Tag Archives: IBM

Don’t Slow Roll Your Transformation

Don't Slow Roll Your Transformation

GUEST POST from Geoffrey A. Moore

Business pundits love to talk about transformation, and consultants drool at the opportunity to tap into a limitless budget, but the truth is, transformations suck.

At minimum, transformation consists of re-engineering your operating model while continuing to operate, with even greater disruption involved if you are revamping your business model at the same time. Now, if you are a privately held enterprise, you might be able to sell this to your board as a “pivot,” and indeed, in the venture world, there is some accommodation built in for such moves. Not so, however, for companies whose shares are publicly held. If this describes you, fasten your seatbelt and read on.

Transformations come with “J curves”—financial projections that have you swimming underwater for some considerable period before you emerge reborn on the other side. Public investors hate J curves. They also worry prospective customers, as well as ecosystem partners, not to mention your own employees. Only a VC loves a J curve, but their attention is on a younger generation.

Nonetheless, everyone understands there are situations where transformation is warranted. For public companies, the most common cause is when the entire franchise is under existential threat. A new technology paradigm is going to categorically obsolete the core franchise, as digital photography did to Kodak, as digital media did to BusinessWeek, as wireless telephony is doing to wireline. It was an existential threat that caused Microsoft to displace its back office software business with Azure’s cloud services, even though the gross margins of the latter were negative while the net margins of the former were stupendous. It was an existential threat that drove Lou Gerstner to reengineer IBM’s hardware-centric business model to focus on services and software. Failure to transform means dissolution of the enterprise. If you are to survive, there are times when you simply have to bite the bullet.

That said, you still have to confront the issue of time. Everyone understands that a transformation will take more than one year, but no one is willing to tolerate it taking three. That is, by the end of the second year you have to be verifiably emerging from the J curve, head out of water, able to breathe positive cash flow, or else you are likely to be written off. That means transformational initiatives should be planned to complete in seven quarters, plus or minus one. That’s the amount of time you can be in the ICU before you risk getting transferred to hospice care.

So, if a transformation is in your future, and you really cannot work around it, then start your planning with the end in mind and calendar that end for seven quarters out. Now, work backward to determine where you will have to be by each of the intervening quarters in order to meet your completion date. When you get back to the current quarter, expect to see you are already two or three quarters behind schedule (not fair, I know, but I already told you that transformations suck). Suppress panic, conduct triage, and start both your engines and the clock.

Final point: given the lack of time and the amount of risk involved, there is only one sensible way to approach a transformation. Prioritize it above everything else, and keep everyone focused on making the intermediate milestones until you are well and truly out of danger. Transformations are no joking matter. Most companies lose their way. Don’t let that be true of you and yours.

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

Image Credit: Pixabay

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Uber Economy is Killing Innovation, Prosperity and Entrepreneurship

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Uber Economy is Killing Innovation, Prosperity and Entrepreneurship

GUEST POST from Greg Satell

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

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

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

The Productivity Paradox Writ Large

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

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

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

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

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

Two Paths To Profitability

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

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

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

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

The Silicon Valley Doomsday Machine

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

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

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

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

Returning To An Innovation Economy

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

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

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

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

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

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

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How to Pursue a Grand Innovation Challenge

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How to Pursue a Grand Innovation Challenge

GUEST POST from Greg Satell

All too often, innovation is confused with agility. We’re told to “adapt or die” and encouraged to “move fast and break things.” But the most important innovations take time. Einstein spent ten years on special relativity and then another ten on general relativity. To solve tough, fundamental problems, we have to be able to commit for the long haul.

As John F. Kennedy put it in his moonshot speech, “We choose to go to the moon in this decade and do the other things, not because they are easy, but because they are hard, because that goal will serve to organize and measure the best of our energies and skills.” Every organization should pursue grand challenges for the same reason.

Make no mistake. Innovation needs exploration. If you don’t explore, you won’t discover. If you don’t discover you won’t invent and if you don’t invent you will be disrupted. It’s just a matter of time. Unfortunately, exploration can’t be optimized or iterated. That’s why grand challenges don’t favor the quick and agile, but the patient and the determined.

1. Don’t Bet The Company

Most grand challenges aren’t like the original moonshot, which was, in large part, the result of the space race with the Soviets that began with the Sputnik launch in 1957. That was a no-holds-barred effort that consumed the efforts of the nation, because it was widely seen as a fundamental national security issue that represented a clear and present danger.

For most organizations, those type of “bet-the-company” efforts are to be avoided. You don’t want to bet your company if you can avoid it, for the simple reason that if you lose you are unlikely to survive. Most successful grand challenges don’t involve a material investment. They are designed to be sustainable.

“Grand challenges are not about the amount of money you throw at the problem, Bernard Meyerson, IBM’s Chief Innovation Officer, told me. “To run a successful grand challenge program, failure should not be a material risk to the company, but success will have a monumental impact. That’s what makes grand challenges an asymmetric opportunity.”

Take, for example Google’s X division. While the company doesn’t release its budget, it appeared to cost the company about $3.5 billion in 2018, which is a small fraction of its $23 billion in annual profits at the time. At the same time, just one project, Waymo, may be worth $70 billion (2018). In a similar vein, the $3.8 billion invested in the Human Genome Project generated nearly $800 billion of economic activity as of 2011.

