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How to Pursue a Grand Innovation Challenge

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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Is Disruption About to Claim a New Victim?

Kodak. Blockbuster. Google?

GUEST POST from Robyn Bolton

You know the stories.  Kodak developed a digital camera in the 1970s, but its images weren’t as good as film images, so it ended the project.  Decades later, that decision ended Kodak.  Blockbuster was given the chance to buy Netflix but declined due to its paltry library of titles (and the absence of late fees).  A few years later, that decision led to Blockbuster’s decline and demise.  Now, in the age of AI, disruption may be about to claim another victim – Google.

A very brief history of Google’s AI efforts

In 2017, Google Research invented Transformer, a neural network architecture that could be trained to read sentences and paragraphs, pay attention to how the words relate to each other, and predict the words that would come next. 

In 2020, Google developed LaMDA, or Language Model for Dialogue Applications, using Transformer-based models trained on dialogue and able to chat. 

Three years later, Google began developing its own conversational AI using its LaMDA system. The only wrinkle is that OpenAI launched ChatGPT in November 2022. 

Now to The Financial Times for the current state of things

“In early 2023, months after the launch of OpenAI’s groundbreaking ChatGPT, Google was gearing up to launch its competitor to the model that underpinned the chatbot.

.

The search company had been testing generative AI software internally for several months by then.  But as the company rallied its resources, multiple competing models emerged from different divisions within Google, vying for internal attention.”

That last sentence is worrying.  Competition in the early days of innovation can be great because it pushes people to think differently, ask tough questions, and take risks. But, eventually, one solution should emerge as superior to the others so you can focus your scarce resources on refining, launching, and scaling it. Multiple models “vying for internal attention” so close to launch indicate that something isn’t right and about to go very wrong.

“None was considered good enough to launch as the singular competitor to OpenAI’s model, known as ChatGPT-4.  The company was forced to postpone its plans while it tried to sort through the scramble of research projects.  Meanwhile, it pushed out a chatbot, Bard, that was widely viewed to be far less sophisticated than ChatGPT.”

Nothing signals the threat of disruption more than “good enough.”  If Google, like most incumbent companies, defined “good enough” as “better than the best thing out there,” then it’s no surprise that they wouldn’t want to launch anything. 

What’s weird is that instead of launching one of the “not good enough” models, they launched Bard, an obviously inferior product. Either the other models were terrible (or non-functional), or different people were making different decisions to achieve different definitions of success.  Neither is a good sign.

When Google’s finished product, Gemini, was finally ready nearly a year later, it came with flaws in image generation that CEO Sundar Pichai called ‘completely unacceptable’ – a let-down for what was meant to be a demonstration of Google’s lead in a key new technology.”

“A let-down” is an understatement.  You don’t have to be first.  You don’t have to be the best.  But you also shouldn’t embarrass yourself.  And you definitely shouldn’t launch things that are “completely unacceptable.”

What happens next?

Disruption takes a long time and doesn’t always mean death.  Blackberry still exists, and integrated steel mills, one of Clayton Christensen’s original examples of disruption, still operate.

AI, LLMs, and LaMDAs are still in their infancy, so it’s too early to declare a winner.  Market creation and consumer behavior change take time, and Google certainly has the knowledge and resources to stage a comeback.

Except that that knowledge may be their undoing.  Companies aren’t disrupted because their executives are idiots. They’re disrupted because their executives focus on extending existing technologies and business models to better serve their best customers with higher-profit offerings.  In fact, Professor Christensen often warned that one of the first signs of disruption was a year of record profits.

In 2021, Google posted a profit of $76.033 billion. An 88.81% increase from the previous year.

2022 and 2023 profits have both been lower.

Image credit: Unsplash

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Happy Employees Make Happy Customers

Happy Employees Make Happy Customers

GUEST POST from Shep Hyken

Often, the best companies to do business with are the best companies to work for. When you look at the Google ratings for Round Room Holdings’ TCC and Wireless Zone, two Verizon Wireless retailers with approximately 1,200 retail stores throughout the U.S., you’ll find they are “hitting it out of the park” in both customer reviews and employee satisfaction. I had a chance to interview Chad Jensen, president of TCC and Wireless Zone since 2019, and he shed light on their incredible success, how they do it, and how any company can have similar results.

We can break down the company’s success into three areas: employees, customers, and community.

