The Surprising Innovation History of the Bicycle

Pedal Power

GUEST POST from John Bessant

Bicycles are big business. It’s hard to get an exact figure but estimates suggest there are around 2 billion bikes in the world today. And of course they exist in all sorts of shapes and sizes — town bikes, racing bikes, mountain bikes, foldable bikes, electric bikes and many more besides. They’re available in cutting-edge high tech versions but their underlying design is very simple. They’re very green — once built they can be repaired and resurrected, some live for ages, handed on from generation to generation.

But bicycles weren’t always around and perhaps it’s worth reflecting a little more on their history, not least because it can teach us some useful lessons about innovation. In particular how (or not) to manage it for impact and scale.

In the earliest days — around 3500 BC — the Mesopotamians used them to make pottery which seems to be the first application of this breakthrough idea. The problem with using them for transport wasn’t so much the wheel as finding an axle strong enough to enable the wheels to work. It took another 300 years before new materials and better carpentry techniques led to their being fixed to chariots and ushering in the era of mobile warfare. But once the wheels started rolling they were attached to an increasing variety of military and domestic vehicles, so it was only going to be a matter of time before someone came up with the idea of using them to enable personal transportation.

Well quite a lot of time, actually. Although there’s probably a sketch for something resembling a bike in Leonardo da Vinci’s notebooks or in some other inventor’s imagination, the reality is that it wasn’t until the early 19 century that the vehicle that we know and love began to see the light of day. That shouldn’t surprise us — innovation depends on a mixture of needs and means and the idea of personal transportation never mind the technologies to enable it was not a particularly high priority. People didn’t travel far — and if they did Nature had already supplied a robust solution in the form of horses (or mules, camels and other alternatives).

The average human being can walk at around 5 km per hour so covering any distance is going to take time and effort. Enter Baron von Drais, a minor aristocrat in Germany who in 1817 came up with the ‘Laufmaschine’ — walking machine — otherwise known as the Draisienne. He was already an experienced engineer and inventor, having come up with several working prototypes for devices like a piano music recording system, a periscope, and a typewriter. (All ideas which turned out, much later, to have considerable significance but not in the form he developed them). And he had a passion for horseless transportation.

This wasn’t some idle curiosity or pet project. Times were tough in the years of the Napoleonic wars and grain prices were high, something not helped by the failure of harvests in 1816. This was the so-called ‘year without a summer’ when the fallout (literally) from a volcanic eruption in south east Asia blotted out the sun. People died of starvation — and horses had an even harder time of it, either starving themselves or else used for food. The possibilities of their being used for transportation shrank faster than the animals themselves.

Drais was also aware of new technologies and materials which he could make use of and he developed a working prototype of his machine on which he could cover the kilometres around his home town of Karlsruhe. He experimented with variations including a four wheeled passenger carriage powered by an (unlucky) servant whose job was to pedal on planks connected to the wheels. But his breakthrough idea was a two-wheeler — the Draisienne. This did away with pedals; instead the rider sat and scooted along the ground with his feet — a kind of adult version of the child’s hobby-horse.

There was nothing childish about the impact this had on moving around the place though. On 12 June 1817, a crowd gathered along the best road in Mannheim, Germany to watch him climb aboard and set out for the Schwetzinger Relaishaus (a coaching inn, located in nearby Rheinau. Less than an hour later, he was back, having completed the 13km round trip in a quarter of the time it would take to walk.

He was a man of vision — and saw the potential for what he had built. By October 1817, he had produced 3-page brochure of laufmaschine designs which pictured possible applications (such as for military couriers or in the postal service) as well as general and leisure transport. He proposed different models with both 2 and 4 wheels and even a tandem and potential customers could choose between standard machiens or customised version. The French version of the brochure, published a year later, included accessories such as lamps, an umbrella and even a sail to help with extra momentum on windy days.

Drais’s laufmaschine was pretty heavy by today’s standards, weighing in at 22kg, made mostly of wood but with hoops of iron nailed to the wheels to function as tyres. This design had an unfortunate side-effect because it made any journey on the fairly primitive roads of the time somewhat less than comfortable. At least the machine was blessed with a brake on the rear wheel; perhaps more important were some of the technologies Drais put to use in his design, like the brass bushes inside the wheel bearings (which enabled the wheels to turn freely) and a trailer to the front wheel which helped the rider maintain balance.

Drais had the vision to see the possibilities in his machine — but he didn’t really have a business model to help him create and capture value from it. Although he staged a number of impressive demonstrations around Europe the reception was mixed and once the novelty wore off the market retreated to being one for hobbyists and pleasure seekers. Riding rinks (where customers could rent a machine for an hour or so) appeared in the parks of various European cities but the mainstream dream of providing personal transportation faded. It wasn’t helped by the appalling state of the roads at the time; without any form of shock absorbers the seat, despite being well-padded, was not a comfortable place to spend much of the day.

‘All’s fair in love and war’ is a principle which often also seems to extend to innovation. The pattern is one of imitation and the first mover is not always the one who can gain advantage, especially if they have inadequate protection for their intellectual property. Drais had tried to patent his idea but it only applied locally, a loophole quickly spotted and exploited by an Englishman, Denis Johnson. He’d seen the early demonstrations and guessed at the significant opportunity such machines might offer. So he set about patenting the idea in England and then building in more systematic fashion a business model around which it might be exploited.

Johnson was a coachmaker so he quickly worked out how to build the machines; what he had to do was create and grow the market. He advertised, offered demonstration machines, organised racing competitions and even established two riding schools where people could learn the skills involved. He adapted the product so that his ‘pedestrian curricle’ had a Ladies Walking Machine variant with a lower saddle such that women could mount the machine decorously.

He was particularly successful in attracting the attention of the young men of the time. This was the era of Beau Brummel and the London Dandies and they enthusiastically took up the idea, adding to it all sorts of fashion accessories — boots, gloves, etc — without which the daredevil owner would not be seen about town. Its popularity amongst this group was heightened by the inherently unsafe nature of something ridden about narrow streets at (relatively) high speed which offered thrills (and accidents) a-plenty until an increasing number of city authorities began banning the machine

It was an expensive hobby. Retailing for around £10 (about £750) it carried additional running costs. Riders wore out their expensive leather boots surprisingly rapidly, and the imposition of fines of £2 (£150 today) for riding on the pavement added to the burden. The fashion for draisiennes began to fade but the real reason for their failure to reach a wider market was down to much simpler economics. By 1820, the price of oats had come back down to pre-1815 levels, and horses were readily available to those who could afford them.

