 2026, private equity firms and megacorporations control approximately 50% of all veterinary clinics in the United States, a staggering leap from just 10% a decade ago. This aggressive “roll-up” strategy is not just changing who signs the paychecks; it is systematically altering the economics of pet ownership, pushing life-saving care and insurance out of reach for many families.
The private equity playbook is simple: acquire independent clinics, centralize administrative functions, and implement standardized, profit-maximizing medical protocols. While proponents argue this brings professional management and better technology, the data suggests a different reality for “pet parents.”
“We are witnessing the financialization of empathy. When a clinic’s primary metric shifts from ‘patient outcome’ to ‘EBITDA multiple,’ the price of a pet’s life becomes a line item that many middle-class families simply can no longer afford.”
Case Study 5: The Industrialized Home
In a world of accelerating change, we often focus on digital transformation, but one of the most significant shifts is happening behind the walls of our homes. The plumbing and HVAC sectors, historically dominated by local family businesses, are currently undergoing a massive private equity roll-up. This financialization is fundamentally decoupling the “service” from the “provider,” leading to an environment where the objective is no longer the longevity of the machine, but the maximization of the average service ticket.
“When a technician is carrying a sales quota instead of a toolbox, the pride of an effective and reasonably priced repair dies. We are trading the resilience of our home infrastructure for the sterile efficiency of a private equity exit strategy.”
— Braden Kelley
The “Roll-Up” Reality: Sales over Service
By early 2026, it is estimated that nearly 40% of residential service revenue in major U.S. metropolitan areas is captured by private equity-backed platforms. These firms utilize a “platform and bolt-on” strategy: they buy a large, reputable local company and then acquire smaller competitors to “bolt on” to the operation. While the name on the truck remains the same to preserve generational trust, the internal culture is replaced by high-pressure sales training.
Mini-Case 1: The Wrench Group and the Pricing Surge
The Wrench Group, backed by Leonard Green & Partners, has become a dominant force in the trades. By consolidating major brands like Abacus and Coolray, they have built a multi-billion dollar platform. In many markets where Wrench or similar entities have taken over, homeowners have reported that a standard “capacitor fix” (a $20 part) that used to cost $150 now frequently results in a $15,000 quote for a full system replacement. This shift effectively raises the barrier to home maintenance, making homeownership increasingly unattainable for the middle class as “repairability” is phased out in favor of “replacement cycles.”
Mini-Case 2: TurnPoint Services and the “Membership” Trap
TurnPoint Services, supported by OMERS Private Equity, has rapidly acquired dozens of local plumbing and electrical brands. A core part of their “innovation” is the aggressive push for proprietary membership programs. While marketed as preventative maintenance, these programs are often designed as lead-generation engines. Technicians are trained to find “critical failures” during routine check-ups, using the membership as a hook to keep the homeowner within the corporate ecosystem. This decreases value for money by forcing consumers into a subscription model for services that were historically transactional and transparent.
The Negative Impact on Innovation
This consolidation has a chilling effect on true innovation. Instead of developing more durable HVAC components or more efficient plumbing diagnostics, “innovation” in the sector is now focused on financing algorithms and sales psychology. When the market is controlled by a few giants whose goal is to sell the company in 3 to 5 years, there is no incentive to invest in 20-year solutions. The result is an Innovation Debt that the homeowner pays through premature system failure and inflated insurance premiums driven by the rising cost of emergency repairs.
The Human Cost of Consolidation
From a human-centered perspective, consolidation produces predictable harms:
Customers pay more for less value
Workers face fewer employers and weaker bargaining power
Entrepreneurs encounter higher barriers to entry
Society loses resilience and adaptability
Innovation ecosystems require tension. Consolidated systems eliminate it.
Rebuilding Conditions for Real Innovation
Restoring innovation is not about punishing success—it is about restoring balance. Healthy systems reward value creation, not value extraction.
That requires:
Modernized antitrust frameworks
Capital access beyond elite networks
Open, interoperable platforms
Human-centered success metrics
Innovation flourishes when power is distributed, competition is real, and human needs—not financial optimization—define progress.
The Path Forward: Human-Centered Systems
If we want to reignite the engine of innovation, we must address the wealth concentration that enables this consolidation. We need policies that protect the “biodiversity” of our markets. Innovation thrives when the barriers to entry are low and the rewards for genuine value creation are high. An innovation speaker like Braden Kelley might tell a boardroom, “Growth is not a zero-sum game of acquisition; it is a generative process of empathy-driven creation.”
We must shift our focus back to the human. When we design markets that prioritize the few, we lose the genius of the many. It is time to climb out of the consolidation gravity well and build an economy that rewards those who dare to build something new, rather than those who simply have the deepest pockets to buy what already exists.
Frequently Asked Questions
How does wealth concentration lead to industry consolidation?
When massive amounts of capital are concentrated in the hands of a few entities or individuals, those players possess the “financial gravity” to acquire competitors, build insurmountable barriers to entry, and buy out emerging startups before they can challenge the status quo.
Why does consolidation decrease innovation?
Innovation requires biological diversity in the marketplace. When an industry consolidates into a duopoly or oligopoly, the remaining players lose the incentive to take risks on breakthrough ideas, shifting instead to rent-seeking.
What is the “Innovation Tax” on consumers?
It is the combination of rising prices and declining value for money that occurs when competition vanishes. Consumers pay more for stagnant products because they have no alternative.
Postscript
Do yourself a favor and avoid private equity owned sandwich chains like Subway, Jimmy John’s, Arby’s, Panera Bread and Jersey Mike’s Subs that have jacked up prices while simultaneously downsizing portions and replacing ingredients with lower quality alternatives. I now routinely go to grocery stores and get a higher quality sandwich at a lower price.
Disclaimer: This article speculates on the potential future direction of society based on current factors. It is hard to predict whether commercial, political and charitable organizations will respond in ways sufficient to alter the course of history or not.
