We Must Unlearn These Three Management Myths

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We Must Unlearn These Three Management Myths

GUEST POST from Greg Satell

Mark Twain is reported to have said, “It’s not what you don’t know that kills you, it’s what you know for sure that ain’t true.” Ignorance of facts is easily remedied. We can read books, watch documentaries or simply do a quick Google search. Yet our misapprehensions and biases endure, even in the face of contradicting facts.

The truth is that much of what we believe has less to do with how we weigh evidence than how we see ourselves. In fact, fMRI studies have suggested have shown that evidence which contradicts our firmly held beliefs violates our sense of identity. Instead of adapting our views, we double down and lash out at those who criticize them.

This can be problematic in our personal lives, but in business it can be fatal. There is a reason that even prominent CEOs can pursue failed strategies and sophisticated investors will back hucksters to the hilt. Yet as Adam Grant points out in Think Again, we can make the effort to reexamine and alter our beliefs. Here are three myths that we need to watch out for.

Myth #1: The “Global Village” Will Be A Nice Place

Marshal McLuhan, in Understanding Media, one of the most influential books of the 20th century, described media as “extensions of man” and predicted that electronic media would eventually lead to a global village. Communities would no longer be tied to a single, isolated physical space but connect and interact with others on a world stage.

To many, the rise of the Internet confirmed McLuhan’s prophecy and, with the fall of the Berlin Wall, digital entrepreneurs saw their work elevated to a sacred mission. In Facebook’s IPO filing, Mark Zuckerberg wrote, “Facebook was not originally created to be a company. It was built to accomplish a social mission — to make the world more open and connected.

Yet, importantly, McLuhan did not see the global village as a peaceful place. In fact, he predicted it would lead to a new form of tribalism and result in a “release of human power and aggressive violence” greater than ever in human history, as long separated—and emotionally charged—cultural norms would now constantly intermingle, clash and explode.

For many, if not most, people on earth, the world is often a dark and dangerous place. When your world is not secure, “open” is less of an opportunity to connect than it is a vulnerability to exploit. Things can look fundamentally different from the vantage point of, say, a tech company in Menlo Park, California then it does from, say, a dacha outside Moscow.

Context matters. Our most lethal failures are less often those of planning, logic or execution than they are that of imagination. Chances are, most of the world does not see things the way we do. We need to avoid strategic solipsism and constantly question our own assumptions.

Myth #2: Winning The “War For Talent” Will Make You More Competitive

In 1997, three McKinsey consultants published a popular book titled The War for Talent, which argued that due to demographic shifts, recruiting the “best and the brightest” was even more important than “capital, strategy, or R&D.” The idea made a lot of sense. What could be more important for a company than its people?

Yet as Malcolm Gladwell explained in an article about Enron, strict adherence to the talent rule contributed to the firm’s downfall. Executives that were perceived to be talented moved up fast. So fast, in fact, that it became impossible to evaluate their performance. People began to worry more about impressing their boss and appearing to be clever than doing their jobs.

The culture became increasingly toxic and management continued to bet on the same failed platitude until the only way to move up in the organization was to undermine others. As we now know, it didn’t end well. Enron went bankrupt in 2001, just four years after The War for Talent highlighted it as a model for others to follow.

The simple truth is that talent isn’t what you win in a battle. It’s what you build by actualizing the potential of those in your organization and throughout your ecosystem, including partners, customers and the communities in which you operate. In the final analysis, Enron didn’t fail because it lost the war for talent, it failed because it was at war with itself.

Myth #3: We Can “Engineer” Management

In 1911, Frederick Winslow Taylor published The Principles of Scientific Management, based on his experience as a manager in a steel factory. It took aim at traditional management methods and suggested a more disciplined approach. Rather than have workers pursue tasks in their own manner, he sought to find “the one best way” and train accordingly.

Before long, Taylor’s ideas became gospel, spawning offshoots such as scientific marketing, financial engineering and the six sigma movement. It was no longer enough to simply work hard, you had to measure, analyze and optimize everything. Over the years these ideas became so central to business thinking that they were rarely questioned.

Yet they should have been. The truth is that this engineering mindset is a zombie idea, a remnant of the logical positivism that was discredited way back in the 1930s and more recent versions haven’t fared any better. To take just one example, a study found that of 58 large companies that announced Six Sigma programs, 91 percent trailed the S&P 500 in stock performance. Yet that didn’t stop the endless parade of false promises.

At the root of the problem is a simple fact: We don’t manage machines, we manage ecosystems and we need to think more about networks and less about nodes. Our success or failure depend less on individual entities, than the connections between them. We need to think less like engineers and more like gardeners.

Don’t Believe Everything You Think

At any given time, there are any number of clever people saying clever things. When you invoke a legendary icon like Marshall McLuhan and say “Global Village,” the concept acquires the glow of some historical, unalterable destiny. But that’s an illusion, just like the “War for Talent” and the idea of “engineering” your way out of managing a business and making wise choices.

