Are Your Customer Surveys Costing You Business?

Are Your Customer Surveys Costing You Business?

GUEST POST from Shep Hyken

Why does a company send out a customer satisfaction survey? Generally, it is to find out if they did a good job or what they can do to make the experience better.

In the weekly Super Amazing Show I do with Brittany Hodak, we talked about surveys. The general consensus was that shorter was better. After the show, we heard from John Hughes, who is connected with me on LinkedIn. Here is a shortened version of his comment:

“Saying, ‘Short surveys are better,’ is a bit like saying tall people are better at basketball. Yes, it helps, but you still have to be talented and have that extra ‘something’ to be a professional basketball player. … Rather than focusing on short surveys, I would say companies should truly investigate the principles by which customers choose them and then try to match the survey to the customers’ willingness to help. Ironically, customers at top service companies (think Ritz-Carlton, USAA, Chewy, Amazon, and Navy Federal Credit Union) are actually more willing to take longer surveys because they appreciate the relationship. An unwillingness to take a survey can be the most direct measure they do not value the relationship.”

First, I love John’s comment, especially the analogy to professional basketball. I won’t argue that some brands have customers who are more willing to take the longer surveys; however, Brittany and I were talking in general terms. And in general, short surveys get higher response rates. I shared with John that depending on how many surveys are sent out – as in a large number – the company can keep the surveys short and ask different questions, which should give them similar feedback as if they sent out fewer longer surveys.

Shep Hyken Customer Survey Cartoon

Here are some findings from our 2024 Customer Service and CX research (sponsored by RingCentral) that back up my comments:

  1. In 2024, 67% of customers said they don’t complete surveys if they are too long.
  2. Furthermore, almost one in five (19%) of customers stopped doing business with a company or brand because its satisfaction surveys were too long.
  3. And 23% of customers stopped doing business with a company because it kept sending too many surveys.

It’s not all gloom and doom for surveys. There are plenty of people who are happy to complete surveys, and we’ll share some of those findings later this year.

Back to John’s comment about customers at top service companies who will take the time to answer longer surveys. There are some rock star brands that are so good that customers are compelled to share their experience in a survey, be it long or short. But for most of us mere mortals, we should pay attention to what most customers are telling us about customer satisfaction surveys.

Image Credits: Unsplash

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Learning About Innovation – From a Skateboard?

How learning about innovation can come from unlikely directions…

Learning about innovation - from a skateboard?

GUEST POST from John Bessant

What have ollies, decks, trucks, popsicles, cruisers and kicktails got in common? If you’d asked me that back in December I would have quietly assumed you were from another planet. But now I’m happy to say I’m in a good position to enlighten you…

It seemed like a good idea for a Christmas present; Lara had trailed it enough to give us a clue that Father Christmas’s arrival with a skateboard in his sack would be a welcome surprise. And the initial impact was decidedly so; unwrapping a bright blue machine with impressive decoration and wheels which lit up as she sped along the corridor in the first test flights.

So it was a good job that the present included a full safety kit of helmet, knee and elbow pads, etc. because she spent much of the next day crashing into bookcases, doors and anything else unfortunate enough to be in the way of her hurtling progress. And that was just inside the house!

Cue the need for some training in the art of riding a skateboard. Since this is a skillset which I am most certainly not in possession of this led me to outsource the problem to our local indoor skateboard park where I booked a couple of lessons. Turned out to be an education for me too; while sheltering from the noise of kids shouting encouragement and challenge at each other and the rumble of wheels over plywood ramps and chicanes I sipped my coffee and thought about some of the innovation lessons it was demonstrating….

Not least the power of innovation to create a whole new market. I had no idea just how big a business skateboarding had become but a quick dive into my phone revealed some impressive facts. Estimates suggest the market size is of the order of $3.2bn in 2022 and forecast to keep growing at 3.5% over the next ten years. That’s a lot of skateboards on the streets and in specialist parks like the one I’m in. Extending my research I came to realise what a sheltered life I’ve been leading — there’s a whole world out there beyond the simple piece of wood on wheels that I thought it was.

And it’s an industry full of innovation. I use something called the ‘4Ps framework’ to explain the different ways you can innovate to my classes — it’s a sort of ‘innovation compass’ that points the different directions you might explore. Skateboarding’s got all of these and plenty of examples.

First there’s product innovation — from core components like wheels and bearings, boards and safety equipment through to fashion and merchandise. The early days saw the emergence of what I now know is called a ‘streetboard’ as a basic design; it still represents nearly half the market in terms of boards sold and has standardised around some core dimensions. They are often called ‘popsicle boards’ (don’t ask me why) and they are the kind of board you’ll typically see out in the streets.

But there’s also the longboard variant which is growing in significance. As its name suggests it’s longer but also lighter and faster on account of its wheel size and construction materials. This — as Lara points out to me, already dissatisfied with her glamourous but un-tricksy popsicle board — is the kind of board you use for performing tricks, racing, freestyling and even dancing. Plus we’ve now got the new wave of electric boards which bring another dimension to the sport, potentially opening up the personal mobility market.

