Four Steps to the Future

Announcing the Newest FREE Addition to the FutureHacking™ Toolkit

Four Steps to the Future

LAST UPDATED: April 12, 2026 at 5:07 PM

by Braden Kelley and Art Inteligencia


The Signal vs. Noise Dilemma

In an era defined by rapid technological shifts and global volatility, the modern professional is often drowning in “trends” but starving for actionable intelligence. The challenge is no longer a lack of information, but the overwhelming volume of it.

The FutureHacking™ Philosophy posits that finding signals isn’t enough — you must be able to connect them to your specific industry, country, and competitive landscape to create value. A signal in isolation is just data; a signal in context is a roadmap.

To bridge this gap, we are thrilled to introduce the FutureHacking Signal Picker. Built specifically for the global Innovation, Futurology, and Experience Design community, this tool moves beyond passive observation. It empowers you to filter out the noise and focus on the high-leverage insights that allow you to move from simply watching the future to actively influencing it.

The Power of Finding, Connecting, and Influencing

Strategic foresight is not a spectator sport. To gain a competitive advantage, organizations must master the triad of Finding, Connecting, and Influencing. The FutureHacking Signal Picker is engineered to facilitate this shift from discovery to impact.

Precision Finding

The first hurdle is moving beyond the “obvious” trends that everyone else is already tracking. By utilizing inputs for specific industries and — crucially — adjacent industries, the Signal Picker uncovers the cross-pollination points where true disruption often begins. It helps you look where your competitors aren’t looking.

Connecting through Multiplied Impact

A signal only matters if it carries weight. Our tool utilizes a proprietary formula to rank signals based on a multiplied impact, uncertainty, and timing factor. This quantitative approach allows you to see the “connective tissue” between a signal’s potential power and its proximity to your current business model, visualized instantly through a dynamic radar chart.

Influencing the Outcome

The ultimate goal of FutureHacking is to shift the organizational mindset from asking “What will happen to us?” to “What can we make happen?” By identifying high-impact signals early, you gain the lead time necessary to shape the market, influence consumer expectations, and design experiences that define the next era of your industry.

The Four Simple But Powerful FutureHacking™ Steps

The FutureHacking Signal Picker is more than a standalone tool; it is the catalyst for a comprehensive strategic journey. By automating the initial discovery phase, it accelerates your ability to move through the proven FutureHacking™ methodology.

STEP ONE: Picking the Signals That Matter

This is where the Signal Picker does the heavy lifting. By inputting your industry, country, competitors, and adjacent sectors, you generate a prioritized list of the top ten signals. The Radar Chart visualization provides an immediate snapshot of the landscape, while the downloadable PDF ensures that these insights are ready to be shared with leadership to drive immediate alignment.

STEP TWO: Mapping Signal Evolution

Once you have identified your primary signals, the next phase is tracking their trajectory. Using FutureHacking tools, you can map how these signals are evolving — whether they are converging with other trends, gaining velocity, or shifting in uncertainty. This step prevents you from being blindsided by the speed of change.

FutureHacking Infographic

STEP THREE: Choosing the Possible, Probable, and Preferable Future

With the signals ranked by impact and timing, you can begin to construct scenarios. We move beyond simple forecasting to ask: What is possible? What is probable? And most importantly, what is our Preferable Future? The tool’s data points provide the objective foundation needed to define where your organization wants to go.

STEP FOUR: Making Your Preferable Future a Reality

The final step is the bridge to action. By analyzing the strategic implications provided by the Signal Picker, you can design the specific innovations and human-centered changes required to manifest your chosen future. It turns foresight into a tangible roadmap for Experience Design and organizational transformation.

Strategic Implications & Competitive Edge

The true value of the FutureHacking Signal Picker lies not just in the data it unearths, but in the strategic clarity it provides. By shifting from a generic “trend watching” approach to a focused signal analysis, organizations can develop a more resilient and proactive posture.

Finding Opportunity in the Adjacencies

Most organizations suffer from industry myopia — they only look at what their direct competitors are doing. The Signal Picker’s inclusion of adjacent industries acts as a secret weapon. It forces a wider lens, identifying how shifts in unrelated sectors — such as a breakthrough in biopharmaceuticals affecting the insurance market — might create a “ripple effect” that becomes your next big opportunity or threat.

Quantifying the Horizon

Strategy often fails when it is based on gut feeling alone. By ranking signals through a multiplied factor of impact, uncertainty, and timing, the tool provides a quantitative justification for innovation investment. It allows teams to visualize their “blind spots” on the radar chart, ensuring that resource allocation is balanced between defending the core and exploring the frontier.

Fostering a Future-Ready Culture

Launching this tool within your organization or community changes the conversation. It transforms strategic planning from a static, annual event into a continuous pulse. When teams can quickly download a PDF of ranked signals and implications, it democratizes foresight, allowing Human-Centered Innovation and Experience Design professionals to lead with data-backed authority and use the report as a jumping off point to input into the deep research tools that AI companies are now offering.

Conclusion & Call to Action

The future isn’t a destination that we passively reach; it is a landscape that we actively co-create. The launch of the FutureHacking Signal Picker marks a significant milestone for the global community of innovators, futurists, and designers, providing the essential “first spark” for the Human-Centered Innovation™ journey.

Join the Global FutureHacking Community

We invite you to step beyond the noise of generic trends and start tracking the signals that will actually define your industry’s next decade. Whether you are navigating digital transformation, crafting next-generation experiences, or leading organizational agility, the right signals are the foundation of your success.

Ready to Hack the Future?

Put the FutureHacking Signal Picker to work today. Input your industry parameters, download your custom Radar Chart, and take the first of the Four Simple But Powerful FutureHacking™ Steps toward making your preferable future a reality.

Access the Signal Picker Tool Now
… and then contact us when you’re ready for the full toolkit and training.

FutureHacking Signals Picker

Remember: The most effective way to predict the future is to design the signals that influence it. Let’s start hacking.

Frequently Asked Questions

How does the Signal Picker rank the top ten signals?

The tool uses a proprietary “Multiplied Impact Factor.” Instead of looking at trends in isolation, it calculates the product of three critical dimensions: Impact (the scale of potential disruption), Uncertainty (the degree of volatility), and Timing (how soon the signal will manifest). This ensures that the signals at the top of your list are both highly relevant and urgent.

Why does the tool ask for “Adjacent Industries”?

Innovation rarely happens in a vacuum; it often “leaks” from one sector to another. By analyzing adjacent industries, the Signal Picker identifies cross-industry signals that your direct competitors are likely overlooking. This provides a broader perspective necessary for the Step Two: Mapping Signal Evolution phase of the FutureHacking™ methodology.

