Tag Archives: ideas

Why Organizations Struggle with Innovation

Why Organizations Struggle with Innovation

GUEST POST from Howard Tiersky

We all know the world is changing rapidly. It’s clear that in order for organizations to remain relevant to the next generation of customers, and even in the next generation of technology, we must adapt, evolve and transform. The field is littered with once-great companies who failed to do this: Blackberry, Nokia, Kodak, Borders, Western Union, Blockbuster, Polaroid.

But accepting major change, or even in some cases small changes, isn’t easy for large companies. At Innovation Loft we’ve worked with scores of major brands on their efforts to conceive, create and launch new products, enter new markets, redefine their value propositions and distribution strategies, and address various types of transformations. We’ve seen some spectacular successes and some tragic near misses. In watching these innovation stories unfold, we’ve concluded that there are three key reasons why innovations fail.

Three Key Reasons Innovations Fail:

  1. The Wrong Idea
  2. Failure to Execute
  3. Sabotage!

It’s important to keep these three domains of risk in mind when approaching any innovation project, and a lot of our work at Innovation Loft is focused on how to manage and mitigate risks in each of these three categories. Let’s look at these one at a time:

1. The Wrong Idea

Change is not always good. New is not always popular. How can you tell the right ideas from the wrong ones? Here are a few practices that can make a big difference.

Focus on Customer Needs

It may seem like Apple has made its success on delivering customers new capabilities they “didn’t know they needed.” And that may be true in the sense that if you had asked customers, they might not have articulated a desire for an iPod or an iPad. However, if you focused on observing consumers in their day-to-day interactions back then, the challenge of dealing with dozens or more CDs, and the decision about which ones to bring clearly created a “pain point.” Fast forward a few years. People trying to curl up with their laptop in bed to watch a movie was clearly awkward, and watching a movie on a small iPhone was also sub-optimal. Apple identified gaps they could fill. Many unsuccessful ideas lack a clear customer value proposition and are based on the assumptions of a benefit consumers will eventually realize.

Test and Iterate

Think of product development as a spiral. Test the simplest, lowest-cost version of your product (even if it’s a paper mockup) to get early feedback from users. Continue that process each step of the way, through launch and beyond, to really understand how consumers are using your product and where it may need improvement.

Pivot

Ultimately, don’t fall in love with your idea. Focus on the value you can create for your customers. Even with the first two points in this list, you can still find yourself launching the wrong idea. That’s the risk of innovation. In a large corporate environment, it’s important to set the expectation up front that there will be flexibility on redefining the product, even substantially, as the project goes on. While this approach may not be consistent with typical enterprise “capital budgeting” processes, it’s critical to the success of innovative projects.

2. Failure to Execute

Even if you have the right idea, you can fail to execute. Effective execution is measured by quality, speed, and communication.

Quality: Does the product fulfill the vision? An initial version of a product may not be as feature-rich as future releases (the original iPhone did not allow copy and paste, let alone the downloading of apps!) The key test is not comprehensive features but doing a few things very well.

Speed: In a world of innovation, we are always in competition. At the initial launch of Android, it was clearly behind the curve compared to iOS. Over time, Android was able to catch up and eventually exceed iOS sales. The two remain locked in an arms race for higher standards and better capabilities, and the timing of improvements clearly has a substantial impact. Nevertheless, Android’s story demonstrates that even with a late start, one can catch up. Kyocera and Nokia were in the market with smartphones several years before Apple.

Communication: Peter Drucker said, “Business has just two functions: innovation and marketing.” The two must go hand-in-hand. Apple’s genius has been the marriage of a great product with great communication.

3. Sabotage

Companies are designed to resist change. Classic business books define how organizations must specify roles and clear processes for how to operate. But this resistance to change is misplaced when it comes to innovation. We’ve seen many great projects killed in infancy, or even after launch and initial success, due to areas of an organization whose interests would be threatened by the success of that transformation.