So the first rule of grand challenges is not to bet the company. They are, in fact, what you do to avoid having to bet the company later on.

2. Identify A Fundamental Problem

Every innovation starts out with a specific problem to be solved. The iPod, for example, was Steve Jobs’s way of solving the problem of having “a thousand songs in my pocket.” More generally, technology companies strive to deliver better performance and user experience, drug companies aim to cure disease and retail companies look for better ways to drive transactions. Typically, firms evaluate investment based on metrics rooted in past assumptions

Grand challenges are different because they are focused on solving fundamental problems that will change assumptions about what’s possible. For example, IBM’s Jeopardy Grand Challenge had no clear business application, but transformed artificial intelligence from an obscure field to a major business. Later, Google’s AlphaGo made a similar accomplishment with self-learning. Both have led to business opportunities that were not clear at the time.

Grand challenges are not just for technology companies either. MD Anderson Cancer Center has set up a series of Moonshots, each of which is designed to have far reaching effects. 100Kin10, an education nonprofit, has identified a set of grand challenges it has tasked its network with solving.

Talia Milgrom-Elcott, Executive Director of 100Kin10, told me she uses the 5 Whys as a technique to identify grand challenges. Start with a common problem, keep asking why it keeps occurring and you will eventually get to the root problem. By focusing your efforts on solving that, you can make a fundamental impact of wide-ranging consequence.

3. Commit To A Long Term Effort

Grand challenges aren’t like normal problems. They don’t conform to timelines and can’t effectively be quantified. You can’t justify a grand challenge on the basis of return on investment, because fundamental problems are too pervasive and ingrained to surrender themselves to any conventional form of analysis.

Consider The Cancer Genome Atlas, which eventually sequenced and published over 10,000 tumor genomes When Jean Claude Zenklusen first came up with the idea in 2005, it was highly controversial, because although it wasn’t particularly expensive, it would still take resources away from more conventional research.

Today, however, the project is considered to be a runaway success, which has transformed the field, greatly expanding knowledge and substantially lowering costs to perform genetic research. It has also influenced efforts in other fields, such as the Materials Genome Initiative. None of this would have been possible without commitment to a long-term effort.

And that’s what makes grand challenges so different. They are not business as usual and not immediately relevant to present concerns. They are explorations that expand conventional boundaries, so cannot be understood within them.

An Insurance Policy Against A Future You Can’t Yet See

Typically, we analyze a business by extrapolating current trends and making adjustments for things that we think will be different. So, for example, if we expect the market to pick up, we may invest in more capacity to profit from greater demand. On the other hand, if we expect a softer market, we’d probably start trimming costs to preserve margins.

The problem with this type of analysis is that the future tends to surprise us. Technology changes, customer preferences shift and competitors make unexpected moves. Nobody, no matter how diligent or smart, gets every call right. That’s why every business model fails sooner or later, it’s just a matter of time.

It’s also what makes pursuing grand challenges is so important. They are basically an insurance policy against a future we can’t yet see. By investing sustainably in solving fundamental problems, we can create new businesses to replace the ones that will inevitably falter. Google doesn’t invest in self-driving cars to improve its search business, it invests because it knows that the profits from search won’t last forever.

The problem is that there is a fundamental tradeoff between innovation and optimization, so few organizations have the discipline to invest in exploration today for a uncertain payoff tomorrow. That’s why so few businesses last.

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

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Thought Sparks – Episodic Innovation

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Raise the curtain on Innovation Theater yet again!

Episodic Innovation

GUEST POST from Rita McGrath

We know that to create meaningful innovations that can move the needle for the companies that sponsor them, attention, resources and commitment needs to be sustained. But in too many organizations, innovation gets started, gets some traction and – just at the brink of discovering something useful – gets cut. Welcome to the world of innovation theater.

Layoffs are in the air

Predictably, firms that spent like drunken sailors during the low-interest-rate free-for-all that we’ve just been through are now reconsidering their spending as the economy looks a little soft, inflation has become a thing and investors are asking for — egads — a route to profitability!

We have seen this movie before, and it is one of the most devastating patterns that afflicts internal corporate venturing, or ICV. It’s worth bringing back some original research by Stanford’s Robert Burgelman and his colleagues to understand it.

The mystery of corporate innovation cycles

Years, ago, Robert Burgelman and co-author Liisa Vilikangas came to a perplexing conclusion. Despite all the talk about innovation, all the energy and money thrown at it and all the noise about accelerators, studios and labs, companies find it extraordinarily difficult to stick to an innovation program.

Indeed, as they observe in this article, “many major corporations experience a strange cyclicality in their ICV (Internal Corporate Venturing) activity. Periods of intense ICV activity are followed by periods when such programs are shut down, only to be followed by new ICV initiatives a few years later. Like seasons, internal corporate venturing programs begin and end in a seemingly endless cycle.”

They identify two influences on how an innovation process can come to grief. The first predictor is how healthy the existing core business is in terms of growth prospects. The second is how much a company has in terms of uncommitted resources – whether that’s cash or people. What you get when you juxtapose the two is a lovely 2×2:

Corporate venturing orphans: With plentiful resources, people get resources to start new ventures, only to find that the core business is quite happy to ignore them. So, things get going, develop for a while, then wither on the vine as the core business essentially refuses to welcome them into the corporate fold.

