Tag Archives: Amazon

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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Prototyping the Future

Experimenting with Emerging Possibilities

Prototyping the Future

GUEST POST from Chateau G Pato

In the high-stakes game of organizational change, inertia is the silent killer. Leaders often talk about innovation, but they are terrified of the risk associated with committing millions to an unproven concept. This fear traps organizations in a cycle of incrementalism. As a human-centered change and innovation thought leader, I argue that the most powerful antidote to this paralysis is prototyping. Prototyping is not merely a step in a design process; it is a mindset — a strategic, disciplined commitment to experimenting with the future in the present. It is the art of making the unknown tangible, allowing us to fail safely, learn quickly, and dramatically increase our Return on Learning (ROL).

We must shift from an obsession with traditional ROI (Return on Investment), which punishes failure, to prioritizing ROL (Return on Learning), which rewards clarity and speed. Prototyping the future requires moving from a culture obsessed with detailed planning to one that values informed iteration. It means creating low-fidelity, high-impact simulations of emerging possibilities — be it a new product, a process, or an entirely new business model. This commitment to creating fast, disposable versions of the future dramatically lowers the psychological cost of failure, fostering the psychological safety necessary for true breakthrough innovation. Whether it’s a cardboard model, a basic wireframe, or an immersive Virtual Reality (VR) simulation, the goal is to maximize the learning extracted per dollar spent.

The Three Imperatives of Strategic Prototyping

To successfully prototype the future, organizations must focus on three core strategic imperatives that accelerate learning and reduce risk:

  • 1. De-Risking the Unknown with Speed: The primary function of a prototype is to identify and test the riskiest assumption in an emerging idea. It must be fast, cheap, and disposable. We aim to fail quickly and often at the conceptual stage, saving significant time and capital that would otherwise be wasted on building a perfect solution for the wrong problem.
  • 2. Generating Empathy Through Tangibility: Abstract ideas are difficult for stakeholders and customers to critique meaningfully. A prototype — whether physical or digital (e.g., an Augmented Reality model) —forces interaction. This human interaction generates deep empathy and reveals hidden needs, emotional reactions, and critical user friction points that no spreadsheet or survey can capture.
  • 3. Creating a Shared Vision: The future is difficult to discuss because everyone imagines it differently. A prototype serves as a Shared Artifact — a concrete, singular point of reference around which a team, and the entire organization, can align their vision, critique constructively, and unify their efforts. This speeds up decision-making and aligns cross-functional silos.

“Don’t fall in love with your first idea. Fall in love with the clarity your first prototype creates.” — Braden Kelley


Case Study 1: The IDEO Shopping Cart – Prototyping the Experience

The Challenge:

The design firm IDEO was challenged by a major grocery chain to redesign the common supermarket shopping cart. The initial, narrow focus was on engineering and durability, which would have resulted in only incremental changes.

The Prototyping Solution:

IDEO’s human-centered approach started not with engineering, but with experiential prototypes. The team quickly built several low-fidelity models using rudimentary materials (duct tape, bins, children’s seats) to test radically different concepts — like a cart with a built-in calculator or one with better maneuverability. They took these rough models into the grocery store for real-time testing, observing customer and employee interaction and failure points.

The Innovation Impact:

By prototyping the user experience rather than the final product, IDEO discovered critical, unarticulated needs—like improved maneuverability and safer child seating—that led to fundamental design shifts. The process proved that fast, visual, and highly interactive prototyping is the most efficient way to unlock breakthrough innovation by placing the human at the center of the learning loop.


Case Study 2: Amazon’s “Working Backwards” – Prototyping the Document

The Challenge:

Amazon, known for its high-velocity innovation, needed a mechanism to ensure that product teams were building things customers actually wanted and that ideas were vetted quickly without expensive software development.

The Prototyping Solution:

Amazon formalized a process called “Working Backwards,” which uses a document-based prototype. Before a single line of code is written, a team must write a Press Release (PR) announcing the finished product to the world. The PR is a one-page, customer-centric narrative explaining the product’s benefit, the problem it solves, and its release date. Accompanying the PR is a detailed FAQ and mock Customer Reviews.

The Innovation Impact:

This simple, text-based prototype forces immediate clarity and user focus. Writing the press release first ensures the team can articulate the customer value proposition before spending any engineering time. If the PR isn’t compelling, the idea is instantly shelved or iterated upon. This low-fidelity, high-discipline prototyping method de-risks multi-million-dollar projects by ensuring the idea is sound and clearly focused on the human need before the execution even begins. It is the ultimate example of prototyping the communication and the value proposition.


Conclusion: Leading with Iteration and ROL

Prototyping the future is the most responsible way to lead change. It replaces the paralyzing certainty of the five-year plan with the agile confidence of constant, low-cost learning. Leaders must create the cultural conditions for this to thrive: namely, by celebrating fast learning and treating failed prototypes as valuable data points, thereby building an organization defined by high Psychological Safety and high ROL.