Image credits: Grok, Gemini
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Personalization was one of the leading rationales for companies investing in digitalization. The idea was that you were going to delight your customers by proactively offering them goods and services they were predisposed to want. This would create customer loyalty, increase their lifetime value, spur word-of-mouth endorsement, drive up Net Promoter Scores (NPS), and solve world hunger.
OK, not so much. A decade or more in, it’s time we ask ourselves, what is the real value of personalization, and how should we allocate our future investments in it? This begins with getting ourselves onto the right playing field in the first place. Personalization has different dynamics depending on whether your enterprise is Business to Consumer (B2C), Business to Business (B2B), B2B2C or B2G2C. Here’s how it plays out.
B2C
Let’s face it — as consumers, we are tired of personalization in its current form. It isn’t really personal, it is just an unending barrage of re-targeted advertising that works statistically but not psychologically. Despite all its promises to the contrary, it is not in fact delightful. So, best to take all that language about delighting our customers and throw it in the trashcan.
Instead of looking for delighters, we should be examining our hygiene factors. These are the things that annoy customers most when they go awry — late shipping, lost luggage, long hold times, rejected passwords, tedious surveys — you name it. Getting hygiene right is hard, but doing so consistently drives brand loyalty through the roof — just ask Amazon. We love what they do so much we subscribe to them! The point is, the things we love are not personal, they are institutional. Amazon has invested enormously in systems that set expectations through timely communication, early anomaly detection, instant alerts, and the like. This is not marketing, it’s logistics, but it is personally delivered, and we feel empowered in a highly differentiated way. (BTW, note to Amazon — you are increasingly over-monetizing your landing pages with sponsored ads, thereby eroding your most valuable asset. You need to set limits and stick to them.)
B2B2C
Rethinking personalization creates a whole new wave of innovation for B2B2C companies to pursue. Instead of optimizing for clicks, help your customers better detect signals. To be fair, some of these could be buying signals, and they should be used to drive consumer traffic along existing lines. But machine learning is also extremely effective at monitoring hygiene factors wherever there is log data to exploit. Omniture was an early pioneer in using this technology for website optimization, and now with generative AI you can let your customers’ websites ask visitors what they are interested in seeing instead of playing whack-a-mole with their best guesses.
The point is, no company is happy with their website, ever — and frankly, for good reason. They are just too hard to navigate, too much about themselves, not enough about the customers and prospects they are there to serve. By focusing on hygiene factors rather than delighters, this can be changed.
B2G2C
OK, when it comes to dealing with government services, no one is really thinking about delighters. Nightmares, on the other hand, do come to mind. Once again, it’s all about hygiene factors. The services that are being offered meet real needs. It’s the obstacles that systems and bureaucracies put in the way of citizens seeking those services that drive everyone crazy.
The fastest way to cut through this mess is to embrace the adage Time is money. The goal is to relentlessly optimize for reducing latency while at the same time reducing fraud as well. This requires the very best in ML and AI, but those resources are available today, and there are plenty of socially minded entrepreneurs who are ready to put in the hard work to make them scale. The core metric of success is time to closure, the tracking of which will be no mean feat. One consequence of its success, to be frank, would be a reduction in bureaucratic employment — not just to free up more money for social services but rather to expedite transaction processing throughout the system. My hope would be that impacted agencies could redeploy their workforces into the field where face-to-face personal interaction actually can make a powerful difference in the moment.
B2B
One question that bugs the you-know-what out of CEOs of successful global enterprises is, Why do our customers keep telling us we are hard to do business with? Of course, the answer is because they are. The real question is what can they do about it? Here are some low-hanging-fruit places to start:
Disintermediate your salespeople from replenishment transactions. Instead, empower customers to transact on their own behalf through digital self-service portals. And extend the same courtesy to partners who are acting as agents on behalf of their customers.
Attack the long tail of your SKUs. Not only do they entangle your salespeople in majoring in minors, they confuse the heck out of your customers.
Stop imposing buying risks on your customers and take them upon yourself instead by tokenizing bundles to allow for swapping out unconsumed portions and truing up on overused ones.
Invest in customer success initiatives that build relationships higher up in the customer organization, leveraging thought leadership marketing, customer health scoring, and executive sponsors focused on deep listening. Customers can tell you what they really need from you if you’ll let them.
Here as elsewhere, the goal is not to delight the customer. Customers don’t want to be delighted. They want to be served – thoughtfully, reliably, and economically. Remember, it’s not about you. It’s about them.
That’s what I think. What do you think?
Image Credit: Pexels
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Do you trust your colleagues? And does your leader trust you? This article is about how the ‘trust mechanism’ affects the ability to change and innovate in any organization.
Many experts think that trust mainly relates to expectations, or more precisely, having positive expectations of others. Still, there is no escaping the fact that trust also implies ‘risk-taking.’ This means that uncertainty is part of the deal, which then means that trust can be abused — with all the problems that follow from that.
One might say that trust as a concept loses its content when not linked to uncertainty and risk. The question, therefore, is whether you would take the chance when something is actually on the line? There are strong arguments for answering ‘yes’ to this question, as the level of trust is closely connected to an organization’s ability to innovate.
Trust as a Mechanism for Innovation
It is not controversial to claim that trust promotes innovation in an organization. But it may be a point that is often unclear and vaguely justified. To make it more explicit and concrete – these are the four ‘mechanisms’ that explain why trust matters:
Trust increases the flow and sharing of knowledge and information. We tend to share information with people we trust rather than those we don’t trust. This works both ways: We are less likely to accept information and knowledge from sources we don’t trust.
Trust promotes workflow and collaboration. Here is why: If we trust a colleague’s work, we can proceed based on what has been done. If we don’t trust what people have done, we will go back to check and verify. ‘Double work’ is both inefficient and boring.