1. Employees: It all starts with the employees. Jensen’s company has a 90% employee satisfaction rating and 70% employee retention in a retail industry with annual employee turnover rates that are well over 100%. Why? Because Jensen made it abundantly clear that the company puts employees first. The best example of this came not even a year after he took over as president when he and the rest of the world faced the pandemic. His leadership style was immediately put to the test. He was adamant about taking care of the employees. First and foremost was safety, as well as a concern for mental health. And he was determined to keep people employed, saying, “Even if it meant we took a hit on our financials, we were okay with that.” He understood early on that the decisions they made would define how they came out of the pandemic. Employees knew the company had their backs. In exchange, they were confident, fulfilled, and engaged with their customers, ensuring they had an experience that would bring them back. Employee satisfaction is at 90%. As I’ve mentioned many times in my past articles, what’s happening inside an organization is felt by customers on the outside. Jensen’s strategy shows this concept can be tremendously successful.

2. Customers: A focus on the employee experience turns into a positive customer experience. The goal is to provide “the best customer service.” Being the best is a lofty goal. While it’s not a contest, the comment speaks to the commitment the retailer has to its customers. The numbers tell the story. The company’s Google score ranges from 4.7 to 4.9 out of five. Jensen beams with pride over the customer satisfaction numbers, as companies he admires, such as Disney and Chick-fil-A, don’t have numbers quite as high. Jensen said, “We checked, and Disneyland’s Google rating was a 4.5. We’re literally (making customers) happier than the ‘Happiest Place on Earth.’” While a high Google rating is validating, Jensen emphasizes it’s really about the experience that gets customers to come back.

3. Community: Jensen’s efforts to give back to the community create positive results on several levels. He explained, “The more we give back to our communities, the more presence we get, and the better employees we get.” Many companies have a purpose beyond profit. It’s typically a recognizable cause, such as sustainability, poverty, medical research, or other popular causes. Companies like Ace Hardware have raised more than $140 million for the Children’s Miracle Network Hospitals. Patagonia gives 1% of its sales to the preservation and restoration of the environment. TCC and Wireless Zone take a more grassroots approach and give back to the communities their stores serve. They sponsor community events, local pet shelters, food banks, school events, and more. They have given more than 1.3 million backpacks filled with school supplies to kids in their communities. While the corporate HQ is behind this “give back” program, it’s the employees who get the most joy out of being a part of it, once again creating a great employee experience.

By prioritizing the TCC and Wireless Zone employee experience, combined with efforts to create an amazing customer experience as well as support for the communities they serve, the result is a company with some of the lowest turnover in the retail industry, higher Google ratings than “The Happiest Place on Earth” and loyal customers who keep coming back. That’s what happens when you create a company that has what Jensen refers to as “a culture of good.”

Image Credits: Pixabay
This article originally appeared on Forbes.com

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Powering the Google Innovation Machine with the World’s Top Minds

Powering the Google Innovation Machine with the World's Top Minds

GUEST POST from Greg Satell

It’s no secret that Google is one of the most innovative companies on the planet. Besides pioneering and then dominating the search industry, it has also become a leader in developing futuristic technologies such as artificial intelligence, driverless cars and quantum computing. It has even launched a life science company.

What makes Google so successful is not one particular process, but how it integrates multiple strategies into a seamless whole. For example, Google Brain started out as a 20% time project, then migrated out to its “X” Division to accelerate development and finally came back to the mothership, where it now collaborates closely with engineering teams to build new products.

Yet perhaps its most important strategy, in fact the one that makes much of the rest possible, is how it partners with top scientists in the academic world. This is no “quick hit,” but a well thought out, long-term game plan designed to establish deep relationships based on cutting edge science and embed that knowledge deeply into just about everything Google does.

Building Deep Relationships to the Academic Community

“We design a variety programs that widen and deepen our relationships with academic scientists,” Maggie Johnson, who heads up University Relations at Google, told me. In fact, there are three distinct ways that Google engages directly with scientists beyond the typical research partnerships with universities.

The first is its Faculty Research Awards program, which are small one-year grants, usually to graduate students or postdocs whose work may be of interest to Google. These are unrestricted gifts, although recipients are highly encouraged to publish their work publicly, that allow the company to develop relationships with young talent at the beginning of their careers.

While anybody can apply for a Faculty Research Award, Focused Research Awards are only available by invitation. Typically, these are awarded to more senior researchers that Google has already had some contact with and last two to three years. However, they are also unrestricted grants that researchers can use as they see fit.