Innovation isn’t just a gleam in the eye, a flash of insight and then instant creation. It’s a lot of hard work, experimentation and improvisation to bring that dream to reality. But even when the first fruits are there there’s still plenty of room for improvement. As Johnson showed, there’s plenty of scope for doing things better, sorting out the bugs and wrinkles, continuously improving on the design. It’s a pattern of restless experimentation, pushing the frontiers of what might be possible. Metalworking technology in particular was improving such that machines could be made strong and (relatively) light, displacing wood as the only means of construction. People explored using different numbers of wheels — two, three, four, more even — opening up the possibilities of carrying multiple passengers.

But innovation is also about sudden leaps, of someone else very often picking up the baton and giving the wheel an extra hard push that sends it off in a new direction. Sometimes this is about timing — a technology which wasn’t available earlier on suddenly appears . or a market which didn’t exist begins to grow to the point where there is a demand for the innovation, pulling it in new refreshed directions. Whatever, this pattern of ‘punctuated equilibrium’ is at the heart of most innovation stories. And in the case of the bicycle it certainly was.

If you are going to have a mysterious legend to weave about the next phase of bicycle innovation where better to do it than Scotland? Land of towering mountains, shady glens, deep lochs and plenty of rain to fill them. Shrouded in mists and secrecy — and home, amongst others to a blacksmith named Kirkpatrick McMillan.

Macmillan completed construction of a pedal driven bicycle of wood in 1839, one which also included iron-rimmed wooden wheels, a steerable wheel in the front and a larger wheel in the rear which was connected to pedals via connecting rods. Various accounts tell of his travelling about the roads near Kier and regularly making the journey to the town of Dumfries (14 miles away) in less than an hour.

He was a modest man and his claim to innovation fame doesn’t rest on patents so much as PR, particularly the research of his relative James Johnston in the 1890s. Johnston wanted “to prove that to my native country of Dumfries belongs the honour of being the birthplace of the invention of the bicycle”. He might have been a little creative with his reworking of history, suggesting for example that Macmillan was the gentleman in question in a Glasgow newspaper report in 1842 of an accident in which an anonymous “gentleman from Dumfries-shire… bestride a velocipede… of ingenious design” knocked over a pedestrian in the Gorbals and was fined five British shillings”.

A criminal record is perhaps not the strongest piece of intellectual property protection and a more robust claim to be the pedal innovator lies with the French. Specifically a young blacksmith and machinist from the town of Nancy called Pierre Lallement. He developed his ideas in 1863 and showed them off publicly during the next year; moved to the USA in 1865 and in the following year registered US Patent number 59915 for his version of the ‘velocipede’.

So most people give the pedal crown — and with it the title of inventor of the modern bicycle — to Lallement. But he was not alone.

In the early 1860s Pierre Michaux (yet another blacksmith) had a successful business producing parts for the carriage trade and had diversified into making “vélocipède à pédales” on a small scale. Across Paris two brothers, Andre and Rene Olivier were students but also came from a wealthy family. This enabled them not only to be early adopters of the bicycle, (enjoying a memorable road trip in 1865 from Avignon to Paris which took them 8 days) but also to become the first entrepreneurs in the game. They saw the considerable potential in pedal cycles and teamed up with Michaux, brought in another friend George de la Boublise and in 1868 set up a partnership to make and sell them.

For a while France (and Paris with its smooth flat roads) became the focus of a market which grew in popularity on both sides of the Atlantic. But a combination of the Franco-Prussian war of 1870 (which stopped French cyclists) and bad roads (whose boneshaking characteristics held back even the hardiest of north American users) meant that the centre of innovation gravity moved to Britain.

Pedal power depends on how much you can push — and cycle design next began to explore ways of maximising this. Two wheels of equal size aren’t particularly good in this equation; better is to have as long a stride as possible since the larger the wheel, the further you can go with one rotation of the pedals. So wheels became higher and higher, the only limit being the length of the rider’s legs. It’s an idea which is good for propulsion but not so good for steering or balance. And so bicycles became ever more exotic looking in their arrangements of wheels and sizes, not least giving birth to the familiar ‘penny farthing’ shape.

But although high wheelers experienced some market growth they weren’t really practical for the average man or woman on the street. Enter John Kemp Starley, an English inventor who came up with a winning idea for a “safety bicycle”, one which would appeal to a much bigger market. His first model was the “Ariel” launched in 1871 and although still featuring wheels of different sizes it was getting closer to a configuration which people would accept. Not least because he integrated many of the key features which people valued — improvements in stability, comfort, usability _especially steering), and all at a price they could afford.

Starley was a classic innovator and over the next fifteen years he developed an increasing range of machines, drawing in ideas and technologies from all over the place. Learning all the time with the market about what it actually wanted, not least through the experience of dissatisfied riders.

For example he sorted out the problem with the wheels. Early bikes had heavy wooden wheels with iron rims but in 1849 William Stanley had invented steel-wheel spider spokes. In 1868, Eugene Meyer in Paris developed an all-metal wheel that relied on the tension of wires rather than compression of heavy metal spokes to achieve structural integrity. Two years later, William Henry James Grout, a builder of velocipedes from Shadwell, London, patented spokes that had eyed nipples at the outer end. Starley drew these ideas together to create (and patent) the spoked wheel in 1874 which gave a much more comfortable ride because of its sprung nature and it also made bicycles much lighter.

In similar fashion he took other ideas and used them as ingredients in the innovation soup which was now coming nicely to the boil. Finally in 1885, Starley introduced the “Rover.” With its nearly equal-sized wheels, centre pivot steering and differential gears that operate with a chain drive, Starley’s “Rover” was the first highly practical iteration of the bicycle. Like Henry Ford with his Model T twenty years later he’d produced the bicycle for Everyman (and woman). It became the dominant design — and it’s pretty much the same shape as we’d recognise today.