If a new product or project is truly going to be transformational for your company, expect it to have enemies. These enemies’ very survival (or their perception of it) may be at stake. Many innovative products that were on the path to “saving the company” are killed through internal sabotage. As soon as there is any misstep in an innovation initiative — as there always is — forces are ready to pounce and convince the powers-that-be that it’s time to “put it out of its misery.” Can you imagine Apple killing the iPhone over Antennaegate or the Apple Maps debacle?

How can you avoid sabotage? One tactic is trying to gain as much organizational alignment as possible during each step of the innovation process. Don’t assume that because a solution seems “obvious” to your team that others will automatically support it. Involving key executives, in addition to as many parts of the organization as possible, will garner more support. Give team members the chance to participate and feel ownership of the initiative. In the words of Harry Truman:

“It’s amazing what you can accomplish if you don’t care who gets the credit.”

So how do you figure out the right answer, get everyone on the same page, and focus on a common innovation goal? At FROM, we use a specific model to approach the process of identifying the most relevant opportunity areas for innovation, and to build group consensus around the best approach. You’ll have to adapt it to your situation, but the model should provide a good starting framework.

This article originally appeared on the Howard Tiersky blog
Image Credits: Unsplash

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Top 10 Human-Centered Change & Innovation Articles of July 2023

Top 10 Human-Centered Change & Innovation Articles of July 2023Drum 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 July’s ten most popular innovation posts:

  1. 95% of Work is Noise — by Mike Shipulski
  2. Four Characteristics of High Performing Teams — by David Burkus
  3. 39 Digital Transformation Hacks — by Stefan Lindegaard
  4. How to Create Personas That Matter — by Braden Kelley
  5. The Real Problem with Problems — by Mike Shipulski
  6. A Triumph of Artificial Intelligence Rhetoric — by Geoffrey A. Moore
  7. Ideas Have Limited Value — by Greg Satell
  8. Three Cognitive Biases That Can Kill Innovation — by Greg Satell
  9. Navigating the AI Revolution — by Teresa Spangler
  10. How to Make Navigating Ambiguity a Super Power — by Robyn Bolton

BONUS – Here are five more strong articles published in June 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 three years:

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Accelerating Innovation Cycles with AI

From Idea to Impact

Accelerating Innovation Cycles with AI

GUEST POST from Chateau G Pato

The innovation landscape has always been a race against time. Ideas are plentiful, but transforming them into tangible impact—a new product, an optimized process, a groundbreaking service—often involves arduous cycles of research, development, testing, and refinement. In today’s hyper-competitive, human-centered world, this pace is simply no longer sufficient. As a thought leader in change and innovation, I believe the single most powerful accelerator for these cycles is Artificial Intelligence. AI isn’t just a tool; it’s a paradigm shift, enabling us to move from nascent concepts to measurable outcomes with unprecedented speed and precision.

For too long, the innovation journey has been characterized by bottlenecks: manual data analysis, slow prototyping, biased feedback interpretation, and iterative development that could stretch for months or even years. AI offers a compelling antidote to these challenges, supercharging every phase of the innovation process. It’s about augmenting human creativity and insight, not replacing it, allowing our teams to focus on the truly strategic and empathetic aspects of innovation while AI handles the heavy lifting of data crunching, pattern recognition, and rapid iteration.

The AI Accelerator: How AI Transforms Each Stage of Innovation

The true power of AI in innovation lies in its ability to enhance and speed up various stages of the innovation cycle:

  • Discovery & Ideation: AI can rapidly analyze vast datasets—market trends, customer feedback, scientific research, patent databases—to identify emerging white spaces, unmet needs, and potential synergies that human teams might miss. Generative AI can even assist in brainstorming novel concepts, providing diverse starting points for human ingenuity.
  • Concept Development & Prototyping: AI-powered design tools can generate multiple design variations based on specified parameters, simulate performance, and even create virtual prototypes in a fraction of the time it would take human designers. This allows for faster testing of diverse ideas.
  • Validation & Testing: Predictive AI models can forecast market reception for new products or features by analyzing historical data and customer behavior, reducing the need for extensive, costly live testing. AI can also analyze user feedback (sentiment analysis) from early tests to quickly identify areas for improvement.
  • Optimization & Launch: AI can optimize product features, pricing strategies, and marketing campaigns in real-time, learning from live data to maximize impact post-launch. For internal process innovations, AI can identify inefficiencies and suggest optimal workflows.
  • Learning & Iteration: Post-launch, AI continuously monitors performance, identifies emerging patterns in customer usage, and suggests further improvements or next-gen features, effectively creating a perpetual feedback loop for continuous innovation.