The third way that Google engages with scientists to to proactively engage leaders in a particular field of interest. Geoffrey Hinton, for example, is a pioneer in neural networks and widely considered one of the top AI experts in the world. He splits his time between his faculty position at the University of Toronto and working on Google Brain.

“Spinning In” World Class Scientists

The academic research programs provide many benefits to Google as a company. They give access to the most promising students for recruiting, allow it to help shape university curriculums and keep it connected to breakthrough research in important fields. However, the most direct benefits probably come inviting researchers to spend a sabbatical year at Google, which it calls its Visiting Faculty Program.

For example, Andrew Ng, a top AI researcher, decided to spend a year working at Google and quickly formed a close working relationship with two of the company’s brightest minds, Greg Corrado and Jeff Dean, who were interested in what was then a new brand of artificial intelligence called deep learning. Their collaboration became the Google Brain project.

The Visiting Faculty Program touches on everything Google does. Recently they’ve had people visiting the company like John Canny at UC Berkeley, who helped with the development of TPU’s, chips specialized to run Google’s AI algorithms and Michael Rabin, a Turing Award winning mathematician who was working on auction algorithms. For every Google priority, at least one of the world’s top minds is working with the company on it.

What makes the sabbatical program unusual is how deeply it is integrated into everyday work at the company. “In most cases, these scientists have already been working with our teams through one of our other programs, so the groundwork for a productive relationship has already been laid,” Maggie Johnson told me.

Developing “Win-Win” Relationships

One of the things that makes Google’s outreach to researchers work so well is that it is truly a win-win arrangement. Yes, the company gets top experts in important fields to work on its problems, but the researchers themselves get to work with unparalleled tools and data sets. They also get a much better sense of what problems are considered important in a commercial environment.

Katya Scheinberg, a Professor at Lehigh University who focuses on optimization problems, found working at Google to be a logical extension of her earlier collaboration with the company. “I had been working on large-scale machine learning problems and had some connections with Google scientists. So spending part of my sabbatical year at the company seemed fairly natural. I learned a lot about the practical problems that private sector researchers are working on,” she told me.

Since leaving Google, she’s found that her time at the company has shifted the focus of her research. “Working at Google got me interested in some different problems and alerted me to the possibility of applying some approaches I had worked on before to different fields of application.”

Sometimes scholars stay for longer and can have a transformative impact on the company. As noted above, Andrew Ng spent several years at the company. Andrew Moore, a renowned computer scientist and a former Dean of Carnegie Mellon’s computer program, took a leave of absence from his university to set up Google’s Research Center in Pittsburgh. Lasting relationships like these are rare in industry, but incredibly valuable.

Connecting to Discovery Is Something Anyone Can Do, But You Have to Make the Effort

Clearly, Google is an unusual company. There’s not many places that can attract the type of talent that it can. However, just about any business can, for example, support the work of a young graduate student or postdoc at a local university. In much the same way, inviting even a senior researcher to come for a short time is not prohibitively expensive.

Innovation is never a single event, but a process of discovery, engineering and transformation. It is by connecting to discovery that businesses can truly see into the future and develop the next generation of breakthrough products. Unfortunately, few businesses realize the importance of connecting with the academic world.

Make no mistake, if you don’t discover, you won’t invent and if you don’t invent you will be disrupted eventually. It’s just a matter of time. However, you can’t just show up one day and decide you want to work with the world’s greatest minds. Even Google, with all its resources and acumen, has had to work really hard at it.

It’s made these investments in time, focus and resources because it understands that the search business, as great as it is, won’t deliver outsized profits forever. Today, we no longer have the luxury to manage for stability, but must prepare for disruption.

— Article courtesy of the Digital Tonto blog and previously appeared on Inc.com
— Image credit: Dall-E on Bing

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Big Companies Should Not Try to Act Like Startups

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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We Need To Stop Glorifying Failure

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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Why Most Corporate Innovation Programs Fail

(And How To Make Them Succeed)

Why Most Corporate Innovation Programs Fail

GUEST POST from Greg Satell

Today, everybody needs to innovate. So it shouldn’t be surprising that corporate innovation programs have become wildly popular. There is an inherent tradeoff between innovation and the type of optimization that operational executives excel at. Creating a separate unit to address innovation just makes intuitive sense.

Yet corporate innovation programs often fail and it’s not hard to see why. Unlike other business functions, like marketing or finance, in a healthy organization everybody takes pride in their ability to innovate. Setting up a separate innovation unit can often seem like an affront to those who work hard to innovate in operational units.