The entrepreneurs behind such ventures either give up in frustration, leave to find a firm with a more welcoming environment or even leave to found a startup that might well compete with the original firm. The interesting story of how Zoom became Zoom is a case in point.

All-out venturing drives: In this situation, there is money to invest, company leadership knows it has a problem, and venturing becomes the holy grail. This can be useful, as it tends to raise the profile of the venturing activity and it finally attracts attention, talent and a seat at the table.

The dilemma is that senior leadership teams in a hurry are apt to put too much time pressure and expectations for rapid growth on a still-uncertain activity. This can cause them to lose faith in its prospects and terminate it before it even has a chance. IBM and Maersk’s effort to create a blockchain platform, TradeLens, feels like that to me. That venture also ignored Bent Flyvbjerg’s excellent advice to avoid complexity to the extent possible.

Venturing seems irrelevant: Here, money and talent is already committed to other things, and the core businesses’ chances are looking pretty good. So why bother with an uncertain, unproven, hard to predict new business activity when you can just ride the existing gravy train, probably for as long as is relevant for the career of a given senior leader?

What happens in this situation is that investments in new capabilities are ignored, and eventually competition catches up or makes your existing operations irrelevant. For instance, Carlson Travel was riding pretty high for a while, and evidently under-invested in technology. Carlson Travel implicitly acknowledged as it struggled through a bankruptcy that it had under-invested in its core digital technologies and customer experiences and promised to spent $100 million on getting up to speed.

Desperately Seeking Corporate Venturing! Ok, so we’ve left investing in the future too late, money is now tight, and we need to deliver something to our customers and investors PRONTO! These situations rarely end well. A desperate senior executive team might well enter into ill-considered acquisitions or now, belatedly, fund the one or two ideas that have survived being neglected.

These are often terrible ideas. See: checkered history of mainline telecom or cable companies entering the content business. AT&T’s misadventures with its forays into the media business are a case in point. Verizon’s as well. Desperation seldom leads to cool-headed deal-making or venturing. A rare exception took place at Xerox Parc, where the invention of the laser printer saved the company after the government forced it to essentially give away its patents to other firms.

It doesn’t have to be this way!

In the next Thought Spark, I’ll describe what we think about all this at Valize, my sister company whose mission is to create predictable and reliable innovation and growth capabilities. In the meantime, please stop pouring money into innovation theater!

Or if you are really itching to start an innovation or transformation program, mail us at growth@valize to set up a time. We can get you off on the right foot. After all, there are no standing ovations for innovation theater.

Image Credits: Unsplash, Pexels, MIT Sloan Review, www.collectivecamp.us

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Big Companies Should Not Try to Act Like Startups

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Big Companies Should Not Try to Act Like Startups

GUEST POST from Greg Satell

In 2009, Jeffrey Immelt set out on a journey to transform his company, General Electric, into a 124 year old startup. Although it was one of the largest private organizations in the world, with 300,000 employees, he sought to become agile and nimble enough to compete with high-flying Silicon Valley firms.

It didn’t end well. In 2017, problems in the firm’s power division led to massive layoffs. Immelt was forced to step down as CEO and GE was kicked off the Dow after 110 years. The company, which was once famous for its sound management, saw its stock tank. Much like most startups, the effort had failed.

Somewhere along the line we got it into our heads that large firms can’t innovate and should strive to act like startups. The truth is that they are very different types of organizations and need to innovate differently. While large firms can’t move as fast as startups, they have other advantages. Rather than try to act like startups, they need to leverage what they have.

Driving Innovation At Scale

The aviation industry is dominated by big companies. With a typical airliner costing tens of millions of dollars, there’s not much room for rapid prototyping. It takes years to develop a new product and the industry, perhaps not surprisingly, moves slowly. Planes today look pretty much the same as ones made decades ago.

Looks, however, can be deceiving. To understand how the aviation industry innovates, consider the case of Boeing’s 787 Dreamliner. Although it may look like any other airplane, Boeing redesigned the materials within it. So a 787 is 20 percent lighter and 20 percent more efficient than similar models. That’s a significant achievement.

Developing advanced materials is not for the faint of heart. You can’t do it in a garage. You need deep scientific expertise, state-of-the-art facilities and the resources to work for years—and sometimes decades— to discover something useful. Only large enterprises can do that,

None of this means that startups don’t have a role to play. In fact one small company, Citrine Informatics, is applying artificial intelligence to materials discovery and revolutionizing the field. Still, to take on big projects that have the potential to make huge global impacts, you usually need a large enterprise.

Powering Startups

All too often, we see large enterprises and startups as opposite sides of the coin, with big companies representing the old guard and entrepreneurs representing the new wave, but that’s largely a myth. The truth is that innovation often works best when large firms and small firms are able to collaborate.

Scott Lenet, President of Touchdown Ventures, sees this first-hand every day. His company is somewhat unique in that, unlike most venture capital firms, it manages internal funds for large corporations. He’s found that large corporations are often seen as value added investors because of everything they bring to the table.

“For example,” he told me, “one of our corporate partners is Kellogg’s and they have enormous resources in technical expertise, distribution relationships and marketing acumen. The company has been in business for over 100 years and it’s learned quite a bit about the food business in that time. So that’s an enormous asset for a startup to draw on.”