Yet notice the trap. None of these things were put forward as mere opinions or perspectives. The McKinsey consultants who declared the “War for Talent” weren’t just expressing an opinion, but revealing the results of a “yearlong study…involving 77 companies and almost 6,000 managers and executives.” (And presumably, they sold the study right back to every one of those 77 companies).

The truth is that an idea can never be validated backward, only forward. No amount of analysis can shape reality. We need to continually test our ideas, reconsider them and adapt them to ever-changing conditions. The problem with concepts like six sigma isn’t necessarily in their design, but that they become elevated something approaching the sublime.

That’s why we shouldn’t believe everything we think. There are simply too many ways to get things wrong, while getting them right is always a relatively narrow path. Or, as Richard Feynman put it, “The first principle is that you must not fool yourself—and you are the easiest person to fool.”

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

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Everyone Clear Now on What ChatGPT is Doing?

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Everyone Clear Now on What ChatGPT is Doing?

GUEST POST from Geoffrey A. Moore

Almost a year and a half ago I read Stephen Wolfram’s very approachable introduction to ChatGPT, What is ChatGPT Doing . . . And Why Does It Work?, and I encourage you to do the same. It has sparked a number of thoughts that I want to share in this post.

First, if I have understood Wolfram correctly, what ChatGPT does can be summarized as follows:

  1. Ingest an enormous corpus of text from every available digitized source.
  2. While so doing, assign to each unique word a unique identifier, a number that will serve as a token to represent that word.
  3. Within the confines of each text, record the location of every token relative to every other token.
  4. Using just these two elements—token and location—determine for every word in the entire corpus the probability of it being adjacent to, or in the vicinity of, every other word.
  5. Feed these probabilities into a neural network to cluster words and build a map of relationships.
  6. Leveraging this map, given any string of words as a prompt, use the neural network to predict the next word (just like AutoCorrect).
  7. Based on feedback from so doing, adjust the internal parameters of the neural network to improve its performance.
  8. As performance improves, extend the reach of prediction from the next word to the next phrase, then to the next clause, the next sentence, the next paragraph, and so on, improving performance at each stage by using feedback to further adjust its internal parameters.
  9. Based on all of the above, generate text responses to user questions and prompts that reviewers agree are appropriate and useful.

OK, I concede this is a radical oversimplification, but for the purposes of this post, I do not think I am misrepresenting what is going on, specifically when it comes to making what I think is the most important point to register when it comes to understanding ChatGPT. That point is a simple one. ChatGPT has no idea what it is talking about.

Indeed, ChatGPT has no ideas of any kind — no knowledge or expertise — because it has no semantic information. It is all math. Math has been used to strip words of their meaning, and that meaning is not restored until a reader or user engages with the output to do so, using their own brain, not ChatGPT’s. ChatGPT is operating entirely on form and not a whit on content. By processing the entirety of its corpus, it can generate the most probable sequence of words that correlates with the input prompt it had been fed. Additionally, it can modify that sequence based on subsequent interactions with an end user. As human beings participating in that interaction, we process these interactions as a natural language conversation with an intelligent agent, but that is not what is happening at all. ChatGPT is using our prompts to initiate a mathematical exercise using tokens and locations as its sole variables.

OK, so what? I mean, if it works, isn’t that all that matters? Not really. Here are some key concerns.

First, and most importantly, ChatGPT cannot be expected to be self-governing when it comes to content. It has no knowledge of content. So, whatever guardrails one has in mind would have to be put in place either before the data gets into ChatGPT or afterward to intercept its answers prior to passing them along to users. The latter approach, however, would defeat the whole purpose of using it in the first place by undermining one of ChatGPT’s most attractive attributes—namely, its extraordinary scalability. So, if guardrails are required, they need to be put in place at the input end of the funnel, not the output end. That is, by restricting the datasets to trustworthy sources, one can ensure that the output will be trustworthy, or at least not malicious. Fortunately, this is a practical solution for a reasonably large set of use cases. To be fair, reducing the size of the input dataset diminishes the number of examples ChatGPT can draw upon, so its output is likely to be a little less polished from a rhetorical point of view. Still, for many use cases, this is a small price to pay.

Second, we need to stop thinking of ChatGPT as artificial intelligence. It creates the illusion of intelligence, but it has no semantic component. It is all form and no content. It is a like a spider that can spin an amazing web, but it has no knowledge of what it is doing. As a consequence, while its artifacts have authority, based on their roots in authoritative texts in the data corpus validated by an extraordinary amount of cross-checking computing, the engine itself has none. ChatGPT is a vehicle for transmitting the wisdom of crowds, but it has no wisdom itself.

Third, we need to fully appreciate why interacting with ChatGPT is so seductive. To do so, understand that because it constructs its replies based solely on formal properties, it is selecting for rhetoric, not logic. It is delivering the optimal rhetorical answer to your prompt, not the most expert one. It is the one that is the most popular, not the one that is the most profound. In short, it has a great bedside manner, and that is why we feel so comfortable engaging with it.