Make no mistake, a corporate innovation program is no panacea. It doesn’t replace the need to innovate every day. Yet a well designed program can augment those efforts, take the business in new directions and create real value. The key to a successful innovation program is to develop a clear purpose built on a shared purpose that can solve important problems.

A Good Innovation Program Extends, It Doesn’t Replace

It’s no secret that Alphabet is one of the most powerful companies in the world. Nevertheless, it has a vulnerability that is often overlooked. Much like Xerox and Kodak decades ago, it’s highly dependent on a single revenue stream. In 2018, 86% of its revenues came from advertising, mostly from its Google search business.

It is with this in mind that the company created its X division. Because the unit was set up to pursue opportunities outside of its core search business, it didn’t encounter significant resistance. In fact, the X division is widely seen as an extension of what made Alphabet so successful in the first place.

Another important aspect is that the X division provides a platform to incubate internal projects. For example, Google Brain started out as a “20% time project.” As it progressed and needed more resources, it was moved to the X division, where it was scaled up further. Eventually, it returned to the mothership and today is an integral part of the core business.

Notice how the vision of the X division was never to replace innovation efforts in the core business, but to extend them. That’s been a big part of its success and has led to exciting new business like Waymo autonomous vehicles and the Verily healthcare division.

Focus On Commonality, Not Difference

All too often, innovation programs thrive on difference. They are designed to put together a band of mavericks and disruptors who think differently than the rest of the organization. That may be great for instilling a strong esprit de corps among those involved with the innovation program, but it’s likely to alienate others.

As I explain in Cascades, any change effort must be built on shared purpose and shared values. That’s how you build trust and form the basis for effective collaboration between the innovation program and the rest of the organization. Without those bonds of trust, any innovation effort is bound to fail.

You can see how that works in Alphabet’s X division. It is not seen as fundamentally different from the core Google business, but rather as channeling the company’s strengths in new directions. The business opportunities it pursues may be different, but the core values are the same.

The key question to ask is why you need a corporate innovation program in the first place. If the answer is that you don’t feel your organization is innovative enough, then you need to address that problem first. A well designed innovation program can’t be a band-aid for larger issues within the core business.

Executive Sponsorship Isn’t Enough

Clearly, no corporate innovation program can be successful without strong executive sponsorship. Commitment has to come from the top. Yet just as clearly, executive sponsorship isn’t enough. Unless you can build support among key stakeholders inside and outside the organization, support from the top is bound to erode.

For example, when Eric Haller started Datalabs at Experian, he designed it to be focused on customers, rather than ideas developed internally. “We regularly sit down with our clients and try and figure out what’s causing them agita,” he told me, “because we know that solving problems is what opens up enormous business opportunities for us.”

Because the Datalabs units works directly with customers to solve problems that are important to them, it has strong support from a key stakeholder group. Another important aspect at Datalabs is that once a project gets beyond the prototype stage it goes to one of the operational units within the company to be scaled up into a real business. Over the past five years businesses originated at Datalabs have added over $100 million in new revenues.

Perhaps most importantly, Haller is acutely aware how innovation programs can cause resentment, so he works hard to reduce tensions through building collaborations around the organization. Datalabs is not where “innovation happens” at Experian. Rather it serves to augment and expand capabilities that were already there.

Don’t Look For Ideas, Identify Meaningful Problems

Perhaps most importantly, an innovation program should not be seen as a place to generate ideas. The truth is that ideas can come from anywhere. So designating one particular program in which ideas are supposed to happen will not only alienate the rest of the organization, it is also likely to overlook important ideas generated elsewhere.

The truth is that innovation isn’t about ideas. It’s about solving problems. In researching my book, Mapping Innovation, I came across dozens of stories from every conceivable industry and field and it always started with someone who came across a problem they wanted to solve. Sometimes, it happened by chance, but in most cases I found that great innovators were actively looking for problems that interested them.

If you look at successful innovation programs like Alphabet’s X division and Experian’s Datalabs, the fundamental activity is exploration. X division explores domains outside of search, while Datalabs explores problems that its customers need solved. Once you identify a meaningful problem, the ideas will come.

That’s the real potential of innovation programs. They provide a space to explore areas that don’t fit with the current business, but may play an important role in its future. A good innovation program doesn’t replace capabilities in the core organization, but leverages them to create new opportunities.