And each of those boards involves multiple contributing streams of innovation around components. Take something as mundane as wheels; naively I assumed they were just roller skate or suitcase wheels attached to a piece of wood. Nope. The early days of metal wheels were fraught with poor performance, high friction and a lot of collateral damage to the surfaces being ridden on. So non-metallic alternatives emerged, from simple clay versions in the 1960s through to today’s polyurethane variants based on Frank Nasworthy’s 1972 invention. This latest iteration also provides an opportunity to build in some of the fancy display electronics which Lara finds such a draw on her board.

Even the humble bearings inside the wheels turn out to be a key innovation step, moving from simple loose ball bearings to sophisticated engineered precision bearings which last longer and give a smooth ride even under the tortuous twists and turns of a ride round the skateboard park.

Or look at the trucks on which the wheels are fitted. They’ve moved from being simple cross-over fixtures taken from roller skating to becoming a high tech branch of the component world, continuously refined to give better turning radius, stability, and control allowing for more complex manoeuvres and tricks. Classic need pull innovation.

Skateboard product innovation also provides an excellent example of the idea of dominant designs and technological trajectories. The classic pattern in which different designs compete in the early days of an innovation before a dominant version emerges which sets the path for further incremental development. Which is periodically interrupted by a radical shift enabled by technology or different market demand.

In the case of skateboards the simple plank of wood on wheels which dominated the early days 1930s was upended (pardon the pun) by Larry Stevenson’s rethinking of the deck to include a kicktail in 1969. This is the upturned rear end of a board which gives better control and crucially enables many of those fancy tricks. It wasn’t long before the double kicktail — a turn-up at each end — became the standard for modern boards.

And we’re not just talking about the boards themselves; there is matching innovation right across the ecosystem which has emerged. Take the case of footwear; the increasing profile of the sector attracted both specialist sports suppliers and also fashion brands and has led to another interactive set of pulls and pushes to create innovation. For example Vans, in the 1970s, introduced the waffle-cup, diamond shoe pattern, offering better grip and foot protection. Since then, skate shoe companies have continuously innovated, focusing on preventing bruises, increasing flexibility, and enhancing grip.

What about process innovation? Watching Lara on the wooden ramps and slopes showed how much this has changed since the early days of trying to travel down a road in a straight line. Now we’re in a world of complex spins and runs, jumps and curves. And supporting them are specialist architects and engineers designing ever more complex experiences across which boards can travel, swivel, twist, turn and jump in multiple ways. Not surprising that in 2016, the International Olympic Committee announced the inclusion of skateboarding in the 2020 Summer Olympics.

There’s also scope for what we’ call ‘position innovation’ — expanding the market to whom the innovation is targeted and changing story being told about it. Skateboarding is no longer the province of hardcore fans — it’s grown to be a mainstream sport, drawing in enthusiasts of an increasingly wide age range. According to a recent survey, skateboarding is marked at the third position in the most popular sports category after football and basketball in the USA. Europe has been catching on fast and Asia now has the highest growth rates — not least China.

It’s also another world, full of fans connected online and physically, creating a sub-culture around the sport. Since the first skateboarding magazine was published back in 1964 a whole media system has emerged spanning print, video, podcasting and films and populated by real life and fictional heroes. With my newly-acquired skateboarding vocabulary even I am able to make more sense of the arcane worlds of Mutant Turtles, Shredders and their like.

And it’s a powerful force in fashion now, and not just as a fan-based marketplace. In 2016, at Paris Fashion Week, Dior launched its winter collection on a neon-coloured skateboard catwalk ramp. The icons are everywhere — and so too are the sponsors, riding their own market waves with their brands plastered all over boards, apparel and other merchandise.

From time to time there is also an opportunity for what we call ‘paradigm innovation’ — changing the way we think about what it is we are doing and how it creates value. It can refer to the ‘business model’ being used or changed — but it can also get right to the heart of what we consider the boundaries and shape of our activity.

We’ve seen this before in then world of sport. Just as Dick Fosbury shifted the way high jump athletes think and move with his famous Fosbury Flop, so skateboarding has had its turning points. I’m reliably assured from my instant education via Wikipedia that Alan Gelfand invented a move in 1978 called the Ollie, which revolutionized the field. It’s the basic move in which the rider leaps in the air without using their hands — and it enabled all those amazing twirls, somersaults and assorted gravity-defying manoeuvres which make the sport so exciting. (You’ll be glad to learn that there are now at least 15 variations on the Ollie including the nollie (nose ollie), the switch ollie, the half-can, the pop-shuvit, and the fakie ollie).

Skateboard Business

So there’s plenty in the current innovation space around skateboarding. But where did it come from? Its origins lie in the 1930s, not surprisingly in the surf-rich worlds of Hawaii and California. The idea of attaching roller skate wheels to a wooden board gave us the ‘skate-scooter’ but it wasn’t until the 1950s that the crossover from the world of surfing really took hold. Standing on a board rather than scooting along with one foot on it led to the need to find ways to balance, turn and move in ways analogous to riding the ocean swell.

