Category Archives: Technology

FORO: The Fear of Reaching Out

FORO: The Fear of Reaching Out

GUEST POST from Shep Hyken

We’ve all experienced long hold times, repeating our “story” because we get transferred from one customer service rep to another, etc. It’s an ugly customer service experience that gives many customers FORO, or the Fear of Reaching Out.

FORO is the result of an experience marred with time-wasting friction that makes customers dislike having to reach out to customer support. Our annual customer service and Customer Experience (CX) research (sponsored by RingCentral) finds that 43% of customers would rather clean a toilet than call customer support. The support experience can be so bad that 60% of customers admit to hanging up on a support agent, 34% admit to yelling at an agent, and 21% admit to cussing at an agent. So, it does make sense that customers would have FORO due to poor experiences they have had with some companies and brands (not all) in the past.

Because some companies get it right and others don’t, the inconsistency makes the customer wonder what the next time will be like. Their past frustration, anxiety or memory of a bad experience creates the unwillingness to call.

I had a chance to interview Gaurav Passi on Amazing Business Radio, and he introduced me to the concept of FORO. Passi is the co-founder and CEO of Zingly.AI, a platform that empowers customers to collaborate with a company, either through AI or with direct human-to-human interactions, to have their questions answered and problems resolved. Below are some of Passi’s most intriguing points, followed by my commentary:

  1. The next 15-20 years will be about the end customer experience. Many consulting companies and business experts recognize that customer experience is more important than a company’s product. Most customers can buy the same product—or at least similar products—from many different sources. What differentiates the companies and brands that sell these products is the experience. Passi agrees and adds that the way companies deliver support is changing. The future of CX is a blend of AI, digital and human/live support. That prompted me to ask Passi a question that concerns many people, especially customer support agents, “Do you see AI replacing live agents in that time frame?” He answered, “I don’t see a world where humans are completely taken out.”
  2. Customers don’t want to talk to a human being — until they do. Passi says that customers often don’t want to talk to a human. They just want an answer as quickly and efficiently as possible. If they can’t get it, then they want to talk to a human … as quickly and efficiently as possible. Even with many customers desiring this self-service approach, Passi cautions that companies should not make the mistake of 100% deflection to digital self-service. He asks, “Even if you achieve 100% deflection, what will happen to your customer satisfaction (CSAT) scores?” Passi shared an example of a client who had chosen to deflect 100% of customer support to digital self-service and had an outage. Because of the outage, the employees ended up talking to customers, human-to-human. Amazingly — or not — CSAT went up. Why? Passi says, “Because there was a human touch when needed.”
  3. Customer patience is at an all-time low. This is a primary symptom of FORO. Customers don’t have the time or patience to go online to a company’s website, find the customer support number, wait on hold, get authenticated, etc. They want, as Passi calls it, a “One shot, one kill experience.” Using the company’s self-service options, often fueled by AI, you ask a question, and an answer comes back. It’s as simple as that. The customer appreciates not having to get on the phone, wait on hold, etc., etc.
  4. AI is not the final answer! While AI is revolutionizing customer service and support by enabling businesses to scale their operations efficiently, maintaining the human touch with customers to foster genuine relationships is still important. But the human touch doesn’t have to kick in until it’s needed. And in the perfect world, the platform will recognize customers’ reactions when they aren’t getting the answers they need. Passi is proud of what he refers to as “the most magical component we’ve created in the past three years,” which is a technology that understands when the customer is not getting the right answer and seamlessly passes them to a human agent to take over.

If you’ve been following my work, you know I’m focused on helping my clients create amazing customer experiences. As Passi and I wrapped up our interview, he mentioned that amazing is what Zingly is about. He shared that his mission, like mine, is to help his customers create amaZINGLY great experiences for their customers. With an increasing demand for customers to have more control over how, when and on which devices they communicate with businesses, the combination of AI and human expertise, paired with transparency and collaboration with customers, can create a more personalized, effective and amaZINGLY great customer experience.

Image Credit: Pixabay

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

Unlocking Trapped Value with AI

Unlocking Trapped Value with AI

GUEST POST from Geoffrey A. Moore

Anyone who has used Chat GPT or any of its cousins will testify to its astonishing ability to provide valuable responses to virtually any query. This is hardly a threat—indeed, it is a boon. So, what are we worrying about?

Well, there is the issue of veracity, of course, and it is true, GPT-enabled assistants can indeed make mistakes. But, come on—humans don’t? We are not looking for gospel truth here. We want highly probable, highly informed answers to questions where we need guidance, and it is clear that GPT-enabled applications are outstanding at meeting this need, for at least three reasons. They are remarkably well-informed. They are available 24/7 on demand with no hold time. And they have infinite patience. So, let’s not kid ourselves. We are massively better off for their emergence on the scene.

What we should be worrying about, on the other hand, is their impact on jobs to be done, employment, and career development. A simple way to think about this is that for any of us to earn money, we have to release some form of trapped value. A bank clerk helps a customer get access to the trapped value in their savings account. A bus driver helps a passenger cope with their trapped value by transporting them to the location where they need to be. A lawyer helps a client get access to trapped value by constructing a contract that meets their needs while protecting against risk. A teacher helps a student access trapped value by helping her solve problems she couldn’t handle before. The principle applies to every job. All systems have points of trapped value, and all jobs are organized around releasing and capturing that value.

Now, let’s introduce generative AI. All of a sudden, a whole lot of trapped value that funded a whole lot of jobs can now be released for free (or virtually for free). Those jobs can be protected in the short term but not forever. In other words, the environment really has changed, and we must assess our new circumstances or fall behind. This is Darwinism at work. Evolution never stops. It can’t. As long as there is change, there will be dislocation, which in turn will stimulate innovation. That’s life.

But here’s the good news. The universe can never eliminate trapped value, it can only move it from place to place. That is, there are always emergent problems to solve, always new opportunities to capitalize on, because every system always traps value somewhere. What Darwinism requires is that we detect the new value traps and redirect our activity to engage with them.