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

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Underground Innovation

How giving people space can make a big difference to your innovation profile

Underground Innovation

GUEST POST from John Bessant

If you’d snuck up behind me last weekend you’d have caught me in the act of painting walls. Not the most exciting of pursuits but it needed to be done so that now I can sit here and write in a freshly-painted room. And importantly one where even my clumsy brushwork doesn’t show in unsightly streaks and overruns. I am amongst millions of painters, professional and otherwise who regularly mutter small votes of thanks to Richard Drew and his invaluable contribution to the world of painting and decorating — masking tape.

This humble but essential innovation is getting on in years but still turns a profit for the company which originated it way back in 1925–3M. But it would never have seen the light of day if company strategy and official policy had prevailed. It exists because of Drew’s late night and unofficial efforts in direct defiance of his boss’s orders.

Drew was working as a technical salesman, dealing with some of the copmpany’s biggest customers for their core product — sandpaper. He spent a lot of time visiting car factories in that newly-growing industry, and in particular the paint shops where sandpaper was used to prepare metal surfaces for painting.

The paint crews were well aware of the good old days when Henry Ford had simplified their job — in 1909 he’d outlined a strategy for his company, which concentrated on a single model (the Model T) which could be built in high volume at low price. Doing this involved a number of trade-offs, not least in terms of massively editing down the choices available to customers. It was at this strategy meeting that he reputedly said ‘Any customer can have a car painted any colour that he wants so long as it is black.’

That decision helped establish the Model T as ‘a car for Everyman at a price every man can afford’, bringing the price down by 75% and putting it within the reach of many people. But it didn’t satisfy the market for long. People wanted more choice in models, styles — and colour schemes. All of which made life more difficult for the skilled craftsmen in the paint shops, trying to deliver ever more exotic paint jobs without slowing down production.

The problem is that when you want to paint with more than one colour then you need to cover up the area you don’t want painted. Which is a clumsy fussy business; early attempts involved using rags, newspapers and scraps of cardboard but then they had to be held in place, making a one-man job into a two-man job. Attempts to solve this by using sticky tape to hold the mask in place also failed; the solvents in the paint dissolved the adhesive on the tape making the whole mask slip and slide all over the surface.

An Innovation Dust-up

Which is where Richard Drew came in, trying to sell a new kind of sandpaper which 3M had launched which offered to cut down the dust created when preparing a metal surface for painting. Hearing some choice language coming from one corner of the shop he walked over to ask what the problem was — to be given an expletive filled tutorial in how not to mask up a paint job. What was needed — he was told in no uncertain terms — was a better adhesive tape which would actually stick and stay stuck!

He went back to his office and began to tinker around with various formulations to try and make something suitable. His boss wasn’t too pleased, ordering him to get back to his main job of selling sandpaper — but he kept on with the quest.

It took him two years and involved a variety of vegetable oils, chicle, linseed, various resins, glue, glycerine and treated crepe paper. What he eventually came up with was a tape strong enough to stick to the surfaces but easy enough to peel off without leaving any scars on the paintwork. Despite its promise his boss wouldn’t allow him to buy the machinery he needed to produce it in quantity — so Drew turned his innovative skills to the problem of financing capital equipment. He bought his machinery in small pieces, each of which cost less than the $99 he was permitted to spend on an item of equipment., and then assembled the machine himself.

This last act finally convinced his boss to let him go ahead — and also provided a lesson which became a company mantra. The boss in question was William McKnight and he made a key policy out of the experience. “If you have the right person on the right project, and they are absolutely dedicated to finding a solution — leave them alone. Tolerate their initiative and trust them.”

And so 3M’s ‘bootlegging’ approach was born, and it persists today embodied now in formal company policy. Give people permission to play around, don’t control them too tightly and let their natural creativity and entrepreneurship do the rest. Their 15% policy (allowing employees to spend up to 15% of their time in pursuit of their own ideas and hunches) has been responsible for thousands of product and process innovations, a few of which (like PostIt Notes) have gone on to be breakthrough radical innovations.

Operating Below the Radar

The masking tape story is a classic example of innovation happening below the radar screen (except the radar wasn’t invented in 1925!). We know today that smart companies who care about innovation invest in the capacity for innovation — R&D and market research, future scoping, etc. Organized innovation, buying themselves options on the future. All good — but maybe only focusing on the formal means potentially missing out on what might be happening underground. Because by their nature people are innovators, prone to experiment and tinker around, frustrated with aspects of their work which they think a little hacking around the edges might help them with. Why not tap into this as another source of innovation?