Going back through its history you quickly find yourself facing a classic example of user-led innovation. Thanks to the pioneering studies of Eric von Hippel and colleagues we know a lot about this type of innovation. It doesn’t begin with the design office in a company or in a marketing agency. Instead it starts with users who face a challenge, feel a frustration or generally seek something different, perhaps new thrills or experiences. They have a high incentive to innovate but this primarily comes from within — it’s not about growing a market or commercial expansion. They have a challenge and they want to deal with it.

In addition to this high incentive to innovate they are tolerant of failure and prepared to experiment and prototype. So many user innovations emerge from this type of experimenting — think of the first pickup trucks which were not designed in Detroit but were the result of farmers modifying the Model Ts and other cars they bought to make them more suitable for farm use.

Importantly because user innovators aren’t primarily motivated for commercial market expansion they are often happy to share and so communities form around promising new ideas. And these communities can significantly accelerate the rate of innovation by pooling both ideas and the results of their experiences.

Which is the classic pattern in many new sports — things like kitesurfing, windsurfing and mountain biking — and certainly characterises skateboarding. Originally developed as a street alternative to riding the waves early prototypes were shared, modified and developed in a co-laboratory on the streets and in communities prepared to share ideas (and how they got those bumps and bruises). Many of the early companies which emerged in this field were founded by users — and a good few failed to grow partly because their founders were more interested in riding their boards than in selling them!

The model persists; much of the move to tricks and through them to specialist materials, safety equipment and even the parks in which such tricks are enabled owe their genesis to user innovators. People like Rodney Mullen, who invented numerous foundational tricks used in modern street skating, and Tony Hawk, who not only pushed the boundaries of skateboarding tricks but also contributed to the design and material innovations through his company, Birdhouse Skateboards.

Skateboard Girl

Watching a seven year old try to master a complex physical skill requiring considerable co-ordination also provided me with another angle on innovation. There’s a strong vision of what she wants to achieve and periodically she’ll pause to watch one of the older kids running through their repertoire of tricks, culminating with jumps, back flips and other seriously cool manoeuvres. But there’s also a determination allied to acceptance of the multiple falls and collisions which go with the learning process. Plus, from time to time a sideways approach to the whole thing.

You can almost see her thinking that these wonderfully sculpted slopes and cliffs and jumps are OK for riding your board but they are also pretty interesting as a surface to be clambered over and played on in their own right. So why not combine the two? Within half an hour she was pretty adept at lying prone on her board and hurtling up and down in a new variant of the sport with more in common with bobsleigh riding. Perhaps I’ve just witnessed the birth ofyet another offshoot innovation?

At the end of the session one of the organizers came up and asked if I fancied having a go. My instincts were all around self-preservation reinforced by the important principle about the impossibility of teaching old dogs new tricks. But a voice was also whispering in my ear that innovation is, of course, all about learning new tricks. Dynamic capability and all that. Time to practice what I preach?

So maybe the next time I write this blog it will be from my hospital bed, having crocked myself up in spectacular fashion but with the satisfied smile of my face that comes to those who finally execute their first ollie….

You can find my podcast here and my videos here

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

Image credits: Dall-E via Microsoft CoPilot

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How I Use AI to Understand Humans

(and Cut Research Time by 80%)

How I Use AI to Understand Humans

GUEST POST from Robyn Bolton

AI is NOT a substitute for person-to-person discovery conversations or Jobs to be Done interviews.

But it is a freakin’ fantastic place to start…if you do the work before you start.

Get smart about what’s possible

When ChatGPT debuted, I had a lot of fun playing with it, but never once worried that it would replace qualitative research.  Deep insights, social and emotional Jobs to be Done, and game-changing surprises only ever emerge through personal conversation.  No matter how good the Large Language Model (LLM) is, it can’t tell you how feelings, aspirations, and motivations drive their decisions.

Then I watched JTBD Untangled’s video with Evan Shore, WalMart’s Senior Director of Product for Health & Wellness, sharing the tests, prompts, and results his team used to compare insights from AI and traditional research approaches.

In a few hours, he generated 80% of the insights that took nine months to gather using traditional methods.

Get clear about what you want and need.

Before getting sucked into the latest shiny AI tools, get clear about what you expect the tool to do for you.  For example:

  • Provide a starting point for research: I used the free version of ChatGPT to build JTBD Canvas 2.0 for four distinct consumer personas.  The results weren’t great, but they provided a helpful starting point.  I also like Perplexity because even the free version links to sources.
  • Conduct qualitative research for meI haven’t used it yet, but a trusted colleague recommended Outset.ai, a service that promises to get to the Why behind the What because of its ability to “conduct and synthesize video, audio, and text conversations.”
  • Synthesize my research and identify insights: An AI platform built explicitly for Jobs to be Done Research?  Yes, please!  That’s precisely what JobLens claims to be, and while I haven’t used it in a live research project, I’ve been impressed by the results of my experiments.  For non-JTBD research, Otter.ai is the original and still my favorite tool for recording, live transcription, and AI-generated summaries and key takeaways.
  • Visualize insights:  MuralMiro, and FigJam are the most widely known and used collaborative whiteboards, all offering hundreds of pre-formatted templates for personas, journey maps, and other consumer research templates.  Another colleague recently sang the praises of theydo, an AI tool designed specifically for customer journey mapping.