Now, given all of the above, it is clear that for any form of user support services, ChatGPT is nothing less than a godsend, especially where people need help learning how to do something. It is the most patient of teachers, and it is incredibly well-informed. As such, it can revolutionize technical support, patient care, claims processing, social services, language learning, and a host of other disciplines where users are engaging with a technical corpus of information or a system of regulated procedures. In all such domains, enterprises should pursue its deployment as fast as possible.

Conversely, wherever ambiguity is paramount, wherever judgment is required, or wherever moral values are at stake, one must not expect ChatGPT to be the final arbiter. That is simply not what it is designed to do. It can be an input, but it cannot be trusted to be the final output.

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

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What Are the Toughest Words to Say?

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What Are the Toughest Words to Say?

GUEST POST from Mike Shipulski

As the world becomes more connected, it becomes smaller. And as it becomes smaller, competition becomes more severe. And as competition increases, work becomes more stressful. We live in a world where workloads increase, timelines get pulled in, metrics multiply and “accountability” is always the word of the day. And in these trying times, the most important word to say is also the toughest.

When your plate is full and someone tries to pile on more work, what’s the toughest word to say?

When the project is late and you’re told to pull in the schedule and you don’t get any more resources, what’s the toughest word to say?

When the technology you’re trying to develop is new-to-world and you’re told you must have it ready in three months, what’s the toughest word to say?

When another team can’t fill an open position and they ask you to fill in temporarily while you do your regular job, what’s the toughest word to say?

When you’re asked to do something that will increase sales numbers this quarter at the expense of someone else’s sales next quarter, what’s the toughest word to say?

When you’re told to use a best practice that isn’t best for the situation at hand, what’s the toughest word to say?

When you’re told to do something and how to do it, what’s the toughest word to say?

When your boss asks you something that you know is clearly their responsibility, what’s the toughest word to say?

Sometimes the toughest word is the right word.

Image credit: Pixabay

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The Magic of Starting with Yes

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The Magic of Starting with Yes

GUEST POST from Shep Hyken

It’s time to revisit the idea of avoiding the word “no,” but this time, I want to approach it from a different angle. First, let me tell you about my friend Dr. Nido Qubein, a devoted husband and father, motivational speaker, entrepreneur, president of High Point University, and mentor to many, who came to this country when he was 17 with little more than $50 to his name. Almost 50 years ago, he attended High Point University, never dreaming that one day he would be president of the institution, a position he accepted in 2005.

Since that time, there has been incredible growth at HPU. In his first year, the university had about 1,400 students enrolled on the 91-acre campus. Today, there are almost 6,000 students, including 623 graduate students. The campus has grown to more than 500 acres, includes 128 buildings, and is considered an elite university.

If you Google “Nido Qubein,” you will see a list of accomplishments that give insight into this man’s extraordinary career. As mentioned, he is a mentor to many, and even as a friend, I am among those who consider him a mentor. I’ve learned much from his willingness to share the lessons he learned from his successes, and today, I want to share a simple lesson we might all want to consider, which has to do with the word no.

If you’ve been following my work, you know I’ve written several articles about avoiding the word no. Christine Trippi and Cameron Mitchell have been featured in The Shepard Letter and in my videos discussing the topic. This time, I give you Nido’s perspective, and even though he’s not talking about customer service or CX, it ties in perfectly.

Nido recognizes that when someone new steps into a leadership role in any type of organization, authenticity and listening skills are of the utmost importance. People can be skeptical. He says, “I always start with a yes. It doesn’t always end that way after we’ve done the study, but a lot of people start with no.”

I love this idea. When our customers ask us for something or they have an issue, starting on a positive note, such as finding a way to use the word yes from the start can help guide the conversation in the right direction. This is what it looks like:

  • “Yes, I understand.”
  • “Yes, that’s a great idea worth considering.”
  • “Yes, you do have a problem, so let’s see what we can do about it.”
  • “Yes, that is a possibility. Let’s look at the situation more closely.”

Nido’s simple leadership lesson is also a powerful customer service lesson. When a customer comes to you with a problem or issue, you are in a leadership position. You are empowered with authority to help the customer. Saying yes is not about giving in. It’s about using the right word at the right time to create a better customer experience.

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Creating More Digital Value for Customers

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Creating more value for customers is how highly successful digital companies like Uber, Amazon, Netflix, and Apple got to where they are today.

Creating More Digital Value for Customers

GUEST POST from Howard Tiersky

So how do you improve your customer value? Think of customer value as an equation — how much do you give me in exchange for how much I give you? There’s the “cost” side of the equation for the customer, and there’s the “benefits” side. Great customer value engineering innovates on both sides of that equation.

Cost

An important part of the “cost” is the money the consumer spends, but it is also measured in time, convenience and level of effort. If the customer has to work harder to extract the value from your offering, this is a perceived increase in cost.

Let’s take the example of Netflix. They have always been aggressive about providing access to large volumes of content for an accessible monthly charge. Their current lowest price is $6.99 per month, less than the cost of a single movie ticket. Netflix also works hard to use personalization to lower the effort it takes to find and play content on any device.

Here are four key ways to reduce the “cost” side of your value proposition. Consider which of these might apply to your offering.