What is the benefit of the downloadable Radar Chart?

The Radar Chart provides an immediate visual map of your strategic horizon. It allows stakeholders to see the balance between short-term certainties and long-term disruptions at a glance. By downloading the PDF, Human-Centered Innovation and Experience Design professionals can instantly present data-backed visualizations to leadership to gain buy-in for future-proofing initiatives.


Image credits: Google Gemini

Content Authenticity Statement: The topic area, key elements to focus on, etc. were decisions made by Braden Kelley, with a little help from Google Gemini to clean up the article, add images and create infographics.

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Artificial Intelligence Powered Teamwork

Artificial Intelligence Powered Teamwork

GUEST POST from David Burkus

Over the past year, leaders have been asking the same questions trying to leverage AI-Powered teamwork: “What should I be doing with ChatGPT?” “How should we be rolling this out to our team?” “What does this mean for the future of work?”

They’re important questions, but they all kind of miss the mark. Because they treat AI like it’s just another IT rollout. Like that time your company moved from email to Slack. Or when everyone was forced to learn a new payroll system. But AI isn’t just another piece of software.

AI isn’t a tool. AI is a teammate.

And until we start treating it that way, we’re going to keep missing the real opportunity.

Why “Tool Thinking” Falls Short

Most people respond to AI in one of three ways. They see it as a threat. They see it as a tool. Or they see it as a teammate.

If you see AI as a threat, you’re going to hesitate. And hesitation is the enemy of progress. You’ll wait. You’ll hold back. But AI isn’t slowing down. And the people who do embrace it — whether they’re colleagues in your department or competitors across the industry — are only going to get better, faster, and more efficient. That puts your performance at risk by comparison. Compared to those using AI, you will performer slower.

If you see AI as a tool, you’re on slightly better footing. You’ll look for ways to automate the repetitive stuff. Email summaries. Meeting notes. Draft responses. All helpful. All productive. But you’re still missing the big value. You’re simplifying, not improving. You’re staying in neutral.

But if you treat AI as a teammate, that’s where transformation starts.

That’s when AI becomes a collaborator. A partner in decision-making. A quiet force that helps your team think more clearly, solve problems faster, and deliver better outcomes.

That’s when you start to unlock the full potential of AI-powered teamwork. That’s when it truly makes you smarter.

Step One: From Slower to Simpler

The first mindset shift is from threat to tool. From slower to simpler. Think about the annoying parts of your job. The copy-paste chores. The tedious admin. The stuff you’re way too smart to be wasting time on. AI can take that off your plate today.

Summarize the endless email chain. Done. Draft that status report. Done. Transcribe your meeting and highlight key action items. Double done.

Not sure where to start? Try this: open whatever AI platform you prefer — ChatGPT, Claude, Gemini, Grok, doesn’t matter — and type:

“Here’s what I do in my job every day. Ask me questions to understand it better, then show me how you could help.”

It will ask follow-ups. It will start mapping your workflows. It will suggest ways to make your day easier, your output faster, and your mind a little clearer.

Congratulations! You’ve moved from slower to simpler.

Step Two: From Simpler to Smarter

Once you’re using AI to simplify tasks, it’s time to use it to sharpen your thinking. Because smarter teams don’t just offload work. They upgrade their decision-making. They collaborate with AI, not just delegate to it.

How? Try turning AI into a devil’s advocate. Feed it your current strategy or plan, then ask:

“Tell me why this could fail.”

You’re not asking it to make decisions. You’re using it to challenge assumptions. To highlight blind spots. To play the role of critic — without the ego. AI provides friction without awkwardness. No one gets defensive when a bot questions your logic.

Want to go deeper? Try these prompts:

  • “What are we overlooking?”
  • “What assumptions might not be true?”
  • “Give me three stronger alternatives to this approach.”

Want to make the feedback even more useful? Ask the AI to role-play:

  • “Think like a strategic consultant.”
  • “Respond like a customer.”
  • “What would a competitor say?”

This is how AI-powered teamwork gets smarter, not just simpler. You’re not just getting a second opinion. You’re getting sharper thinking, without the politics.

Step Three: Make It a Team Habit

And here’s where the real breakthrough happens: when AI becomes a shared part of your team’s workflow — not just your personal productivity hack.

Use it in meetings to take notes. To draft action items. To highlight decisions made.

But also, use it before meetings. Drop your agenda into the chatbot and ask what you’re missing. Run your strategy plan through it and ask for feedback before your next off-site.

This only works if the whole team adopts it. And that’s where leaders come in.

Leaders need to be intentional. Because while AI can streamline collaboration, it can also introduce risks. If team members outsource their attention to a bot, they may stop listening. If everything’s recorded, people may speak up less. The quiet voices might go even quieter.

That’s why leadership still matters. Psychological safety? Still your job. Empathy? Still your job. Motivation and morale? Still your job.

AI can’t do that for you. But what it can do is give you more time to focus on it. Because when the bots handle the mechanics, you can focus on the human side of leadership — the part that never gets automated.

The Future of AI-Powered Teamwork

So, where’s your team right now? Are you stuck in “slower,” resisting change? Are you in “simpler,” just automating inbox chores? Or are you starting to work “smarter,” using AI to enhance how your team thinks and collaborates?

Wherever you are, there’s room to grow. Don’t just ask what AI can do. Ask how your team can do better work with it. Try a prompt. Test an idea. Challenge a plan. Start treating AI like a teammate, not a tool. Because the future of AI-powered teamwork isn’t about tech. It’s about trust. It’s about how you use new capabilities to build better teams, make better decisions, and do work that actually matters.

And that’s something worth getting smarter about.

Image credit: Google Gemini

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The Augmented Mind

Beyond Recall: The Strategic Evolution of Human Digital Memory

LAST UPDATED: April 10, 2026 at 3:39 PM

The Augmented Mind

GUEST POST from Art Inteligencia


The Dawn of the Extended Mind

For decades, we have treated our digital devices as external filing cabinets — places where we “put” information to be retrieved later. However, as the volume of data we consume shifts from a manageable stream to an overwhelming deluge, the traditional boundaries of the human mind are being tested. We are now entering a profound transition from Information Management to Cognitive Partnership.

The “Cognitive Crisis” is no longer a future threat; it is our current reality. Traditional search functions and folder-based storage hierarchies are failing the modern knowledge worker because they rely on perfect recall of where a file was placed or exact matching of keywords. When our biological hardware reaches its limit, our productivity and creativity suffer.

Digital Memory Augmentation represents a fundamental shift. It moves us beyond simple backups and toward active, AI-driven cognitive extensions. This isn’t about replacing human thought with an algorithm; it is a human-centered design opportunity to create a digital scaffold for our intellect. By augmenting our memory, we free the brain from the mundane task of storage, allowing it to return to its highest and best use: imagination, synthesis, and meaningful connection.