Starley’s work kick-started the industry into its growth phase. His company grew and with it the product range, opening up cycling to a wide market in the ways Baron von Drais had dreamt about seventy years earlier. The safety bicycle completely displaced the high wheeler and by 1889 there were around 200,000 bicycles on the roads of Europe.

Ten years later over a million machines were being pedalled around the world. Innovation didn’t stop there — and with each new development the pace of growth accelerated. Pneumatic tyres made of rubber made for a smoother ride, chain drives meant the power came from the rear wheel leaving the front to steer and making cornering easier. The application of gears helped tame even the most stubborn of inclines and opened up the whole landscape to conquest by bicycle. And inventors began looking to provide alternatives to legs as the main power source, with a battery electric cycle appearing. And over in Germany Gottfried Daimler played around with hooking an internal combustion engine up to a cycle to create the motorbike…..

So it’s not entirely surprising that we now have 2 billion bicycles pedalling their way along roads and up and down the mountainsides of the world. There’s still plenty of scope for further innovation, for branching in new directions and picking up old ones — the e-scooter craze looks like a good candidate for becoming the next major shift, with not a few nods back in the direction of good old Baron von Drais. What’s clear , though, is that these innovations will only take hold and become widely adopted if we pay attention to working at the system level.

Successful scaling of innovation is all about wheels within wheels…

(A little song to close with….)

You can listen to a podcast of this story here

And watch a video version on my YouTube channel here

If you’d like more songs, stories and other resources on the innovation theme, check out my website here

And if you’d like to learn with me take a look at my online courses here

Originally published at https://johnbessant.substack.com on July 24, 2026.

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New CX Leader? Why an Independent Audit Belongs in Your First 90 Days

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New CX Leader? Why an Independent Audit Belongs in Your First 90 Days

by Braden Kelley and Art Inteligencia

Walking into a new customer experience role — CX lead, CMO, VP of Customer Success — comes with an unspoken clock. You have a window, usually measured in months rather than years, where you’re expected to understand what you inherited and start showing you can improve it. Most new leaders spend that window doing exactly the wrong thing first.

The trap of trusting what you’re told

Every new leader inherits a story about the customer experience, told by the people who built it. It’s rarely dishonest — it’s just inevitably shaped by whoever’s closest to each part of the business, and by what the previous regime chose to measure and report upward. Spending your first quarter absorbing that story, then acting on it, means your first major decisions are built on someone else’s blind spots, not your own judgment.

Why independence matters more here than almost anywhere else

An internal review, run by your own team in your first months, has a structural problem: the people doing the reviewing often have a stake in what it finds, whether or not anyone intends that. A team that built the current onboarding flow isn’t the ideal group to independently evaluate whether it’s working. An independent audit doesn’t carry that conflict — it walks the journey and evaluates the data with no incentive to protect any particular decision that came before you.

It gives you a real baseline, not a borrowed one

Six months from now, when you’re reporting on what’s improved, you’ll want a credible “before” picture that isn’t just a set of dashboard screenshots someone else built. An audit run at the start of your tenure — covering validated personas, a current journey map, an honest read of the existing data, firsthand walkthroughs of the real experience, and a look at how you compare to competitors — becomes the fixed point everything else gets measured against. Without it, your progress reporting six or twelve months in rests on metrics your predecessor chose, defined, and possibly optimized for their own narrative.

It tells you where to spend your political capital first

New leaders get a limited amount of organizational goodwill to spend on change, and spending it on the wrong priority is one of the most common ways a promising tenure stalls early. A structured audit gives you a prioritized, evidence-based view of where the real gaps are — not the loudest complaint in the building, not the pet project someone’s been pushing for years, but where the customer data and the firsthand journey walk actually point. That’s a far stronger position to walk into your first big budget conversation from than “my gut says we should fix X.”

It’s a credibility move, not just a diagnostic one

There’s also a simple organizational-politics benefit that’s easy to underrate: commissioning an outside, objective audit early signals that you’re not there to defend the status quo or protect any particular team’s prior decisions. That reads very differently to a skeptical organization than announcing changes based on your own first impressions, however well-founded those impressions might be.

Where to start

If you’re inside your first few months in a CX role and want to see where an independent read of your team’s own current state stands, the Customer Experience Audit Checklist walks through the same five activities a full audit runs. And if you want a defensible number to bring into your first budget conversation, the CX ROI Calculator is a fast way to get one. When you’re ready for the real diagnostic, a Customer Experience Audit run in your first 90 days gives you the independent baseline every decision after that can stand on.

Download the Customer Experience Audit Checklist as a PDFImage Credits: Pexels

Content Authenticity Statement: The topic area, key elements to focus on, etc. were decisions made by Braden Kelley, with a little help from Claude to clean up the article.

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Do You Have Too Many Balls in the Air?

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Do You Have Too Many Balls in the Air?

GUEST POST from Mike Shipulski

In today’s world of continuous improvement, everything is seen as an opportunity for improvement. The good news is things are improving. But the bad news is without governance and good judgement, things can flip from “lots of opportunity for improvement” to “nothing is good enough.” And when that happens people would rather hang their heads than stick out their necks.

When there’s an improvement goal is propose like this “We’ve got to improve the throughput of process A by 12% over the next three months.” a company that respects their people should want (and expect) responses like these:

As you know, the team is already working to improve processes C, D, and E and we’re behind on those improvement projects. Is improvement of process A more important than the other three? If so, which project do you want to stop so we can start work on process A? If not, can we wait until we finish one of the existing projects before we start a new one? If not, why are you overloading us when we’re making it clear we already have too much work?

Are we missing customer ship dates on process A? If so, shouldn’t we move resources to process A right now to work off the backlog? If we have no extra resources, let’s authorize some overtime so we can catch up. If not, why is it okay to tolerate late shipments to our customers? Are you saying you want us to do more improvement work AND increase production without overtime?

That’s a pretty specific improvement goal. What are the top three root causes for reduced throughput? Well, if the first part of the improvement is to define the root causes, how do you know we can achieve 12% improvement in 3 months? We learned in our training that Deming said all targets are artificial. Are you trying to impose an artificial improvement target and set us up for failure?

Continuous improvement is infinitely good, but resources are finite. Like it or not, continuous improvement work WILL be bound by the resources on hand. Might as well ask for continuous improvement work in a way that’s in line with the reality of the team’s capacity.