“AI doesn’t just speed up innovation; it fundamentally redefines the possible, turning months into days and guesses into data-driven insights.”

Human-Centered AI for Innovation: A Crucial Distinction

It’s vital to emphasize that integrating AI into innovation must remain human-centered. The goal is not to automate innovation away from people, but to empower people to innovate better, faster, and with greater impact. AI should serve as an invaluable co-pilot, handling the computational burden so that human teams can focus on:

  • Empathy and Understanding: Interpreting the emotional nuances of customer needs that AI cannot grasp.
  • Strategic Vision: Setting the direction, defining the ethical guardrails, and making the ultimate strategic decisions.
  • Creative Problem-Solving: Leveraging AI’s insights to spark truly original, human-relevant solutions.

Case Study 1: Pharma Research Acceleration with AI (BenevolentAI)

The Challenge:

Drug discovery is notoriously slow, expensive, and high-risk. Identifying potential drug candidates for specific diseases often takes years of laborious research, involving sifting through vast amounts of scientific literature and conducting countless lab experiments. The human-driven cycle from initial idea to clinical trial could span a decade or more.

AI as an Accelerator:

BenevolentAI, a leading AI drug discovery company, uses its platform to accelerate this process dramatically. Their AI system can:

  • Analyze Scientific Literature: Rapidly process and understand millions of scientific papers, clinical trial results, and proprietary datasets to identify relationships between genes, diseases, and potential drug compounds that human scientists might overlook.
  • Generate Hypotheses: Propose novel hypotheses for drug targets and disease mechanisms, suggesting existing drugs that could be repurposed or identifying entirely new molecular structures for development.
  • Predict Efficacy and Safety: Use predictive modeling to assess the likelihood of success and potential side effects of drug candidates early in the process, reducing wasted effort on less promising avenues.

The Result:

By leveraging AI, BenevolentAI has significantly reduced the time it takes to identify and validate promising drug candidates. For example, they identified a potential treatment for Parkinson’s disease, successfully repurposing an existing drug, and advancing it to clinical trials in a fraction of the traditional timeframe. This acceleration means getting life-saving treatments to patients faster, transforming the innovation cycle from an agonizing crawl to a rapid, data-driven sprint, all while maintaining strict human oversight and ethical considerations.


Case Study 2: Generative AI in Product Design (Nike)

The Challenge:

Designing high-performance athletic footwear involves a complex interplay of biomechanics, material science, aesthetics, and manufacturing constraints. Iterating on designs to optimize for factors like weight, durability, and shock absorption used to be a time-consuming, manual process involving physical prototypes and extensive testing. The innovation cycle for a new shoe model could take 18-24 months.

AI as an Accelerator:

Companies like Nike have begun integrating generative AI into their product design processes. Generative design algorithms can:

  • Explore Design Space: Given a set of design parameters (e.g., desired weight, material properties, aesthetic guidelines), the AI can rapidly generate hundreds or thousands of unique sole structures or upper designs. These designs often push the boundaries of human intuition, creating novel geometries optimized for performance.
  • Simulate Performance: AI-powered simulation tools can instantly analyze the generated designs for factors like stress points, airflow, and energy return, providing immediate feedback on their potential performance without needing to build physical prototypes.
  • Suggest Material Optimization: The AI can also suggest optimal material combinations or placement to achieve desired characteristics, further speeding up the development process.