1. Charge less. This is the most obvious step. The danger is that competing on price alone can be a dangerous game and take both you and your competitors into a place where it can be difficult to make money or run a sustainable business. However, we see many of the most successful companies in the digital space not necessarily “discounting” their offer but finding ways to re-engineer their entire cost model via innovative approaches that leverage this new digital world in order to offer more for less. For example, Amazon is able to undercut the prices of many brick and mortar retailers because they don’t have the cost of retail stores and because of the large scale of their operation. Google is able to offer email for free because they have devised a way to make money via advertising rather than charging for the service.

2. Change your payment model. Blockbuster rented videos on a “per video” basis. Netflix’s first innovation was not streaming or House of Cards but rather the subscription model for video “rental.” Similarly, Amazon created a major innovation with Amazon Prime when they offered subscription 2-day shipping services. But subscription is not the only way to change the game. Disaggregation is another. Apple changed the music industry by focusing on selling individual tracks of music rather than entire albums. They then applied this same approach to episodic TV episodes which were previously only available to be purchased in “full season” DVD sets.

3. Reduce the customer’s effort. Uber takes the effort out of getting around. They extremely simplified the process of ordering a car service, paying, talking to the driver about where you are headed and managing your expense records. These may be small things, but they add up. Just like we are willing to pay more for milk at 7-11 to avoid the grocery store if your offering is less effort for the user it reduces the overall “cost.”

4. Reduce unexpected costs. Look for opportunities to save a user money that they would be paying to someone else. If a user can drive less or avoid shipping costs, you have saved them money, and they may not mind giving you a little more. An old-school example, AAA sells roadside assistance but included with this subscription are discounts to most hotels and some other travel-related services. These discounts cost AAA nothing and add value to the membership.

Benefits

Now that we’ve removed some of the “cost,” how can we augment the benefits? Here are five techniques to increase the benefits side of the equation.

1. Offer more stuff. HBO recently partnered with Sesame Workshop to add over 20 seasons of Sesame Street to their on-demand offering. Dropbox continues to increase the storage they will give you for your $9.99 monthly subscription. Consider cost-effective ways to simply give the user more of what they are coming to you for.

2. Add features. Google office massively increased the value of their “PowerPoint” competitor by enabling cloud-based real-time collaboration. Consider how to expand the features your product offers to add value.

3. Increase shareability. The more people that can utilize a single purchase, the more value it has. Apple created their family plan so that apps purchased from their App store can be used by anyone in the family. Amazon created a way to “lend” a Kindle book to a friend.

4. Increase durability or longevity. Extending the realistic lifespan of your product extends the value. For example demonstrating the “future-proofing” you have included in your solution so that it will be forward-compatible with the “next generation” of technology adds value to your offer.

5. Add flexibility. If customers can use your product in different ways, apply it to more “needs” in their life, this increases the value. You may have subscribed to Dropbox to share files with clients, but Dropbox has added and promotes features also to make it a great place to sync and store your personal photos and act as a “backup” in case of hard drive failure. Apple constantly markets the diverse ways their products can be used. iPhones are also cameras, calculators, GPS devices, musical instruments, word processors, currency converters and presentation tools. Every additional way your iPhone can be used potentially replaces another product you would have to buy and adds value.

Which of these opportunities to enhance the value equation for your customer best fit your business? For those that don’t seem to “fit,” try a thought experiment for each and consider if it did fit, how would you apply it? You might discover a breakthrough that would transform your whole value proposition.

This article originally appeared on the Howard Tiersky blog

Image Credits: Howard Tiersky, FROM

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Don’t Listen to the ‘We Can’t Do That’ Lie

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These Are the Truths

Don't Listen to the 'We Can't Do That' Lie

GUEST POST from Robyn Bolton

How many times have you proposed a new idea and been told, “We can’t do that?” Probably quite a few.  My favorite memory of being told, “We can’t do that,” happened many years ago while working with a client in the publishing industry:

Client: We can’t do that.

Me: Why?

Client: Because we already tried it, and it didn’t work.

Me: When did you try it?

Client: 1972

Me: Well, things certainly haven’t changed since 1972, so you’re right, we definitely shouldn’t try again.

I can only assume they appreciated my sarcasm as much as the idea because we eventually did try the idea, and, 30+ years later, it did work. But the client never would have enjoyed that success if my team and I had not seen through “we can’t do that” and helped them admit (confess) what they really meant.

Quick acknowledgment

Yes, sometimes “We can’t do that” is true.  Laws and regulations define what can and can’t be done.  But they are rarely as binary as people make them out to be.  In those gray areas, the lie of “we can’t do that” obscures the truth of won’t, not able to, and don’t care.

“I won’t do it.”

When you hear “can’t,” it usually means “won’t.”  Sometimes, the “won’t” is for a good reason – “I won’t do the dishes tonight because I have an urgent deadline, and if I don’t deliver, my job is at risk.”  Sometimes, the “won’t” isn’t for a good reason – “I won’t do the dishes because I don’t want to.”  When that’s the case, “won’t” becomes “can’t” in the hope that the person making the request backs off and finds another solution. 