Practice your prompts

“Garbage in.  Garbage out.” Has never been truer than with AI.  Your prompts determine the accuracy and richness of the insights you’ll get, so don’t wait until you’ve started researching to hone them.  If you want to start from scratch, you can learn how to write super-effective prompts here and here.  If you’d rather build on someone else’s work, Brian at JobsLens has great prompt resources. 

Spend time testing and refining your prompts by using a previous project as a starting point.  Because you know what the output should be (or at least the output you got), you can keep refining until you get a prompt that returns what you expect.    It can take hours, days, or even weeks to craft effective prompts, but once you have them, you can re-use them for future projects.

Defend your budget

Using AI for customer research will save you time and money, but it is not free. It’s also not just the cost of the subscription or license for your chosen tool(s).  

Remember the 80% of insights that AI surfaced in the JTBD Untangled video?  The other 20% of insights came solely from in-person conversations but comprised almost 100% of the insights that inspired innovative products and services.

AI can only tell you what everyone already knows. You need to discover what no one knows, but everyone feels.  That still takes time, money, and the ability to connect with humans.

Run small experiments before making big promises

People react to change differently.  Some will love the idea of using AI for customer research, while others will resist with.  Everyone, however, will pounce on any evidence that they’re right.  So be prepared.  Take advantage of free trials to play with tools.  Test tools on friends, family, and colleagues.  Then under-promise and over-deliver.

AI is a starting point.  It is not the ending point. 

I’m curious, have you tried using AI for customer research?  What tools have you tried? Which ones do you recommend?

Image credit: Unsplash

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Why Quiet Geniuses Excel at Breakthroughs

Why Quiet Geniuses Excel at Breakthroughs

GUEST POST from Greg Satell

When you think of breakthrough innovation, someone like Steve Jobs, Jeff Bezos or Elon Musk often comes to mind. Charismatic and often temperamental, people like these seem to have a knack for creating the next big thing and build great businesses on top of them. They change the world in ways that few can.

Yet what often goes unnoticed is that great entrepreneurs build their empires on the discoveries of others. Steve jobs didn’t invent the computer or the mobile phone any more than Jeff Bezos discovered e-commerce or Elon Musk dreamed up electric cars. Those things were created by scientists and engineers that came long before.

In researching my book, Mapping Innovation, I got to know many who truly helped create the future and I found them to be different than most people, but not in a way that you’d expect. While all were smart and hardworking, the most common trait among them was their quiet generosity and that can teach us a lot about how innovation really works.

How Jim Allison Figured it All Out

At least in appearance, Jim Allison is a far cry from how you would normally picture a genius to look like. Often disheveled with a scruffy beard, he kind of mumbles out a slow Texas drawl that belies his amazingly quick mind. Unassuming almost to a fault, when I asked him about his accomplishments he just said, “well, I always did like figuring things out.”

When Jim was finishing up graduate school, scientists had just discovered T-cells and he told me that he was fascinated by how these things could zip around your body and kill things for you, but not actually hurt you. The thing was, nobody had the faintest idea how it all worked. So Jim decided to become an immunologist and devote his life to figuring it all out.

Over the next few decades, he and his colleagues at other labs did indeed do much to figure it out. They found one receptor, called B-7, which acts like an ignition switch that initiates the immune response, another, CD-28, that acts like a gas pedal and revs things up into high gear and a third, called CTLA-4, that puts on the brakes so things don’t spin out of control.

Jim played a part in all of this, but his big breakthrough came from the work of another scientist in his lab, which made him suspect that the problem with cancer wasn’t that our immune system can’t fight it, but that it puts the brakes on too soon. He thought that if he could devise a way to pull those brakes off, we could cure cancer in a new and different way.

As it turned out, Jim was right. Today, cancer immunotherapy has become a major field unto itself and, in October 2018, he won the Nobel Prize for his discovery of it. Yet the truth is that it wasn’t one major breakthrough, but a decades-long process of slowly putting the pieces together that made it all possible.

How Gary Starkweather Went From Blowup To Breakthrough

Gary Starkweather is every bit as quiet and unassuming as Jim Allison. Yet when I talked to him a few years ago, I could still hear the anger in his voice as he told me about an incident that happened almost 50 years before. In the late 60s, Gary had an idea to invent a new kind of printer, but his boss at Xerox was thwarting his efforts.

At the time, Gary was one of the few experts in the emerging field of laser optics, so there weren’t many others who could understand his work, much less how it could be applied to the still obscure field of computers. His boss was, in fact, was so hostile to Gary’s project that he threatened to fire anyone who worked with him on it.

