Tag Archives: Amazon

Can You Become the Earth’s Most Customer-Centric Company?

Can You Become the Earth's Most Customer-Centric Company?

GUEST POST from Shep Hyken

If I asked 10 people who they thought could be planet Earth’s most customer-centric company, I bet a majority would have the same answer. I’ll share that company’s name at the end of this article. For now, you can guess.

Cindy, from my office, had a customer service issue. Here are the steps she took to resolve the problem:

  1. She went to the company’s website and clicked on customer support.
  2. She answered a few questions, and once the technology identified her problem, a chatbot popped up.
  3. After interacting with the chatbot briefly, the bot wrote, “Let me transfer you to an agent,” moving from a chatbot to live chat.
  4. At some point, the agent suggested getting on the phone, and rather than have Cindy call, she asked for Cindy’s number. Once Cindy shared it, the phone rang almost instantly.
  5. From there, the agent carried out a conversation that eventually resolved Cindy’s problem.

I asked Cindy how she liked that experience, and she quickly answered, “Amazing!”

Just a few minutes later, Cindy received a short survey asking for her feedback with the message:

Your feedback is helping us build Earth’s Most Customer-Centric Company.

With that in mind, let’s look at some lessons we can learn from the company that aspires to be the most customer-centric company on the planet:

  1. Digital First – The company made it easy to start the customer support process with a digital self-service solution. While there was a live agent option, it wasn’t presented until later. Cindy had to answer a few questions and click a few boxes before moving on. And this part is important. The process was easy and intuitive. She was digitally “hand-held” through the process, which included the chatbot.
  2. The Human Backup – The chatbot was programmed to understand when it wasn’t getting Cindy’s answer, and it immediately transferred her to a live chat with a customer support agent. Eventually, the live online chat turned into a phone call when the agent wanted more details and knew it would be easier to talk than text. Rather than Cindy calling the company, she simply had to enter her phone number into the chat, and within seconds, the phone rang, and she was talking to the customer support agent.
  3. A Seamless Omni-Channel Experience – The definition of an omni-channel experience is a continuous conversation moving from one form of communication to the next. Cindy went from answering questions on the website to a chatbot, to live chat, and then to the phone. All was seamless, and the “conversation” continued rather than forcing Cindy to tell her story repeatedly. The agent on the phone picked up where the chat ended and quickly solved her problem. This is the way omni-channel is supposed to work.

This is a perfect example of the modern customer support experience. And did you guess what company this article is about? If you said Amazon, you’re absolutely right!

Image Credits: Shep Hyken, Pexels

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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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Stuff Your Stoking with Innovation for $4.24

Stuff Your Stoking with Innovation for $4.24

Wow! Exciting news!

While supplies last you can get the hardcover version of my best-selling book Stoking Your Innovation Bonfire for only $4.24 (88% off), including free delivery in the USA from Amazon!

Sorry, unfortunately Amazon doesn’t have a discount on the kindle version, which remains at $28.00, so this is quite the deal!

  • The offer is only valid while supplies list (or until Amazon changes the price) so act fast!

Quick reminder: Everyone can download lots of free tools from this web site, including:

  • 700+ quote posters
  • The Experiment Canvas™
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  • 10 Free Human-Centered Change Tools
  • Nine Innovation Roles card design

Follow this link to select multiple items and download them ALL AT ONCE!

And finally, I created the Human-Centered Change methodology to help organizations get everyone literally all on the same page for change. The 70+ visual, collaborative tools are introduced in my book Charting Change, including the powerful Change Planning Canvas™. The toolkit has been created to help organizations:

  • Beat the 70% failure rate for change programs
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Playing to Win the Customer Service Game

Playing to Win the Customer Service Game

GUEST POST from Shep Hyken

One of the more enjoyable activities in my life is playing hockey. When I’m in town – not out speaking at conferences – I lace up the skates several times a week to play in a friendly hockey game. In close games, when my team is up by one or two goals, I remember my school days when our coaches encouraged us to continue playing to score, even when we were winning, versus switching to more defensive play to prevent the other team from scoring.

So, what does this have to do with business, specifically customer service and CX? Plenty!

In any team sport, the goal is to win. In the customer service world, we should create a “game plan” to deliver an experience that is perfect, never requiring a customer to reach out to us because of problems. Consider what Jeff Bezos of Amazon said many years ago: “The best customer service is if the customer doesn’t need to call you, doesn’t need to talk to you. It just works.” That’s a perfect example of playing to win.