(Especially since it’s actually not that expensive in terms of lost productive time. The origin of the 15% figure at 3M was McKnight’s the observation that this was the time people spent on coffee breaks and on lunch breaks and so on, times when they could do some of this unofficial innovation).

It’s not just the benefits in terms of the possible product and process innovations which it might lead to. It’s also a powerful motivator, something which can help retain and inspire employees. Allowing people time and space to explore communicates a core company value — — it’s an invitation to tinker to hack things, to play around. And it has certainly paid off for 3M and other companies; consider these examples:

  • The Sony PlayStation started as a bootleg project by Ken Kutaragi, an engineer who secretly worked on a video game console with Nintendo without Sony’s approval.
  • The HP DeskJet printer was originally developed by a group of HP engineers who wanted to create a low-cost inkjet printer for personal use. They used bootleg parts and software to build their first prototype, which they hid under a tablecloth when not in use.
  • The first spreadsheet software was created by two programmers Dan Bricklin and Bob Frankston, who worked on their project without any formal support or funding from their employers. They went on to found their own company, Visicalc, which for a while was the market leader in the field.
  • Google’s 20% allowing employees time to spend on personal projects led to several innovations including Google Maps, Google News and Gmail.
  • Toshiba’s pioneering notebook computer was developed by a team of engineers who worked on it covertly for four years. They used their own laptops and software tools to create a prototype that featured innovative elements such as a lightweight design, a long battery life and a high-performance processor. The project was initially rejected by the management, but later accepted after some modifications. Introduced in 1985 it became a global leader in the portable computer market.
  • BMW has a long history of bootleg innovations which have gone on to become success stories. For example the Z1 roadster was developed by a small team of engineers who worked on it secretly for four years. They used their own time and resources to create a prototype that featured innovative elements such as a plastic body, retractable doors and a modular design. The project was eventually discovered by the top management and approved for production in 1986. And the iDrive was developed by a team of engineers who worked on it without any formal mandate or budget, using their own laptops and software tools. They also conducted user tests with their own cars and friends. The project was initially rejected by the management, but later became a standard feature in many BMW models. These projects helped legitimise what the company now calls ‘U-boat’ projects , recognising the value of the bootlegging approach.

Forbidden Fruit

Peter Augsdorfer made a classic study of the phenomenon, reported it in his wonderful book ‘Forbidden fruit’ in which he highlights many examples of such ‘bootlegging’ approaches. (The term originated during the 1920s when the US government banned the manufacture and sale of hard liquor; the measure didn’t have the desired effect of wiping out the industry and sobering up the country. Instead it triggered a wave of illegal but at times highly innovative ways around the problem, essentially driving innovation underground and out of sight . This included hiding illicit liquor down the inside of boots).

Augsdorfer argues that bootlegging can be seen as a form of learning under uncertainty, where employees experiment with new ideas and technologies without formal approval or support. In other words it’s an unofficial extension of the R&D/exploration work which companies need to do anyway.

Importantly it’s an approach which can have other positive benefits for organizations beyond the innovations which its employees create, such as enhancing motivation and employee retention and fostering a culture of internal entrepreneurship. But it has its ‘dark side’; there are negative outcomes including wasting time and resources, violating ethical norms and — a big challenge for those trying to ‘manage’ it — undermining organizational control and co-ordination frameworks.

Innovation Missionaries

Augsdorfer orginally wrote about this 25 years ago but a recent article in the Sloan Management Review reminds us that such underground innovation is alive and well. It’s not a case of ‘one size fits all’ and their article highlights a number of different approaches. It also usefully identifies three key archetypes of characters who may be innovators of this kind. They call them ‘missionaries’, ‘users’ and ‘explorers’.

Missionaries have a particular interest in the development of the company; their self-adopted ‘mission’ is to improve things. Characters like Richard Drew would fall into this category, seeing their own progress as being tied up with the fortunes of the company they work for and tapping into its resources to help them achieve their goals.

User innovators are essentially frustrated in what they are doing — they develop hacks and work arounds to solve problems particularly in the area of process innovation and their ideas can often be surfaced through suggestion schemes and other mechanisms.

And explorers are concerned with pushing the frontiers of what they do, sometimes going in directions which the company does not believe is possible. The risk here is that they pursue their ideas too far, detracting from their mainstream work and official company strategy.