The Three Pillars of Augmented Memory

To move beyond simple storage and into true augmentation, we must look at how digital systems interface with our lived experience. This evolution is built upon three foundational pillars that transform raw data into a functional extension of our intellect.

1. Seamless Capture

The greatest friction in traditional memory management is the act of “saving.” When we have to pause our flow to take a note, bookmark a page, or file a document, we break our cognitive momentum. Seamless Capture shifts the burden from the user to the environment. Through “digital exhaust” — the ambient collection of our meetings, readings, and interactions — augmentation systems ensure that the “sparks” of insight are never lost simply because we were too busy to write them down.

2. Contextual Resonance

A memory is useless if it exists in a vacuum. Traditional systems rely on folders or tags, which require us to remember how we categorized information in the past. Contextual Resonance uses semantic analysis to understand the “why” and “how” behind a piece of information. By linking a data point to a specific project, a person, or even an emotional state, the system mimics the associative nature of the human brain, making retrieval feel like a natural thought rather than a database query.

3. Proactive Synthesis

The ultimate goal of augmentation is to move from reactive searching to proactive assistance. Proactive Synthesis is the stage where the system acts as a true partner. Instead of waiting for a prompt, the “Second Brain” identifies patterns across years of data and surfaces relevant insights at the moment they are most useful. It creates “digital serendipity,” connecting a conversation you had this morning with a research paper you read three years ago, fueling innovation through automated cross-pollination.

Reimagining the Innovation Lifecycle

Innovation is rarely the result of a single “Eureka!” moment; it is a cumulative process of gathering sparks, connecting dots, and refining concepts over time. By integrating digital memory augmentation, we transform the innovation lifecycle from a fragile, hit-or-miss endeavor into a robust, high-velocity engine for growth.

1. The End of “Lost Ideas”

How many breakthrough concepts have been lost to the ether simply because they occurred in the shower, during a commute, or in the middle of a casual conversation? Memory augmentation ensures that the “sparks” — the messy, early-stage thoughts and sketches — are captured in real-time. By removing the friction of documentation, we preserve the raw materials of innovation before they can be overwritten by the next urgent task.

2. Cross-Pollination at Scale

The most powerful innovations often come from combining ideas from two completely unrelated fields. However, our biological memory is prone to “siloing” information by department or project. A digital memory layer can scan across decades of organizational history and disparate personal interests to find hidden links. It allows an engineer to see how a solution from a 2015 project might solve a 2026 problem, facilitating a level of cross-pollination that was previously impossible for a single human mind to manage.

3. Accelerating Mastery

In a world of hyper-specialization, the “time-to-expertise” is a major bottleneck for innovation. Memory augmentation acts as a cognitive scaffold, allowing individuals to rapidly navigate complex institutional knowledge and technical documentation. By having a “Second Brain” that remembers the technical nuances and past failures of a specific domain, innovators can stand on the shoulders of their own past experiences (and those of their predecessors) much faster, shifting their energy from learning the foundation to building the future.

Designing for Trust and Human Agency

As we integrate digital memory more deeply into our lives, the design challenge shifts from technical feasibility to ethical responsibility. If we are to treat a digital system as an extension of our own mind, that system must be designed with an uncompromising focus on the user’s autonomy, privacy, and long-term cognitive health.

1. The Privacy Imperative

For digital memory augmentation to be successful, the “Second Brain” must be a private sanctuary. Users will only record their raw thoughts, private conversations, and vulnerable moments if they have absolute certainty that their data is not being used for advertising or surveillance. Designing for trust means prioritizing on-device processing and end-to-end encryption — ensuring that the user remains the sole owner and curator of their digital history.

2. Combatting Cognitive Atrophy

A significant concern with augmentation is the risk of “cognitive laziness.” Just as GPS has weakened our innate sense of navigation, there is a risk that total recall tools could weaken our ability to focus or synthesize information independently. Human-centered design must focus on augmentation, not replacement. The goal is to build tools that act as a “cognitive bicycle” — strengthening our ability to connect ideas and think critically by offloading the low-value task of rote memorization.

3. The Ethics of Perfection

Human memory is naturally fallible; we forget, we forgive, and we move on. A world where every mistake, every awkward comment, and every outdated opinion is preserved with photographic clarity presents a psychological challenge. We must design systems that allow for the “right to be forgotten” and the ability to prune our digital archives. True augmentation should support the human capacity for growth and evolution, rather than chaining us to a static version of our past selves.

The Ecosystem: Titans and Trailblazers

The landscape of memory augmentation is currently a race between established tech giants integrating AI into our daily operating systems and agile startups building dedicated hardware for total recall. By 2026, the market has moved beyond experimental prototypes to functional, cross-platform tools that are reshaping how we interact with our own history.

1. Established Platforms

  • Apple (Apple Intelligence): Apple has positioned itself as the “Privacy-First” memory partner. By leveraging on-device processing and Private Cloud Compute, iOS 26 and macOS Sequoia allow users to search for specific moments across photos, emails, and notes using natural language — creating “Memory Movies” and surfacing context-aware suggestions without ever exposing raw data to the cloud.
  • Microsoft (Windows Recall & Copilot): Despite early privacy hurdles, Microsoft has refined “Recall” into a sophisticated enterprise tool. It creates a searchable photographic timeline of everything you’ve seen and done on your PC, allowing professionals to instantly jump back to a specific slide, website, or conversation from weeks prior.
  • Meta (Ray-Ban Meta & AI): Meta is utilizing hardware to move memory augmentation into the physical world. Their smart glasses act as ambient “eyes and ears,” allowing users to ask, “Hey Meta, what was the name of that restaurant I walked past yesterday?” or “What did my colleague say about the project deadline?”

2. Disruptive Startups

  • Limitless (The Pendant): Limitless has become the go-to for “Total Recall” hardware. Their wearable AI pendant records and transcribes in-person meetings and impromptu conversations, utilizing “Automatic Speaker Recognition” to create smart summaries and reminders that sync across all productivity suites.
  • Mem.ai: Moving beyond traditional note-taking, Mem 2.0 has evolved into an “AI Thought Partner.” It eliminates the need for folders by using a self-organizing knowledge graph that automatically links new thoughts to past research, surfacing relevant context as you type.
  • Heirloom (Heirloom.cloud): Focused on the bridge between analog and digital, Heirloom uses AI to digitize, contextualize, and narrate family histories and personal archives, ensuring that legacy memories remain searchable and meaningful for future generations.
  • The Neural Frontier (Neuralink & Synchron): While still largely focused on clinical applications for motor and speech restoration, the successful 2025-2026 human trials for Brain-Computer Interfaces (BCIs) have laid the groundwork for future direct-to-brain memory retrieval and cognitive offloading.