Trust provides relief for leaders. The reason is this: If you trust a colleague, they can ‘take care of’ tasks that you are responsible for. This frees up and strengthens your own capacity as a leader. Thus, it becomes easier to prioritize other important matters that require your attention.
Trust boosts mental capacity. The reason is that low trust creates psychological strain. Tired and suspicious individuals have little energy left. Thus, it’s not easy to be creative and constructive.
Trust improves performance. Expectations are an important component of trust. A person who experiences positive expectations directed toward themselves and their work will perform better. In research, this is known as the Rosenthal effect.
Research points out that trust is a basic premise for social life. In practice, social participation simply assumes some degree of trust; thus, pure distrust is basically the same as pure madness.
Trust and Control
In general, we can say that a culture of control dampens innovation within an organization. However, it might be a little too simple to postulate that control and trust are true opposites.
In practice these two will exist in combination. Organizations do not have zero need for control over what is going on. The point is rather to be aware that there are links between the two, meaning that control measures can easily have an unfortunate effect on the organization. The introduction of a quality control system may be perceived as a sign of distrust in employees. Such a measure, introduced with good intentions, may thus become the start of a negative spiral of decreasing trust in the organization. In general, there is reason to assume that increased control in an organization will detrimentally affect the internal motivation of the employees and therefore their creativity. Thus the ‘impulse’ to commit to innovation is undermined.
Even if there is no either-or in the relationship between control and trust, there is good reason to be aware that a balance must be struck: What is the genuine need for control? Is there more control than necessary in this organization? Thus the heaviest burden of evidence should be on the control mechanism in a good organization. You should have good reasons for increasing control activities in an organization if innovation is important for the enterprise.
Trust Requires Courage
We can confidently conclude that trust is a ‘gold mine’ for a business. However, there always comes some sort of risk with it — because you can never be 100 percent certain that things will turn out well when you trust someone. Therefore, it requires a certain kind of courage if you want to get access to this gold mine. This means that building trust within an organization starts with courageous leaders. When you, as a leader, demonstrate trust in an employee, the likelihood increases that the employee will reflect it back. In this way, you contribute to gradually developing a culture of trust within your organization. The thing about trust is that it is not something that can be ‘used up’ through use; rather, the opposite is true: the more it is used, the greater it can become.
It should be added that other factors will also influence employees’ levels of trust in an organization. Research particularly highlights the experience of fairness as crucial for the development of trust among employees. More specifically, this involves respectful treatment, fair procedures, and equitable distribution of resources. If you want to build trust, it is therefore important to consider how fair things appear to the average employee. One key aspect here will be to strive for as much openness and transparency within the organization as possible.
Trust is One Piece in the Puzzle of Innovation
The question of what strengthens the ability to change and innovate in an organization has, of course, more answers than just ‘trust’. The more complete answer to the question may be outlined as an ideal organization — a ‘dream organization’ – characterized by the features shown in the following model:
This model is derived from the book How to Become a Dream Organization (Amundsen, 2025). As you can see, there are eight messages in the model: All of them start with one of the eight ‘outer’ words and are then read through to what is written in the center. This will give you sentences such as: ‘Trust promotes ability to change and innovate,’ and so on. Each of these eight themes has its own chapter (numbered in a clockwise direction from the top), thus providing the concepts in the diagram with content and reasoning. The idea is to show why and how these features have a positive impact on the ability of organizations to change and innovate.
The point with all of this is of a more practical nature: That you will be able to contribute to making the organization you work in better — for yourself and for your enterprise.
An exploration of how rising costs of living reduce cognitive surplus, suppress innovation, and limit organizational and societal progress.
LAST UPDATED: January 19, 2026 at 4:43 PM
GUEST POST from Art Inteligencia
I am frequently asked about the ingredients of a successful innovation ecosystem. We talk about venture capital, high-speed internet, patent laws, and university partnerships. But we rarely talk about the most fundamental requirement of all: human physiological and psychological security.
Innovation is not a purely intellectual exercise; it is an emotional and biological one. It requires a specific state of mind — one that is open, curious, and willing to embrace the possibility of failure. However, when a society faces systemic affordability challenges — skyrocketing rents, food insecurity, and the crushing weight of debt — we are effectively taxing the cognitive bandwidth of our greatest resource: people.
“Innovation is not a luxury of the elite, but a byproduct of a society that provides its citizens enough stability to dream. When we price people out of their basic needs, we price ourselves out of our future.” — Braden Kelley
The Cognitive Tax of Scarcity
To understand why affordability kills innovation, we must look at how the human brain functions under stress. Human-centered innovation is rooted in the idea that people solve problems when they have the mental “slack” to do so. When an individual is constantly calculating how to cover a 30% increase in rent or skipping meals to pay for childcare, they are operating in survival mode.
In survival mode, the brain’s prefrontal cortex — the center for higher-order thinking, long-term planning, and creative synthesis — takes a backseat to the amygdala. We become more reactive, more short-term focused, and significantly more risk-averse. You cannot disrupt an industry when you are terrified of an eviction notice.
This “scarcity mindset” creates a hidden drain on productivity and creativity. It is a form of Innovation Debt that we are accruing as a society, where the interest is paid in ideas that were never born because the potential innovators were too exhausted to think of them.
In organizations, this manifests as:
Employees avoiding bold ideas for fear of failure
Reduced participation in innovation programs
Higher burnout and turnover among creative talent
A preference for incrementalism over experimentation
“Innovation requires slack — slack in time, money, attention, and emotional safety. When survival becomes the primary occupation, imagination is the first casualty.” — Braden Kelley
Case Study 1: The Silicon Valley “Talent Flight”
The Situation
For decades, Silicon Valley was the undisputed epicenter of global innovation. However, by the early 2020s, the median home price in the region exceeded $1.5 million. While established tech giants could afford to pay engineers high salaries, the support ecosystem — the teachers, the artists, the junior researchers, and the “garage tinkerers” — could not.