He also points out that, while large firms tend to know how to do things well, they can’t match the entrepreneurial energy of someone striving to build their own business. “Startups thrive on new ideas,” Lenet says “and big firms know how to scale and improve those ideas. We’ve seen some of our investments really blossom based on that kind of partnership.”

Creating New Markets

Another role that large firms play is creating and scaling new markets. While small firms are often more agile, large companies have the clout and resources to scale and drive impact. That often also creates opportunities for entrepreneurs as well.

Consider the case of personal computers. By 1980, startups like Apple and Commodore had already been marketing personal computers for years, but it was mostly a cottage industry. When IBM launched the PC in 1981, however, the market exploded. Businesses could now buy a computer from a supplier that they knew and trusted.

It also created fantastic opportunities for companies like Microsoft, Intel and a whole range of entrepreneurs who flocked to create software and auxiliary devices for PCs. Later startups like Compaq and Dell created PC clones that were compatible with IBM products. The world was never the same after that.

Today, large enterprises like IBM, Google and Amazon dominate the market for artificial intelligence, but once again they are also creating fantastic opportunities for entrepreneurs. By accessing the tools that the tech giants have created through APIs, small firms can create amazing applications for their customers.

Innovation Needs Exploration

Clearly, large firms have significant advantages when it comes to innovation. They have resources, customer relationships and deep expertise to not only invent new things, but to scale businesses and bring products to market. Still, many fail to innovate effectively, which is why the average lifespan of companies on the S&P 500 continues to decline.

There’s no reason why that has to be true. The problem is that most large organizations spend so much time and effort fine-tuning their operations to meet earnings targets that they fail to look beyond their present business model. That’s not due to any inherent lack of capability, it’s due to a lack of imagination.

Make no mistake, if you don’t explore, you won’t discover. If you don’t discover you won’t invent and if you don’t invent you will be disrupted. So while you need to focus on the business at hand, you also need to leave some resources un-optimized so that you can identify and develop the next great opportunity.

A good rule of thumb to follow is 70-20-10. Focus 70% of your resources on developing your present business, 20% of your resources on opportunities adjacent to your current business, such as new markets and technologies and 10% on developing things that are completely new. That’s how you innovate for the long term.

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

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Four Change Empowerment Myths

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Four Change Empowerment Myths

GUEST POST from Greg Satell

We live in a transformational age. Powerful technologies like the cloud and artificial intelligence are quickly shifting what it means to compete. Social movements like #MeToo and #BlackLivesMatter are exposing decades of misdeeds and rewriting norms. The stresses of modern life are creating new expectations about the relationship between work and home.

Every senior manager and entrepreneur I talk to understands the need to transform their enterprise, yet most are unsure of how to go about it. They ordinarily don’t teach transformation in business school and most management books minimize the challenge by reducing it to silly platitudes like “adapt or die.”

The truth is that change is hard because the status quo always has inertia on its side. Before we can drive a true transformation, we need to unlearn much of what we thought we knew. Change will not happen just because we want it to, nor can it be willed into existence. To make change happen, we first need to overcome the myths that tend to undermine it.

Myth #1: You Have To Start With A Bang

Traditionally, managers launching a new initiative have aimed to start big. They work to gain approval for a sizable budget as a sign of institutional commitment. They recruit high-profile executives, arrange a big “kick-off” meeting and look to move fast, gain scale and generate some quick wins. All of this is designed to create a sense of urgency and inevitability.

That works well for a conventional initiative, but for something that’s truly transformational, it’s a sure path to failure. Starting with a big bang will often provoke fear and resistance among those who don’t see the need for change. As I explain in my book, Cascades, real change always starts with small groups, loosely connected, united by a shared purpose.

That’s why it’s best to start off with a keystone change that represents a concrete and tangible goal, involves multiple stakeholders and paves the way for future change. That’s how you build credibility and momentum. While the impact of that early keystone change might be limited, a small, but successful, initiative can show what’s possible.

For example, when the global data giant Experian sought to transform itself into a cloud-based enterprise, it started with internal API’s that had limited effect on its business. Yet those early achievements spurred on a full digital transformation. In much the same way, when Wyeth Pharmaceuticals began its shift to lean manufacturing, it started with a single process at a single plant. That helped give birth to a 25% reduction of costs across the board.

Myth #2: You Need A Charismatic Leader And A Catchy Slogan

When people think about truly transformational change, a charismatic leader usually comes to mind. In the political sphere, we think of people like Mahatma Gandhi, Martin Luther King Jr. and Nelson Mandela. On the corporate side, legendary CEOs like Lou Gerstner at IBM and Steve Jobs at Apple pulled off dramatic turnarounds and propelled their companies back to prosperity.

Yet many successful transformations don’t have a charismatic leader. Political movements like Pora in Ukraine and Otpor and Serbia didn’t have clear leadership out front. The notably dry Paul O’Neill pulled of a turnaround at Alcoa that was every bit as impressive as the ones at IBM and Apple. And let’s face it, it wasn’t Bill Gates’s Hollywood smile that made Microsoft the most powerful company of its time.

The truth, as General Stanley McChrystal makes clear in his new book, Leaders: Myth and Reality, is that leadership is not so much about great speeches or snappy slogans or even how gracefully someone takes the stage, but how effectively a leader manages a complex ecosystem of relationships and builds a connection with followers.