Case Studies: Augmentation in the Real World

To move from the theoretical to the practical, we must look at how digital memory augmentation is already solving deep-seated organizational and individual challenges. These two case studies illustrate how extending our cognitive capacity directly translates into business value and human safety.

Case Study 1: Resolving the “Institutional Memory” Gap in Professional Services

The Challenge: A global management consulting firm was suffering from “reinventing the wheel.” With over 10,000 consultants globally, teams were frequently spending hundreds of hours on research and analysis that had already been performed by colleagues in different regions or years prior. Internal surveys showed that senior partners were spending 25% of their time simply trying to remember who had the specific “tribal knowledge” needed for a new pitch.

The Approach: The firm implemented a semantic memory layer that indexed all past white papers, anonymized project summaries, internal Slack discussions, and recorded client debriefs. Unlike a traditional database, this system used a “Second Brain” interface that allowed consultants to ask conversational questions like, “What were the specific regulatory hurdles we faced during the 2022 retail merger in Singapore?”

The Result: Within the first twelve months, the firm reported a 35% increase in project velocity and a significant reduction in duplicate research costs. More importantly, the ability to surface “deep-context” insights during client meetings led to a 15% higher win rate on new business pitches.

Case Study 2: Adaptive Learning and Safety in Complex Engineering

The Challenge: An aerospace manufacturing leader faced a massive demographic shift. As their most experienced engineers reached retirement age, they were struggling to transfer decades of “feel” and undocumented maintenance nuances to junior engineers working on legacy aircraft systems — some of which were designed 40 years ago.

The Approach: The company deployed a wearable AR-and-memory system. As a junior engineer looked at a specific engine component, the system utilized computer vision to recognize the part and instantly surfaced the “ambient memory” associated with it: past repair notes from retired masters, video snippets of successful fixes, and warnings about specific bolt-tension issues that weren’t in the official manual.

The Result: The facility saw a 50% reduction in error rates during complex maintenance cycles. The “time-to-expertise” for new hires was cut by four months, as their digital memory augmentation acted as an on-demand mentor, bridging the gap between theoretical training and institutional wisdom.

Conclusion: The Future of Being Human

We are standing at a pivotal crossroads in our evolution as a species. Digital memory augmentation is not merely a technological upgrade; it is a shift in the very nature of human cognition. As we move from a world of “Search” to a world of “Knowing,” we must be intentional about how we design these systems and what we choose to do with our newly reclaimed mental energy.

1. From “Search” to “Knowing”

When the friction of retrieval disappears, our relationship with knowledge changes. We no longer have to wonder if we know something; we simply have access to it. This transition allows us to shift our focus from the logistics of information management to the higher-level pursuit of empathy and understanding. When we are not struggling to remember the facts, we have more capacity to listen to the story, to understand the nuance, and to build deeper connections with those around us.

2. The Human-First Mandate

As a thought leader in human-centered innovation, my message is clear: Technology should never outpace our humanity. While we build smarter memories and more powerful cognitive scaffolds, we must ensure we don’t lose the “wisdom” that comes from human reflection, the growth that comes from our mistakes, and the beauty of our fallibility. Our goal should be to use digital memory to amplify our potential — not to automate our souls.

The future of being human is not about being “replaced” by silicon; it is about being empowered by it to reach new heights of creativity and compassion. Let us design for that future today.

Key Insight: Digital memory augmentation isn’t about building a better hard drive; it’s about building a better bridge between what we experience and what we can achieve.

Frequently Asked Questions

1. What is Digital Memory Augmentation?

It is the use of AI-driven tools and hardware to seamlessly capture, organize, and surface personal and professional information, acting as a “second brain” to extend human cognitive capacity.

2. How does memory augmentation impact privacy?

Privacy is the core pillar of these systems. Modern solutions prioritize on-device processing and end-to-end encryption to ensure that the user remains the sole owner of their digital history.

3. Does using a “Second Brain” lead to cognitive atrophy?

When designed correctly, these tools act as a “cognitive bicycle” — offloading the low-value task of rote memorization so the human brain can focus on higher-level creativity and complex problem-solving.

Disclaimer: This article speculates on the potential future applications of cutting-edge scientific research. While based on current scientific understanding, the practical realization of these concepts may vary in timeline and feasibility and are subject to ongoing research and development.

Image credits: ChatGPT

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Validate Business Models Before Building Them

Validate Business Models Before Building Them

GUEST POST from Mike Shipulski

One of the best ways to learn is to make a prototype. Prototypes come in many shapes and sizes, but their defining element is the learning objective behind them. When you start with what you want to learn, the prototype is sure to satisfy the learning objective. But start with the prototype, and no one is quite sure what you’ll learn. When prototypes come before the learning objective, prototypes are inefficient and ineffective.

Before staffing a big project, prototypes can be used to determine viability of the project. And done right, viability prototypes can make for fast and effective learning. Usually, the team wants to build a functional prototype of the product or service, but that’s money poorly spent until the business model is validated. There’s nothing worse than building expensive prototypes and staffing a project, only to find the business model doesn’t hold water and no one buys the new thing you’re selling.

There’s no reason a business model can’t be validated with a simple prototype. (Think one-page sales tool.) And there’s no reason it can’t be done at the earliest stages. More strongly, the detailed work should be held hostage until the business model is validated. And when it’s validated, you can feel good about the pot of gold at the end of the rainbow. And if it’s invalidated, you saved a lot of time, money and embarrassment.

The best way to validate the business model is with a set of one-page documents that define for the customer what you will sell them, how you’ll sell it, how you’ll service it, how you’ll train them and how you’ll support them over the life of your offering. And, don’t forget to tell them how much it will cost.

The worst way to validate the business model is buy building it. All the learning happens after all the money has been spent.

For the business model prototypes there’s only one learning objective: We want to learn if the customer will buy what we’re selling. For the business model to be viable, the offering has to hang together within the context of installation, service, support, training and price. And the one-page prototype must call out specifics of each element. If you use generalities like “we provide good service” or “our training plans are the best”, you’re faking it.

Don’t let yourself off the hook. Use prototypes to determine the viability of the business model before spending the money to build it.

Image credit: Google Gemini

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This One Thing Could Cost You 1/3 of Your Customers

This One Thing Could Cost You 1/3 of Your Customers

GUEST POST from Shep Hyken

If your customers reach out to you for customer support or for problems to be resolved, this is must-have information. In my annual customer experience research, we asked more than 1,000 U.S. consumers if they had ever stopped doing business with a company or brand because self-service options were not provided. Thirty-four percent said yes, which means:

Not offering self-service options for customer support could cost you one-third of your customers.