The innovation landscape moves too fast for slow, secretive, and large-scale commitments. By adopting the three imperatives—speed, empathy generation, and shared vision creation—through prototyping, you ensure that your organization remains perpetually adaptive.

“Stop trying to predict the future. Start building disposable versions of it.” — Braden Kelley

That is the definitive strategy for unlocking continuous, human-centered innovation.

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

Image credit: 1 of 950+ FREE quote slides available at http://misterinnovation.com

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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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Leveraging Data to Drive Innovation Success

Leveraging Data to Drive Innovation Success

GUEST POST from Art Inteligencia

In today’s hyper-competitive business landscape, the ability to innovate is no longer just a strategic advantage; it’s an imperative for survival. However, innovation is often seen as a mysterious, complex process that is difficult to manage or measure. Enter data-driven innovation—a methodology that combines the vast potential of data analytics with the creative processes of innovation to not only generate groundbreaking ideas but also validate and scale them effectively.

This article explores how organizations can leverage data to foster a culture of innovation, reduce risk, and ultimately achieve greater success. We’ll also dive into case studies of companies that have successfully utilized data-driven strategies to revolutionize their business models.

The Role of Data in Innovation

Data serves as the backbone of informed decision-making, offering insights that can guide businesses through the uncertainties of the innovation process. From identifying unmet customer needs to predicting future trends, data provides the actionable intelligence required for both incremental and disruptive innovation. By leveraging big data, businesses can:

  • Understand customer behavior and preferences more deeply.
  • Identify new market opportunities and emerging trends.
  • Enhance product development processes through insights.
  • Track and measure the impact of innovation initiatives.

Let’s explore two case studies of companies that have successfully harnessed data to drive innovation.

Case Study 1: Netflix’s Predictive Analytics in Content Creation

Netflix is a pioneering example of how data can be leveraged to innovate in the realm of content creation. The streaming giant utilizes data analytics not only to understand viewer preferences but also to predict future content success. Utilizing a plethora of data points such as viewing history, search queries, and ratings, Netflix makes informed decisions about which shows to produce or license.

One of the most notable examples of this strategic approach is the creation of the critically acclaimed series “House of Cards.” Netflix analyzed user data to determine that a political drama starring Kevin Spacey and directed by David Fincher would likely succeed. This data-driven gamble resulted in a highly popular show that garnered millions of views and set new standards for original programming.

Case Study 2: Amazon’s Use of Machine Learning for Customer Experience

Amazon is another prime example of leveraging data to foster innovation, particularly in customer experience. The e-commerce giant employs data-driven strategies to personalize the shopping experience, optimize pricing, and streamline operations.

Amazon’s recommendation engine, powered by robust machine learning algorithms, analyzes user behavior and purchase history to suggest products that customers are likely to buy. This not only enhances the customer experience but also boosts sales and customer loyalty. Furthermore, Amazon uses data from customer feedback and return patterns to innovate in product delivery and supply chain management, ensuring faster and more efficient service.

Conclusion

The integration of data into the innovation process has transformed how organizations develop and implement new ideas. By leveraging data strategically, businesses can reduce the risks associated with innovation, tailor their offerings to meet customer needs more effectively, and capitalize on new market opportunities. As technology progresses, those who embrace data-driven innovation will continue to thrive, pushing the boundaries of what is possible and setting new benchmarks for success.

Extra Extra: 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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Balancing Short-Term Wins and Long-Term Innovation Goals

Balancing Short-Term Wins and Long-Term Innovation Goals

GUEST POST from Art Inteligencia

Certainly, I would be happy to craft an article under the guise of Braden Kelley. Here is a sample of what that article could look like:

In the dynamic landscape of business, organizations are often torn between the pressure to deliver short-term results and the necessity to invest in long-term innovation. While short-term wins are essential for maintaining momentum and stakeholder confidence, long-term goals focus on sustainable growth and staying competitive. Achieving the right balance is crucial for sustained success. Let’s explore how two companies managed this delicate balancing act, and what lessons we can learn from their experiences.

Case Study 1: Amazon’s Dual Approach

Amazon is a classic example of a company that expertly balances the pursuit of short-term successes while steadily advancing its long-term innovation strategy. Early on, Amazon focused sharply on capturing market share and increasing customer satisfaction. These short-term wins were evident in its relentless focus on customer service and improvements in logistics.

However, Amazon did not lose sight of its long-term goals. By investing heavily in technology such as cloud computing and AI, it paved the way for strategic innovations like Amazon Web Services (AWS) and Alexa. These long-term investments have significantly contributed to Amazon’s future-ready business model and its diversification beyond retail.

This dual approach teaches us the importance of not allowing immediate results to overshadow the necessity for visionary investments. Leaders must ensure their teams are aligned with the company’s innovation strategy while addressing the challenges of today.

Case Study 2: Nokia’s Transformation Challenge

Nokia’s story serves as a cautionary tale of how the emphasis on short-term wins can sometimes impede long-term innovation goals. In its heyday, Nokia was a leader in mobile phones, focusing heavily on capitalizing on its strong market position with incremental innovations that brought short-term profits.