And one thing to remember for all projects – there’s no partial credit. When you’re 80% done on ten projects, zero projects are done. It’s infinitely better to be 100% done on a single project.

Image credits: Pixabay

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2026 Customer Service and CX Trend Predictions

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2026 Customer Service and CX Trend Predictions

GUEST POST from Shep Hyken

Welcome to my annual article featuring customer service and customer experience (CX) trends and predictions. This year is another two-part article divided into two specific categories. Part One features trends and predictions that have little or nothing to do with AI. It may be that technology, including AI, helps drive the trend, but the overarching concept is not specific to AI. Part Two (coming next week) will include my AI and technology predictions. With that in mind, here are the first five of my 10 predictions:

When it comes to customer service and CX, customers continue to be smarter. I’ve opened with this same trend for several years, and it is becoming more relevant each year. Our customers know what great customer service is. They don’t compare you to your direct competitor. Instead, they compare you to their favorite company or brand to do business with. That sets a subconscious benchmark for what they consider good service. Brands like Amazon, Apple, Costco, Ritz-Carlton and others known for delivering a great experience are who you are now compared to.
Proactive service will become a new competitive advantage. Convenience and speed have been important competitive differentiators. Now, we can add the concept of proactive service. Proactive service equates to “no service,” meaning customers don’t have to reach out because you’ve already fixed the problem or communicated with them before they needed to. For example, you receive an email or text message from your internet provider informing you of an outage, with updates on the progress they are making to repair the problem. Or the airline that informs you of a travel delay and automatically re-books you so you don’t have to pick up the phone and wait on hold to talk to an agent.
Customers will expect companies to value and respect their time. My annual customer service and CX research finds that the importance of a company valuing its customers’ time is increasingly important. Customers equate speed with respect, and anything that they consider a waste of time, such as waiting on hold, repeating themselves, being transferred numerous times or anything else that steals their time away, is inconvenient friction that will cause customers to switch to a competitor, hoping for a better experience.
Employees will expect the same experience internally that customers expect externally. Getting and keeping good employees has never been more important—and difficult. Customer experience starts on the inside of the organization. Treating employees the same way you want customers to be treated sets a standard. In addition, employees can’t deliver a great experience if they are struggling with broken systems, unclear processes and outdated tools. While I’ve written about this many times over the years, it seems to be one of the topics that comes up in almost every conversation I have with the leadership of a company.
Trust will be recognized as part of the customer experience. Of course, the customer expects you to do what you say you will do. It’s always been that way. Customers want to do business with a company that delivers what it promises, with integrity and aligned values. And when companies deliver a better customer experience, they earn greater trust from their customers. (According to my annual CX research, 83% of consumers said a good customer experience increases their trust in a company or brand.) However, no matter how friendly and nice a company treats its customers, if the customer doesn’t get what they expect or there are ethical issues, it’s game over.

Most of these trends and predictions shouldn’t surprise you. The customer’s knowledge and experience with companies that excel in CX play a role in putting these trends and predictions in the spotlight. To make these trends actionable, consider the following:

Don’t compare your service experience to your direct competition, but instead to your favorite companies to do business with outside of your industry.
Be proactive and fix problems or communicate with customers before they contact you.
Identify the friction that causes customers to “waste time,” and work to eliminate or mitigate the friction.
Treat your employees the way you want your customers to be treated. Your CX strategy starts on the inside of your company.
Do what you promise. Whenever a customer decides to do business with you, there is an implied contract. In addition, an ethical breach becomes a bigger issue than just losing one customer. It puts your company’s reputation in jeopardy.

These trends aren’t complicated, but they are important. When companies focus on what customers value most (ease, honesty and consistency), they earn trust, loyalty and repeat business.

This article was originally published on Forbes.com.

Image Credits: Shep Hyken

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The Actual Future of AI

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The Actual Future of AI

GUEST POST from Geoffrey Moore

AI is the number one topic in the boardroom this year, and everybody wants to know how it is going to play out and what that means for their enterprise. Well, it’s not as if we have never seen versions of this movie before. How did the Internet play out? The Worldwide Web? eCommerce? Cloud computing? Smartphones? Digital marketing? Ride-sharing? Streaming media?

This is the Technology Adoption Life Cycle at work, for sure, and has been the basis of my life’s work and that of many colleagues as well. That said, however, most of our time has been spent helping clients see how best to navigate the current state of that life cycle, either as a disruptor or a disruptee. That’s all well and good, but what the board really wants to know is what can we expect from the end state. Where will all this land, and what future do we need to prepare for?

To answer this question properly we need to lay out the landscape of work along two axes (shockingly, creating a 2X2 matrix, the gold standard for all consulting models). One axis discriminates between output that is differentiating, giving customers a reason to choose your offers over those of your competitors, in contrast to work that is industry standard, things every competitor is expected to deliver. The other axis discriminates on the basis of risk exposure, distinguishing between outcomes that are mission-critical where failure is not an option, in contrast to outcomes that can tolerate a certain amount of scrap or rework.

We call this the core/context framework, and when overlaid onto the future of AI, it can look something like this:

Core Context Framework Geoffrey Moore

In the context of this diagram here is how I predict the next ten years of AI will play out:

1. Stupid stuff first. One thing to which we will all testify is that there is no lack of stupid stuff encumbering the workflow of our daily lives. Wherever bureaucracy reigns, there will be an unending stream of compliance requirements, be that in the public or the private sector, and we suffer this burden because it does underpin the rule of law, albeit onerously.

Fulfilling these requirements does not take creative genius, it takes attention to detail and considerable patience. Humans are not strong on either front, but AI is, and this is where enterprises are already weighing in and will continue to do so for the rest of the decade and more.

That said, the ROI from such efforts is modest. Basically, we are automating an inefficient system, which does reduce cost, and does free up human talent to be used elsewhere. But what we find is that human talent is not as fungible as we would want, many displaced workers cannot find employment at a comparable salary, and the rest of the enterprise is not improved in any marked way. Things overall are better, but not a lot better.

2. Cool stuff in parallel. When it comes to new technology, wherever the risk barrier is low, technology enthusiasts will lean in regardless, whether that be on their own time or their employer’s. What they are doing is playing with an inefficient system, seeing what the bright new shiny object might bring to the table. This does take creative genius as well as some creative license, so once again, patience is required, but this time it is on the part of the investor or supervisor.