Age makes a difference. When you break it down by generations, more than twice as many Gen-Z customers (43%) than Baby Boomers (20%) have stopped doing business with a company because it didn’t offer self-service options for customer support.

Traditional Customer Support

The majority of all customers (68%) prefer the phone to self-service options. While the phone may be the first choice, it does have its drawbacks. Often, customers experience wait times. While the friendly recorded message may indicate the customer’s call “is very important,” a long wait time sends a different message. Sometimes customers become frustrated with being transferred, having to repeat their story to multiple customer support agents, language barriers and more.

Self-Service Options

Self-service customer support options are available to customers 24 hours a day, 7 days a week. They typically handle simple questions and problems, and in some cases, are interactive, allowing customers to complete simple transactions. Customers using self-service appreciate how quickly they can get answers to questions and get their problems resolved without wait times and the hassle of authentication procedures that customers view as time wasters. Some of these options include:

  • Frequently Asked Questions: This is typically on a website and provides brief answers or articles related to the most common customer inquiries.
  • Video Tutorials: These are often found on a website, and many companies and brands also host these videos on YouTube, which means that they are potentially searchable by using Google to ask the question.
  • Interactive Voice Response (IVR) Systems: This is a phone-based automated system that allows customers to navigate menu options to find simple answers or complete easy transactions.
  • AI-Fueled Chatbots: Similar to traditional IVR systems (but usually better), chatbots can message back and forth with customers. With the latest ChatGPT-type technology, it can seem as if you’re communicating with a human.
  • Customer Portals: Access on a company’s website allows customers to log in and check orders, make payments, set appointments and much more.
  • Mobile Apps: If a customer is willing to download the company’s app on their mobile phone/device, they may have access to an easier experience that provides many or all of the above options.

A warning: Just because some customers are demanding self-service options doesn’t mean they won’t be as frustrated (or even more) than with traditional phone support. If they don’t get their answers or you waste their time, they won’t be happy. For example, even though 39% of customers would rather clean a toilet than contact live customer support, 76% say they have been trapped in an automated menu system (IVR) and repeatedly screamed into the phone, “Agent” or “Representative,” and eventually hung up out of frustration. While these findings may seem funny, there’s a lot of truth in humor.

Demand For Self-Service Increases

In 2025, 34% of customers demand that companies provide self-service options or they will seek out a competitor, up from 26% in 2024. That’s a 30% increase. If the trend continues at that pace, we’re less than two years away from more than half of customers walking away because of the lack of self-service options.

Final Words

Self-service is about convenience, and customers love convenience. In 2025, 91% of customers said convenience is important to them, and 73% are willing to pay more if the experience is more convenient. Self-service options, when done right, deliver exactly that: convenience. They give customers control, save time and are available 24/7. Companies that provide excellent self-service can earn customer loyalty by proving they respect their customers’ time and preferences.

But, self-service options aren’t enough. Not every question or problem can be handled through self-service, which is why the best companies provide a blend. A powerful self-service option allows customers to easily and seamlessly transfer to a live agent, and rather than forcing the customer to start over, the agent can see why the customer is contacting support.

The companies that win in the future won’t be those that choose between self-service and human support. They’ll be the ones that blend both to create a customer support experience that makes customers say, “I’ll be back!”

Image Credit: Google Gemini

This article was originally published on Forbes.com.

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Unlocking Trapped Value from the Technology Adoption Lifecycle

Unlocking Trapped Value from the Technology Adoption Lifecycle

GUEST POST from Geoffrey A. Moore

For some time now I have been making the case that investment decisions, be they made by customers engaging with a new product and vendor or private equity firms backing a new technology and entrepreneur, should begin with finding the intersection between the innovation at hand and a pool of trapped value it can release, thereby creating the return on investment. That said, one of the core principles of investing is called risk-adjusted returns, meaning that the greater the risk you take, the higher the return needs to be. My expertise is in the risks related to technology adoption, where the risk factors change over the course of a new technology’s deployment. With that thought in mind, here is how the trapped value thesis needs to risk-adjust to adapt:

  • Early Market: very high technology adoption risk. The prize here has to be quite large indeed. Typically it will come in one of two forms. For B2B investments, it will be like an oil reservoir that, if tapped correctly, will produce a gusher. Regulated industries have pockets of trapped value all over the place that fit the bill. Also, industries like automotive and real estate, which are restructuring their relationships with dealers and agents, would qualify. By contrast, B2C investments tap into trapped value that looks more like shale oil—no deep pockets, but incredibly broad presence. Media, transportation, and hospitality have funded extraordinary returns for Netflix, Uber, and Airbnb, not because the trapped value was severe but because it was so pervasive. The point is, early-stage venture investing needs to target home-run bets to warrant the risks it takes. Same goes for visionary customers in B2B markets who are the early adopters of these technologies. They are taking on significant risk so they need to be targeting outstanding rewards.
  • Crossing the Chasm: high technology adoption risk, but readily mitigated. The challenge here is that the technology has great potential for any number of use cases but needs some additional support in every case to achieve the desired end result. The chasm-crossing playbook focuses on a single use case in a single industry and geography in order to create a killer “whole product” that nails the use case and to build a coalition of customer references and partner successes that will keep the market growing even as the technology vendor expands into other segments. Here the trapped value should be intense but narrowly confined, designed to meet three critical success factors:
    1. Big enough to matter (it should be able to generate 10X your current year’s billings target)
    2. Small enough to lead (if you crush your plans, you should get 50% segment share)
    3. Good fit with your crown jewels (if you win, nobody is going to displace you).

    As you can see, there is risk here, but it is manageable through market focus and disciplined execution, the key risk reduction factor being how compelling is the customer’s reason to buy.