And even when we look at charismatic leaders a little more closely, we see that it is what they did off stage that made the difference. Gandhi forged alliances between Hindus and Muslims, upper castes and untouchables as well as other facets of Indian society. Mandela did something similar in South Africa. Martin Luther King Jr. was not a solitary figure, but just one of the Big Six of civil rights.

That’s why McChrystal, whom former Defense Secretary Bob Gates called, “perhaps the finest warrior and leader of men in combat I had ever met,” advises that leaders need to be “empathetic crafters of culture.” A leader’s role is not merely to plan and direct action, but to inspire and empower belief.

Myth #3: You Need To Piece Together A Coalition

While managing stakeholders is critical, all too often it devolves into a game theory exercise in which a strategically minded leader horse trades among competing interests until he or she achieves a 51% consensus. That may be enough to push a particular program through, but any success is bound to be short-lived.

The truth is that you can’t transform fundamental behaviors without transforming fundamental beliefs and to do that you need to forge shared values and a shared consciousness. It’s very hard to get people to do what you want if they don’t already want what you want. On the other hand, if everybody shares basic values and overall objectives, it’s much easier to get everybody moving in the same direction.

For example, the LGBT movement foundered for decades by trying to get society to accept their differences. However, when it changed tack and started focusing on common values, such as the right to live in committed, loving relationships and to raise happy, stable families, public opinion changed in record time. The differences just didn’t seem that important any more.

In a similar vein, when Paul O’Neill took over Alcoa in 1987, the company was struggling. So analysts were puzzled that when asked about his strategy he said that “I intend to make Alcoa the safest company in America.” Yet what O’Neill understood was that safety goes part and parcel with operational excellence. By focusing on safety, it was much easier to get the rank and file on board and, when results improved, other stakeholders got on board too.

Myth #4: You Will End With The Vision You Started With

When Nelson Mandela first joined the struggle to end Apartheid, he was a staunch African nationalist. “I was angry at the white man, not at racism,” he would later write. “While I was not prepared to hurl the white man into the sea, I would have been perfectly happy if he climbed aboard his steamships and left the continent of his own volition.”

Yet Mandela would change those views over time and today is remembered and revered as a global citizen. In fact, it was the constraints imposed by the broad-based coalition he forged that helped him to develop empathy, even for his oppressors, and led him to govern wisely once he was in power.

In much the same way, Lou Gerstner could not have predicted that his tenure as CEO at IBM would be remembered for its embrace of the Internet and open software. Yet it was his commitment to his customers that led him there and brought his company back from the brink of bankruptcy to a new era of of prosperity.

And that is probably the most important thing we need to understand change. In order to make a true impact on the world, we first need to change ourselves. Every successful journey begins not with answers, but with questions. You have to learn how to walk the earth and learn things along the way. You know you’ve failed only when you end up where you started.

— Article courtesy of the Digital Tonto blog and an earlier version appeared on Inc.com
— Image credit: Pixabay

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We Need To Stop Glorifying Failure

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Here’s What To Do Instead

We Need To Stop Glorifying Failure

GUEST POST from Greg Satell

Over 50% of startups fail (and that number goes up to 75% for venture backed startups). The same is true of about three quarters of corporate transformations, which is probably why the average lifespan on the S&P 500 continues to shrink. These statistics tell a humbling story: few significant endeavors ever actually succeed.

So it’s probably not surprising that we’ve come to glorify failure. We are urged to “fail fast” and are cheered on when we do. Failure, after all, is hard evidence that you’ve tried something difficult and paid the price. Yet failure, as anyone who actually experienced it knows well, is a horrible, painful thing.

As I explain in Cascades, great transformations are achieved not by glorifying failure, but when we learn from mistakes and begin to do things differently. That’s how great enterprises are transformed, industries are disrupted and then remade a new and seemingly all powerful tyrants are overthrown. Failure is something we should never accept, but rather overcome.

Ask The Hard Questions

Go to just about any innovation conference and you will find some pundit on the stage telling the story of some corporate giant, usually Blockbuster, Kodak or Xerox, that stumbled and failed. It is then explained that these firms were run by silly, foolish people who simply didn’t want to see the signs of disruption around them.

These stories are almost never true and, in fact, should be seen as ridiculous on their face. It takes no small amount of intelligence, drive and ambition to run a significant enterprise so to suggest that executives managing highly successful businesses were utter dopes beggars belief. The truth is that smart, hard working people fail all the time.

Once you realize that it forces you to ask some hard questions. Why did these smart, successful people fail? Why weren’t the dangers lurking more obvious? What hidden forces were working against them? Why did they think that they actions they undertook, after no small amount of deliberation, were the best of the available options?

Consider the case of Mahatma Gandhi and his Himalayan miscalculation. In 1919, he organized a series of demonstrations to protest against unjust laws passed by the British Raj. These were successful at first, but soon got out of hand and eventually led to the massacre at Amritsar, in which British soldiers left hundreds dead and more than a thousand wounded.

Most people would have simply concluded that the British were far too cruel and brutal to be dealt with peacefully. Gandhi, however, looked for the error in his own actions and learned from his mistakes. A decade later, rather than embark on a wholesale revolt, he identified a keystone change that would break the logjam. Today, both the salt march that resulted, and Gandhi himself, have become icons.