Publicly funded agencies sometimes interpret this as a mandate for training programs, but we have to be careful here. Training works well for disseminating established skills that address known problems. It does not work well, however, where the problems are still being determined and the skills are as yet undeveloped. Novelty, in other words, demands creativity. It is simply not negotiable.

Getting back to the impact of generative AI, we should understand that it is an advisory technology. It is not automation. That is, it is not eliminating the need for human beings to make judgment calls. Rather, it is accelerating the preparation for so doing and framing the options in ways that make decision-making more straightforward. By solving for the old value traps, it is giving us the opportunity to up our game. It’s our job to step up to add net new value to the equation.

The best way to do this is to ferret out the emerging new value traps. Who is the customer now? What is the bottleneck that is holding them back? How could that bottleneck be broken open? What is the reward for so doing? These are the fundamental questions that drive any business model. We know how to do this. It’s just that we have been riding on the inertia of the past set of solutions for so long we may have atrophied in some of the muscles we need now. One thing we need not worry about is the universe running out of trapped value. If you are ever in doubt, just read the day’s headlines and be reassured. The world needs our help. Any tool that helps us do our part better is a blessing.

That’s what I think. What do you think?

Image Credit: Pexels

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

Beyond the AI Customer Experience Hype

Beyond the AI Customer Experience Hype

GUEST POST from Shep Hyken

I’ve been writing a lot about artificial intelligence (AI) and the digital customer experience (CX). Many of the executives I interview and the articles I refer to are all about how AI is revolutionizing, changing, helping and sometimes hurting CX. So we’ve heard from experts. How about if we heard from the customers?

That’s exactly what we did in our annual customer service and CX research sponsored by RingCentral. We asked more than 1,000 U.S. consumers about their experiences with AI and digital customer support, and here are the basic findings for 2024:

The Good

  1. Sixty-two percent of U.S. consumers expect that AI (and related technologies) will be the primary mode of customer service in the future. But how about today? As you will see in some of the findings below, not everyone feels AI is ready for primetime customer service and CX.
  2. Thirty-eight percent believe AI and related technologies will lead to more personalized customer experiences. Personalization has been a hot topic for marketing and CX leaders. AI is giving companies and brands far greater capabilities to use customer data to create a personalized experience. Customers enjoy doing business with companies that recognize them and use the information they have to create a better experience.
  3. Forty-nine percent think AI technologies have the potential to improve the overall customer experience. This is good news, however, the next group of findings shows that companies still have an uphill battle to get customers to adopt and embrace a CX fueled by AI.

The Bad

  1. Only 32% of customers have successfully resolved a customer service issue using AI or ChatGPT technologies. That number is low. One theory is that customers often don’t realize AI is what’s behind what they are doing. Some think AI is chatbots and automated voice response systems that interact with them like a human would or should.
  2. Fifty-six percent of customers admit to being scared of technologies like AI and ChatGPT. Some of these customers may have watched movies where computers take over the world or robots go rogue, none of which are grounded in reality. However, some customers simply don’t trust the technology because of past bad experiences.
  3. Sixty-three percent of customers are frustrated with self-service options using AI, ChatGPT and similar technologies. Frustration is different than being scared, but it has the same impact: customers would rather avoid technology and talk to a live human for support and service.

As I studied the significance of these findings as a whole, the overarching theme of why AI has not caught on as a viable and reliable customer support option is inconsistency. Included in the annual study is a finding that 70% of customers choose talking to a live customer service agent on the phone as their primary channel for customer service.

Why? It’s easier, and customers know what to expect when they talk and interact with live agents. What they don’t want to experience is a self-service solution powered by AI that takes them through a series of prompts that eventually lead to a dead end, where they end up having to call the company anyway.

There’s good reason for the fear and frustration. As more customers are exposed to AI and start to understand it, their inconsistent experiences from one company to the next are creating a confidence problem. The latest technology, which is very cost-effective for even small businesses, has not been purchased and implemented by a majority of businesses.

As of the beginning of this year, just 27% of customers think self-service or automated customer support using AI-powered technology can deliver as good of a customer experience as a live agent. That number will eventually go up, although not as quickly as it needs to. Once companies recognize that bad service equates to lost business, they will make the investment to do it right. It’s not an option if they want their customers to say, “I’ll be back!”

This article was originally published on Forbes.com

Image Credits: Unsplash

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

Audacious

How Humans Win in an AI Marketing World

Exclusive Interview with Mark Schaefer

Mark W SchaeferThe rise of artificial intelligence (AI) has led to a tsunami of AI-generated content, and according to Gemini these are some of the concerns for marketers:

  • Erosion of Brand Authenticity: AI can generate marketing copy, social media posts, and even personalized emails. The fear is that over-reliance on AI-generated content could lead to a loss of genuine brand voice and connection with customers, making marketing feel impersonal and manufactured.
  • Decreased Content Quality and Creativity: While AI can produce grammatically correct and seemingly relevant content, it may struggle with nuanced storytelling, truly innovative ideas, and emotionally resonant messaging that connects deeply with human audiences. This could lead to a decline in the overall quality and impact of marketing content.
  • Over-Saturation of Generic Content: If many marketers use similar AI tools and prompts, there’s a risk of the internet becoming flooded with repetitive and unoriginal content. This could make it harder for brands to stand out and capture attention in a crowded digital landscape.
  • Misuse for Deceptive Marketing Tactics: AI could be used to create highly targeted but deceptive marketing campaigns, such as generating fake reviews, creating convincing but misleading product descriptions, or even impersonating real people or brands. This could erode consumer trust and damage the reputation of ethical marketing practices.
  • Loss of Control Over Brand Messaging: While AI can assist with content creation, marketers may find it challenging to maintain complete control over the messaging and tone of AI-generated content. This could lead to inconsistencies in branding and potentially even PR crises if the AI produces something inappropriate or off-brand.


Now that we’ve got the ironic bit out of the way of asking AI to tell us what marketers have to fear from AI (in italics), let’s dive into the heart of this article and hear from the humans.