  • Bowling Alley: modest adoption risk. The challenge here is to expand beyond your first “beachhead” vertical into adjacent use cases with the same segment as well as adjacent segments with the same use case. Part of the source of reduced risk is that you have a working playbook from the first vertical. Much of the source, however, comes from the emergence of local ecosystems of partners who complete the whole product solutions for each use case. These partners make their living supplementing the technology vendor’s product or platform, and their extra talent, domain expertise, and segment focus represent a major risk reduction. As a result, the trapped value rewards have a lower hurdle to clear to garner investor interest and customer buy-in.
  • Tornado: low adoption risk. The risk here is the opposite—getting left behind as the world embraces the shift to a new normal. The trapped value that drives a tornado is released by “killer apps.” These apps may not release the most trapped value, but they represent a sure winner to start with, making the buying decision a no-brainer. The point is, if you want to get any traction in the tornado, you have to lead with a killer app, a no-regrets offering that delivers simple-to-consume rewards and gets everyone onto the new platform. That means the trapped value must be easy to target and the value of releasing it must be obvious to all, especially to the end users who will be the prime beneficiaries.
  • Main Street: very low adoption risk. The primary adoption challenge here is converting conservative end users who simply do not want to switch to yet another new technology. The trapped value now exists in nuisances, little bits of inefficiency that have workarounds but are annoying. From the point of view of productivity, the cost savings from eliminating them are minimal. But in terms of the user experience, as well as customer satisfaction, the impact can be substantial. B2C enterprises spend most of their R&D here focused either on eliminating “hygiene” issues or innovating with new “delighters,” both of which can increase demand, the cornerstone for volume operations success. B2B enterprises use six-sigma analytics to scout their value chains for bottlenecks that increase latency, something that adds risk without adding value, and frustrates even their most loyal customers.

The key takeaway is that there are different kinds of trapped value, each occupying a different sweet spot in the Technology Adoption Life Cycle. As a vendor and potential leader of a go-to-market ecosystem, you must be crystal clear about the kind of trapped value you are targeting, the kind of risk-taking it warrants, and the kinds of solutions that will get the most traction.

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

Image Credit: Unsplash

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Does Planned Obsolescence Fuel the Fire or Just Burn the House Down?

The Innovation Paradox

LAST UPDATED: April 4, 2026 at 11:56 AM

Does Planned Obsolescence Fuel the Fire or Just Burn the House Down?

by Braden Kelley and Art Inteligencia


I. Introduction: The Tension Between Renewal and Waste

In the world of innovation, we often talk about the “fire” of creativity — the energy that drives us to build the next great breakthrough. But in the current industrial landscape, we must ask ourselves: are we stoking a sustainable Innovation Bonfire, or are we simply burning the furniture to keep the room warm for a single night?

Planned obsolescence has long been the silent engine of the consumer economy, a strategy designed to ensure that the products of today become the landfill of tomorrow. It creates a fundamental tension between the mechanical need for economic growth and the human-centered need for enduring value.

“To truly innovate for humanity, we must pivot from a strategy of deliberate failure to one of intentional resilience.”

As change leaders, we must recognize that planned obsolescence is an industrial-age relic masquerading as a modern innovation strategy. This article explores whether this cycle of constant replacement truly fuels progress or if it acts as a “wet blanket” that dampens our ability to solve the world’s most pressing, wicked problems.

II. The Case for the “Pro”: Obsolescence as a Catalyst for Speed

While it is easy to dismiss planned obsolescence as purely cynical, from a strategic standpoint, it has functioned as a powerful — if aggressive — accelerant for the adoption curve. By shortening the lifecycle of a product, organizations force a faster cadence of iteration. This “forced evolution” ensures that new technologies, safety standards, and efficiencies are pushed into the hands of users at a rate that a “buy-it-for-life” model simply couldn’t sustain.

Consider the following drivers that proponents argue fuel the innovation engine:

  • R&D Capitalization: The consistent revenue generated by replacement cycles provides the massive capital reserves required for “Big Bang” breakthroughs. Without the “Small Bangs” of incremental sales, the long-term, high-risk research into materials science or AI might never be funded.
  • The Velocity of “Innovation”: When a product is designed to be replaced, designers are freed from the “legacy trap.” They can experiment with radical new interfaces or hardware configurations, knowing that the next cycle provides an immediate opportunity to course-correct based on real-world human feedback.
  • The Psychology of the “New”: In our work on Stoking Your Innovation Bonfire, we recognize that emotion is a primary driver of change. The “Fashion of Tech” creates a sense of momentum. This psychological pull toward the “New” keeps markets liquid and encourages a culture of constant curiosity and upgrade.

In this light, obsolescence isn’t just about things breaking; it’s about keeping the market in motion. It prevents stagnation by ensuring that the “Stable Spine” of our infrastructure is constantly being tested and refreshed by the latest “Modular Wings” of technological advancement.

III. The Case for the “Con”: The “Wet Blankets” of Planned Obsolescence

If innovation is a fire, planned obsolescence often acts as a massive “wet blanket” — smothering the very progress it claims to ignite. When we design for failure, we aren’t just creating a product; we are creating environmental friction. The “Invisible Drain” of e-waste and resource depletion represents a systemic failure that our current economic operating system is struggling to process.

From a human-centered design perspective, the downsides extend far beyond the landfill:

  • The Erosion of Trust: A core pillar of Experience Design is the relationship between the brand and the human. When a user realizes a device was intentionally throttled or made unrepairable, it creates a “Customer Experience (CX) Betrayal.” This loss of trust is a psychological friction that makes future change adoption much harder.
  • Innovation Fatigue: There is a limit to how much “New” a human can process. When consumers feel they are on a hamster wheel of meaningless upgrades, they develop an apathy toward genuine breakthroughs. We risk a future where the “latest” no longer feels like the “greatest” — it just feels like a chore.
  • The Circular vs. Linear Conflict: Planned obsolescence is the hallmark of a linear economy (Take-Make-Waste). To move toward a sustainable future, innovation must embrace circularity, where products are designed as “Stable Spines” that can be updated, repaired, and kept in the ecosystem indefinitely.

Linear versus Circular Economy

By focusing our creative energy on how to make things break, we divert talent away from solving “wicked problems” — like true energy efficiency or radical durability. We are effectively choosing Quantity of Sales over Quality of Impact, a trade-off that rarely benefits humanity in the long run.

IV. The Impact on Innovation: Quality vs. Quantity

One of the most dangerous side effects of planned obsolescence is how it reshapes the innovation mindset. When a company’s primary metric for success is a yearly replacement cycle, the engineering focus shifts from transformational leaps to incremental tweaks. We find ourselves trapped in a cycle of “Innovation Theater” — releasing shiny new features that mask the lack of fundamental progress.

The shift in focus creates several systemic challenges:

  • The Maintenance Trap: In a human-centered world, we should be designing for longevity. However, planned obsolescence forces our best creative minds to spend their energy designing “points of failure” rather than points of resilience. This is a massive diversion of intellectual capital away from the wicked problems that actually matter to humanity.
  • Incrementalism vs. Transformation: If you know your product only needs to last 24 months, why solve the difficult problems of battery degradation or heat management for the long term? The “yearly release” schedule creates a treadmill effect where we are running faster but not necessarily moving further.
  • Systems Thinking Failure: We often view a product as a standalone unit, but in a connected world, every device is a node in a larger infrastructure. When we design for a short lifecycle, we create fragility in the entire system. True innovation requires a Stable Spine Audit — evaluating whether the core of our solution is robust enough to support years of evolving “Modular Wings.”