But that doesn’t always work. Bezos quickly discovered that as perfect as Amazon might be, once the package left the warehouse, control was in the hands of delivery companies such as the USPS, FedEx, or UPS. If there was a delivery problem, even if it wasn’t Amazon’s fault, the customer still called Amazon.

That’s where Amazon learned to play great defense, typically managing complaints or issues so well that the company has earned a reputation for amazing customer service. And they still play to win. They continue to open more distribution sites and grow their fleet of airplanes and vehicles to manage the entire experience, so they don’t have to rely on outside vendors as much. And as perfect as they try to be, there will still be problems, so a good defense, as in a good customer service experience, supports the effort to win.

While we can’t all be Amazon, we can play a similar game. We need defense, which is the ability to respond to our customers’ questions, problems, needs, and complaints in a way that renews confidence for them to continue doing business with us. However, we must also play to win, which means continuously improving the customer experience, including eliminating or mitigating any of those customer issues.

Shep Hyken Award Cartoon

In the customer service world, playing to win in customer service means eliminating the reasons customers call us for problems and complaints. Playing defense is focusing on being good at handling our customers’ problems or complaints. We need to be good at both.

Image Credits: Shep Hyken, Pexels

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Software Isn’t Going to Eat the World

Software Isn't Going to Eat the World

GUEST POST from Greg Satell

In 2011, technology pioneer Marc Andreessen declared that software is eating the world. “With lower start-up costs and a vastly expanded market for online services,” he wrote, “the result is a global economy that for the first time will be fully digitally wired — the dream of every cyber-visionary of the early 1990s, finally delivered, a full generation later.

Yet as Derek Thompson recently pointed out in The Atlantic, the euphoria of Andreessen and his Silicon Valley brethren seems to have been misplaced. Former unicorns like Uber, Lyft, and Peloton have seen their value crash, while WeWork saw its IPO self-destruct. Hardly “the dream of every cyber-visionary.”

The truth is that we still live in a world of atoms, not bits and most of the value is created by making things we live in, wear, eat and ride in. For all of the tech world’s astounding success, it still makes up only a small fraction of the overall economy. So, taking a software centric view, while it has served Silicon Valley well in the past, may be its Achilles heel in the future.

The Silicon Valley Myth

The Silicon Valley way of doing business got its start in 1968, when an investor named Arthur Rock backed executives from Fairchild Semiconductor to start a new company, which would become known as Intel. Unlike back east, where businesses depended on stodgy banks for finance, on the west coast venture capitalists, many of whom were former engineers themselves, would decide which technology companies got funded.

Over the years, a virtuous cycle ensued. Successful tech companies created fabulously wealthy entrepreneurs and executives, who would in turn invest in new ventures. Things shifted into hyperdrive when the company Andreessen founded, Netscape, quadrupled its value on its first day of trading, kicking off the dotcom boom.

While the dotcom bubble would crash in 2000, it wasn’t all based on pixie dust. As the economist W. Brian Arthur explained in Harvard Business Review, while traditional industrial companies were subject to diminishing returns, software companies with negligible marginal costs could achieve increasing returns powered by network effects.

Yet even as real value was being created and fabulous new technology businesses prospered, an underlying myth began to take hold. Rather than treating software business as a special case, many came to believe that the Silicon Valley model could be applied to any business. In other words, that software would eat the world.

The Productivity Paradox (Redux)

One reason that so many outside of Silicon Valley were skeptical of the technology boom for a long time was a longstanding productivity paradox. Although throughout the 1970s and 80s, business investment in computer technology was increasing by more than 20% per year, productivity growth had diminished during the same period.

In the late 90s, however, this trend reversed itself and productivity began to soar. It seemed that Andreessen and his fellow “cyber-visionaries were redeemed. No longer considered outcasts, they became the darlings of corporate America. It appeared that a new day was dawning and the Silicon Valley ethos took hold.

While the dotcom crash deflated the bubble in 2000, the Silicon Valley machine was soon rolling again. Web 2.0 unleashed the social web, smartphones initiated the mobile era and then IBM’s Watson’s defeat of human champions on the game show Jeopardy! heralded a new age of artificial intelligence.

Yet still, we find ourselves in a new productivity paradox. By 2005, productivity growth had disappeared once again and has remained diminished ever since. To paraphrase economist Robert Solow, we see software everywhere except in the productivity statistics.