That said, in the domain of consumer products and services, there is the potential for blockbuster ROI here, as any number of freemium plays have demonstrated in the past. Many are short-lived, to be sure (remember ringtones?), but in their short life, they can capture an extraordinary amount of discretionary spend. And others can mature into abiding infrastructure as search, messaging, and file sharing have all demonstrated.

The key here is that these are not mission-critical and, therefore, do not attract regulatory regimes. If and when they should do so, as is happening with social media now, then their economics can turn upside down in a hurry.

3. Serious stuff takes time. This is where most of the big and abiding ROI will come from. When work is mission-critical but not differentiating, it requires considerable investment in table-stakes processes, which garner no premium in the marketplace. To be brutally honest, there is no prize for doing this work well but considerable penalties for any mistakes you make (think ransomware for a bone-chilling example).

In the 1990s, there was an Internet-enabled revolution in enterprise manufacturing that introduced global outsourcing as a high-ROI way to address mission-critical context workloads—move the work from your company, where it is context, to their company, where it is core. This was a hugely disruptive innovation, allowing the economies of China, India, and now Southeast Asia, to expand at exponential rates, creating increasingly vibrant middle classes where there were none before. However, these benefits have come with a price, both in terms of geopolitical risks, supply chain vulnerabilities, and societal downsides, all of which we are still trying to come to terms with.

Here, AI can have a major impact, not by automating an efficient system, but by completely reengineering it. This will entail on-shoring a lot of manufacturing and displacing a lot of call centers as we introduce more and more AI into these mission-critical workflows. The gains will be in faster response to changing market demands, better returns from high-variability small-volume manufacturing runs, and reduced scrap and rework. At the outset, these changes will entail a considerable amount of human-in-the-loop processing, but eventually, because AI-enabled systems need never stop learning, the human will become the biggest source of error in the system, and we will transition to full autonomy (self-driving cars will be a case study of this transition).

4. Game-changing happens when it happens. There is a reason why so many billionaires have appeared in my lifetime (I personally forgot to become one). Their fortunes are the natural outcome whenever a disruptive innovation does not simply reengineer the existing inefficient system but instead completely replaces it. Amazon Prime, Uber, Netflix, Salesforce, NVIDIA, Apple — each company categorically changed the landscape, rendering the incumbents irrelevant, redirecting the cash flows of their entire industry to flow past their doors.

These outcomes are inevitable, but they are also unpredictable. They are what puts the venture in venture capital. The good news for incumbents is that they do not happen very often, and even when they appear to be succeeding, they can still stumble and fall. That said, sooner or later there will be a reckoning, and that is when the incumbents need to activate their Transformation Zone if they are going to survive the transition.

My altruistic wish is that for AI, this time around, the target will be the public sector. Higher education, social services, healthcare, and law enforcement are all staggering under increasingly untenable demands accompanied by shrinking workforces and restricted budgets. All of them are target-rich environments for applying AI both to stupid stuff and serious stuff. We have never disrupted these sanctums in the past, each having been ruled by regulatory regimes and professional guilds that have deeply conservative roots blocking the kinds of changes that are now needed. Displacing these systems will take decades, but the ROI, both financial and social, would be truly game-changing.

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

— Image credit: Gemini

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Customer Experience Audit for B2B SaaS

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What Makes This Journey Different

Customer Experience Audit for B2B SaaS

by Braden Kelley and Art Inteligencia

Most customer experience frameworks are written with a single decision-maker in mind — one person, one moment of dissatisfaction, one chance to leave. B2B SaaS almost never works that way, and an audit approach borrowed from consumer retail will miss most of what actually matters in a software buying and renewal relationship.

The journey has more than one customer in it

A single SaaS account often includes a buyer who approved the budget, an admin who configured the product, and a set of end users who never spoke to sales at all and may not even know your company name. Each of these roles experiences a completely different journey, forms a completely different opinion, and has completely different influence over renewal. An audit that only interviews the buyer — the person easiest to reach — misses the end users whose day-to-day frustration is often what actually drives churn, quietly, long before a renewal conversation happens.

Onboarding failures don’t show up until months later

In consumer contexts, a bad first experience usually shows up immediately — a return, a one-star review, a quick churn. In B2B SaaS, a confusing onboarding often doesn’t kill the relationship on day one. It just means the product never gets adopted the way it was sold to be used, usage stays shallow, and the account quietly becomes a non-renewal a year later for reasons that trace directly back to week one. Walking the onboarding journey firsthand — not reviewing the onboarding flowchart, but actually going through it as a new user would — is where this kind of audit consistently finds the most expensive gaps.

Support tickets are a lagging indicator, not a leading one

By the time a SaaS customer files a support ticket, they’ve usually already tried to solve the problem themselves, asked a colleague, checked the help docs, and given up more than once. The ticket is the tip of a much larger iceberg of friction that a support-ticket dashboard alone will never show you. This is exactly why data evaluation in an audit has to be paired with firsthand journey walking — the tickets tell you what people were frustrated enough to report; the journey walk tells you everything they weren’t.

Expansion revenue depends on trust building quietly in the background

Upsell and cross-sell in SaaS rarely happen through a single sales conversation — they happen because a champion inside the account has quietly built confidence in the product over months of ordinary use. Every piece of friction in that ordinary use is a small tax on that trust, invisible individually, but cumulative. An audit that maps the full post-sale journey — not just the support-facing parts — is usually where the connection between “small usability annoyance” and “expansion revenue we didn’t get” becomes visible for the first time.

Competitive benchmarking means something different here

In B2B SaaS, your real competitive benchmark often isn’t your closest direct competitor — it’s the best onboarding flow or support experience your buyer has encountered anywhere in their software stack. B2B buyers import their expectations from whatever consumer-grade product experience they use daily, which means “good enough” is a moving target set well outside your own category.

Where to start

If any of this sounds like it’s describing gaps you suspect exist but haven’t confirmed, the Customer Experience Revenue Leakage Self-Assessment is a good first step to see where your own program stands across the five core audit activities. From there, a Customer Experience Audit scoped specifically to a multi-stakeholder SaaS journey — buyer, admin, and end user — finds what a single-persona review structurally can’t.