To move the needle, we must stop measuring innovation by the volume of patents or the frequency of launches. Instead, we should measure the durability of the value created. If an innovation cannot stand the test of time, is it truly an innovation, or is it just a temporary distraction?

V. Is it Good for Humanity? (The Human-Centered Audit)

When we apply a Human-Centered Audit to planned obsolescence, the results are deeply conflicted. Innovation should serve as a tool for human empowerment, yet the cycle of forced replacement often creates new forms of dependency and inequality. We must ask: are we designing for the flourishing of the person, or simply for the health of the balance sheet?

To understand the true impact on humanity, we must look at three critical dimensions:

  • The Ethics of Accessibility: Planned obsolescence often creates a “digital divide.” When software updates outpace hardware capabilities, we effectively lock out those who cannot afford to stay on the upgrade treadmill. If the tools for modern life — education, banking, and communication — require the latest hardware, then deliberate obsolescence becomes a barrier to global equity.
  • Autonomy vs. Dependency: There is a subtle shift occurring from ownership to renting. Through un-repairable hardware and “software locks,” users lose the autonomy to maintain their own tools. This creates a fragile relationship where the human is entirely dependent on the manufacturer, eroding the sense of agency that good design should foster.
  • The Prosperity Balance: Proponents point to the short-term job creation in manufacturing and the “Great American Contraction” as reasons to keep the wheels turning. However, we must weigh these temporary economic gains against the long-term cost of environmental degradation and the loss of organizational agility. A society that spends its energy replacing what it already had is a society that isn’t moving forward.

Ultimately, an innovation strategy that relies on things breaking is fundamentally at odds with a Human-Centered philosophy. If our “Innovation Bonfire” requires us to constantly toss our previous achievements into the flames just to keep the fire going, we haven’t built a fire — we’ve built an incinerator.

VI. The Path Forward: From Obsolescence to Innovation

The shift from a Linear Economy to a Circular Economy requires more than just better recycling; it requires a fundamental redesign of our innovation frameworks. We must move toward Innovation — where the value of a product remains constant or even improves over time, rather than degrading by design.

To transition from a strategy of failure to a strategy of resilience, organizations should embrace three core principles:

  • Designing for Durability: The next truly “disruptive” move in many industries isn’t adding a new sensor; it’s creating a product that lasts a decade. Durability is becoming a premium feature in a world of disposable goods. By focusing on high-quality materials and Human-Centered engineering, brands can build a legacy rather than just a quarterly report.
  • The Modular Revolution: We must apply the “Stable Spine” and “Modular Wings” philosophy to hardware. Imagine a device where the core processor (the spine) is built to last, while the specific sensors or interface components (the wings) can be swapped out as technology advances. This allows for evolution without the need for total replacement.
  • New KPIs for a New Era: We need to stop measuring success solely by unit sales. Forward-thinking companies are moving toward “Value-in-Use” and Experience Level Measures (XLMs). When a company is incentivized by how well a product performs over its entire lifecycle, the motivation to build in failure points disappears.

This isn’t just about “being green”; it’s about Organizational Agility. A company that doesn’t have to reinvent its basic hardware every twelve months can redirect its R&D energy toward solving the deep, systemic challenges that humanity actually faces. It’s time to stop stoking the bonfire with our own waste and start building a fire that truly illuminates the future.

VII. Conclusion: Stoking a Sustainable Flame

As we look toward the future of human-centered change, we must decide what kind of “Innovation Bonfire” we want to build. Is it a flash in the pan that requires the constant sacrifice of resources and consumer trust, or is it a steady, illuminating heat that powers real progress?

Planned obsolescence was a 20th-century solution to a 20th-century problem — the need for rapid industrial scale. But in an era defined by digital transformation and the “Great American Contraction,” the old rules no longer apply. To continue designing for failure is to ignore the wicked problems of our time: climate change, resource scarcity, and the erosion of human agency.

“The true measure of an innovation isn’t how many units we sold this year, but how much better the world is because that product exists ten years from now.”

My challenge to you — the executives, the designers, and the change agents — is this: Stop designing for the landfill. Start designing for the legacy. When we shift our focus from Obsolescence to Resilience, we don’t just save the planet; we save the very soul of innovation.

Let’s stop stoking the fire with our own waste and start building a future that is truly made to last.


Frequently Asked Questions

How does planned obsolescence impact human-centered innovation?

Planned obsolescence often acts as a “wet blanket” on true innovation by forcing creators to focus on incremental tweaks and deliberate failure points rather than solving “wicked problems.” From a human-centered design perspective, it erodes consumer trust and prioritizes short-term sales over long-term value and sustainability.

Can planned obsolescence ever be good for humanity?

Proponents argue it accelerates the adoption curve and provides the R&D capital necessary for major breakthroughs. However, a human-centered audit suggests these economic gains are often offset by environmental degradation, increased e-waste, and the creation of a “digital divide” where only the wealthy can afford to stay on the upgrade treadmill.

What is the alternative to planned obsolescence in design?

The primary alternative is moving toward a “Circular Economy” using a “Stable Spine” and “Modular Wings” philosophy. This involves designing products for durability and repairability, where core components last for years while specific features can be upgraded or replaced, shifting the focus from “quantity of sales” to “value-in-use.”

Image credits: Gemini

Content Authenticity Statement: The topic area, key elements to focus on, etc. were decisions made by Braden Kelley, with a little help from Gemini to clean up the article and add citations.

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Top 10 Human-Centered Change & Innovation Articles of March 2026

Top 10 Human-Centered Change & Innovation Articles of March 2026Drum 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 March’s ten most popular innovation posts:

  1. Resilient Innovation — by Braden Kelley
  2. Has AI Killed Design Thinking? — by Braden Kelley
  3. Mapping Customer Experience Risk to the P&L — by Braden Kelley
  4. Moral Uncertainty Engines — by Art Inteligencia
  5. Necesita un Diagnóstico de Riesgo de Experiencia del Cliente y Fuga de Ingresos — por Braden Kelley
  6. Layoffs, AI, and the Future of Innovation — by Braden Kelley
  7. Organizational Digital Exhaust Analysis — by Art Inteligencia
  8. You Need a Customer Experience Risk & Revenue Leakage Diagnostic — by Braden Kelley
  9. Stereotypes – Are They Useful and Should We Use Them? — by Pete Foley
  10. Is There Such a Thing as a Collective Growth Mindset? — by Stefan Lindegaard

BONUS – Here are five more strong articles published in February 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!