Making Space for Innovation

So what makes underground innovation work? It’s not simply waving a magic wand, Harry Potter style, and casting the ‘Innovate!’ spell. Instead a number of things need to come together:

  • Allowing space — time, access to resources, etc. The exact amount — 15, 20 or even higher percentages of time — is irrelevant. It’s the signal that matters, communicating that it is OK to experiment around the edges and that there won’t be negative consequences for such action. What often happens is that this small amount of investment encourages employees to spend much more of their own time and initiative, often working long unpaid hours in pursuit of their ideas. At the limit (as Paula Criscuouolo and her colleagues point out) there are good examples of bootlegging arising from contexts in which there is no formal space or time allocation but an underlying perception that it is still OK to ‘dig around a little’.
  • Giving boundaries — defining the space within which innovation is possible and permission to explore there. For example we don’t necessarily want bootleg innovation in the formulation of pharmaceutical products but that leaves plenty of scope for other ideas, particularly in process innovation.
  • Establishing a development pathway to pick up on bootleg ideas. There’s no point stimulating lots of bootlegging behaviour if employees have nowhere to channel their ideas once they start to develop. In the case of 3M there’s a clear pathway which allows employees to take bright ideas and pitch for varying amounts of internal funding and other resources to grow and scale their innovations. Such functionality is increasingly built into innovation collaboration platforms and many companies — such as Liberty Global with their Spark programme — have established employee entrepreneurship pathways in parallel to their suggestion schemes.
  • Communicate trust as a core value — allowing bootleggers to feel a sense of psychological safety about what they are doing and that they will not be penalised for their activities.
  • Reward and recognise — it’s no coincidence that one of the things about 3M is that the people who have been involved in developing bootleg projects to fruition are then rewarded not just with resources and money but also with the opportunity to carry their venture forward. One of the two people involved in the development of Post it notes was Art Fry who moved on to run the division for 3M. The originator of the laptop computer within Toshiba similarly went on to run that division of their business.
  • Encourage intelligent failure — the down-side of allowing people to take initiative is that they will make mistakes. Importantly one of McKnight’s famous comments was that Management that is destructively critical when mistakes are made kills initiative. And it’s essential that we have many people with initiative if we are to continue to grow.’

Underground innovation has a lot to offer -but as the above suggests it isn’t a simple matter of mimicking Google or 3M, allocating a percentage of time and then waiting for the magic to happen. Successful organizations make employee involvement a key plank in building their innovation culture; something William Mcknight learned from his experience as Richard Drew’s manager. By 1929 he was running the entire 3M company and he pulled together some of the core principles through which their culture developed — including what he called his ‘Basic rule of management’. It’s deceptively simple and it serves well as a motto for anyone interested in tapping into underground innovation:

“delegate responsibility and encourage men and women to exercise their initiative.”

Image Credits: Pixabay

You can find a podcast version of this here and a video version here

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

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Good Design Makes Technology Disappear

Good Design Makes Technology Disappear

by Braden Kelley

The late Clayton Christensen wrote a little book called The Innovator’s Dilemma that many of you I’m sure have read. Many people think of it as a book about disruptive innovation, but it can be much more than that if you shift your perspective.

The Classic Disruptive Innovation Example

One of the case study examples is that of mini-mills disrupting the rolled steel producers in the steel industry by starting at the bottom of the food chain with the production of low margin re-bar and then moving upwards into higher margin steel products. This is seen as the blueprint for how you disrupt an industry. You go first where the incumbents are least likely to be concerned about new entrants – low margin products – a market that incumbents might actually be happy to lose, because their average margins will actually increase and wall street will potentially reward them in the short-term with higher stock prices.

But if you shift your perspective on this case study and apply it to emerging technology, something new emerges.

Learning and Adoption Require a Compelling Use Case BEFORE They Can Occur

I’ve been listening to a lot of podcasts while I work lately. Podcasts with leading scientists from around the world. One of the core themes that continuously emerges is that innovation is really hard and takes a long time. I was really struck by iRobot co-Founder Rodney Allen Brooks speaking about how they had a target of launching the Roomba at $200 and this meant that he had FIFTY CENTS per unit to spend on a piece of silicon to power their invention. He told the story of running around Taiwan looking for a chip that was cheap enough and was handicapped in ways that wouldn’t matter for their particular application – as ALL chips in that price range are going to have severe limitations. This is a great story for highlighting some of the unexpected challenges in turning an invention into an innovation.

Another interesting innovation case study – on the failure side – is that of Google Glass. The smart glasses arrived as an overhyped and underwhelming product and died on the vine in a very short period of time. One of the key reasons for their failure was the lack of a compelling use case, and another was that technology was too front and center – so much so that Google Glass seemed like a creepy invention.