Download the Customer Experience Audit Checklist as a PDFImage Credits: Pexels

Content Authenticity Statement: The topic area, key elements to focus on, etc. were decisions made by Braden Kelley, with a little help from Claude to clean up the article.

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The Revenue Hiding In Plain Sight

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The Revenue Hiding In Plain Sight

by Braden Kelley and Art Inteligencia

Why your gut already knows something’s wrong, and how to finally prove it.

You’ve seen it before. The numbers look okay on paper, but something just doesn’t feel right. Churn is creeping up. Conversions aren’t where they should be. Your support team is busier than ever. Yet, when you dig into the dashboards, nothing is jumping out and screaming for your attention.

So, like so many leaders do, you wait. You hope it’s a blip. You tell yourself the team will course correct. But deep down, you already know what’s really going on… Your customers are quietly voting with their feet.

Here’s the hard truth: The biggest threats to your revenue aren’t always obvious. They’re hiding in the frustrating onboarding flow your team has grown numb to. They’re buried in the clunky renewal process that only your customers seem to notice. They’re tucked away in the dozen micro-moments of friction you’ve accepted as “just the way things are.”

If You Can’t See It, You Can’t Fix It

For years, we’ve obsessed over measuring sentiment. NPS, CSAT, and star ratings all have their place. But as an experience designer, I can tell you this: sentiment doesn’t always open up a spreadsheet. Revenue does.

The problem is, most organizations don’t have a way to connect those frustrating customer moments to the bottom line. The result? CX initiatives get deprioritized, underfunded, or worse… they become shelfware because leaders can’t see the business case to act.

That’s exactly why I created the CX Revenue Leak Self-Assessment.

Five Minutes To Clarity

This isn’t just another survey. It’s a reality check for growth-minded leaders. In just five minutes, you’ll answer seven pointed questions about churn, conversions, support costs, renewals, customer sentiment, visibility, and your team’s ability to act. What you get in return is immediate clarity.

You’ll walk away with a Leak Score that tells you if you’re in a low, medium, or high-risk category, a laser-focused tip you can act on today, and a clear path forward. No email gate to get your results. No fluff. Just the truth about where your revenue is at risk.

So, if that nagging feeling hasn’t gone away, don’t ignore it. Take the CX Revenue Leak Self-Assessment right now and finally put a number to what your gut has been trying to tell you.

From “How Bad Is It?” To “How Much Can We Recover?”

Once you know where the leak is coming from, the next logical question is always, “how much is this actually costing us?” That’s where our CX ROI Calculator comes in. It’s the perfect companion to your results, helping you model a realistic, defensible range of recoverable revenue in seconds. It’s not the focus, but it’s the tool that will get your CFO nodding their head.

When You Need More Than a Quick Fix

Sometimes, a tip and a number are enough to get the ball rolling. Other times, you need to go deeper. You need to uncover the root cause of that leak, prioritize what to do first, and build a roadmap your team will actually adopt. Not one that collects dust.

That’s the heart of our independent Customer Experience Audit. It’s built on a simple belief: human-centered change only works when it’s paired with a business case that’s undeniable. That’s why we don’t just hand you a report, we deliver a 3-week action plan with effort vs. impact and estimated revenue lift for each of your top priorities.

The Cost of Waiting Is Greater Than You Think

Every day you wait to address that friction is another day of lost revenue you won’t get back. The good news? You don’t have to boil the ocean to make progress. You just need to start by shining a light on your biggest leak.

So, do what great leaders do. Get curious. Get clarity. Then, get moving.

Start Your 5-Minute Assessment Now

Your customers are already telling you something. It’s time to hear what their actions are saying about your revenue.

Image Credits: Microsoft AI

Content Authenticity Statement: The topic area, key elements to focus on, etc. were decisions made by Braden Kelley, with a little help from Microsoft AI to clean up the article.

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Never Trust a Guru

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Never Trust a Guru

GUEST POST from Greg Satell

In 2005 W. Chan Kim and Renée published Blue Ocean Strategy, which found that “blue ocean” launches, those in new categories without competition, far outperformed the shark-infested “red ocean” line extensions that are the norm in the corporate world. It was an immediate hit, selling over 3.5 million copies.

Bain consultants Chris Zook and James Allen’ published, Profit from the Core, around the same time. They found that firms that focused on their ”core” far outperformed those who strayed. For example, they warned that Amazon was putting itself from peril for expanding its business beyond books and predicted dire results.

Clearly, none of this makes sense. How can you both “focus on your core” and seek out “blue oceans?” It betrays logic that both strategies could outperform one another. Today, Amazon makes most of its money outside of books. Yes, new markets lack competitors, but they also lack customers. The truth is that most business research is surprisingly shoddy.

Cargo Cult Science

When Richard Feynman took the podium to give the commencement speech at CalTech in 1974, he told the strange story of cargo cults. In certain islands in the South Pacific, he explained, tribal societies had seen troops build airfields during World War and were impressed with the valuable cargo that arrived at the bases.

After the troops left, the island societies built their own airfields, complete with mock radios, aircraft and mimicked military drills in the hopes of attracting cargo themselves. It seems more than a little silly, and of course, no cargo ever came. Yet these tribal societies persisted in their strange behaviors.

Feynman’s point was that we can’t merely mimic behaviors and expect to get results. To illustrate what he meant, he told a story about going to a new-age resort where people were learning reflexology. A man was sitting in a hot tub rubbing a woman’s big toe and asking the instructor, “Is this the pituitary?” Unable to contain himself, the great physicist blurted out, “You’re a hell of a long way from the pituitary, man.”

What makes science real is not fancy sounding words or slick charts with numbers on them. Business gurus often boast of their “research” that consists of hundreds of case study interviews and large databases containing data on thousands of firms, but without the proper methods and controls, those things are meaningless.

The Problem With Case Studies

Organizations are often inscrutable and hard to research. That’s why the preferred mode of analysis is case studies in which insiders are interviewed and a particular situation is interpreted by investigators. These can be helpful, but they also have severe limitations.

First, with shareholders and customers to please, managers are rarely eager to talk about failures. So we usually only hear about successes. Those, of course, are important but also subject to survivorship bias. For example, if a risky strategy results in 1% of the firms being wildly successful and 99% going out of business, then we’ll tend to hear glowing accounts of that lucky 1% and we’ll miss the vast majority that flamed out.