The Platform Fallacy

Today, pundits are touting a new rosy scenario. They point out that Uber, the world’s largest taxi company, owns no vehicles. Airbnb, the largest accommodation provider, owns no real estate. Facebook, the most popular media owner, creates no content and so on. The implicit assumption is that it is better to build software that makes matches than to invest in assets.

Yet platform-based businesses have three inherent weaknesses that aren’t always immediately obvious. First, they lack barriers to entry, which makes it difficult to create a sustainable competitive advantage. Second, they tend to create “winner-take-all” markets so for every fabulous success like Facebook, you can have thousands of failures. Finally, rabid competition leads to high costs.

The most important thing to understand about platforms is that they give us access to ecosystems of talent, technology and information and it is in those ecosystems where the greatest potential for value creation lies. That’s why, to become profitable, platform businesses eventually need to invest in real assets.

Consider Amazon: Almost two thirds of Amazon’s profits come from its cloud computing unit, AWS, which provides computing infrastructure for other organizations. More recently, it bought Whole Foods and began opening Amazon Go retail stores. The more that you look, Amazon looks less like a platform and more like a traditional pipeline business.

Reimagining Innovation for a World of Atoms

The truth is that the digital revolution, for all of the excitement and nifty gadgets it has produced, has been somewhat of a disappointment. Since personal computers first became available in the 1970’s we’ve had less than ten years of elevated productivity growth. Compare that to the 50-year boom in productivity created in the wake of electricity and internal combustion and it’s clear that digital technology falls short.

In a sense though, the lack of impact shouldn’t be that surprising. Even at this late stage, information and communication technologies only make up for about 6% of GDP in advanced economies. Clearly, that’s not enough to swallow the world. As we have seen, it’s barely enough to make a dent.

Yet still, there is great potential in the other 94% of the economy and there may be brighter days ahead in using computing technology to drive advancement in the physical world. Exciting new fields, such as synthetic biology and materials science may very well revolutionize industries like manufacturing, healthcare, energy and agriculture.

So, we are now likely embarking on a new era of innovation that will be very different than the digital age. Rather than focused on one technology, concentrated in one geographical area and dominated by a handful of industry giants, it will be widely dispersed and made up of a diverse group of interlocking ecosystems of talent, technology and information.

Make no mistake. The future will not be digital. Instead, we will need to learn how to integrate a diverse set of technologies to reimagine atoms in the physical world.

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

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Top 10 Human-Centered Change & Innovation Articles of August 2022

Top 10 Human-Centered Change & Innovation Articles of August 2022Drum roll please…

At the beginning of each month we will profile the ten articles from the previous month that generated the most traffic to Human-Centered Change & Innovation. Did your favorite make the cut?

But enough delay, here are August’s ten most popular innovation posts:

  1. Why Amazon Wants to Sell You Robots — by Shep Hyken
  2. Now is the Time to Design Cost Out of Our Products — by Mike Shipulski
  3. How Consensus Kills Innovation — by Greg Satell
  4. The Four Secrets of Innovation Implementation — by Shilpi Kumar
  5. Reset and Reconnect in a Chaotic World — by Janet Sernack
  6. This 9-Box Grid Can Help Grow Your Best Future Talent — by Soren Kaplan
  7. ‘Fail Fast’ is BS. Do This Instead — by Robyn Bolton
  8. The Power of Stopping — by Mike Shipulski
  9. The Battle Against the Half-Life of Learning — by Douglas Ferguson
  10. The Phoenix Checklist – Strategies for Innovation and Regeneration — by Teresa Spangler

BONUS – Here are five more strong articles published in July that continue to resonate with people:

If you’re not familiar with Human-Centered Change & Innovation, we publish 4-7 new articles every week built around innovation and transformation insights from our roster of contributing authors and ad hoc submissions from community members. Get the articles right in your Facebook, Twitter or Linkedin feeds too!

Have something to contribute?

Human-Centered Change & Innovation is open to contributions from any and all innovation and transformation professionals out there (practitioners, professors, researchers, consultants, authors, etc.) who have valuable human-centered change and innovation insights to share with everyone for the greater good. If you’d like to contribute, please contact me.

P.S. Here are our Top 40 Innovation Bloggers lists from the last two years:

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Why Amazon Wants to Sell You Robots

Why Amazon Wants to Sell You Robots

GUEST POST from Shep Hyken

It was recently announced that Amazon.com would be acquiring iRobot, the maker of the Roomba vacuum cleaner. There are still some “hoops” to jump through, such as shareholder and regulatory approval, but the deal looks promising. So, why does Amazon want to get into the vacuum cleaner business?