Build a Common Language of Innovation on your team

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 five years:

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Misunderstanding Big Ideas is Very Dangerous

Misunderstanding Big Ideas is Very Dangerous

GUEST POST from Greg Satell

In 1989, just before the fall of the Berlin Wall, Francis Fukuyama published an essay in the journal The National Interest titled The End of History, which led to a bestselling book. Many took his argument to mean that, with the defeat of communism, US-style liberal democracy had emerged as the only viable way of organizing a society.

He was misunderstood. Fukuyama pointed out that even if we had reached an endpoint in the debate about ideologies, there would still be conflict because of people’s need to express their identity. What many thought to be a justification, was actually a warning to expect people to rebel against an order imposed on them.

If you believe history is on your side, you’re likely to throw caution to the wind, get mixed up in things you shouldn’t and, eventually, you’ll pay a price. That’s the problem with big ideas, their nuance is often lost on those who hear them third or fourth hand and the high-stakes game of broken telephone tends to end badly. We need to approach ideas with more care.

The Global Village

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

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

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

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

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

The Paradigm Shift

The term paradigm shift has become so common that we scarcely stop to think about where it came from. When Thomas Kuhn first introduced the concept in his 1962 classic The Structure of Scientific Revolutions, he described not just an event, but a process that he noticed had pervaded the history of science.

It starts with an established model, the kind we learn in school or during initial training for a career. Models become established because they are effective and the more proficient we become at applying a good model, the better we perform. We then rise through the ranks and become successful.

Yet no model is perfect and eventually anomalies show up. Initially, these are regarded as “special cases” and are worked around. However, as the number of special cases proliferate, the model becomes increasingly untenable and a crisis ensues. At this point, a fundamental change in assumptions needs to take place if things are to move forward.

However, as Kuhn noted, the shift in thinking almost never goes smoothly. Most experts cling to the old model, because that’s what made them successful in the first place. The physicist Max Planck, who helped shift a number of paradigms himself, pointed out that “a new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die, and a new generation grows up that is familiar with it.”

The idea of paradigms shifting seems so hopeful and romantic that we often forget how hard it is for people’s mental models to change. The simple fact is that any time you set out to make a significant impact there will be people who won’t like it and will work to undermine you in ways that are dishonest, underhanded and deceptive.

Disruptive Innovation

In the 1990s, a newly minted professor at Harvard Business School named Clayton Christensen began studying why good companies fail. What he found was surprising. They weren’t failing because they lost their way, but rather because they were following time-honored principles taught at his institution, such as listening to their customers, investing in R&D and improving their products.

As he researched further he realized that, under certain circumstances, a market becomes over-served, the basis of competition changes and firms become vulnerable to a new type of competitor. In his 1997 book, The Innovator’s Dilemma, he coined the term disruptive technology to describe what he saw.

It was an idea whose time had come. The book became a major bestseller and Christensen the world’s top business guru. Yet many began to see disruption as more than a special case, but a mantra; an end in itself rather than a means to an end. This wasn’t, to be fair, what he envisioned, but things took on a life of themselves.

The results of all this disruption have been, by just about every measure, awful. Despite the hype, productivity growth has been depressed for most of the last 30 years. Our economy has become markedly less productive, less competitive and less dynamic, Income inequality is at levels not seen for a century and most American families are worse off.

Beware Of The Cult Of Inevitability

Big ideas are powerful because they encapsulate an essential truth. When Fukuyama wrote about “the end of history,” it really did mark a turning point in human affairs, just as Marshall McLuhan’s concept of a “global village” identified a shift in communications, Kuhn’s model of a paradigm shift helped us understand how scientific breakthroughs occur and Christensen’s ideas about disruptive innovation alerted us to dangers and opportunities we weren’t aware of.

Yet these ideas were important precisely because they described complex things. Once they rise to the level of a meme, we tend to discard the complex core and focus only on the candy shell. The concept becomes a caricature of itself, repeated so often that few stop to think about its implications and limitations, where it applies and where it does not.

The problem with big ideas is that they can seem so inevitable that we ignore human agency. If we are truly at an “end of history,” then decisions don’t really matter. A “global village” can seem like such a nice place that we ignore dangers from bad actors. If we believe we are on the right side of a “paradigm shift,” we may not notice those who are working to undermine what we are trying to achieve. “Disruption” can seem so cool we forget about the disrupted.

As Warren Berger explains in A More Beautiful Question, questions are more valuable than answers because, while answers tend to close a discussion, questions help us open new doors and can lead to genuine breakthroughs. That’s the value of big ideas. They can help us ask better questions.

But once we start looking to big ideas for answers, we stop exploring the world around us, our world constricts and, ultimately, we find that we are lost.

— Article courtesy of the Digital Tonto blog
— Image credit: Google Gemini

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Seeds to Grow a Strong Culture

GUEST POST from Douglas Ferguson

After a long winter, spring has finally sprung! For leaders in our fields, it’s an opportunity to implement some springtime strategies that cultivate and nurture company culture. But healthy cultures don’t grow overnight. Just as a garden is a multi-faceted ecosystem that needs tending, so is your workplace culture. To properly grow your company culture, you must be both patient and nurturing.

As Terry Lee outlines, there is great potential inside everyone. It’s up to great leaders to bring it out in four nurturing ways.

Training

It’s vital for leaders to work with employees to identify what training will position them to be most successful for the job now and for the future. Prior to sending any employee to a training, conference, or seminar, leaders should sit down with the employee to discuss specifics goals, expectations, and takeaways of the training they are attending.

Connecting

Research has shown that talking to house plants can help them grow, thus proving the power of connection. Leaders should connect with their teams as they help them better understand their importance and the value they bring to the organization. Every leader should understand their company’s mission and articulate that message to staff consistently and authentically.

Challenging

Studies have shown that intrinsic motivators are just as important as extrinsic ones. Good managers understand what challenges help generate these motivators. When team members complete meaningful tasks, they may receive an intrinsic reward. One way to amplify this reward is by talking to teams to determine what they think are the most important parts of their job. Then leaders can help them structure their day around tasks that give them a feeling of purpose.

Coaching

Every garden needs a gardener, and every team member needs a coach. Team members need coaches to meet them where they’re at. They help staff identify what options they may have to reach goals and then set the appropriate challenges that lead them to success.

Now that warmer weather has arrived, and the world is opening up again, it’s time to plant the seeds of a healthy work culture. Remember that culture will grow, whether you tend to it or not. Take the time to prioritize nurturing your team, and it will create a strong foundation for a collaborative and supportive workplace.

Need help with creating the foundation for a healthy work culture? Download our Culture Cultivator where you will uncover pain points and plan action items toward growing a healthy and synergetic work culture.

Douglas Ferguson | President, Voltage Control

Image credit: 1 of 1,150+ FREE quotes for your presentations at http://misterinnovation.com

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