Furious, the normally mild mannered Gary went over his boss’s head. He walked into the Senior Vice President’s office and threatened, “Do you want me to do this for you or for someone else?” For the stuffy, hierarchical culture of Xerox, it was outrageous behavior, but as luck would have it, the stunt paid off. News of Gary’s work made it across the country to the fledgling computer lab that Xerox had recently established in California, the Palo Alto Research Center (PARC).

Gary thrived in the freewheeling, collaborative culture at PARC. The researchers there had developed a graphical technology called bitmapping, but had no way to print the images out until he showed up. His development of the laser printer was not only a breakthrough in its own right, but with the decline of Xerox’s copier business, it actually saved the company.

The Wild Ideas Of Charlie Bennett

Charlie Bennett is one of those unusual minds that amazes everyone he meets. He told me that when he was growing up in the quiet Westchester village of Croton-on-Hudson he was a “geek before geeks were cool.” While the other kids were playing sports and trading baseball cards, what really inspired Charlie was Watson and Crick’s discovery of the structure of DNA.

So he went to college and majored in biochemistry and then went on to Harvard to do his graduate work, where he served as James Watson’s teaching assistant. Yet it was an elective course he took on the theory of computation that would change his fate. That’s where he first encountered the concept of a Turing Machine and he was amazed how similar it was to DNA.

So Charlie never became a geneticist, but went to work for IBM as a research scientist. It proved to be just the kind of place where a mind like his could run free, discussing wild ideas like quantum cryptography with colleagues around the globe. It was one of those discussions, with Gilles Brassard, that led to his major breakthrough.

What the two discussed was the wildest idea yet. They proposed to transfer information by quantumly entangling photons, something that Einstein had derisively called “spooky action at a distance” and was adamant couldn’t happen. Yet the two put a team together and, in 1993, successfully completed the quantum teleportation experiment.

That, in turn, led Charlie just a few months later to write down his four laws of quantum information, which formed the basis for IBM’s quantum computing program. Today, in his eighties, Charlie is semi-retired, but still goes into the labs at IBM research to quietly discuss wild ideas with the younger scientists, such as the quantum internet that’s continuing to emerge now.

For Innovation, Generosity Is A Competitive Advantage

My conversations with Jim, Gary, Charlie and many others made an impression on me. They were all giants in their fields (although Jim hadn’t won his Nobel yet) and I was a bit intimidated talking to them. Yet I found them to be some of the kindest, most generous people I ever met. Often, they seemed as interested in me as I was in them.

In fact, the behavior was so consistent that I figured it couldn’t be an accident. So I researched the matter further and found a number of studies that helped explain it. One, at Bell Labs, found that star engineers had a knack for “knowing who knows.” Another at the design firm IDEO found that great innovators essentially act as “knowledge brokers.“

A third study helps explain why knowledge brokering is so important. Analyzing 17.9 million papers, the researchers found that the most highly cited work tended to be mostly rooted within a traditional field, with just a smidgen of insight taken from some unconventional place. Breakthrough creativity occurs at the nexus of conventionality and novelty.

So as it turns out, generosity is often a competitive advantage for innovators. By actively sharing their ideas, they build up larger networks of people willing to share with them. That makes it that much more likely that they will come across that random piece of information and insight that will help them crack a really tough problem.

So if you want to find a truly great innovator, don’t look for the ones that make the biggest headlines are that are most inspiring on stage. Look for those who spend their time a bit off to the side, sharing ideas, supporting others and quietly pursuing a path that few others are even aware of.

— Article courtesy of the Digital Tonto blog and previously appeared on Inc.com
— Image credits: Pixabay

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Iterate Your Thinking

Iterate Your Thinking

GUEST POST from Dennis Stauffer

One of the things that all sound innovation processes have in common is some way to iterate. To repeatedly work through a process that allows you to refine whatever you’re trying to create.

That might be building a prototype, testing it and building another version based on what you’ve learned. It might be gathering customer feedback and making adjustments that are more appealing or solve a problem more effectively. It might be exploring more than one business model or marketing strategy until you find one that works.

We tend to think of those iterations as making refinements to a product or strategy, but more than anything, it’s refining your own thinking. It’s being willing to change how you understand the world, by challenging your assumptions and beliefs—your mindset.

We’ve grown accustomed to thinking of learning as mastering a set of already well-defined concepts, like how to solve a math problem or memorizing facts from history. But innovation—and life in general—requires a different kind of learning. More like gradually mastering how to play a sport or musical instrument, or drive a car. This kind of learning is a more incremental process. One that prompts questions like:

  • How might I be wrong, and need to correct myself?
  • What do I not understand as well as I could?
  • What are some alternative beliefs and opinions, to the ones I have?
  • How might someone else see things differently and what could I learn from them?

The ability to iterate your own thinking, by being open to new interpretations of what you experience, is crucial to innovation. It’s also a good strategy for ordering your life, so you don’t lock onto a mindset that may not be the most effective for you.

Mental iteration is a powerful life skill—and healthy innovation habit—that also helps you innovate yourself.

View this post as a video here:

Image Credit: Pixabay

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Problems are Required for Progress to Occur

Problems are Required for Progress to Occur

GUEST POST from Mike Shipulski

Without a problem, there can be no progress.
And only after there’s too much no progress is a problem is created.
And once the problem is created, there can be progress.