Test Your Hypotheses (Cheaply)

If you want to get a project going in a typical organization, the first thing you do is try to procure a big budget. So you write up an impressive business plan, examine the political tea leaves and work your contacts. If you’re successful, you can build out a great staff, line up tier-one partners and really hit the ground running.

You also can’t make any mistakes. Unless your plan was truly bulletproof from conception (and it never is) or you just get really lucky, you’re going to make some big, well-funded, well-staffed blunder that you’ll have to scramble to recover from. Unless you catch it early or have the political clout within your organization to get more money, you are likely to fail.

Now consider how Nick Swinmurn started his business. As Eric Ries explained in The Lean Startup, instead of spending money on some expensive marketing study to see if people would buy shoes online, he simply built a cheap site. When he got an order, he would go to the store, buy the pair at retail, and ship it out. He lost money on every sale.

That’s a terrible way to run a business, but a great way to test a business hypothesis. Once he knew that people were willing to buy shoes online, he started Zappos, which quickly grew to dominate the market for selling shoes online. It was sold to Amazon in 2009, ten years after Swinmurn started, for $940 million.

Build A Network

We tend to think that success is the result of hard work and talent. Yet look at any category and one brand tends to dominate. There are many search engines, but only one Google, just like there are many smartphone manufacturers, but only one Apple. Both are great products, but they end up taking the vast majority of profits in their industry. Are they really that much better than their competitors?

The truth is, as Albert-László Barabási explains in The Formula, is that performance is bounded, but success isn’t. You can be better than your competitors, but not that much better. On the other hand, there are no limits to success because networks tend to be dominated by a central node.

To understand why, consider the case of Albert Einstein. Until April 3rd, 1921, he was a prominent scientist, but by no means an icon. In fact, much of his press coverage was negative. But on that date, he arrived in America with the Zionist leader Chaim Weizmann. Reporters covering the event mistook the enormous crowds there to meet Weizmann as fans of Einstein and the story made the first page of all major newspapers.

That, along with his brilliance and endearing personality, is what catapulted Einstein to iconic status. In a similar vein, Google launched its product on the techie-dense Stanford computer network and Apple introduced the iPhone to its already expansive fan base. It’s networks, not nodes, that drive success.

Stop Disrupting And Start Solving Problems

Walk down any grocery store aisle and it becomes clear that there is no shortage of ideas. At any given time there are countless opportunities for line extensions, expansions into new categories, partnerships and other things. Executives spend countless hours discussing the merits and demerits of ideas like these.

Yet innovation isn’t about ideas, it’s about solving problems. That’s why most ideas fail, because they don’t address a meaningful problem that people really need solved. Nobody really needs a different flavor of cereal, but Zappos, Google and Apple all met needs that people cared about and that made all the difference.

That’s why companies that last not only look to solve problems for today’s customers, but also take on grand challenges. These are not “bet the company” type of propositions, but long, sustained efforts that seek to fundamentally change the realm of the possible, like Google’s more than decade long quest to create a self-driving car or IBM’s generational pursuit of quantum computing.

The truth is that you never really have to fail because, if you make your efforts sustainable, you can always learn from mistakes and try again. Failure rarely stems from a lack of effort, but is guaranteed by a myopic vision.

— Article courtesy of the Digital Tonto blog and an earlier version appeared on Inc.com
— Image credit: Unsplash

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Where People Go Wrong with Minimum Viable Products

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Where People Go Wrong with Minimum Viable Products

GUEST POST from Greg Satell

Ever since Eric Reis published his bestselling book, The Lean Startup, the idea of a minimum viable product (MVP) has captured the imagination of entrepreneurs and product developers everywhere. The idea of testing products faster and cheaper has an intuitive logic that simply can’t be denied.

Yet what is often missed is that a minimum viable product isn’t merely a stripped down version of a prototype. It is a method to test assumptions and that’s something very different. A single product often has multiple MVPs, because any product development effort is based on multiple assumptions.

Developing an MVP isn’t just about moving faster and cheaper, but also minimizing risk. In order to test assumptions, you first need to identify them and that’s a soul searching process. You have to take a hard look at what you believe, why you believe it and how those ideas can be evaluated. Essentially, MVP’s work because they force you to do the hard thinking early.

Every Idea Has Assumptions Built In

In 1990, Nick Swinmurn had an idea for a business. He intended to create a website to sell shoes much like Amazon did for books. This was at the height of the dotcom mania, when sites were popping up to sell everything from fashion to pet food to groceries, so the idea itself wasn’t all that original or unusual.

What Swinmurn did next, however, was. Rather than just assuming that people would be willing to buy shoes online or conducting expensive marketing research, he built a very basic site, went to a shoe store and took pictures of shoes, which he placed on the site. When he got an order, he bought the shoes retail and shipped them out. He lost money on every sale.

That’s a terrible way to run a business, but a great — and incredibly cheap — way to to test a business idea. Once he knew that people were willing to buy shoes online, he began to build all the elements of a fully functioning business. Ten years later, the company he created, Zappos was acquired by Amazon for $1.2 billion.

Notice how he didn’t just assume that his business idea was viable. He tested it and validated it. He also learned other things, such as what styles were most popular. Later, Zappos expanded to include handbags, eyewear, clothing, watches, and kids’ merchandise.