For my client, “We can’t do that” actually meant, “I won’t do that because it failed before and, even though that was thirty years ago, I’m afraid it will fail again, and I will be embarrassed, and it may impact my reputation and job security.”

You can’t work with “can’t.”  You can work with “won’t.”  When someone “won’t” do something, it’s because there’s a barrier, real or perceived.  By understanding the barrier, you can work together to understand, remove, or find a way around it.

“I’m not able to do it.”

“Can’t” may also come with unspoken caveats.  We can’t do that because we’ve never done it before and are scared.  We can’t do that because it is outside the scope of our work.  We can’t do that because we don’t know how. 

Like “won’t,” you can work with “not able to” to understand the gap between where you are now and where you want to go.  If it’s because you’re scared of doing something new, you can have conversations to get smarter about the topic or run small experiments to get real-world learnings.  If you’re not able to do something because it’s not within your scope of work, you can expand your scope or work with people who have it in their scope.  If you don’t know how, you can talk to people, take classes, and watch videos to learn how.

“I don’t care.”

As brave as it is devastating, “we can’t do that” can mean “I don’t care enough to do that.” 

Executives rarely admit to not caring, but you see it in their actions. When they say that innovation and growth are important but don’t fund them or pull resources at the first sign of a wobble in the business, they don’t care. If they did care, they would try to find a way to keep investing and supporting the things they say are priorities.

Exploring options, trying, making an effort—that’s the difference between “I won’t do it” and “I don’t care.”    “I won’t do that” is overcome through logic and action because the executive is intellectually and practically open to options. “I don’t care” requires someone to change their priorities, beliefs, and self-perception, changes that require major personal, societal, or economic events.

Now it’s your turn to tell the truth

Are you willing to ask the questions to find them?

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Change Leaders Must Anticipate and Overcome Resistance

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Change Leaders Must Anticipate and Overcome Resistance

GUEST POST from Greg Satell

When Barry Libenson arrived at Experian as Global CIO in 2015, he devoted his first few months to speaking with customers. Everywhere he went he heard the same thing: they wanted access to real-time data. On the surface, it was a straightforward business transformation, but Libenson knew that it was far more complicated than that

To switch from batch processed credit reports to real-time access would require a technology transformation—from an on-premise to a cloud architecture—and in order to develop cloud applications effectively, he would have to initiate a skills-based transformation—from waterfall to agile development.”

So what at first appeared to be a straightforward initiative was actually three separate transformations stacked on top of one another. To make things even more difficult, people had good reason to be hostile to each aspect. Still, by being strategic about overcoming resistance from the start, he achieved a full transformation in less than three years.

Understanding Cognitive Biases

One of the key concerns about Libenson’s program at Experian was that the company would lose control over its business model. The firm had prospered selling processed credit reports. Giving customers real-time access to data seemed to undercut a value proposition that had proven itself over decades, almost as if McDonald’s decided to stop selling hamburgers.

These were not casual criticisms. In fact, they reflected instinctual cognitive biases that are deeply rooted in our consciousness. The first, loss aversion, reflects our tendency to avoid losses rather than seek out new gains. The second, called the availability heuristic, reflects our preference for information that is easy to access and internalize, such as the decades of profits generated by credit reports rather than the vague promise of a new cloud-driven business model.

A similar dynamic is plays out between the Black Lives Matter movement and police unions. One could argue, with significant evidence, that the smart play for police unions would be to come to some accommodation with protesters’ concerns to avoid more draconian policies later on. Yet after meticulously building their power base for decades, they have shown little willingness to make concessions.

Libensen and his team were able to navigate these challenges with two key strategies. First, he started with internal API’s, rather than fully open applications, as a keystone change,. That helped bridge the gap between the initial and desired future state. Second, the program was opt-in at first. Those program managers who were excited about creating cloud-based products got significant support. Those who weren’t were left alone.

Navigating Asymmetrical Impacts

Another obstacle to overcome was the fact that some people were more affected than others. In the case of Experian’s skills-based transformation from waterfall to agile development, which was essential to making the business and technology transformations possible, the change hit more senior personnel harder than junior ones.

Many of the project managers at the company had been doing their jobs for years—even decades—and took great pride in their work. Now they were being told they needed to do their jobs very differently. For a junior employee with limited experience, that can be exciting. For those more invested in traditional methods, the transition can more difficult.

Here again, the opt-in strategy helped navigate some thorny issues. Because no one was being forced to switch to agile development, it was hard for anyone to muster much resistance. At the same time, Libenson established an “API Center of Excellence” to empower those who were enthusiastic about creating cloud-based products.

As the movement to the cloud gained steam and began to generate real business results, the ability to build cloud-based projects became a performance issue. Managers that lagged began to feel subtle pressure to get with the program and to achieve what their colleagues had been able to deliver.

Overcoming Switching Costs

Experian facilitates billions of transactions a month. At that scale, you can’t just turn the ship on a dime. Another factor that increased the risk is the very nature of the credit business itself, which makes cybersecurity a major concern. In fact, one of Experian’s direct competitors, Equifax, had one of the biggest data breaches of the decade.