When you know there’s a problem just over the horizon, you have a problem.
Your problem is that no one else sees the future problem, so they don’t have a problem.
And because they have no problem, there can be no progress.
Progress starts only after the calendar catches up to the problem.

When someone doesn’t think they have a problem, they have two problems.
Their first problem is the one they don’t see, and their second is that they don’t see it.
But before they can solve the first problem, they must solve the second.
And that’s usually a problem.

When someone hands you their problem, that’s a problem.
But if you don’t accept it, it’s still their problem.
And that’s a problem, for them.

When you try to solve every problem, that’s a problem.
Some problems aren’t worth solving.
And some don’t need to be solved yet.
And some solve themselves.
And some were never really problems at all.

When you don’t understand your problem, you have two problems.
Your first is the problem you have and your second is that you don’t know what your problem by name.
And you’ve got to solve the second before the first, which can be a problem.

With a big problem comes big attention. And that’s a problem.
With big attention comes a strong desire to demonstrate rapid progress. And that’s a problem.
And because progress comes slowly, fervent activity starts immediately. And that’s a problem.
And because there’s no time to waste, there’s no time to define the right problems to solve.

And there’s no bigger problem than solving the wrong problems.

Image credit: Pexels

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Is Customer Obsession a Two-Way Street At Your Company?

Is Customer Obsession a Two-Way Street At Your Company?

GUEST POST from Shep Hyken

One of my favorite ways to measure a customer’s satisfaction level with a company or brand is by using the Net Promoter Score (NPS) question, which is, “On a scale of zero to 10, how likely are you to recommend this company to a friend or colleague?” If the customer answers with a nine or a 10, they are known as a “promoter.” The insight is obvious. The customer experience was good enough for them to recommend the company. That would be sufficient if all you were interested in was customer satisfaction, but taking this to the next level is to wonder if the customer will actually recommend the company to another person.

That’s what led Marbue Brown, founder of Customer Obsession Advantage (COA), to create a study. His goal was to find out what type of customer would go from saying they would recommend a company to actually doing so. The COA interviewed more than 1,200 consumers who rated 22 recognized brands to compare customers classified as NPS promoters and customers who were obsessed with a brand.

Consider the following findings from the COA study:

  1. 82% of obsessed customers say they will recommend you to others.
  2. 42% report they have already recommended you more than five times in the past year.
  3. 44% say they always/usually share their feelings about the company with others when given the opportunity.
  4. 26% say they have placed online reviews.
  5. 88% say they will “absolutely” repurchase in the next 12 months.

These are more than just findings. These are behaviors. Consider that 42% of customers have already recommended the company or brand five or more times in the past year. That’s huge! Or, that 26% placed online reviews. How would you like one in four customers to leave positive reviews about you? (Rhetorical question). These are significant actions that create positive word-of-mouth marketing moments.

Whatever metric you have chosen to measure customer satisfaction— NPS, CSAT (Customer Satisfaction), CES (Customer Effort Score), Time Well Spent, etc.—they are all good tools that serve a purpose and provide important information, but they must be used for more than vanity. A high NPS is just a number, and it should offer more than bragging rights. While it’s nice to know you’re making your customers happy enough to recommend you, leave reviews, etc., it’s more important to recognize that these high scores are opportunities to take action. In other words, actions speak louder than words. A high NPS does not guarantee a customer will promote your business. You must determine if they are obsessed with your brand. While the customer with a high COA score may promote without prompting, why take a chance that they won’t?

For example, a high NPS is especially powerful in the B2B world, where salespeople often call on their customers. When a customer gives a high score, follow up with a phone call or personalized email to thank them for the high score and ask them, “In our survey, you mentioned you would recommend us. Would you be willing to share the names or make introductions to those people?” You may be pleasantly surprised at the positive responses you get from customers who are obsessed with your company.

The insights from Brown’s COA study highlight the behaviors of obsessed customers. The challenge is for us to take traditional metrics like NPS, CSAT and others to another level. A willingness to recommend (a Net Promoter) is just another way to measure customer satisfaction unless you do something with the data. The magic happens when this willingness turns into a tangible action that includes repeated recommendations, online reviews and a customer who says, “I’ll be back” and means it! That’s the difference between a willingness to promote and customer obsession.

Image Credits: Pexels

This article originally appeared on Forbes.com

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Next Generation Leadership Traits and Characteristics

Next Generation Leadership Traits and Characteristics

GUEST POST from Stefan Lindegaard

What are the traits and characteristics for a new generation of leaders, those who will shape the future in this sea of uncertainty?

To me, this is more about mindset than age. However, the mindset which I hint at below and that I believe we need more of reside well within the younger generation.

Thus, we could see a higher number of younger executives in the coming years even though they lack the leadership experience and skills that have been normal for leaders in their roles. They need to learn fast and hopefully do this while being surrounded with experiences in different ways.