The Audaciousness of Humans

I had the opportunity recently to interview Mark Schaefer, a globally-acclaimed author, keynote speaker, and marketing consultant. He is a faculty member of Rutgers University and one of the top business bloggers and podcasters in the world. Audacious: How Humans Win in an AI Marketing World is his eleventh book, exploring how companies can create more effective marketing by being audacious.

Below is the text of my interview with Mark and a preview of the kinds of insights you’ll find in Audacious presented in a Q&A format:

1. We are seeing a marketing evolution from messages to stories, agree or disagree? Or is the evolution to something else?

This is an interesting question. Marketing is about creating customers. Our ability to do that has been dramatically changed by technology.

Let’s say 50 years ago, messages and taglines were about our only options. Advertising is expensive. Space was limited.

But in the Internet age, we have virtually unlimited space to tell a story at no cost. And stories can be created by anyone. I think the evolution of marketing right now is when we can do something so worthy, so memorable, so useful, that our customers can’t wait to tell the stories for us.

2. What impact are we seeing from AI on marketing?

There are two types of marketing – performance and brand marketing.

Performance marketing is about repetitive acts like ads that create traffic for the top of the funnel. These activities will almost certainly be dominated by AI.

Brand marketing creates meaning – an emotional expectation for your company or product. In this respect, AI can still have a major impact on creativity and planning, but I forecast that there will still be a human role to play for years to come.

The most effective connections still come from relationships with people!

3. Product, service, solution, experience… In today’s world, which is the most important?

The beauty of our world is that it is filled with people who have diverse perspectives and needs! Some people might buy on value, some might buy on performance, or even the status they feel when they own a product.

However, at the very highest level, I think experience is an interesting opportunity for brands. Let’s look at Patagonia, for example, it does not product the cheapest clothes, or the most functional or beautiful. But the brand MEANS something to a devoted fans because of a shared experience or responsible outdoor recreation.

4. With people drowning in content, how are marketers supposed to reach their target customers?

This question really cuts the heart of my research and writing over the last 15 years and it is the theme of my new book Audacious: How Humans Win in an AI Marketing World.

The book reveals research that shows that the vast majority of marketing and advertising is boring and ineffective and AI is making it more so. I would say we are in a pandemic of dull.

Competent doesn’t cut it. Competent is ignorable. So we need to ignite human creativity in a new way by disrupting traditions and norms. Changing HOW we tell a story. Changing WHERE we tell a story. Changing WHO tells the story.

It is time for audacity in our marketing. That is the only way we’ll cut through the clutter to be seen and heard. Audacity is now a survival skill.

5. Shock and Awe, which one should marketers focus on and why?

Audacious: How Humans Win in an AI Marketing WorldI actually address both of these in the new book!

Awe is an under-appreciated source of success in marketing. It’s not just about something that is vast and overwhelming. It can be something as simple as bringing people together in a meaningful new way that creates a shared experience. Wouldn’t it be amazing if people added more awe to their marketing?

Shock is also an overlooked idea. I don’t mean being offensive or reckless, but just waking up the sense to something completely different. A good example of this is Liquid Death, the fastest-growing beverage brand in America.

Nobody calls their product “Death.” So right from the start they have your attention. Their advertising features water boarding and kids chugging glasses of sugar. It is difficult to watch. But you don’t forget it, either.

6. You’re in charge of marketing the iPhone 17 and it’s basically the same as the iPhone 16, except now it’s available in Magenta. How would you change the marketing for a product that basically hasn’t changed?

This product introduction might actually work, but not for everyone.

You might recall that Apple introduced a black “U2” iPod many years ago. It sold out. It only worked because Apple already had a massive base of loyal fans – and so did U2! So even though the product wasn’t very different, the meaning for the fanbase was.

Normally, introducing a product with no discernible new value would be foolish but it is possible if the brand has meaning.

An example from my book is the game Cards Against Humanity. People invested in a hole in the ground and dried cow turds because they just wanted to be part of the fun. The value was in the meaning, not the product.

7. What does disruptive marketing look like now and in the future? What will become normalized?

The irony is, disruptive marketing is rapidly normalized. Here’s what I mean. The cover of my book is a world first – a QR code that creates an evolving, morphing cover based on the stories in the book. That is disruptive.

But you can only be disruptive once. From here on out, anybody who has QR code book cover will simply be copying me. The disruption has been normalized. You can only be audacious once.

8. Why are there so many damn QR codes in the book? 😉 (wink)

My book is full of “oh wow” moments. But a lot of them are better viewed than described. For example, a star of the book is Michael Krivicka, the king of viral video. I have never met a person with a keener sense of storytelling. There is no way you can appreciate his skill without seeing a video, so I provided QR code links so everyone has the chance to do that!

9. Where should marketers be careful as they challenge the standard ways of marketing, to be audacious?

There are lots of reasons why marketers should be conservative and traditional, especially when following laws and regulations.

However – if you’re staying in a boring box because there is fear in your organization, because dull is normal in your industry, or simply afraid, then you are vulnerable. The AI bots are here. They are competent, and in most cases more than competent. But you still own crazy. The companies that unleash the unique human fireworks of creativity will thrive in the AI era!

Conclusion

Thank you for the great conversation Mark!

I hope everyone has enjoyed this peek into the mind of the man behind the inspiring new title Audacious: How Humans Win in an AI Marketing World!

Image credits: BusinessesGrow.com (Mark W Schaefer)

Content Authenticity Statement: If it wasn’t clear above, the short section in italics was written by Google’s Gemini and the rest of this article is from the minds of Mark Schaefer and Braden Kelley.

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

Turns Out the Tin Foil Hat People Were Right

Turns Out the Tin Foil Hat People Were Right

by Braden Kelley

Turns out ‘Havana Syndrome’ is most likely the result of a directed electromagnetic, not ultrasonic, attack against CIA, U.S. military, F.B.I agents and State Department personnel and their family members. I couldn’t figure out how to embed this YouTube short, so here is the link.