Every change encounters switching costs and that can slow the pace of change. In one particularly glaring example, the main library at Princeton University took 120 years to switch to the Library of Congress classification system because of the time and expense involved. Clearly, that’s an extreme case, but every change effort needs to take inevitable frictions into account.

That’s why Libenson didn’t push for speed initially, but started small, allowing the cloud strategy to slowly prove itself over time. As win piled upon win, the process accelerated and the transformation became more ingrained in the organization. Within just a few years, those who opposed the move to the cloud were in the distinct minority.

As General Stanley McChrystal explained in Team of Teams, he experienced a similar dynamic revamping Special Operations in Iraq. By shifting his force’s focus from individual team goals to effective collaboration between teams, he may have slowed down individual units. However, as a collective, his forces increased their efficiency by a factor of seventeen, measured by the amount of raids they were able to execute.

In every transformation, there is an inherent efficiency paradox. In order to produce change for the long-term, you almost always lose a little bit of efficiency in the short-term. That’s why it’s important to start small and build momentum as you go.

Leveraging Resistance To Forge A New Vision

Any change, if it is important and potentially impactful, is going to encounter fierce resistance. As Saul Alinsky noted, every revolution inspires its own counter-revolution. That’s why three quarters of organizational transformations fail, because managers too often see it as a communication exercise, rather than a strategic effort to empower those who are already enthusiastic about change to influence everyone else.

In the case of Experian’s move to the cloud, the objections were not unfounded. Offering customers real-time access to data did have the potential to upend the traditional credit report business model. Switching to a new technology architecture does raise cybersecurity concerns. Many senior project managers really had served the company well for decades with traditional development methods.

As Global CIO, Libenson could have ignored these concerns. He could have held a “townhall” and launched a major communication effort to convince the skeptics. Yet he did neither of these things. Instead, he treated the resistance not as an obstacle, but as a design constraint. He identified people who were already enthusiastic about the shift and empowered them to make it work. Their success built momentum and paved the way for what became a major transformation .

In fact, Experian’s cloud architecture unlocked enormous value for the firm and its customers. The company’s API hub made good on Libenson’s initial promise of supporting real-time access to data and today processes over 100 million transactions a month. It has also enabled a completely new business, called Ascend, now one of the company’s most successful products.

The truth is that bringing about fundamental, transformational change takes more than clever slogans and happy talk. The status quo always has inertia on its side and never yields its power gracefully. You need to be clear-eyed and hard-nosed. You need to understand that for every significant change, there will be some who seek to undermine it in ways that are dishonest, underhanded and deceptive.

The difference between successful revolutionaries and mere dreamers is that those who succeed anticipate resistance and build a plan to overcome it.

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

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Humanizing Agility

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Humanizing Agility

GUEST POST from Janet Sernack

Like many others, I invested time in isolation during the pandemic to engage in various online learning programs. As a highly credentialed coach to many global Agile and SCRUM leaders in major international and local organizations, I enrolled in an Agile coach certification program and enthusiastically attended all daily sessions. It was a disastrous learning experience, verifying my perception of the Agile community’s focus on a prescriptive rules-driven process to agility. The Agile Manifesto’s  highest priority is satisfying customers through the early and continuous delivery of valuable software; only two of the 12 principles mention people – “Business people and developers must work together daily throughout the project” and “the best architectures, requirements, and design emerge from self-organizing teams.” So, with this in mind, what might be some of the benefits of integrating a technological and process-driven disciplined approach towards humanizing agility?

I am a conceptual and analytical thinker, an entrepreneur, and an innovator who is acknowledged as a global thought leader on the people side of innovation. I also teach, mentor, and coach people to be imaginative, inquisitive, and curious, always asking many open questions. I empower, enable, and equip them to become change-agile, cognitively, and emotionally agile and develop their innovation agility. The presenters responded to my method of inquiry by assuming that I knew nothing about Agile despite knowing nothing about my background.

As a result, they failed to certify me without communicating or consulting with me directly, despite my meeting all of the course evaluation criteria and having more than 10,000 hours of facilitation and more than 1,000 hours of coaching experience on the people side of change. I also have a comprehensive background in humanizing total quality management, continuous improvement, and start-up methodologies in major organizations.

I contacted the training company and challenged their decision, only not to be “heard” and be paid lip service when confronted by a rigid, linear, conventional, disconnected approach to agility and its true role and capability in catalysing change, innovation and teaming.

This is especially true considering the senior SCRUM and Agile leaders I was coaching at the time experienced very few problems with Agile’s disciplined process and technological side. They specifically requested coaching support to develop strategies to resolve their monumental challenges and complex issues involving “getting people to work together daily” and operating as “self-organizing teams.” How do they go about humanizing agility?

Making sense of agility

Despite my disappointment, I bravely continued researching how to make sense of agility and link and integrate it with the people side of change, innovation, and teams. I intended to enable leaders to execute agile transformation initiatives successfully by combining a human-centered approach to agile software development through humanizing agility.  