I think this will be most prominent in Asia and even parts of Africa and South America where there is a stronger belief in the future compared to Europe and even the USA with its stronger sentiment of complacency as well as many overwhelming challenges.

Many current executives will of course also develop in good ways so I suggest we look for traits and characteristics in both groups such as:

  1. Holistic point of view (intrapreneurial skills)
  2. Understanding of psychological safety and the growth mindset (and ability to lead with and through this)
  3. Ability to constructively handle conflict
  4. Optimism, passion and drive
  5. Curiosity and belief in change
  6. Tolerance for / ability to deal with uncertainty
  7. Adaptive fast learner with sense of urgency
  8. Talent for networking / strategic influencing

The desired end-game? Leaders who are capable of the almost super-human task of both managing day-to-day activities and shaping the future.

Get the Right People on the Bus

By shaping the future, I mean the ability to thrive with transformation/change, apply new ways of working and improve collaboration capabilities while pursing new business opportunities and innovation.

Just a discussion starter. What do you think?

Image Credit: Pexels, Stefan Lindegaard

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Predicting Unintended Consequences

The 93% Rule

Predicting Unintended Consequences

GUEST POST from Robyn Bolton

Unintended consequences often catch us off guard despite their predictability.  The moment they occur, we gasp in shock, shake our heads, and look at each other in wide-eyed horror at this thing that just happened that we could never ever ever have anticipated. 

Yet, when (if) we do an After-Action Review, we often realize that these consequences were not entirely unforeseeable. In fact, had we anticipated them, we might have made different decisions.

The Unintended Consequences of Spreadsheets

In 1800 BCE, ancient Babylonians started recording data by scratching grids and columns onto clay tablets, and the spreadsheet was born.  Over the millennia, we went from clay tablets to papyrus to parchment and then paper. 

Fast forward to 1963 when R. Brian Walsh of Marquette University ported the Business Computer Language (BCL) program to an IBM 7040, and electronic spreadsheets became a reality.  The introduction of VisiCalc by Apple in 1979 revolutionized spreadsheet capabilities, followed by Lotus 123 and Microsoft Excel. Today, spreadsheets are ubiquitous in education, business operations, financial markets, budgeting, and even personal inventories.

Unintended yet predictable consequences

While spreadsheets have undoubtedly enhanced efficiency and accuracy compared to traditional methods like clay tablets or hand-drawn tables on parchment, their ease of use has inadvertently led to complacency.

We stopped engaging in a multi-millennial habit of discussing, debating, and deciding before making a spreadsheet. We started flippantly asking people to create spreadsheets and providing little, if any, guidance because “it’s easy to make changes and run scenarios.”

This shift resulted in a reliance on automated models and a lack of shared assumptions or analytical rigor in decision-making processes.

Of course, these behaviors were never intended.  They were, however, very predictable.

93% of Human Behavior is predictable.

Research spanning disciplines as varied as network scientists, anthropology, neuropsychology, and paleontology shines a light on how truly predictable we are.

Here are some examples:

Emotions before Reason: Ask someone if they make decisions based on their motivations, aspirations, and fears and use data to justify the decisions, and they’ll tell you no. Ask them the last time someone else made a decision that “made no sense,” and you’ll listen to a long list of examples.

Small gains now are better than big gains later: Thoughtfully planning before using solutions like spreadsheets, word processing, email, and instant messaging could save us time at work and help us get home 30 minutes earlier or work a few hours less on the weekend.  But saving a few seconds now by brain-dumping into Word, setting up a “flexible” spreadsheet, and firing off a text feels much better.

Confidence > Realism: We’ve all been in meetings where the loudest voice or the most senior person’s opinion carried the day.  As we follow their lead, we ignore signs that we’re wrong and explain away unexpected and foreboding outcomes until we either wake up to our mistakes or adjust to our new circumstances.

Predict the 93%. Create for the 7%

Acknowledging the predictability of human behavior is not an endorsement of stereotypes but a recognition of our innate cognitive processes. By incorporating this understanding into design, innovation, and decision-making processes, we better anticipate potential outcomes and mitigate unintended consequences.

While 93% of human behavior may follow predictable patterns rooted in evolutionary instincts, focusing on the remaining 7% allows for the exploration of unique behaviors and novel solutions.  By embracing both aspects of human nature, we can navigate challenges more effectively and anticipate a broader range of outcomes in our endeavors, leading to informed decision-making and value creation.

Now, if I could only get Excel to stop auto-converting numbers into date/time format.

Image credit: Pixabay

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Value Doesn’t Disappear

It Shifts From One Place to Another

Value Doesn't Disappear

GUEST POST from Greg Satell

A few years ago, I published an article about no-code software platforms, which was very well received. Before long, however, I began to get angry — and sometimes downright nasty — comments from software engineers who were horrified by the notion that you can produce software without actually understanding the code behind it.

Of course, no-code platforms don’t obviate the need for software engineers, but rather automate basic tasks so that amateurs can design applications by themselves. These platforms are, necessarily, limited but can increase productivity dramatically and help line managers customize technology to fit the task at hand.