It doesn’t!

At least not for the purpose of simply selling vacuum cleaners. What it wants to do is to get further entrenched into the daily lives of its customers, and Amazon has done an excellent job of just that. There are more than 200 million Amazon Prime members, and 157.4 million of them are in the United States. According to an article in USA Today, written by David Chang of the Motley Fool, Amazon Prime members spend an average of $1,400 per year. Non-Amazon Prime members spend about $600 per year.

Want more numbers? According to a 2022 Feedvisor survey of 2,000-plus U.S. consumers, 56% visit Amazon daily or at least a few times a week, which is up from 47% in 2019. But visiting isn’t enough. Forty-seven percent of consumers make a purchase on Amazon at least once a week. Eight percent make purchases almost every day.

Amazon has become a major part of our lives. And does a vacuum cleaner company do this? Not really, unless it’s iRobot’s vacuum cleaner. A little history about iRobot might shed light on why Amazon is interested in this acquisition.

iRobot was founded in 1990 by three members of MIT’s Artificial Intelligence Lab. Originally their robots were used for space exploration and military defense. About ten years later, they moved into the consumer world with the Roomba vacuum cleaners. In 2016 they spun off the defense business and turned their focus to consumer products.

The iRobot Roomba is a smart vacuum cleaner that does the cleaning while the customer is away. The robotic vacuum cleaner moves around the home, working around obstacles such as couches, chairs, tables, etc. Over time, the Roomba, which has a computer with memory fueled by AI (artificial intelligence) learns about your home. And that means Amazon has the capability of learning about your home.

This is not all that different from how Alexa, Amazon’s smart device, learns about customers’ wants and needs. Just as Alexa remembers birthdays, shopping habits, favorite toppings on pizza, when to take medicine, what time to wake up and much more, the “smart vacuum cleaner” learns about a customer’s home. This is a natural extension of the capabilities found in Alexa, thereby giving Amazon the ability to offer better and more relevant services to its customers.

To make this work, Amazon will gain access to customers’ homes. No doubt, some customers may be uncomfortable with Amazon having that type of information, but let’s look at this realistically. If you are (or have been) one of the hundreds of millions of Amazon customers, it already has plenty of information about you. And if privacy is an issue, there will assuredly be regulations for Amazon to comply with. They already understand their customers almost better than anyone. This is just a small addition to what they already know and provides greater capability to deliver a very personalized experience.

And that is exactly what Amazon plans to do. Just as it has incorporated Alexa, Ring and eero Wi-Fi routers, the Roomba will add to the suite of connected capabilities from Amazon that makes life easier and more convenient for its customers.

If you take a look at the way Amazon has moved from selling books to practically everything else in the retail world, and you recognize its strategy to become part of the fabric of its customers’ lives, you’ll understand why vacuum cleaners, specifically iRobot’s machines, make sense.

This article originally appeared on Forbes

Image Credit: Shep Hyken

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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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Digital Transformation Roadmap

An Actionable Guide to Planning and Executing Your Transformation Strategy

Digital Transformation Roadmap

GUEST POST from Chateau G Pato

In today’s rapidly evolving digital landscape, businesses are faced with the critical challenge of adapting to the demands of a digital economy. The key to successful digital transformation lies in developing a comprehensive roadmap that outlines a clear strategy for leveraging technology to drive business growth and innovation.

Creating a digital transformation roadmap requires a strategic approach that encompasses a thorough assessment of organizational goals, current capabilities, and technology infrastructure. By developing a roadmap that is both comprehensive and actionable, businesses can effectively navigate the complexities of digital transformation and achieve sustainable success in the digital age.

Case Study Example 1: Coca-Cola

One of the most iconic brands in the world, Coca-Cola has successfully embraced digital transformation to drive business growth and enhance customer engagement. By focusing on leveraging technology to create personalized experiences for customers, Coca-Cola has been able to stay ahead of the competition and maintain its leadership position in the market.

To support its digital transformation efforts, Coca-Cola developed a comprehensive roadmap that included investing in cutting-edge technologies, such as AI and machine learning, to better understand customer preferences and deliver targeted marketing campaigns. By leveraging data analytics and automation tools, Coca-Cola has been able to streamline its operations and improve efficiency, while also enhancing the overall customer experience.