The Innovation Impact
Innovation thrives on cross-pollination. When only the wealthy can afford to live in a hub, the diversity of thought collapses. We began to see a “homogenization of innovation,” where new startups focused almost exclusively on problems faced by high-income individuals (e.g., luxury delivery apps) rather than solving systemic human challenges. The high cost of living created a barrier to entry that effectively barred the next generation of “scrappy” innovators who didn’t have a safety net or venture backing.
The Result
Data showed a significant migration of talent to “secondary” hubs like Austin, Denver, and Lisbon. While this decentralization has benefits, the initial friction and lost momentum in the primary hub represented a massive opportunity cost for breakthrough research that requires physical proximity and intense collaboration.
The Death of the “Garage Startup”
The “garage startup” is a cherished myth in innovation circles, but it relies on a very real economic reality: the availability of low-cost, low-risk space. Hewlett-Packard, Apple, and Google all started in spaces that were relatively cheap to rent or own.
In today’s urban environments, that “low-risk space” has vanished. When every square foot of a city is optimized for maximum real estate yield, there is no room for the inefficient, messy work of early-stage experimentation. We are replacing “maker spaces” with luxury condos, and in doing so, we are dismantling the physical infrastructure of the Fail Fast philosophy. If the cost of your “lab” (your garage or basement) is $3,000 a month, you cannot afford to fail. And if you cannot afford to fail, you will never truly innovate.
Case Study 2: Food Insecurity in the Academic Pipeline
The Situation
A 2023 study of graduate students in North America revealed that nearly 30% experienced some form of food insecurity. These are the individuals tasked with the most rigorous scientific and social research — the literal “R” in R&D.
The Innovation Impact
Graduate students are the primary engine of university-led innovation. When these researchers spend their nights worrying about calorie counts instead of quantum counts, the quality of research suffers. The persistence required to push through a failed experiment is diminished when physical health is compromised.
The Result
Universities noted a decline in “high-risk, high-reward” thesis topics. Students began gravitating toward “safe” research areas with guaranteed funding or clear paths to corporate employment to pay off student loans and eat. The “Failure Budget” for these young innovators was effectively zero, leading to a stifling of the very exploratory research that historically leads to major scientific breakthroughs.
Case Study 3: A Manufacturing Firm’s Productivity Paradox
A mid-sized manufacturing company invested heavily in digital transformation and innovation training, yet saw minimal improvement in idea generation or experimentation. Leadership initially blamed culture and skills.
A deeper assessment revealed a different root cause: nearly 40 percent of the workforce was experiencing food or housing insecurity. Employees were working second jobs, skipping medical care, and managing chronic stress.
The company shifted strategy. It introduced wage stabilization, subsidized meals, and emergency financial support. Within twelve months, participation in continuous improvement programs doubled, and frontline innovation proposals increased by over 60 percent.
Innovation did not fail due to lack of tools. It failed due to lack of breathing room.
Why Affordability Shapes Risk Appetite
Innovation requires people to take risks that may not pay off immediately. But when the margin for error is razor-thin, risk becomes reckless rather than courageous.
Employees who fear eviction or medical debt are far less likely to:
Challenge entrenched assumptions
Experiment with unproven ideas
Advocate for long-term investments
Speak candidly about systemic flaws
Affordability challenges quietly turn organizations into compliance machines rather than learning systems.
Conclusion: A Call for Human-Centered Policy
If we want to maintain a competitive edge in a rapidly changing world, we must view affordability as an innovation policy. Rent control, affordable housing, student debt relief, and food security are not just “social issues”; they are the foundational layers of a healthy innovation funnel.
We need to create “slack” in our systems. We need to ensure that the next great thinker is not working three gig-economy jobs just to keep the lights on. As leaders, we must advocate for a world where people are free to use their entire brain for the work of change, rather than wasting half of it on the math of survival.
True innovation starts with a simple human truth: A mind preoccupied with where to sleep cannot dream of how to fly.
Frequently Asked Questions
Q: How do high housing costs impact an organization’s innovation potential?
A: High housing costs force talent to relocate or spend a disproportionate amount of cognitive energy on survival. This reduces “cognitive bandwidth,” making employees more risk-averse and less likely to engage in the creative problem-solving or “intrapreneurship” required for organizational growth.
Q: What is the “Cognitive Tax” of affordability challenges?
A: The cognitive tax is the mental drain caused by financial stress. When individuals are worried about basic needs like food and rent, their prefrontal cortex — the area responsible for complex decision-making and creativity — is overwhelmed by the stress of survival, effectively lowering their functional IQ and creative output.
Q: Can innovation survive in an environment of economic scarcity?
A: While scarcity can occasionally breed “frugal innovation,” systemic affordability challenges generally stifle breakthrough innovation. Breakthroughs require “slack” — time, resources, and mental space — to experiment and fail. Without basic economic security, individuals cannot afford the risk of failure.
Disclaimer: This article speculates on the potential future direction of society based on current factors. It is hard to predict whether commercial, political and charitable organizations will respond in ways sufficient to alter the course of history or not.
Image credits: ChatGPT
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About ten years ago, IBM invited me to talk with some key members on the Watson team, when the triumph of creating a machine that could beat the best human players at the game show Jeopardy! was still fresh. I wrote in Forbes at the time that we were entering a new era of cognitive collaboration between humans, computers and other humans.
One thing that struck me was how similar the moment seemed to how aviation legend Chuck Yeager described the advent of flying-by-wire, four decades earlier, in which pilots no longer would operate aircraft, but interface with a computer that flew the plane. Many of the macho “flyboys” weren’t able to trust the machines and couldn’t adapt.
Now, with the launch of ChatGPT, Bill Gates has announced that the age of AI has begun and, much like those old flyboys, we’re all going to struggle to adapt. Our success will not only rely on our ability to learn new skills and work in new ways, but the extent to which we are able to trust our machine collaborators. To reach its potential, AI will need to become accountable.