Similarly, when FORTRAN, the first real computer language, was invented, many who wrote machine code objected, much like the software engineers did to my article. Yet Fortran didn’t destroy computer programming, but democratized and expanded it. The truth is that value never disappears. It just shifts to another place and that’s what we need to learn to focus on.

Why Robots Aren’t Taking Our Jobs

Ever since the financial crisis we’ve been hearing about robots taking our jobs. Yet just the opposite seems to be happening. In fact, we increasingly find ourselves in a labor shortage. Most tellingly, the shortage is especially acute in manufacturing, where automation is most pervasive. So what’s going on?

The fact is that automation doesn’t actually replace jobs, it replaces tasks. To understand how this works, think about the last time you walked into a highly automated Apple store, which actually employs more people than a typical retail location of the same size. They aren’t there to ring up your purchase any faster, but to do all the things that a machine can’t do, like answer your questions and solve your problems.

A few years ago I came across an even more stark example when I asked Vijay Mehta, Chief Innovation Officer for Consumer Information Services at Experian about the effect that shifting to the cloud had on his firm’s business. The first order effect was simple, they needed a lot less technicians to manage its infrastructure and those people could easily be laid off.

Yet they weren’t. Instead Experian shifted a lot of that talent and expertise to focus on creating new services for its customers. One of these, a cloud enabled “data on demand” platform called Ascend has since become one of the $4 billion company’s most profitable products.

Now think of what would have happened if Experian had merely seen cloud technology as an opportunity to cut costs. Sure, it would have fattened its profit margins temporarily, but as its competitors moved to the cloud that advantage would have soon been eroded and, without new products its business would soon decline.

The Outsourcing Dilemma

Another source of disruption in the job market has been outsourcing. While no one seemed to notice when large multinational corporations were outsourcing blue-collar jobs to low cost countries, now so-called “gig economy” sites like Upwork and Fiverr are doing the same thing for white collar professionals like graphic designers and web developers.

So you would expect to see a high degree of unemployment for those job categories, right? Actually no. The Bureau of Labor Statistics expects demand for graphic designers to increase 4% by 2026 and web developers to increase 15%. The site Mashable recently named web development as one of 8 skills you need to get hired in today’s economy.

It’s not hard to see why. While it is true that a skilled professional in a low-cost country can do small projects of the same caliber as those in high cost countries, those tasks do not constitute a whole job. For large, important projects, professionals must collaborate closely to solve complex problems. It’s hard to do that through text messages on a website.

So while it’s true that many tasks are being outsourced, the number of jobs has actually increased. Just like with automation, outsourcing doesn’t make value disappear, but shifts it somewhere else.

The Social Impact

None of this is to say that the effects of technology and globalization hasn’t been real. While it’s fine to speak analytically about value shifting here and there, if a task that you spent years to learn to do well becomes devalued, you take it hard. Economists have also found evidence that disruptions in the job market have contributed to political polarization.

The most obvious thing to do is retrain workers that have been displaced, but it turns out that’s not so simple. In Janesville, a book which chronicles a small town’s struggle to recover from the closing of a GM plant, author Amy Goldstein found that the workers that sought retraining actually did worse than those that didn’t.

When someone loses their job, they don’t need training. They need another job and removing yourself from the job market to take training courses can have serious costs. Work relationships begin to decay and there is no guarantee that the new skills you learn will be in any more demand than the old ones you already had.

In fact, Peter Capelli at the Wharton School argues that the entire notion of a skills gap in America is largely a myth. One reason that there is such a mismatch between the rhetoric about skills and the data is that the most effective training often comes on the job from an employer. It is augmenting skills, not replacing them that creates value.

At the same time, increased complexity in the economy is making collaboration more important, so often the most important skills workers need to learn are soft skills, like writing, listening and being a better team player.

You Can’t Compete With A Robot By Acting Like One

The future is always hard to predict. While it was easy to see that Amazon posed a real problem for large chain bookstores like Barnes & Noble and Borders, it was much less obvious that small independent bookstores would thrive. In much the same way, few saw that ten years after the launch of the Kindle that paper books would surge amid a decline in e-books.

The one overriding trend over the past 50 years or so is that the future is always more human. In Dan Schawbel’s recent book, Back to Human, the author finds that the antidote for our overly automated age is deeper personal relationships. Things like trust, empathy and caring can’t be automated or outsourced.

There are some things a machine will never do. It will never strike out in a little league game, have its heart broken or see its child born. That makes it hard — impossible really — for a machine ever to work effectively with humans as a real person would. The work of humans is increasingly to work with other humans to design work for machines.

That why perhaps the biggest shift in value is from cognitive to social skills. The high paying jobs today have less to do with the ability to retain facts or manipulate numbers (we now use a computer for those things), but require more deep collaboration, teamwork and emotional intelligence.

So while even the most technically inept line manager can now easily produce an application that it would have once required a highly skilled software engineer, to design the next generation of technology, we need engineers and line managers to work more closely together.

— Article courtesy of the Digital Tonto blog and previously appeared on Inc.com
— Image credits: Pixabay

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