It’s not new information, but it’s new to me that the traumatic brain injuries from these attacks are something that the trusty tin foil hat might prevent.

These attacks include the initial incidents in Havana, a well-documented case in Moscow, and incidents in Vienna, Colombia, China, Vietnam, and in at least one Central Asian country according to JustSecurity.org.

This is notable as the title suggests, because it means that there is a defense against these kinds of attacks that damage the brain. So, has anyone out there invested in protective headgear for their travel to certain regions that is a little more modern than the tin foil hat?

For more detail on the investigation into these attacks and their source, here is the most recent 60 Minutes episode:

And if you’re feeling a real risk, or just a little paranoid, a quick search for “EMF Hat” on Amazon or your favorite electronic retailer will return A LOT OF OPTIONS for your modern tin foil hat. Here is a sampling of the Amazon results, which you can see includes baseball cap, beanie, and even hood options.

EMF Protection Hats

Anyone out there wear one of these on a regular basis? Is it just for peace of mind or are there noticeable benefits that you can describe?

Any manufacturer out there want me to try one and document my experience?

Should the countries of the world come together and ban these weapons?

Do domestic laws need to be updated to classify this kind of attack as attempted murder?

Image credit: Wikimedia Commons, screenshot from Amazon

Subscribe to Human-Centered Change & Innovation WeeklySign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.

Innovation or Not – The VR Path to the Super Bowl

Innovation or Not - The VR Path to the Super Bowl

GUEST POST from Art Inteligencia

In the competitive arena of sports, athletes and coaches are perpetually seeking the next edge, the innovative stroke of genius that will propel them towards success. Enter Jayden Daniels, a pioneer quarterback who has embraced one of the most cutting-edge tools in sports performance enhancement: Virtual Reality (VR) training. Is this a true innovation or just another gimmick? Let’s journey through the lens of Jayden’s experience and see how this technology is reshaping the sporting world.

The Virtual Reality Revolution in Sports

For decades, athletes have relied on traditional training regimes, focusing on physical conditioning and repetitive skill drills. However, VR has transformed the landscape by introducing immersive environments where athletes can practice without the physical constraints of time, space, or risk of injury. Through VR headsets and meticulously simulated environments, players like Jayden Daniels are able to visualize and rehearse plays and strategies, improve their decision-making, and enhance their mental resilience.

“VR training is like a playbook come to life—it gives players the opportunity to be in the game without being on the field.”

Realizing this potential, Daniels incorporated VR training into his routine, and the results have been phenomenal. His ability to read defenses and execute plays has been augmented by this technology, helping him transition from mere player to game-changer.

Here is a video that tells the in depth story with commentary, but it won’t let me embed it here so just click the link in the box to watch it on YouTube:

EDITOR’S NOTE: Key takeaways include the technology’s ability to run at 1.75x speed so that on game day things slow down for the quarterback and he is able to engage in extra preparation without the entire team having to be present, and even to familiarize himself with away stadium nuances like where the play clocks are, etc.

Case Study #1: The Championship Turnaround

One of the most striking illustrations of VR’s impact occurred during a pivotal championship game. Daniels’ team was facing a formidable opponent known for their complex defensive schemes. The team’s traditional preparation methods were proving inadequate against such a sophisticated defense.

In the weeks leading to the game, Daniels immersed himself in VR simulations of the opponent’s defense. He studied every blitz, every zone coverage, and every adaptive quirk under the close guidance of his coaches, who were able to create a virtual replica of the team they were facing. By the time the championship game arrived, Daniels was not only prepared—he was several steps ahead.

During the game, his performance was near flawless. He anticipated defensive movements with uncanny accuracy, leading his team to a come-from-behind victory that analysts credited in large part to his innovative use of VR.

The MVP Moment

This VR-driven insight culminated in one memorable play: a perfectly executed fake pass that caught the opposing defense entirely off-guard, leading to the game-winning touchdown. This wasn’t just victory—it was an unveiling of how technology and sport can harmonize to create extraordinary outcomes.

Case Study #2: The Rival Rumble

In another celebrated match-up, Daniels faced his long-time rivals—a team that had bested his own in recent seasons. Known for their reactive plays and dynamic shifts, this opponent posed a considerable mental challenge that extended beyond physical prowess.

Once again, VR training became Daniels’ secret weapon. By simulating hundreds of scenarios, his VR regimen enabled him to practice responses to the rival’s play-calling tendencies, helping him build a memory bank of potential outcomes and counter-strategies.

When faced with crucial decisions on the field, Daniels was markedly less stressed and more composed. He deftly outmaneuvered the rival’s defense, leading his team to a decisive victory, and doing so with an air of confidence that captivated spectators and silenced skeptics.

The VR Vision

By the end of the season, Daniels had not only improved his own performance but had also inspired a wave of interest and investment in VR training across the league. Teams began revisiting their training paradigms, nudging the sports industry towards a more tech-savvy future.

Innovation or Not?

Jayden Daniels’ success with VR training may invite debates about whether this is innovation or merely a novel tool in an athlete’s repertoire. Regardless of where you stand, what cannot be denied is the transformative impact VR has had on enhancing an athlete’s strategic prowess and mental fortitude.

Beyond just quick optical improvements, VR training stands at the intersection of cognitive science and performance enhancement, offering a paradigm where mental sharpness is honed in tandem with physical capabilities. For Daniels, and countless athletes following in his footsteps, VR presents a formidable new teammate in their quest for greatness.

As we stand at the threshold of a technologically enhanced sports era, the question still lingers in the locker room and boardrooms: Is VR the future of sports training, or just another fleeting fad? For Jayden Daniels, it’s clear that VR is more than just a tool—it’s a revelation.

Image credit: Wikimedia Commons – All-Pro Reels of District of Columbia, USA

Subscribe to Human-Centered Change & Innovation WeeklySign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.

The Breakthrough Lifecycle

The Breakthrough Lifecycle

GUEST POST from Greg Satell

Many experts suspect that the COVID crisis is receding into the background. It is, of course, hard to know for sure. There will continue to be debate and we will still need to have some mitigating measures in place. Still, for the most part, people are back at work, kids are in school, and relatively normal routines have returned.