Recognizing Data Bias
With humans, we work diligently to construct safe and constructive learning environments. We design curriculums, carefully selecting materials, instructors and students to try and get the right mix of information and social dynamics. We go to all this trouble because we understand that the environment we create greatly influences the learning experience.
Machines also have a learning environment called a “corpus.” If, for example, you want to teach an algorithm to recognize cats, you expose it to thousands of pictures of cats. In time, it figures out how to tell the difference between, say, a cat and a dog. Much like with human beings, it is through learning from these experiences that algorithms become useful.
However, the process can go horribly awry. A famous case is Microsoft’s Tay, a Twitter bot that the company unleashed on the microblogging platform in 2016. In under a day, Tay went from being friendly and casual (“humans are super cool”) to downright scary, (“Hitler was right and I hate Jews”). It was profoundly disturbing.
Bias in the learning corpus is far more common than we often realize. Do an image search for the word “professional haircut” and you will get almost exclusively pictures of white men. Do the same for “unprofessional haircut” and you will see much more racial and gender diversity.
It’s not hard to figure out why this happens. Editors writing articles about haircuts portray white men in one way and other genders and races in another. When we query machines, we inevitably find our own biases baked in.
Accounting For Algorithmic Bias
A second major source of bias results from how decision-making models are designed. Consider the case of Sarah Wysocki, a fifth grade teacher who — despite being lauded by parents, students, and administrators alike — was fired from the D.C. school district because an algorithm judged her performance to be sub-par. Why? It’s not exactly clear, because the system was too complex to be understood by those who fired her.
Yet it’s not hard to imagine how it could happen. If a teacher’s ability is evaluated based on test scores, then other aspects of performance, such as taking on children with learning differences or emotional problems, would fail to register, or even unfairly penalize them. Good human managers recognize outliers, algorithms generally aren’t designed that way.
In other cases, models are constructed according to what data is easiest to acquire or the model is overfit to a specific set of cases and is then applied too broadly. In 2013, Google Flu Trends predicted almost double as many cases there actually were. What appears to have happened is that increased media coverage about Google Flu Trends led to more searches by people who weren’t sick. The algorithm was never designed to take itself into account.
The simple fact is that an algorithm must be designed in one way or another. Every possible contingency cannot be pursued. Choices have to be made and bias will inevitably creep in. Mistakes happen. The key is not to eliminate error, but to make our systems accountable through, explainability, auditability and transparency.
To Build An Era Of Cognitive Collaboration We First Need To Build Trust
In 2020, Ofqual, the authority that administers A-Level college entrance exams in the UK, found itself mired in scandal. Unable to hold live exams because of Covid-19, it designed and employed an algorithm that based scores partly on the historical performance of the schools students attended with the unintended consequence that already disadvantaged students found themselves further penalized by artificially deflated scores.
The outcry was immediate, but in a sense the Ofqual case is a happy story. Because the agency was transparent about how the algorithm was constructed, the source of the bias was quickly revealed, corrective action was taken in a timely manner, and much of the damage was likely mitigated. As Linus’s Law advises, “given enough eyeballs, all bugs are shallow.”
The age of artificial intelligence requires us to collaborate with machines, leveraging their capabilities to better serve other humans. To make that collaboration successful, however, it needs to take place in an atmosphere of trust. Machines, just like humans, need to be held accountable, their decisions and insights can’t be a “black box.” We need to be able to understand where their judgments come from and how they’re decisions are being made.
Senator Schumer worked on legislation to promote more transparency in 2024, but that is only a start and the new administration has pushed the pause button on AI regulation. The real change has to come from within ourselves and how we see our relationships with the machines we create. Marshall McLuhan wrote that media are extensions of man and the same can be said for technology. Our machines inherit our human weaknesses and frailties. We need to make allowances for that.
— Article courtesy of the Digital Tonto blog
— Image credit: Flickr
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Leaders aspire to create a “dream organization” not merely for the sake of prestige or profit, but because they recognize that a deeply aligned, human-centered culture is the ultimate multiplier of potential. In a dream organization, the traditional friction between individual aspiration and corporate objective vanishes, replaced by a shared sense of purpose and psychological safety that allows innovation to flourish naturally. These leaders understand that when employees feel truly seen, valued, and empowered to contribute their best work, the organization becomes antifragile — capable of navigating uncertainty with a level of agility and commitment that cannot be bought or mandated. Ultimately, the quest for a dream organization is an investment in a sustainable future where the workplace acts as a catalyst for both professional excellence and personal fulfillment.
Today we dive deep into what it takes to create a “dream organization” through a dialogue with our special guest.
Helping Leaders Build Their Dream Organization
I recently had the opportunity to interview Oscar Amundsen, a full Professor of Organization Studies at the Norwegian University of Science and Technology.
He has extensive experience in researching various industries and businesses. His work is focused on change and innovation in organizations. This includes related topics such as leadership, culture, trust, motivation, and organizational development. In these fields, he has published numerous books and scientific articles.
Amundsen’s goal is to develop research-based knowledge AND at the same time make the research concrete and accessible. The point is to make the knowledge useful for creating better organizations. Whether the enterprise is in the public, voluntary or private sector.
1. What does it take for an organization to break its own practices and develop new ones?
Organizations can be seen as ‘organisms’ that develop habits. And we all know that habits are not easy to break. But organizations can also be seen as ‘tools for achieving goals’. Since the world around the organization changes, the organization itself must also change to remain a suitable tool for the (changed) tasks that need to be solved.
As a leader, you must have the ability to identify the need for change. This means you need to look both ‘outward and inward’: What is required of us in a changing environment? And what does this mean for how we work within this organization?
Many leaders overlook that the latter question requires deep knowledge of what is happening inside the organization. Therefore, you should consult with employees who are close to the core tasks of the organization. You don’t know everything yourself, and you need some knowledge from the ‘foot soldiers’ to make the organization better.