However, as the mobile market rapidly evolved, Nokia struggled to adapt to the smartphone revolution initiated by competitors like Apple and Google. The company’s inability to prioritize long-term innovation left it vulnerable, ultimately losing significant market share.

Nokia’s experience underscores the importance of maintaining a forward-thinking approach, not just defending current market positions but also actively exploring new technologies and trends. For more insights on how organizations can navigate such transformations successfully, check out our article on Navigating the Challenges of Leading Innovation.

Key Takeaways

  • Align Short-Term Wins with Long-Term Objectives: Organizations need a clear strategy that links tactical successes with overarching innovation goals. Short-term wins should act as stepping stones towards long-term vision.
  • Invest in Future Readiness: To remain competitive, firms must invest in technologies and trends that secure long-term growth. This may involve reallocating resources from short-term-focused projects.
  • Balance and Measure: Utilize metrics that evaluate both short-term performance and progress towards long-term goals. This balanced scorecard approach can help ensure no critical area is neglected.

The path to balancing short-term and long-term objectives is fraught with choices that can heavily influence a company’s trajectory. For more strategies on driving innovation, explore our piece on Creating a Culture of Innovation.

This article provides a balanced view on how two companies have managed short-term wins and long-term goals. It includes links to further readings on relevant topics, offering a comprehensive exploration of the subject. If you need any modifications or additional details, feel free to let me know!

Extra Extra: 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: Pixabay

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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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Balancing Short-Term Wins and Long-Term Innovation Goals

Balancing Short-Term Wins and Long-Term Innovation Goals

GUEST POST from Chateau G Pato

In today’s rapidly evolving business landscape, organizations face the dual challenge of achieving short-term wins while steadily progressing towards long-term innovation goals. The ability to balance these two objectives is crucial for sustainable success. In this article, we will explore strategies for maintaining this balance and examine two compelling case studies that highlight the importance of aligning short-term and long-term efforts.

Strategies for Balancing Short-Term and Long-Term Goals

To successfully balance short-term wins with long-term innovation goals, organizations should consider the following strategies:

  • Set Clear Objectives: Outline specific, measurable objectives that align with both short-term and long-term goals.
  • Foster an Innovative Culture: Cultivate a culture that encourages experimentation, learning, and the sharing of ideas.
  • Ensure Agility: Implement agile methodologies to quickly adapt to changes and seize opportunities.
  • Allocate Resources Wisely: Allocate resources, including time, budget, and talent, strategically to support both immediate and future initiatives.
  • Monitor and Adjust: Continuously monitor progress and be prepared to adjust plans as necessary to maintain alignment with overall goals.

Case Study 1: Adobe – Embracing Continuous Innovation

Background

Adobe, a multinational software company known for its creative tools such as Photoshop and Illustrator, faced a critical decision in the early 2010s. The company needed to transition from traditional software licensing to a cloud-based subscription model to ensure long-term growth and innovation.

Short-Term Wins

To gain buy-in and demonstrate immediate value, Adobe introduced Adobe Creative Cloud, allowing users to subscribe to their software on a monthly basis. This move provided immediate financial gains by creating a steady, recurring revenue stream, and giving customers more flexibility.

Long-Term Innovation

While the transition to a subscription model was a significant short-term win, Adobe also invested heavily in long-term innovation. They focused on integrating AI and machine learning across their platforms, as well as expanding their ecosystem with new tools and services. The shift to Creative Cloud allowed Adobe to continuously update their software, ensuring that customers had access to the latest innovations without the need for new purchases.

Impact

The balance of short-term wins with a focus on long-term goals enabled Adobe to thrive in a rapidly changing market. Today, Adobe Creative Cloud is a cornerstone of the company’s success, providing substantial value to customers while ensuring sustained innovation.

Case Study 2: Amazon – Innovating for the Future

Background

Amazon, the global e-commerce and technology giant, has consistently balanced short-term operational efficiency with long-term innovation. One notable example of this balance is their approach to Amazon Web Services (AWS).

Short-Term Wins

Initially, Amazon focused on optimizing its retail operations to achieve short-term wins. They streamlined logistics, optimized the supply chain, and enhanced customer experience. These efforts generated immediate gains and established Amazon as a leader in the retail space.

Long-Term Innovation

Simultaneously, Amazon recognized the potential of cloud computing and invested heavily in the development of AWS. This long-term vision required substantial investment but promised a revolutionary shift in how businesses manage their IT infrastructure. AWS allowed Amazon to introduce new services and products, such as data analytics and machine learning, which have had a transformative impact across industries.

Impact

The strategy of balancing short-term improvements with visionary, long-term projects has paid off profoundly for Amazon. AWS is now a significant revenue generator and a critical driver of the company’s future growth and innovation. Amazon’s ability to balance the two has made it one of the most valuable and innovative companies in the world.

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: Pixabay

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