Generations from now, historians will most likely still question what lessons are to be gleaned from the past few years. Should we strengthen our multilateral institutions or have they become so sclerotic that they need to be dismantled? Is the rise of populist nationalism a harbinger for the future or a flash in the pan?

One thing I don’t expect to be hotly debated, in fact seems perfectly clear even now, is that science saved us. Untold thousands, working mostly anonymously in labs around the world, created a vaccine of astonishing efficacy in record time. It is these types of breakthroughs that change the course of history and, if we can embrace their power, lead us to a better future.

A Seemingly Useless Idea

The MRNA technology that led to the Moderna and Pfizer-BioNTech vaccines have the potential to revolutionize medical science. It can rapidly reprogram the machinery in our cells to manufacture things that can potentially cure or prevent a wide range of diseases, from cancer to malaria, vastly more efficiently than anything we’ve ever seen before.

Yet while revolutionary, it is not at all a new idea. In fact Katalin Karikó, who pioneered the approach, published her first paper on mRNA-based therapy way back in 1990. Unfortunately, she wasn’t able to win grants to fund her work and, by 1995, things came to a head. She was told that she could either direct her energies in a different way, or be demoted.

This type of thing is not unusual. Jim Allison, who won the Nobel Prize for his work on cancer immunotherapy, had a very similar experience when he had his breakthrough, despite having already become a prominent leader in the field. “It was depressing,” he told me. “I knew this discovery could make a difference, but nobody wanted to invest in it.”

The truth is that the next big thing always starts out looking like nothing at all. Things that really change the world always arrive out of context for the simple reason that the world hasn’t changed yet.

Overcoming Resistance

Humans tend to see things in a linear fashion. It is easier for us to imagine a clear line of cause and effect, like a row of dominoes falling into each other, rather than a series of complex interactions and feedback loops. So it shouldn’t be surprising that, in hindsight, breakthrough ideas seem so obvious that only the most dim-witted would deny their utility.

When we think of something like, say, electricity, we often just assume that it was immediately adopted and the world simply changed overnight. After all, who could deny the superiority of an efficient electric motor over a big, noisy steam engine? Yet as the economist Paul David explained in a famous paper, it took 40 years for it to really take hold.

There are a few reasons why this is the case. The first is switching costs. A new technology almost always has to replace something that already does the job. Another problem involves establishing a learning curve. People need to figure out how to unlock the potential of the new technology. To bring about any significant change you first have to overcome resistance.

With electricity, the transition happened slowly. It wouldn’t have made sense to immediately tear down steam-powered factories and replace them. At first, only new plants used the electricity. Yet it wasn’t so much the technology itself, but how people learned to use it to re-imagine how factories functioned that unlocked a revolution in productivity gains.

In the case of mRNA technology, no one had seen a mRNA vaccine work, so many favored more traditional methods. Johnson & Johnson and AstraZeneca, for example, used a more traditional DNA-based approach using adenoviruses that was much better understood, rather than take a chance on a newer, unproven approach.

We seem to be at a similar point now with mRNA and other technologies, such as CRISPR. They’ve been proven to be viable, but we really don’t understand them well enough yet to unlock their full potential.

Building Out The Ecosystem

When we look back through history, we see a series of inventions. It seems obvious to us that things like the internal combustion engine and electricity would change the world. Still, as late as 1920, roughly 40 years after they were invented, most American’s lives remained unchanged. For practical purposes, the impact of those two breakthroughs were negligible.

What made the difference wasn’t so much the inventions themselves, but the ecosystems that form around them. For internal combustion engines it took a separate networks to supply oil, to build roads, manufacture cars and ships and so on. For electricity, entire industries based on secondary inventions, such as household appliances and radios, needed to form to fully realize the potential of the underlying technology.

Much of what came after could scarcely have been dreamed of. Who could have seen how transportation would transform retail? Or how communications technologies would revolutionize warfare? Do you really think anybody looked at an IBM mainframe in the 1960s and said, “Gee, this will be a real problem for newspapers some day?”

We can expect something similar to happen with mRNA technology. Once penicillin hit the market in 1946, a “golden age” of antibiotics ensued, resulting in revolutionary new drugs being introduced every year between 1950 and 1970. We’ve seen a similar bonanza in cancer immunotherapies since Jim Allison’s breakthrough.

In marked contrast to Katalin Karikó’s earlier difficulty in winning grants for her work, the floodgates have now opened as pharma companies are now racing to develop mRNA approaches for a myriad of diseases and maladies.

The Paradox Of New Paradigms

The global activist Srdja Popović once told me that when a revolution is successful, it’s difficult to explain the previous order, because it comes to be seen as unbelievable. Just as it’s hard to imagine a world without electricity, internal combustion or antibiotics today, it will be difficult to explain our lives today to future generations.

In much the same way, we cannot understand the future through linear extrapolation. We can, of course, look at today’s breakthroughs in things like artificial intelligence, synthetic biology and quantum computing, but what we don’t see is the second or third order effects, how they will shape societies and how societies will choose to shape them.

Looking at Edison’s lightbulb would tell you nothing about radios, rock music and the counterculture of the 60s, much like taking a ride in Ford’s “Model T” would offer little insight into the suburbs and shopping malls his machine would make possible. Ecosystems are, by definition, chaotic and non-linear.

What is important is that we allow for the unexpected. It was not obvious to anyone that Katalin Karikó could ever get her idea to work, but she shouldn’t have had to risk her career to make a go of it. We’re enormously lucky that she didn’t, as so many others would have, taken an easier path. It is, in the final analysis, that one brave decision that we have to thank for what promises to be brighter days ahead.

All who wander are not lost.