I would also add that ‘breaking away’ is precisely a hallmark of all innovation. If you are going to do things in new ways, you have to break with what is established (in a market, in a practice, etc.). However, all such breaks require a willingness to take risks. You can never know with one hundred percent certainty how it will turn out, even though you should of course avoid taking reckless chances with your business. But you must accept that things can go wrong from time to time in order to achieve something new.
2. What are the keys to promoting the ability to both change and innovate?
This is precisely the question that the book answers. I present a research-based model with eight keys to strengthening the ability for change and innovation. The book is therefore structured around eight chapters, each addressing one of these keys. The point is to show how these eight mechanisms influence the capacity for change and innovation. This knowledge gives you the opportunity to build and develop an organization that not only solves its tasks smarter and better, but also becomes an attractive place to be for both leaders and other employees.
3. Why do people resist sharing new practices?
If you have an organization where people are afraid of making mistakes and trying new things, much will happen in secret. In the book, I write about an employee who comes up with a new and efficient way of working but keeps it hidden from both colleagues and managers because she fears her solution deviates from established procedures. She knows the solution is both sound and sensible. It is only when a researcher visits the organization that she (anonymously) shares her new way of working. Her lack of trust in leadership means that a new practice remains with her, even though it could have spread (and been improved) if it had been openly discussed among employees and managers. This organization misses out on the resource that ordinary employees represent for improving and renewing the business.
4. What are the keys for leaders to manage that determine whether trust or mistrust dominates?
Let me first say that trust is worth its weight in gold in this context. The reason is that trust in an organization is absolutely fundamental to building its ability to innovate. In the book I highlight five aspects that explain why and how trust influences the organization’s ability to change and innovate.
As a leader, you should understand these aspects, because only then can you say something meaningful about the state of trust within the organization.
Practicing trust requires a certain degree of courage. Trusting someone always (in principle) involves some risk: You can never be 100 percent certain that the trust you show will be honored. It may sound strange, but despite this, I recommend a more trust-based leadership approach because it has so many positive effects.
Concretely, you should reflect on the signals you personally send out, but may be even more important: You should examine the control systems used in your organization. Is there more control than necessary in some areas? What is the purpose of that control? Is it to ‘catch’ people making mistakes, or is it to learn from mistakes?
5. Why is autonomy so important to employees?
There is solid research evidence to support the claim that autonomy is, in fact, a fundamental human need (along with mastery and belonging). All people function better when they have some influence over their own situation – of course within the goals and frameworks set by the organization. In the book, I discuss how autonomy strengthens people’s motivation and drive – and (not least) increases their willingness to contribute constructively within an organization. It is well-established knowledge from innovation research that autonomy, within good boundaries, is positive for innovation.
6. Why is it important for organizations to have positive vibes and how is this different from optimism?
Optimism is good, but it can actually become a ‘straitjacket’. In the book, I illustrate this through a case where I explain the spectacular fall of mobile phone manufacturer Nokia. At the turn of the millennium, they were the world’s largest mobile phone producer. But a culture developed within the company where it was ‘not allowed’ to raise objections or criticize the strategy. Management only wanted to hear good news. The short version of this story is that Nokia was therefore unprepared when the iPhone entered the market, and gradually disappeared until the remnants were bought up some years later.
On the other hand: Having positive feelings toward your own company, is of great value to the organization. This is something completely different from a demand for pure optimism. Research suggests that such positive feelings influence your relationship with colleagues and the organization. The point is that a positive atmosphere makes you more:
Helpful: The mechanism is ‘feel good – do good’. Things flow more smoothly, including knowledge sharing.
Engaged: You become willing to make sacrifices and go the extra mile.
Protective: You ‘speak proudly’ about the company externally and help prevent dangers and trouble.
Constructive: You are more likely to come up with constructive suggestions.
The last point directly impacts an organization’s ability to change and innovate, while the first three strengthen that ability indirectly.
7. What do tolerance of failure and diversity look like in practice?
Tolerance for mistakes is essential for achieving innovation. In a ‘zero-error culture,’ you will struggle to innovate simply because people are afraid to experiment, to try and fail. Although mistakes will always happen, it is useful to distinguish between different types of mistakes: What you want to encourage (and have more of) are what can be called ‘intelligent mistakes.’
These are mistakes that occur when you deliberately try something new. The goal is to learn so that you can move forward with what you are trying to develop. Other types of mistakes can be called basic or complex. These are the ones you want as few of as possible, but you cannot say they should never exist. Research shows that if you have zero tolerance for mistakes, they will be hidden, and you lose the opportunity to learn from them.
When it comes to diversity, I write in the book about how different types of perspectives and knowledge are valuable for innovation. I emphasize that leaders should demonstrate a certain level of humility and recognize that they need others’ insights to make good decisions.
8. What is practical anchoring and why is it so important?
Practical anchoring is essentially about involving the right employees in change processes. The point is that you need knowledge of actual practice to carry out sensible change work. People in the organization should see the benefit of the changes you are planning if you want them on board when changes are implemented. This makes sense not only for engagement and motivation but also to ensure you don’t create a less efficient organization with duplicate work and potential obstacles to doing a good job.
9. Why does fear play such a big role in organizations’ ability to change & innovate?
This is a broad topic, which I dedicate an entire chapter to in the book. The short version is that fear leads employees to avoid participating and contributing with their knowledge and experience. We are social beings who generally want to avoid the risk of offering an original contribution or asking a critical or fundamental question if there are potential negative consequences. In the Nokia case, we also see that people became tactical regarding their own career opportunities within the organization: They eventually learned that those who asked critical (but necessary) questions lost opportunities in the company. This caused engineers to drift to the sidelines – even on strategic technical issues.