Agility refers to a leader, team, or organization’s ability to make timely, effective, and sustained changes that maintain superior performance. According to Pamela Myer’s book “The Agility Shift”, – an agility shift is the intentional development of the competence, capacity and confidence to learn, adapt and innovate in changing contexts for sustainable success. We have incorporated this approach into our innovation learning and coaching curriculum at ImagineNation™ and iterated and pivoted it over the past 12 years in empowering, enabling and equipping people to become “agility shifters” by humanizing agility.

Humanizing agility differently

Agility can be humanized and expanded to include change, cognitive, innovation, and organizational agility, all powerfully fueled by people’s emotional energy. This is fundamental to achieving success through non-growth or growth strategies and delivering equitable and sustainable outcomes that will make the world a better place for all humanity.  

It involves identifying pivots, unlearning, learning, and relearning, embracing new approaches, frameworks, and tools, and developing new 21st-century mindsets, behaviors, and skills.

Humanizing agility involves empowering, enabling, and equipping people to be, think and act differently autonomously and competently, especially in the conflicted, chaotic, unstable post-COVID world of emerging unknowns.

Like innovation, agility is contextual.

Humanizing agility supports people to adapt, grow and thrive, become nimble by enabling:

  • Teams to deliver product releases as shorter sprints to collect customer feedback to iterate and pivot product development.
  • Leaders, teams, and organizations respond quickly and adapt to market changes, internally and externally.
  • People must think and feel and be able to quickly make intentional shifts to be effective, creative, inventive, and innovative in changing contexts.

That empowers, enables and equips people with the mindsets, behaviors, and skills to adapt, grow, and thrive by developing their confidence, capacity, and competence to catalyze and mobilize their power to move quickly and easily, think creatively and critically to make faster decisions and solve complex problems with less effort.  

Humanizing Agility – The Five Elements

1. Emotional energy

Emotional energy is the catalyst that fuels creativity, invention, and innovation.

Understanding and harnessing this energy inspires and motivates individuals to explore and embrace creative thinking strategies in partnership with AI.

Emotional energy catalyses people’s intrinsic motivation, conviction, hope, positivity, and optimism to approach their world purposefully, meaningfully, and differently.

When people are true to their calling, they make extra efforts and are healthier, which positively impacts their well-being and improves their resilience.

2. Change agility

Change agility is the ability to anticipate, respond, be receptive, and adapt to constant and accelerating change in an uncertain, unstable, conflicted world.

It involves developing a new perspective of change as a continuous, iterative, and learning process that has to be embedded in every action and interaction, not a separate standalone process.

Requiring the development of new mental models, states, traits, mindsets, behaviors, and skills to drive business and workforce outcomes that are critical for an organization to survive and thrive through any change.

Change becomes an ongoing opportunity, not a threat or liability, and humanizing agility in the context of change agility is a core 21st-century competency for leaders, teams and coaches.

3.Cognitive agility

Cognitive agility is the extent to which people can adapt and shift their perspectives and thought processes when doing so leads to more positive outcomes. 

Cognitive agility refers to how flexible and adaptive people can be with their thoughts in the face of change, uncertain circumstances, and random and unexpected events and situations. Being cognitively agile helps people break down their neuro-rigidity and eliminate any core fixed mindsets; it supports their neuro-plasticity and develops a growth mindset and ability to perceive the world through multiple lenses and differing perspectives.

Humanizing agility in the context of cognitive agility enables people to make sense of and understand the range of challenges, problems, and paradoxes at the deeper systemic and surface levels, preparing them for smart risk-taking, effective decision-making, and intelligent problem-solving. 

4.Innovation agility

Innovation agility is the extent to which people develop the courage, compassion and creativity to safely deep-dive into and dance with cognitive dissonance—to passionately, purposefully, and apply creative tension and develop neuro-elasticity, to play in the space where possibility lives—between the present state and the desired creative, inventive, and innovative outcome.

To empower, engage, and enable people to use their human ingenuity and harness their collective intelligence to be innovative in the age of AI by adapting and growing in ways that add value to the quality of people’s lives, which is appreciated and cherished.

5.Organizational and leadership agility

Organizational agility involves developing an ability to renew itself, adapt, innovate, change quickly, and succeed in a rapidly changing, uncertain and unstable operating environment. It requires a paradoxical balance of two things: a dynamic capability, the ability to move fast—speed, nimbleness, responsiveness and stability, and a stable foundation—a platform of things that don’t change to provide a rigorous and disciplined pillar.

Organizations and leaders prioritizing humanizing agility also prioritize differing and creative ways of being, thinking and acting. They maintain their strength by focusing on their core competencies while regularly stretching themselves for maximum flexibility, adaptiveness and resilience.

Finally…. Imagine humanizing agility

Imagine what you could do and the difference we could make to people, customers, organizations, communities and the world by humanizing agility in ways that embrace and embody the five elements of agility to harness the human ingenuity and people’s collective intelligence guide vertical, horizontal and transformational changes the world and humanity need right now.