— Article courtesy of the Digital Tonto blog
— Image credits: Pixabay

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

Startups, Companies, Acquisitions and Hurricanes

Startups, Companies, Acquisitions and Hurricanes

GUEST POST from Mike Shipulski

If you run a company, the most important thing you can control is how you allocate your resources. You can’t control how the people in your company will respond to input, but you can choose the projects they work on. You can’t control which features and functions your customers will like, but you can choose which features and functions become part of the next product. And you can’t control if a new technology will work, but you can choose the design space to investigate. The open question – How to choose in a way that increases your probability of success?

If you want to buy a company, the most important thing you can control is how you allocate your resources. In this case, the resources are your hard-earned money and your choice is which company to buy. The open question – How to choose in a way that increases your probability of success?

If you want to invest in a startup company, the most important thing you can control is how you allocate your resources. This case is the same as the previous one – your money is the resource and the company you choose defines how you allocate your resources. This one is a little different in that the uncertainty is greater, but so is the potential reward. Again, the same open question – How to choose in a way that increases your probability of success?

Taking a step back, the three scenarios can be generalized into a category called a “system.” And the question becomes – how to understand the system in a way that improves resource allocation and increases your probability of success?

These people systems aren’t predictable in an if-A-then-B way. But they do have personalities or dispositions. They’ve got characteristics similar to hurricanes. A hurricane’s exact path cannot be forecasted, the meteorologist can use history and environmental conditions to broadly define regions where the probability of danger is higher. The meteorologist continually monitors the current state of the hurricane (the system as it is) and tracks its position over time to get an idea of its trajectory (a system’s momentum). The key to understanding where the hurricane could go next: where it is right now (current state), how it got there (how it has behaved over time), and how have other hurricanes tracked under similar conditions (its disposition). And it’s the same for systems.

To improve your understanding of how your system may respond, understand it as it is. Define the elements and how those elements interact. Then, work backward in time to understand previous generations of the system. Which elements were improved? Which ones were added? Then, like the meteorologist, start at the system’s genesis and move forward to the present to understand its path. Use the knowledge of its path and the knowledge of systems (it’s important to be the one that improves the immature elements of the system and systems follow S-curves until the S-curve flattens) to broadly define regions where the probability of success is higher.

These methods won’t guarantee success. But, they will help you choose projects, choose acquisitions, choose technologies, and choose startups in a way that increases your probability of success.

Image credits: Pexels

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

Top 100 Innovation and Transformation Articles of 2024

Top 100 Innovation and Transformation Articles of 2024

2021 marked the re-birth of my original Blogging Innovation blog as a new blog called Human-Centered Change and Innovation.

Many of you may know that Blogging Innovation grew into the world’s most popular global innovation community before being re-branded as Innovation Excellence and being ultimately sold to DisruptorLeague.com.

Thanks to an outpouring of support I’ve ignited the fuse of this new multiple author blog around the topics of human-centered change, innovation, transformation and design.

I feel blessed that the global innovation and change professional communities have responded with a growing roster of contributing authors and more than 17,000 newsletter subscribers.

To celebrate we’ve pulled together the Top 100 Innovation and Transformation Articles of 2024 from our archive of over 2,500 articles on these topics.

We do some other rankings too.

We just published the Top 40 Innovation Bloggers of 2024 and as the volume of this blog has grown we have brought back our monthly article ranking to complement this annual one.

But enough delay, here are the 100 most popular innovation and transformation posts of 2024.

Did your favorite make the cut?

1. Organizational Debt Syndrome Poses a Threat – by Stefan Lindegaard

2. FREE Innovation Maturity Assessment – by Braden Kelley

3. The Education Business Model Canvas – by Arlen Meyers, M.D.

4. The Role of Stakeholder Analysis in Change Management – by Art Inteligencia

5. Act Like an Owner – Revisited! – by Shep Hyken

6. Iterate Your Thinking – by Dennis Stauffer

7. SpaceX is a Masterclass in Innovation Simplification – by Pete Foley

8. What is Human-Centered Change? – by Braden Kelley

9. A 90% Project Failure Rate Means You’re Doing it Wrong – by Mike Shipulski

10. Should a Bad Grade in Organic Chemistry be a Doctor Killer? – by Arlen Meyers, M.D.

11. How Netflix Built a Culture of Innovation – by Art Inteligencia

12. Fear is a Leading Indicator of Personal Growth – by Mike Shipulski

13. Sustaining Imagination is Hard – by Braden Kelley

14. No Regret Decisions: The First Steps of Leading through Hyper-Change – by Phil Buckley

15. The Art of Adaptability: How to Respond to Changing Market Conditions – by Art Inteligencia

16. Sprint Toward the Innovation Action – by Mike Shipulski

17. Marriott’s Approach to Customer Service – by Shep Hyken

18. Top 5 Future Studies Programs – by Art Inteligencia

19. Reversible versus Irreversible Decisions – by Farnham Street

20. 50 Cognitive Biases Reference – Free Download – Courtesy of TitleMax

21. Free Human-Centered Change Tools – by Braden Kelley

22. Designing an Innovation Lab: A Step-by-Step Guide – by Art Inteligencia

23. Why More Women Are Needed in Innovation – by Greg Satell

24. How to Defeat Corporate Antibodies – by Stefan Lindegaard

25. The Nine Innovation Roles – by Braden Kelley

26. Top 40 Innovation Bloggers of 2023 – Curated by Braden Kelley

27. Human-Centered Change – by Braden Kelley

28. Visual Project Charter™ – 35″ x 56″ (Poster Size) and JPG for Online Whiteboarding – by Braden Kelley

29. FutureHacking – Be Your Own Futurist – by Braden Kelley

30. ACMP Standard for Change Management® Visualization – 35″ x 56″ (Poster Size) – Association of Change Management Professionals – by Braden Kelley