10. Getting 100% participation is always a good thing, right?
There are many benefits to involving people in both innovation and change efforts. The point is to make the best use of the knowledge resources you have within the organization for the benefit of the organization. In addition, you become a more attractive employer if you allow people to participate in development. Modern employees actually expect to have some influence over their work situation and to use their knowledge in ways that benefit both themselves and the organization.
That said, I still emphasize in the book that there is a balance here: It’s not as if everyone should have an opinion on everything and participate in every possible process. That would only create chaos and overload for people in key roles. In the book, I use the term ‘participation satisfaction’ to describe this. People have different needs for involvement—both personally and, most importantly, based on the role they have. Conclusion: Not “the more participation, the better,” but balanced according to need.
11. Any question I didn’t ask that you want to answer?
Well, you haven’t asked me about the title of the book. I want to underline that “the dream organization” is not meant as a utopic situation. Rather, it’s meant more like a goal image. A goal image for those who want to build and become stronger in change and innovation. So, the book is about improving the organization – and at the same time making it attractive to be a part of – as a leader and as an employee.
So, the title of the book is an invitation to raise your gaze a little and ask something like: “What steps could I take to build a better organization? How can I develop a workplace where people like to work – and where change and innovation are a natural part of working?” That’s the kind of organization I want to help make reality with this book.
For decades, organizations have operated like giant, slow-moving mammals with centralized nervous systems. Information traveled from the extremities (the employees and customers) up to the brain (management), where decisions were made and sent back down as commands. But in our hyper-connected, volatile world, this centralized model is failing. To thrive, we must evolve. We must move toward Collaborative Sensing — what I call The Mesh.
The Mesh is a paradigm shift where every person, every device, and every interaction becomes a sensor. It is a decentralized network of intelligence that allows an organization to sense, respond, and adapt in real-time. Instead of waiting for a quarterly report to tell you that a project is failing or a customer trend is shifting, The Mesh tells you the moment the first signal appears. This is human-centered innovation at its most agile.
“The smartest organizations of the future will not be those with the most powerful central computers, but those with the most sensitive and collaborative human-digital mesh. Intelligence is no longer something you possess; it is something you participate in.” — Braden Kelley
From Centralized Silos to Distributed Awareness
In a traditional hierarchy, silos prevent information from flowing horizontally. In a Mesh environment, data is shared peer-to-peer. Collaborative sensing leverages the wisdom of the crowd and the precision of the Internet of Things (IoT) to create a high-resolution picture of reality. This isn’t just about “big data”; it is about thick data — the qualitative, human context that explains the numbers.
When humans and machines collaborate in a sensing mesh, we achieve what I call Anticipatory Leadership. We stop reacting to the past and start shaping the future as it emerges. This requires a culture of radical transparency and psychological safety, where sharing a “negative” signal is seen as a contribution to the collective health of the mesh.
Leading the Charge: Companies and Startups in the Mesh
The landscape of collaborative sensing is being defined by a mix of established giants and disruptive startups. IBM and Cisco are laying the enterprise-grade foundation with their edge computing and industrial IoT frameworks, while Siemens is integrating collaborative sensing into the very fabric of smart cities and factories. On the startup front, companies like Helium are revolutionizing how decentralized wireless networks are built by incentivizing individuals to host “nodes.” Meanwhile, Nodle is creating a citizen-powered mesh network using Bluetooth on smartphones, and StreetLight Data is utilizing the mesh of mobile signals to transform urban planning. These players are proving that the most valuable data is distributed, not centralized.
Case Study 1: Transforming Safety in Industrial Environments
The Challenge
A global mining operation struggled with high rates of “near-miss” accidents. Traditional safety protocols relied on manual reporting after an incident occurred. By the time management reviewed the data, the conditions that caused the risk had often changed, making preventative action difficult.
The Mesh Solution
The company implemented a collaborative sensing mesh. Workers were equipped with wearable sensors that tracked environmental hazards (gas levels, heat) and physiological stress. Simultaneously, heavy machinery was outfitted with proximity sensors. These nodes communicated locally — machine to machine and machine to human.
The Human-Centered Result
The “sensing” happened at the edge. If a worker’s stress levels spiked while a vehicle was approaching an unsafe zone, the mesh triggered an immediate haptic alert to the worker and slowed the vehicle automatically. Over six months, near-misses dropped by 40%. The organization didn’t just get “safer”; it became a learning organization that used real-time data to redesign workflows around human limitations and strengths.
Case Study 2: Urban Resilience and Citizen Sensing
The Challenge
A coastal city prone to flash flooding relied on a few expensive, centralized weather stations. These stations often missed hyper-local rain events that flooded specific neighborhoods, leaving emergency services flat-footed.
The Mesh Solution
The city launched a Citizen Sensing initiative. They distributed low-cost, connected rain gauges to residents and integrated data from connected cars’ windshield wiper activity. This created a high-density sensing mesh across the entire geography.
The Human-Centered Result
Instead of one data point for the whole city, planners had thousands. When a localized cell hit a specific district, the mesh automatically updated digital signage to reroute traffic and alerted residents in that specific block minutes before the water rose. This moved the city from crisis management to collaborative resilience, empowering citizens to be active participants in their own safety.
Building Your Organizational Mesh
If you are looking to help your team navigate this transition, start by asking: Where is our organization currently numb? Where are the blind spots where information exists but isn’t being sensed or shared?
To build a successful Mesh, you must prioritize:
Interoperability: Ensuring different sensors and humans can “speak” to each other across platforms.
Privacy by Design: Ensuring the mesh protects individual identity while sharing collective insight.
Incentivization: Why should people participate? The mesh must provide value back to those who provide the data.
The Mesh is not just a technological infrastructure; it is a human-centered mindset. It is the realization that we are all nodes in a larger system of intelligence. When we sense together, we succeed together.
Frequently Asked Questions on Collaborative Sensing
Q: What is Collaborative Sensing or ‘The Mesh’?