Please find out more about our work at ImagineNation™.

Please find out about our collective learning products and tools, including The Coach for Innovators, Leaders, and Teams Certified Program, presented by Janet Sernack. It is a collaborative, intimate, and profoundly personalized innovation coaching and learning program supported by a global group of peers over 9-weeks. It can be customized as a bespoke corporate learning program.

Image Credit: Pexels

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Sometimes to Innovate You Must Do the Following

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Sometimes to Innovate You Must Do the Following

GUEST POST from Mike Shipulski

What it takes to do new work:

Confidence to get it wrong and confidence to do it early and often.

Purposeful misuse of worst practices in a way that makes them the right practices.

Tolerance for not knowing what to do next and tolerance for those uncomfortable with that.

Certainty that they’ll ask for a hard completion date and certainty you won’t hit it.

Knowledge that the context is different and knowledge that everyone still wants to behave like it’s not.

Disdain for best practices.

Discomfort with success because it creates discomfort when it’s time for new work.

Certainty you’ll miss the mark and certainty you’ll laugh about it next week.

Trust in others’ bias to do what worked last time and trust that it’s a recipe for disaster.

Belief that successful business models have half-lives and belief that no one else does.

Trust that others will think nothing will come of the work and trust that they’re likely right.

Image credit: Unsplash

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Customer Service Makes You Money

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Customer Service Makes You Money

GUEST POST from Shep Hyken

Necessity is the mother of invention. In 2003, Marton Anka, the founder of LogMeIn, now GoTo, spent three hours a day in Budapest crossing a bridge between Buda and Pest, the two halves of Hungary’s capital. He hated the “downtime,” so he invented remote access to a server so he could log in from anywhere—hence, the name of the company, LogMeIn.

Over time, the company expanded its offerings, had a few mergers and acquisitions and ultimately became GoTo, a company that makes IT management, support and business communications easy. Many of you reading this article may be familiar with GoTo Webinar and GoTo Meeting. These communication products (and others) have developed into a company focused on customer communication tools, phone systems, contact center platforms and engagement tools such as web chat, SMS communications, social media and more.

That’s the backdrop of my Amazing Business Radio interview with Joseph Walsh, vice president of product marketing at GoTo. We focused on several important concepts for CX leaders to consider as customer service continues to evolve and become one of the most powerful growth engines that fosters repeat business and customer loyalty. Below are the main points, followed by my comments:

  • The entire company must work in tandem with the customer support department. The old term silo came to mind. Many companies still have departments that operate almost autonomously, in silos, without regard to the other departments. Imagine the power a customer support agent working with a customer would have if they could easily reach out to someone in product development, accounting or sales in real time to get answers to their customer’s questions. Walsh says, “You need fast access to subject matter experts in other parts of the company.” This eliminates having to call the customer back and cuts down on the time it takes to answer customers’ questions and resolve their issues.

There are four stages of contact centers. Walsh talked about the four stages/lifecycle of a typical contact center. For an organization to understand where it is today, it must see where it fits into the different stages of contact centers, which are:

    1. Initiate Conversations: This is the traditional contact center. It’s where most companies start to build and expand their customer support department. They prepare to field multiple calls, answer emails, etc., often using basic/standard phone systems and computers to get started. People are trained with scripts, and while a good start, it’s still basic at best.
    2. Collaboration: This goes back to Walsh’s first point about collaborating with experts and departments throughout the company. On the customer’s first (and hopefully only) call, the agent can reach out to the appropriate people to get the right answers and convey that information to the customer for a much better experience.
    3. Digital Transformation: Walsh used the word omnichannel to describe how different communication channels work together seamlessly. A customer may start with a social media post to ask for help. At some point, they may be texting. That’s followed up with a phone conversation. But what makes this special is that it is a progressive conversation using these different communication platforms versus multiple interactions in which the customer must start over and repeat the story or problem at every interaction. Walsh says, “At this stage, the people and companies are beginning to master the craft of customer experience.”
    4. Automate and accelerate: This is where the modern contact center has evolved. Most of the first three stages of the lifecycle merge with modern technology and allow customers to employ self-service, work out problems and answer questions on their own. Automated processes and AI create a better experience by reducing and/or eliminating mundane, repetitive tasks. Customers and employees are happy.

    Customer service becomes a growth opportunity. It surprises me that some business leaders still view customer service as a cost center. The new way of looking at CX is that it is a revenue generator that retains customers and grows business. Walsh said, “The more evolved, digitally powered contact center is a growth center for achieving higher customer service scores that drive repeat customers and give the customer such a happy experience that they’re not concerned about price.” This powerful statement can be backed up with data proving customer service doesn’t cost. It pays!

    In a competitive marketplace, companies must prioritize exceptional customer experiences to thrive. By embracing collaboration, digital transformation and automation, companies and brands can turn customer service from a cost center into a growth engine. As Walsh emphasized, a digitally evolved contact center does more than simply improve service. It also drives loyalty, revenue and growth.

    Image Credits: Pexels

    This article originally appeared on Forbes.com

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