Another issue with the case study method is that it is necessarily limited. When researchers did a case study on a company I used to run, to take just one example, they interviewed insiders (including me) and did their best to interpret what they heard and what they could glean from background information regarding the market.

While I don’t think anything was inaccurate, it wasn’t exactly the truth either. Only a handful of people were interviewed, almost all of them were concentrated in a single part of the business and none of them, besides me, were involved in making decisions. The issues presented in the case study simply weren’t the ones we were actually wrestling with.

The problem with case studies is that they offer little to no documentation. In more rigorous fields like, say, sociology or psychology, researchers are expected to share their data so that others can interpret it. Unfortunately, that’s rarely true in business research.

Working Around The Glitches In Our Brains’ Machinery

We tend to imagine that our minds are some sort of machines, recording what we see and hear, then storing those experiences away to be retrieved at a later time, but that’s not how our brains work at all. Humans have a need to build narratives. We like things to fit into neat patterns and fill in the gaps in our knowledge so that everything makes sense.

Psychologists often point to a halo effect, the tendency for an impression created in one area to influence opinion in another. For example, when someone is physically attractive, we tend to infer other good qualities and when a company is successful, we tend to think other good things about it.

The truth is that our thinking is riddled with subtle yet predictable biases. We are apt to be influenced not by the most rigorous information, but what we can most readily access. We make confounding errors that confuse correlation with causality and then look for information that confirms our judgments while discounting evidence to the contrary.

Unfortunately, so many of the popular management ideas today come from people who never actually operated a business, such as business school professors and consultants. These are often people who’ve never failed. They’ve been told that they’re smart all their lives and expect others to be impressed by their ideas, not to examine them thoroughly.

That’s why it’s so important to not to believe everything you think, there are simply too many ways to get things wrong and so few ways to get things right.

It’s More Important To Be Careful Than Smart

When I lived in Poland, a common aphorism advised that “life is cruel, and full of traps.” From an American perspective, the aphorism can be a bit of a culture shock. We tend to believe in the power of positivity, the American dream and the can-do spirit. Negativity can be seen as something worse than a weakness, both an indulgence and a privation at the same time.

Over the years, however, I came to respect the Poles’ innate suspicion. The truth is that we are far too easily fooled and taken in by those prey on the glitches in our cognitive machinery. Often business gurus have fooled themselves. They believe they have special powers of insight and get taken in by the glitches we all have in our mental machinery.

We get taken in because we want their claims to be true. We’d like to think that there is a secret we’re missing, that there’s a black magic that we’re not privy to and, if we prove our worth and obtain access to a few simple truths, we’ll capture the success that eludes us. Things can seem simple in a PowerPoint deck, but the truth is that the world is a messy place.

That’s why we need to train ourselves to ask the tough questions. What are we not seeing? What data is missing? What are alternative interpretations for the evidence being presented? It’s more important to be careful than smart. We can only make decisions on higher or lower levels of confidence. In the real world, there are no “sure things.”

— Article courtesy of the Digital Tonto blog
— Image credit: Pexels

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How to Lead Cross-Functional Teams Without Cracking

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How to Lead Cross-Functional Teams Without Cracking

GUEST POST from David Burkus

You’ve just been asked to lead a new team. But here’s the catch: it’s not really your team. It’s a group pulled together from different departments – sales, marketing, product, maybe even someone from legal whose job seems to be vetoing everything. These aren’t people you hired. They don’t report to you. And they probably don’t report to each other either.

You’ve been handed what might be called a “project committee” or “task force,” but what you really have is a cross-functional team. And while cross-functional teams should be engines of innovation, agility, and organizational alignment, the truth is most of them don’t work very well.

But they can, if you lead them the right way.

The Promise and Problem of Cross-Functional Teams

In theory, cross-functional teams are supposed to break down silos, accelerate execution, and bring diverse perspectives to complex problems. And sometimes they do.

But more often than not, they stall out. One study found that 75% of cross-functional teams are actually dysfunctional—they miss deadlines, blow budgets, or fail to stay aligned with organizational priorities. And it’s not because the individuals aren’t talented. It’s because collaboration across departments requires a different kind of leadership. One that starts with structure, not just speed.

Too many team leaders, especially those new to cross-functional work, start with the work itself. They jump straight into assigning tasks, setting up meetings, and building timelines. That seems logical, it’s a project after all.

But if you don’t pause to clarify goals, define roles, and build new communication norms, your team will default back to the ways of working they know best—the ways of working from their own silos. And that means your team will function more like a loosely affiliated group than a truly collaborative unit.

Why Most Approaches Fail

Cross-functional dysfunction isn’t about poor communication, it’s about misaligned expectations. Everyone brings different priorities, pressures, and mental models into the room. The marketer thinks about brand. The engineer thinks about feasibility. The legal team thinks about risk. And no one is wrong.

But if you don’t create a shared understanding early, those different viewpoints don’t complement each other—they compete. Left unchecked, people stick to their departmental defaults, and the very diversity that was supposed to spark innovation becomes a source of friction.

How Cross-Functional Teams Win

To lead a cross-functional team effectively, you don’t just manage the project, you design the team.

Here’s how.

1. Clarify Goals and Roles

Before anyone touches a task list, you need to get the team aligned on two foundational questions: What are we trying to achieve? Who is doing what to get us there?

That may sound obvious. But in cross-functional teams, ambiguity reigns. Everyone assumes someone else is handling a task. Or worse, two people assume they’re both in charge.

Start by mapping out the scope of the project together. Identify major deliverables. Then ask the group: “Who here feels best equipped to own this?” Let people step forward. If there’s debate, facilitate it. If someone volunteers for a stretch assignment, support them, perhaps by pairing them with a more experienced teammate.

This approach does more than assign work. It sends a message: this is a team, not a collection of departments. And you’re here not just to execute—but to develop.

2. Set Communication Norms

Every department has its own way of working. Some teams live in Slack. Others still rely on email. Some expect immediate responses. Others have a “48-hour rule.” If you don’t align early, miscommunication is inevitable.