The Cautionary Tale Of Google Glass

Now compare how Swinmurn launched his business with Google’s Glass debacle. Instead of starting with an MVP, it announced a full-fledged prototype complete with a snazzy video. Through augmented reality projected onto the lenses, users could seamlessly navigate an urban landscape, send and receive messages and take photos and videos. It generated a lot of excitement and seemed like a revolutionary new way to interact with technology.

Yet criticism quickly erupted. Many were horrified that hordes of wandering techno-hipsters could be surreptitiously recording us. Others had safety concerns about everything from people being distracted while driving to the devices being vulnerable to hacking. Soon there was a brewing revolt against “Google Glassholes.”

Situations like the Google Glass launch are startlingly common. In fact, the vast majority of new product launches fail because there’s no real way to know whether you have the right product-market fit customers actually get a chance to interact with the product. Unfortunately, most product development efforts start by seeking out the largest addressable market. That’s almost always a mistake.

If you are truly creating something new and different, you want to build for the few and not the many. That’s the mistake that Google made with its Glass prototype.

Identifying A Hair On Fire Use Case

The alternative to trying to address the largest addressable market is to identify a hair-on-fire use case. The idea is to find a potential customer that needs to solve a problem so badly that they almost literally have their hair on fire. These customers will be more willing to co-create with you and more likely to put up with the inevitable bugs and glitches that always come up.

For example, Tesla didn’t start out by trying to build an electric car for the masses. Instead, it created a $100,000 status symbol for Silicon Valley millionaires. Because these customers could afford multiple cars, range wasn’t as much of a concern. The high price tag also made a larger battery more feasible. The original Tesla Roadster had a range of 244 miles.

The Silicon Valley set were customers with their hair on fire. They wanted to be seen as stylish and eco-friendly, so were willing to put up with the inevitable limitations of electric cars. They didn’t have to depend on them for their commute or to pick the kids up at soccer practice. As long as the car was cool enough, they would buy it.

Interestingly, Google Glass made a comeback as an industrial product and had a nice run from 2019 to 2023 before they went away for good. For hipsters, an augmented reality product is far from a necessity, but a business that needs to improve productivity can be a true “hair-on-fire” use case. As the product improves and gains traction, it’s entirely possible that it eventually makes its way back to the consumer market in some form.

Using An MVP To Pursue A Grand Challenge

One of the criticisms of minimum viable products is that they are only suited for simple products and tweaks, rather than truly ambitious projects. Nothing could be further from the truth. The reality is that the higher your ambitions, the more important it is for you to start with a minimum viable product.

IBM is one company that has a long history of pursuing grand challenges such as the Deep Blue project which defeated world champion Garry Kasparov at chess and the Blue Gene project which created a new class of “massively parallel” supercomputers. More recently were the Jeopardy grand challenge, which led to the development of its current Watson business and the Debater project.

Notice that none of these were fully featured products. Rather they were attempts to, as IBM’s Chief Innovation Officer, Bernie Meyerson, put it to me, invent something that “even experts in the field, regard as an epiphany and changes assumptions about what’s possible.” That would be hard to do if you were trying to create a full featured product for a demanding customer.

That’s the advantage of creating an MVP. It essentially acts as a research lab where you can safely test hypotheses and eliminate sources of uncertainty. Once you’ve done that, you can get started trying to build a real business.

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

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Diversity as a Catalyst for Innovation

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GUEST POST from Chateau G Pato

In today’s hyper-competitive global market, organizations are continuously striving for innovative solutions to complex challenges. With the world growing more interconnected, the concept of diversity and inclusion has become not just a moral obligation but also a strategic advantage for innovation. A diversified workforce brings varied perspectives and skills, fueling creativity and driving transformation. In this article, I explore how embracing diversity serves as a catalyst for innovation through insightful case studies and evidence-based practices.

The Power of Diverse Perspectives

Diversity comes in many forms, including but not limited to race, gender, age, cultural background, and professional experience. Each aspect of diversity contributes unique lenses through which problems can be viewed, thus sparking fresh ideas and innovative solutions. It allows organizations to empathize with a wider array of customers and respond to their needs in nuanced ways.

Case Study 1: IBM’s Diversity Initiative

IBM is a leading example of how diversity can drive innovation. Recognizing the wealth of different perspectives afforded by a diverse workforce, IBM instituted “Diversity 3.0.” This initiative aimed not just to hire diverse talent but to embed inclusion into the very fabric of its operations.

By creating diverse teams tasked with innovation projects, IBM discovered that such groups were able to solve problems more effectively and create products that resonated globally. For instance, the formation of a multicultural team led to the development of IBM Watson’s language translation services. Through the team’s varied backgrounds and insights, IBM was able to refine Watson’s capabilities, making it a powerful tool across different languages and cultures.

Case Study 2: The LEGO Group’s Diverse User Base

The LEGO Group showcases how embracing diversity can influence product development and innovation. Traditionally, LEGO had focused on a narrow demographic. However, by engaging with a more inclusive user base, LEGO discovered untapped potential in diverse customer insights.

LEGO’s creation of the “LEGO Ideas” platform, where fans of all ages and backgrounds could submit and vote on designs, allowed the company to leverage this diversity. It resulted in innovative sets that appealed to a wider audience, such as the “Women of NASA” set. This initiative not only boosted creativity and market reach but also reinforced the brand’s commitment to inclusion.