“Making access to information just instant and intuitive. By doing that, technology fades into the background, and we’re more connected with the people and things around us.”

This quote is pulled directly from the video below about Google’s reboot of their smart glasses initiative:

Google’s Live Translation Glasses arrive this time without a product page, without a formal product name and promising much less.

One of the things that really struck me in this short video is that while it is super easy to anchor on the value of the translation piece – displaying Mandarin on screen from an English voice for example – they have several other powerful uses cases, including:

  • People who have single-sided deafness
  • People who don’t want to wear hearing aids, or for whom hearing aids don’t work
  • People who are fully deaf
  • People who are trying to learn a new language

Do One Thing Really Well and Build From There

Google’s Live Translation Glasses remind me of another pair of smart glasses launched a little while back in the glow of the Google Glass failure – Amazon’s Echo Frames.

Amazon’s Echo Frames build themselves around the compelling use case of hands-free searching and calling. They have speakers and a microphone, connect to your iOS or Android smartphone, and can even be fitted with prescription lenses.

Amazon Echo Frames

Don’t Strip the Gears on Your Innovation Machine

Our ability to imagine usually outpaces our ability to execute and it can be a challenge to rein in our imagination to match our ability to not just execute, but to do so profitably and at a pace that our customers can see their way to adopt it.

When we look at my Innovation is All About Value methodology, we can also see that companies fail less often at value creation, and more frequently at value access and value translation.

When your start small and build around a compelling use case it is easier to get the value translation right and it is easier to build the key value access components to support your value creation.

Timing matters…

Price matters…

Compelling use cases matter…

What’s yours?

Keeping the end in mind and the future in sight – is important – but it is more valuable to identify where to start and add value as you go.

Don’t strip the gears on your innovation machine and keep innovating!

Image credit: The Verge, Amazon

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Creating a Culture of Everyday Innovation

Creating a Culture of Everyday Innovation

GUEST POST from Chateau G Pato

In today’s rapidly evolving business landscape, organizations must prioritize innovation in order to stay competitive and thrive. However, many companies struggle to foster a culture of innovation that transcends the occasional brainstorming session or special project. True innovation must become a part of the fabric of daily operations, ingrained in the mindset of every employee from top to bottom.

So, how can organizations instill a culture of everyday innovation? By encouraging and empowering their employees to contribute ideas and improve processes continuously. Here are two case studies that exemplify this approach:

Case Study 1: Google

Google is renowned for its culture of innovation, which is evident in its diverse range of products and services. One key to Google’s success is its “20% time” policy, where employees are encouraged to spend 20% of their work hours pursuing their own passion projects. This policy has led to the creation of products like Gmail and Google Maps, which have revolutionized the way we communicate and navigate the world.

Google also holds regular hackathons, where employees come together to brainstorm and develop new ideas in a collaborative environment. These events not only foster creativity and innovation but also help break down silos between teams and departments, encouraging cross-pollination of ideas.

By empowering employees to take risks, experiment, and think outside the box, Google has created a culture of everyday innovation that drives the company’s success.

Case Study 2: 3M

3M is another organization that excels at fostering innovation in its day-to-day operations. One of 3M’s most famous innovations is the Post-it Note, which was the result of a serendipitous discovery by a scientist trying to develop a strong adhesive. This accidental invention led 3M to adopt a philosophy of “innovating by mistake,” encouraging employees to explore new ideas and opportunities without fear of failure.

3M also has a program called “Genesis Grants,” which provides funding for employees to pursue innovative projects that align with the company’s strategic goals. This initiative not only incentivizes employees to think creatively but also shows that the company values and supports their ideas.

By creating a supportive environment where employees are encouraged to experiment, take risks, and think outside the box, 3M has built a culture of everyday innovation that drives continuous improvement and propels the company forward.

Conclusion

Creating a culture of everyday innovation requires more than just lip service from leadership. Organizations must empower their employees to contribute ideas, experiment, and take risks in order to drive meaningful change and stay ahead of the competition. By following the examples set by companies like Google and 3M, organizations can cultivate a culture of innovation that fuels growth, creativity, and success.

SPECIAL BONUS: The very best change planners use a visual, collaborative approach to create their deliverables. A methodology and tools like those in Change Planning Toolkit™ can empower anyone to become great change planners themselves.

Image credit: misterinnovation.com

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