At your kickoff meeting, have the team co-create its communication norms. Ask questions like:

How will we keep each other updated on progress?
What tools should we use, and for what?
How do we request help?
How often should we meet?
How will we make decisions?
How will we give and receive feedback?

Document the answers. Make them visible and accessible. Then refer back to them, especially when things get bumpy.

These shared norms help your team navigate differences in communication style and prevent misunderstandings from becoming major roadblocks.

3. Build Empathy Through Common Understanding

Communication norms help people speak to each other. Empathy helps them listen with each other.

People on a cross-functional team aren’t just bringing different skills—they’re bringing different definitions of success. One team member might be evaluated on speed, another on accuracy, another on cost control. If you don’t understand the pressures your teammates are under, you’ll misunderstand their decisions—and maybe their intentions.

One powerful exercise: ask each team member to explain how their performance is measured back in their “home” department. What does success look like? What’s their boss expecting from them? What’s at stake?

You can even create simple “user manuals” for each team member that explain how they like to work, how they make decisions, and what stresses them out.

The more your team understands each other, the easier it becomes to collaborate, and to resolve conflicts when they arise.

4. Foster Psychological Safety

Here’s something most people miss: a lack of disagreement on a cross-functional team isn’t a sign of alignment. It’s a sign of silence.

In the early days of a new team, people tend to be polite. They nod along. They bite their tongues. They say things like, “That’s interesting,” when they really mean, “That will never work.”

But innovation doesn’t happen through politeness. It happens through candor. And candor requires psychological safety—the belief that you can speak up without fear of rejection or ridicule.

To build that safety, model vulnerability as a leader. Say things like, “What am I missing?” or “This is a rough idea—feel free to poke holes.” When people challenge you, thank them. When disagreements emerge, guide the group to evaluate ideas based on assumptions, not egos. Ask, “What assumptions are we each making?” rather than “Who’s right?”

Psychological safety isn’t about eliminating conflict. It’s about making conflict productive.

5. Celebrate Small Wins

Cross-functional projects often span months or even years. And when the deadline feels distant, motivation can wane, especially when team members are juggling other priorities.

That’s why milestones matter. Break the project into phases. Define what success looks like for each one. Then, when your team hits a milestone, celebrate it. A shout-out in a meeting. A thank-you email. A Slack emoji reaction.

Research shows that even small wins, when recognized, can boost morale and performance. Just make sure your recognition is authentic and specific. People know when you’re faking it.

Final Thought: It’s Never Too Late to Reset

Maybe you’re reading this and thinking, “Great… but I’m already halfway through leading a cross-functional team that’s barely functioning.”

Good news: it’s never too late to pause and reset. Call a meeting. Clarify goals. Align on roles. Set communication norms. Celebrate any progress you’ve made. Then start fresh from there.

Cross-functional teams can be challenging. But when they’re led well, they become more than the sum of their parts. They become engines of innovation and drivers of real change across your organization.

And you? You become the kind of leader who makes collaboration work, even when no one reports to you.

Image credit: Unsplash

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7 Signs Your Company Needs a Customer Experience Audit

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7 Signs Your Company Needs a Customer Experience Audit

by Braden Kelley and Art Inteligencia

Most companies don’t wake up one day and decide they need a customer experience (CX) audit. They notice something’s off — a number that won’t move, a complaint that keeps recurring in slightly different words — and spend months treating the symptom before anyone names the actual problem. If any of the following sound familiar, that’s usually the moment to stop treating symptoms.

1. Your satisfaction scores have plateaued, not declined

A declining NPS is easy to act on — something clearly broke, and you go find it. A plateaued score is harder, because nothing is obviously wrong, and yet nothing is getting better either, no matter what you try. That’s usually a sign the problem isn’t in the parts of the experience your survey is capturing. It’s in the parts nobody’s measuring.

2. Customer complaints keep circling the same theme without ever naming the same issue

Different words, different tickets, different customers — but if you squint, they’re all describing the same friction from slightly different angles. That pattern usually means the actual root cause is a step upstream of where the complaints are landing, and no one’s traced it back far enough to find it.

3. Your team has strong opinions about “what customers want” — and no recent research to back it up

Every organization develops internal folklore about its customers over time, and folklore calcifies fast. If the last time anyone formally validated your personas was more than a year or two ago, there’s a real chance the assumptions steering your roadmap and your customer’s actual expectations have quietly drifted apart.

4. Frontline teams routinely “work around” the same problem instead of escalating it

When support or sales staff have built informal scripts or manual fixes for a recurring issue, that’s a sign the organization has adapted to a problem instead of solving it. It also means leadership likely has no visibility into how often it’s happening, because a workaround is specifically designed not to generate a ticket.

5. You’re investing in acquisition, and retention isn’t keeping pace

New customer growth that isn’t showing up in overall revenue growth is one of the clearest tells that the experience, not the funnel, is where the leak is. It’s a math problem before it’s ever discussed as an experience problem — and by the time it’s obviously an experience problem, it’s usually cost you a lot more than an audit would have.

6. A competitor keeps coming up in customer conversations for reasons that aren’t about price

When customers mention a competitor unprompted, and the comparison isn’t about cost, it’s almost always about experience — how easy something is, how fast a question gets answered, how the relationship feels. That’s a benchmarking gap, and it’s one of the harder ones to see from inside your own organization.

7. Nobody in leadership has personally walked the customer journey in the last year

This is the simplest sign and the one most often overlooked. If the people making decisions about the customer experience are working entirely from dashboards and secondhand reports, rather than having recently gone through the journey themselves, there’s a structural gap between what leadership believes is happening and what’s actually happening.

What to do if two or more of these sound familiar

One of these signs, on its own, might just be normal organizational noise. Two or three together is a pattern worth taking seriously. If you want a more structured way to check where the real gaps are, the Customer Experience Audit Checklist walks through the same five areas a professional audit examines, so you can see for yourself before committing to anything larger.

If you’re already fairly confident there’s a real problem and want to know roughly what it’s costing you, the CX ROI Calculator is the fastest way to put a number on it — and from there, a Customer Experience Audit is how you find out exactly where to fix it first.

Download the Customer Experience Audit Checklist as a PDF

Image Credits: Pexels

Content Authenticity Statement: The topic area, key elements to focus on, etc. were decisions made by Braden Kelley, with a little help from Claude to clean up the article.

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