Case Study Example 2: Amazon

As one of the world’s largest e-commerce companies, Amazon has set the standard for digital transformation in the retail industry. By continuously innovating and adapting to changing consumer preferences, Amazon has been able to stay at the forefront of digital innovation and drive significant growth in its business.

Amazon’s digital transformation roadmap is centered around leveraging technology to enhance the customer experience and drive operational efficiency. By investing in cloud computing, data analytics, and artificial intelligence, Amazon has been able to streamline its operations, optimize its supply chain, and deliver personalized recommendations to customers. As a result, Amazon has been able to create a seamless shopping experience that has helped to drive customer loyalty and increase sales.

Conclusion

Digital transformation is a complex and challenging process that requires careful planning and execution. By developing a comprehensive roadmap that outlines a clear strategy for leveraging technology to drive business growth and innovation, businesses can effectively navigate the complexities of digital transformation and achieve sustainable success in the digital age. By following the examples set by companies like Coca-Cola and Amazon, businesses can learn valuable insights on how to successfully plan and execute their digital transformation strategy.

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: Pexels

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Building an Effective Innovation Team

Key Roles and Responsibilities

Building an Effective Innovation Team

GUEST POST from Art Inteligencia

Innovation is the lifeblood of any organization striving to stay ahead in today’s dynamic and competitive business landscape. To foster a culture of creativity and cultivate groundbreaking ideas, building an effective innovation team is paramount. This article explores key roles and responsibilities within such teams and delves into two compelling case studies that exemplify the power of a well-structured innovation team.

Key Roles within an Innovation Team:

1. Innovation Leader:

The innovation leader acts as the driving force and visionary within the team. This role encompasses setting the team’s mission, goals, and strategies, while continuously inspiring and motivating members towards innovative thinking. Additionally, the innovation leader ensures alignment between the innovation team’s objectives and organizational goals.

2. Ideation Specialists:

Ideation specialists concentrate on generating and refining ideas. They possess a unique ability to break the shackles of conventional thinking and nurture a culture of ideation within the team. By encouraging brainstorming sessions and implementing various ideation frameworks, such as Design Thinking or Six Thinking Hats, they facilitate the generation of diverse and creative ideas.

3. Market Research Analysts:

Market research analysts play a pivotal role in ensuring that ideas generated by the team have a strong foundation in market insights and customer needs. By conducting comprehensive market research, analyzing trends, and identifying potential opportunities and risks, they empower the team to make data-driven decisions and prioritize projects with the highest market potential.

4. Technical Experts:

Technical experts bring specialized knowledge and skills to the innovation team. They provide essential technical expertise to assess feasibility, prototype ideas, and overcome technological obstacles. Their contributions enable the team to transform concepts into tangible innovative solutions.

Case Study 1: Pixar Animation Studios:

Pixar Animation Studios, renowned for its groundbreaking animation technology and storytelling, exemplifies the power of an effective innovation team. Their team structure ensures cross-functional collaboration and diversity of perspectives. While the innovation leader sets a clear vision and encourages creativity, ideation specialists foster an environment of open communication and brainstorming sessions. Technical experts work closely with creative teams, developing cutting-edge animation technology. The result is a history of powerful animated films that have revolutionized the industry.

Case Study 2: Amazon:

Amazon, a global leader in e-commerce and disruptive technology, demonstrates the significance of market research analysts within an innovation team. By creating dedicated teams focused on researching market trends, consumer preferences, evolving technologies, and potential risks, Amazon keeps a pulse on market dynamics. These market research analysts enable Amazon’s innovation teams to make informed decisions, identify emerging business opportunities, and create products and services that anticipate customer demands.

Conclusion

Building an effective innovation team necessitates carefully defining key roles and responsibilities. Braden Kelley’s Nine Innovation Roles is a great tool for looking at this particular subject matter, and he makes several resources available for free on this site. By having an innovation leader who inspires, ideation specialists who foster an environment of creativity, market research analysts who provide insights, and technical experts who bring ideas to life, organizations can achieve breakthrough innovation. Case studies such as Pixar Animation Studios and Amazon exemplify the immense value of a well-structured innovation team. Through the implementation of these key roles and responsibilities, enterprises can foster a culture of innovation, leading to sustained growth and success in today’s ever-evolving business landscape.

Bottom line: Futurology is not fortune telling. Futurists use a scientific approach to create their deliverables, but a methodology and tools like those in FutureHacking™ can empower anyone to engage in futurology themselves.

Image credit: Pexels

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