Build a common language of innovation on your team


31. Overcoming Resistance to Change – by Chateau G Pato

32. Are We Abandoning Science? – by Greg Satell

33. How Networks Power Transformation – by Greg Satell

34. What Differentiates High Performing Teams – by David Burkus

35. The 6 Building Blocks of Great Teams – by David Burkus

36. Unintended Consequences. The Hidden Risk of Fast-Paced Innovation – by Pete Foley

37. The Role of Employee Training and Development in Enhancing Customer Experience – by Art Inteligencia

38. The Pyramid of Results, Motivation and Ability – by Braden Kelley

39. Your Strategy Must Reach Beyond Markets to Ecosystems – by Greg Satell

40. What is the difference between signals and trends? – by Art Inteligencia

41. Next Generation Leadership Traits and Characteristics – by Stefan Lindegaard

42. Latest Interview with the What’s Next? Podcast – Featuring Braden Kelley

43. A Tipping Point for Organizational Culture – by Janet Sernack

44. Accountability and Empowerment in Team Dynamics – by Stefan Lindegaard

45. Design Thinking for Non-Designers – by Chateau G Pato

46. The Innovation Enthusiasm Gap – by Howard Tiersky

47. The One Movie All Electric Car Designers Should Watch – by Braden Kelley

48. The Ultimate Guide to the Phase-Gate Process – by Dainora Jociute

49. Innovation Management ISO 56000 Series Explained – by Diana Porumboiu

50. How to Create an Effective Innovation Hub – by Chateau G Pato


Accelerate your change and transformation success


51. Imagination versus Knowledge – Is imagination really more important? – by Janet Sernack

52. Stoking Your Innovation Bonfire – by Braden Kelley

53. A Shortcut to Making Strategic Trade-Offs – by Geoffrey A. Moore

54. How to Make Navigating Ambiguity a Super Power – by Robyn Bolton

55. Three HOW MIGHT WE Alternatives That Actually Spark Creative Ideas – by Robyn Bolton

56. Problems vs. Solutions vs. Complaints – by Mike Shipulski

57. Innovation or Not – Liquid Trees – by Art Inteligencia

58. Everyone Clear Now on What ChatGPT is Doing? – by Geoffrey A. Moore

59. Leadership Best Quacktices from Oregon’s Dan Lanning – by Braden Kelley

60. Will Innovation Management Leverage AI in the Future? – by Jesse Nieminen

61. The Power of Position Innovation – by John Bessant

62. Creating Organizational Agility – by Howard Tiersky

63. A Case Study on High Performance Teams – by Stefan Lindegaard

64. Secrets to Overcoming Resistance to Change – by David Burkus

65. How to Write a Failure Resume – by Arlen Meyers, M.D.

66. 9 of 10 Companies Requiring Employees to Return to the Office in 2024 – by Shep Hyken

67. The Five Keys to Successful Change – by Braden Kelley

68. What is Social Analysis? – by Art Inteligencia

69. Dare to Think Differently – by Janet Sernack

70. Parallels Between the 1920’s and Today Are Frightening – by Greg Satell

71. What is Trend Spotting? – by Art Inteligencia

72. Driving Change is Not Enough – You Also Have To Survive Victory – by Greg Satell

73. 5 Simple Steps to Team Alignment – by David Burkus

74. Building a Better Change Communication Plan – by Braden Kelley

75. The Role of Leadership in Fostering a Culture of Innovation – by Art Inteligencia

76. 4 Simple Steps to Becoming Your Own Futurist – An Introduction to the FutureHacking™ methodology – by Braden Kelley

77. Four Hidden Secrets of Innovation – by Greg Satell

78. Why Organizations Struggle with Innovation – by Howard Tiersky

79. An Introduction to Strategic Foresight – by Stefan Lindegaard

80. Learning About Innovation – From a Skateboard? – by John Bessant


Get the Change Planning Toolkit


81. 800+ FREE Quote Posters – by Braden Kelley

82. Do you have a fixed or growth mindset? – by Stefan Lindegaard

83. Generation AI Replacing Generation Z – by Braden Kelley

84. The End of the Digital Revolution – by Greg Satell

85. Is AI Saving Corporate Innovation or Killing It? – by Robyn Bolton

86. The Experiment Canvas™ – 35″ x 56″ (Poster Size) – by Braden Kelley

87. America Drops Out of the Ten Most Innovative Countries – by Braden Kelley

88. 5 Essential Customer Experience Tools to Master – by Braden Kelley

89. AI as an Innovation Tool – How to Work with a Deeply Flawed Genius! – by Pete Foley

90. Four Ways To Empower Change In Your Organization – by Greg Satell

91. Agile Innovation Management – by Diana Porumboiu

92. Do Nothing More Often – by Robyn Bolton

93. Five Things Most Managers Don’t Know About Innovation – by Greg Satell

94. The Fail Fast Fallacy – by Rachel Audige

95. Top Six Trends for Innovation Management in 2025 – by Jesse Nieminen

96. How to Re-engineer the Incubation Zone – by Geoffrey A. Moore

97. Flaws in the Crawl Walk Run Methodology – by Braden Kelley

98. Master the Customer Hierarchy of Needs – by Shep Hyken

99. Rise of the Atomic Consultant – Or the Making of a Superhero – by Braden Kelley

100. A Shared Language for Radical Change – by Greg Satell

Curious which article just missed the cut? Well, here it is just for fun:

101. Is Disruption About to Claim a New Victim? – by Robyn Bolton

These are the Top 100 innovation and transformation articles of 2024 based on the number of page views. If your favorite Human-Centered Change & Innovation article didn’t make the cut, then send a tweet to @innovate and maybe we’ll consider doing a People’s Choice List for 2024.

If you’re not familiar with Human-Centered Change & Innovation, we publish 1-6 new articles every week focused on human-centered change, innovation, transformation and design insights from our roster of contributing authors and ad hoc submissions from community members. Get the articles right in your Facebook feed or on Twitter or LinkedIn too!

Editor’s Note: Human-Centered Change & Innovation is open to contributions from any and all the innovation & transformation professionals out there (practitioners, professors, researchers, consultants, authors, etc.) who have a valuable insight to share with everyone for the greater good. If you’d like to contribute, contact us.

Subscribe to Human-Centered Change & Innovation WeeklySign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.