Strategies for Harnessing Diversity

Inclusive Leadership: Leaders must create a culture where diversity is valued and where different voices are heard. This involves not only recruiting diverse talent but also ensuring they feel empowered to contribute.
Cross-Cultural Collaboration: Encouraging collaboration among teams from different cultural backgrounds can foster creative problem-solving and lead to innovative breakthroughs.
Training and Education: Providing continuous learning opportunities about the benefits of diversity and developing skills to manage diverse teams can pave the way for sustained innovation.

Conclusion

Diversity is no longer just a metric to be achieved, but a critical driver of innovation. By fostering an inclusive culture, organizations can draw on a broader spectrum of ideas and perspectives, leading to groundbreaking innovations. As the world continues to change at a rapid pace, those who embrace diversity as a catalyst for innovation will not only survive but thrive.

Let us commit to weaving diversity into the strategic fabric of our organizations and unlock the full potential of our collective creativity.

Extra Extra: Because innovation is all about change, Braden Kelley’s human-centered change methodology and tools are the best way to plan and execute the changes necessary to support your innovation and transformation efforts — all while literally getting everyone all on the same page for change. Find out more about the methodology and tools, including the book Charting Change by following the link. Be sure and download the TEN FREE TOOLS while you’re here.

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Design Thinking versus Human-Centered Design

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Clearing the Confusion

Design Thinking versus Human-Centered Design

GUEST POST from Chateau G Pato

In the realm of innovation and creative problem-solving, two approaches often emerge as frontrunners: Design Thinking and Human-Centered Design. While these methodologies share similarities, they are not identical. Understanding their nuances is essential for organizations striving to remain competitive and truly meet the needs of their users.

Understanding Design Thinking

Design Thinking is a solution-focused methodology that revolves around a structured innovation cycle. It comprises five stages:

Empathize
Define
Ideate
Prototype
Test

This approach is both iterative and non-linear, allowing teams to move back and forth between phases as needed. It emphasizes understanding the end-user, challenging assumptions, and redefining problems to identify alternative strategies and solutions.

Exploring Human-Centered Design

Human-Centered Design (HCD), on the other hand, is an approach that prioritizes the users, their needs, and their challenges at every phase of the design process. HCD is deeply rooted in empathy for the user, with a strong focus on co-creation and active involvement of stakeholders throughout the design and development process.

HCD follows a similar journey to Design Thinking with slightly different emphases: Inspiration, Ideation, and Implementation. Its essence lies in creating solutions that are not only innovative but also truly resonate with and enhance users’ experiences.

Key Differences

While both methodologies prioritize the user and involve iterative processes, the key differences lie in their application and focus:

Application Scope: Design Thinking is often applied more broadly beyond design contexts, in corporate strategy, service design, and product management. Human-Centered Design, however, remains closely tied to the design field itself.
Emphasis: HCD places a stronger emphasis on empathy and user engagement throughout the process, while Design Thinking maintains a balance between user needs and business viability.

Case Study 1: IBM’s Adoption of Design Thinking

IBM’s Transformation Through Design Thinking

IBM is an exemplary case study of how embracing Design Thinking cultivates innovation. Traditionally known for its technical and engineering prowess, IBM found itself needing to pivot towards a more user-oriented approach to keep pace with evolving market demands.

By training over 100,000 employees in Design Thinking, IBM fundamentally shifted its corporate culture. This initiative encouraged cross-functional collaboration and a deeper connection to user insights. As a result, IBM was able to accelerate product development cycles and significantly improve the customer experience across their service offerings.

An example of this transformation is the redesign of IBM’s enterprise cloud offerings. Through Design Thinking workshops, they discovered that the complexity of their product was hindering user adoption. By empathizing with the user and iterating on design prototypes, IBM streamlined its cloud interface, leading to a significant uptick in user satisfaction and engagement.

Case Study 2: IDEO and Human-Centered Design in Action

IDEO’s Human-Centered Design Approach to Healthcare

IDEO, a global design company, is a beacon of Human-Centered Design, particularly renowned for its work in healthcare. One compelling case is IDEO’s collaboration with the healthcare sector to redesign patient experience.

By employing HCD techniques, IDEO involved patients, doctors, and nurses in the entire design process. Through in-depth interviews, shadowing medical staff, and empathy-building exercises, IDEO identified that the anxiety and fear surrounding hospital visits stemmed largely from uncertainty and lack of clear communication.

Taking these insights, IDEO created new hospital layouts that integrated clearer signage and communication touchpoints. They developed prototype communication tools that ensured patients were continually informed of treatment processes. These changes dramatically reduced patient anxiety and improved overall satisfaction scores in the hospitals they partnered with.

Conclusion: Bridging the Gap

To clear the confusion between Design Thinking and Human-Centered Design, organizations need to realize that while both are valuable, their adoption depends on specific needs and contexts. Design Thinking may be better suited for broader strategic or organizational innovation, whereas Human-Centered Design offers unparalleled depth in user-focused product and experience development.

Ultimately, integrating the strengths of both methodologies can create a powerful design and innovation strategy that not only meets user needs but also drives meaningful business results. By cultivating a culture of empathy and user engagement, organizations can transcend traditional problem-solving paradigms and achieve sustainable innovation.

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