A: Collaborative Sensing is a decentralized approach to intelligence where humans and IoT devices work in a networked “mesh” to share real-time data. Unlike top-down systems, it relies on distributed nodes to sense, process, and act on information locally and collectively.
Q: How does Collaborative Sensing benefit human-centered innovation?
A: It moves the focus from “big data” to “human context.” By sensing environmental and social signals in real-time, organizations can respond to human needs with greater empathy and precision, reducing friction in everything from city planning to workplace safety.
Q: What is the primary challenge in implementing a Mesh network?
A: The primary challenge is trust and data governance. For a mesh to work effectively, participants must be confident that their data is secure, anonymous where necessary, and used for collective benefit rather than invasive surveillance.
Disclaimer: This article speculates on the potential future applications of cutting-edge scientific research. While based on current scientific understanding, the practical realization of these concepts may vary in timeline and feasibility and are subject to ongoing research and development.
Image credits: Google Gemini
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We think we have more control than we really have. We imagine an idealized future state and try desperately to push the organization in the direction of our imagination. Add emotional energy, define a rational approach, provide the supporting rationale and everyone will see the light. Pure hubris.
What if we took a different approach? What if we believed people want to do the right thing but there’s something in the way? What if like a log jam in a fast-moving river, we remove the one log blocking them all? What if like a river there’s a fast-moving current of company culture that wants to push through the emotional log jam that is the status quo? What if it’s not a log at all but, rather, a Peter Principled executive that’s threatened by the very thing that will save the company?
The Peter Principled executive is a tough nut to crack. Deeply entrenched in the powerful goings on of the mundane and enabled by the protective badge of seniority, these sticks-in-the-mud need to be helped out of the way without threatening their no-longer-deserved status. Tricky business.
Rule 1: If you get into an argument with a Peter Principled executive, you’ll lose.
Rule 2: Don’t argue with Peter Principled executive.
If we want to make it easy for the right work to happen, we’ve got to learn how to make it easy for the Peter Principled executive to get out of the way. First, ask yourself why the executive is in the way. Why are they blocking progress? What’s keeping them from doing the right thing? Usually it comes down to the fear of change or the fear of losing control. Now it’s time to think of a work product that will help make the case there’s a a better way. Think of a small experiment to demonstrate a new way is possible and then run the experiment. Don’t ask, just run it. But the experiment isn’t the work product. The work product is a short report that makes it clear the new paradigm has been demonstrated, at least at small scale. The report must be clear and dense and provide objective evidence the right work happened by the right people in the right way. It must be written in a way that preempts argument – this is what happened, this is who did it, this is what it looks like and this is the benefit.
It’s critical to choose the right people to run the experiment and create the work product. The work must be done by someone in the chain of command of the in-the-way executive. Once the work product is created, it must be shared with an executive of equal status who is by definition outside the chain of command. From there, that executive must send a gracious email back into the chain of command that praises the work, praises the people who did it and praises the leader within the chain of command who had the foresight to sponsor such wonderful work.
As this public positivity filters through the organization, more people will add their praise of the work and the leaders that sponsored it. And by the time it makes it up the food chain to the executive of interest, the spider web of positivity is anchored across the organization and can’t be unwound by argument. And there you have it. You created the causes and conditions for the log jam to unjam itself. It’s now easy for the executive to get out of the way because they and their organization have already been praised for demonstrating the new paradigm. You’ve built a bridge across the emotional divide and made it easy for the executive and the status quo to cross it.
Asking for the right work product is a powerful skill. Most error on the side of complication and complexity, but the right work product is just the opposite – simple and tight. Think sledgehammer to the forehead in the form of and Excel chart where the approach is beyond reproach; where the chart can be interpreted just one way; where the axes are labeled; and it’s clear the status quo is long dead.
Business model is dead and we’ve got to stop trying to keep it alive. It’s time to break the log jam. Don’t be afraid. Create the right work product that is the dynamite that blows up the status quo and the executives clinging to it.
Image credit: Pexels
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There seems to be a lot of controversy and questions surrounding artificial intelligence (AI) being used to support customers. The customer experience can be enhanced with AI, but it can also derail and cause customers to head to the competition.
Last week, I wrote an article titled Just Because You Can Use AI, Doesn’t Mean You Should. The gist of the article was that while AI has impressive capabilities, there are situations in which human-to-human interaction is still preferred, even necessary, especially for complex, sensitive or emotionally charged customer issues.
However, there is a flip side. Sometimes AI is the smart thing to use, and eliminating human-to-human interaction actually creates a better customer experience. The point is that just because a human could handle a task doesn’t mean they should.
Before we go further, keep in mind that even if AI should handle an issue, my customer service and customer experience (CX) research finds almost seven out of 10 customers (68%) prefer the phone. So, there are some customers who, regardless of how good AI is, will only talk to a live human being.
Here’s a reality: When a customer simply wants to check their account balance, reset a password, track a package or any other routine, simple task or request, they don’t need to talk to someone. What they really want, even if they don’t realize it, is fast, accurate information and a convenient experience.
The key is recognizing when customers value efficiency over engagement. Even with 68% of customers preferring the phone, they also want convenience and speed. And sometimes, the most convenient experience is one that eliminates unnecessary human interaction.
Smart companies are learning to use both strategically. They are finding a balance. They’re using AI for routine, transactional interactions while making live agents available for situations requiring judgement, creativity or empathy.
The goal isn’t to replace humans with AI. It’s to use each where they excel most. That sometimes means letting technology do what it can do best, even if a human could technically do the job. The customer experience improves when you match the right resource to the customers’ specific need.
That’s why I advocate pushing the digital, AI-infused experience for the right reasons but always – and I emphasize the word always – giving the customer an easy way to connect to a human and continue the conversation.
In the end, most customers don’t care whether their problem is solved by a human or AI. They just want it solved well.
Image credits: Google Gemini, Shep Hyken
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