Uber Economy is Killing Innovation, Prosperity and Entrepreneurship

Uber Economy is Killing Innovation, Prosperity and Entrepreneurship

GUEST POST from Greg Satell

Today, it seems that almost everyone wants to be the “Uber” of something, and why not? With very little capital investment, the company has completely disrupted the taxicab industry and attained a market value of over $100 billion. In an earlier era, it would have taken decades to have created that kind of impact on a global scale.

Still, we’re not exactly talking about Henry Ford and his Model T here. Or even the Boeing 707 or the IBM 360. Like Uber, those innovations quickly grew to dominance, but also unleashed incredible productivity. Uber, on the other hand, gushed red ink for more than a decade despite $25 billion invested. In 2021 it lost more than $6 billion, the company made progress in 2022 but still lost money, and it was only in 2023 that they finally made a profit.

The truth is that we have a major problem and, while Uber didn’t cause it, the company is emblematic of it. Put simply, a market economy runs on innovation. It is only through consistent gains in productivity that we can create real prosperity. The data and evidence strongly suggests that we have failed to do that for the past 50 years. We need to do better.

The Productivity Paradox Writ Large

The 20th century was, for the most part, an era of unprecedented prosperity. The emergence of electricity and internal combustion kicked off a 50-year productivity boom between 1920 and 1970. Yet after that, gains in productivity mysteriously disappeared even as business investment in computing technology increased, causing economist Robert Solow to observe that “You can see the computer age everywhere but in the productivity statistics.”

When the internet emerged in the mid-90’s things improved and everybody assumed that the mystery of the productivity paradox had been resolved. However, after 2004 productivity growth disappeared once again. Today, despite the hype surrounding things such as Web 2.0, the mobile Internet and, most recently, artificial intelligence, productivity continues to slump.

Take a closer look at Uber and you can begin to see why. Compare the $25 billion invested in the ride-sharing company with the $5 billion (worth about $45 billion today) IBM invested to build its System 360 in the early 1960s. The System 360 was considered revolutionary, changed computing forever and dominated the industry for decades.

Uber, on the other hand, launched with no hardware or software that was particularly new or revolutionary. In fact, the company used fairly ordinary technology to dis-intermediate relatively low-paid taxi dispatchers. The money invested was largely used to fend off would-be competitors through promoting the service and discounting rides.

Maybe the “productivity paradox” isn’t so mysterious after all.

Two Paths To Profitability

Anybody who’s ever taken an Economics 101 course knows that, under conditions of perfect competition, the forces of supply and demand are supposed to drive markets toward equilibrium. It is at this magical point that prices are high enough to attract supply sufficient to satisfy demand, but not any higher.

Unfortunately for anyone running a business, that equilibrium point is the same point at which economic profit disappears. So to make a profit over the long-term, managers need to alter market dynamics either through limiting competition, often through strategies such as rent seeking and regulatory capture, or by creating new markets through innovation.

As should be clear by now, the digital revolution has been relatively ineffective at creating meaningful innovation. Economists Daron Acemoglu and Pascual Restrepo refer to technologies like Uber, as well as things like automated customer service, as “so-so technologies,” because they displace workers without significantly increasing productivity.

Joseph Schumpeter pointed out long ago, market economies need innovation to fuel prosperity. Without meaningful innovation, managers are left with only strategies that limit innovation, undermine markets and impoverish society, which is what largely seems to have happened over the past few decades.

The Silicon Valley Doomsday Machine

The arrogance of Silicon Valley entrepreneurs seems so outrageous—and so childishly naive— that it is scarcely hard to believe. How could an industry that has produced so little in terms of productivity seem so sure that they’ve been “changing the world” for the better. And how have they made so much money?

The answer lies in something called increasing returns. As it turns out, under certain conditions, namely high up-front investment, negligible marginal costs, network effects and “winner-take-all markets,” the normal laws of economics can be somewhat suspended. In these conditions, it makes sense to pump as much money as possible into an early Amazon, Google or Facebook.

However this seemingly happy story has a few important downsides. First, to a large extent these technologies do not create new markets as much as they disrupt or displace old ones, which is one reason why productivity gains are so meager. Second, the conditions apply to a small set of products, namely software and consumer gadgets, which makes the Silicon Valley model a bad fit for many groundbreaking technologies.

Still, if the perception is that you can make a business viable by pumping a lot of cash into it, you can actually crowd-out a lot of good businesses with bad, albeit well-funded ones. In fact, there is increasing evidence that is exactly what is happening. Rather than an engine of prosperity, Silicon Valley is increasingly looking like a doomsday machine.

Returning To An Innovation Economy

Clearly, we cannot continue “Ubering” ourselves to death. We must return to an economy fueled by innovation, rather than disruption, which produces the kind of prosperity that lifts all boats, rather than outsized profits for a meager few. It is clearly in our power to do that, but we must begin to make better choices.

First, we need to recognize that innovation is something that people do, but instead of investing in human capital, we are actively undermining it. In the US, food insecurity has become an epidemic on college campuses. To make matters worse, the cost of college has created a student debt crisis, essentially condemning our best and brightest to decades of indentured servitude. To add insult to injury, healthcare costs continue to soar. Should we be at all surprised that entrepreneurship is in decline?

Second, we need to rebuild scientific capital. As Vannevar Bush once put it, “There must be a stream of new scientific knowledge to turn the wheels of private and public enterprise.” To take just one example, it is estimated that the $3.8 billion invested in the Human Genome Project generated nearly $800 billion of economic activity as of 2011. Clearly, we need to renew our commitment to basic research.

Finally, we need to rededicate ourselves to free and fair markets. In the United States, by almost every metric imaginable, whether it is industry concentration, occupational licensing, higher prices, lower wages or whatever else you want to look at capitalism has been weakened by poor regulation and oversight. Not surprisingly, innovation has suffered.

Perhaps most importantly, we need to shift our focus from disrupting markets to creating them, from “The Hacker Way”, to tackling grand challenges and from a reductionist approach to an economy based on dignity and well being. Make no mistake: The “Uber Economy” is not the solution, it’s the problem.

— Article courtesy of the Digital Tonto blog
— Image credits: Pixabay

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.