The Result:

The integration of generative AI allows Nike’s design teams to explore a vastly larger array of design possibilities and to iterate on ideas at an accelerated pace. What once took weeks or months of manual design and physical prototyping can now be achieved in days. This not only shortens the overall innovation cycle for new footwear (reducing time-to-market) but also leads to more innovative, higher-performing products that better meet the specific needs of athletes. The human designer remains at the helm, guiding the AI and making critical creative choices, but their capabilities are amplified exponentially.


Conclusion: The Future of Innovation is Intelligent

The journey from a raw idea to a market-ready innovation has never been faster, nor more critical. Artificial Intelligence is not merely an optional add-on; it is becoming an essential engine for accelerating innovation cycles across every industry. By intelligently augmenting human capabilities, AI allows organizations to move beyond incremental improvements to truly transformative breakthroughs.

As leaders, our role is to embrace this technological evolution with a human-centered approach. We must leverage AI to free our teams from mundane tasks, empower them with deeper insights, and enable them to focus their unique creativity and empathy where it truly matters. The future of innovation is intelligent, collaborative, and, above all, accelerated. It’s time to harness AI to build a future where every great idea has a fast track to impact.

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: Microsoft CoPilot

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Five Keys to Leading Creative Teams Successfully

Five Keys to Leading Creative Teams Successfully

GUEST POST from David Burkus

Creativity is a team sport.

It’s been that way for a long time. But the level of teamwork required to solve problems and find innovation has increased over the last decade and even century. Most of the simple problems of the world have been solved, and the ones that remain are too often too complex to be solved by any lone, individual genius.

But not all teams fair equally when it comes to creative tasks, because many team leaders are better prepared to lead teams where the work is simple and easy to define. When reaching team goals is ambiguous and requires more creative thinking it also requires a different type of leadership.

In this article, we’ll outline those differences. We’ll cover five ways to lead creative teams.

1. Show Them the Constraints

The first way to lead creative teams is to show them the constraints. It may sound a little counterintuitive—after all aren’t we supposed to “think outside the box”? But one of the first things creative teams need is an understanding of the constraints of the problem—of the box their answer needs to fit inside. Research suggests creativity is more activated when people understand the constraints of the problem. Constraints aide in the convergent thinking of sifting through ideas that needs to accompany the divergent thinking of generating lots of ideas. You need both. But you need constraints first so that people know ahead of time how to judge the ideas they generate.

2. Support Their Ideas

The second way to lead creative teams is to support their ideas. Nothing stops the creative flow of ideas on a team more than hearing “That’ll never work” or “That’s not how we do things around here.” Leaders need to champion the ideas their team puts forward, at least until the idea generation phase is complete. When people think their leadership isn’t going to consider their ideas, they stop sharing them. Leaders need to not only support ideas when the team is discussing them, but also support ideas when it comes to selling them up the chain of approval needed to implement the idea. Without that support, people just stop trying.

3. Teach Them to Fight Right

The third way to lead creative teams is to teach them to fight right. We like to think of creative teams as fun and cohesive. But the opposite is true. There’s a lot of friction on a creative team. And research suggests that the most creative teams leverage task-focused conflict to generate more and better ideas. But those teams also know how to keep it task-focused and keep it from devolving into personality fights and hurt feelings. And often that requires leaders who can demonstrate and teach their people to fight for their ideas, but not fight their teammates.

4. Test What You Can

The fourth way to lead creative teams is to test what you can. Ideally, teams are going to generate a lot of different ideas. And it’s a bad idea to chase consensus and settle on an idea too soon. Instead, the most creative teams test out multiple different ideas to learn more from what worked and didn’t work, and then combine those lessons into a new and better idea. But too often, leaders facilitate a brainstorming session, circle the idea they like best, and that’s the end of it. Instead, the best leaders test as much as they can as often as they can.

5. Celebrate Their Failures

The final way to lead creative teams is to celebrate their failures. If you’re testing a lot of ideas, your team will fail. But if they fail small on a test, they’ll reduce the chances of failing big later. In addition, failures carry all sorts of lessons that can be learned to better understand the problem and generate even better ideas. That doesn’t happen unless the team understands that failure is part of the process, which is why the best leaders celebrate the risks that team members took and the learning moments their failures generated.

In fact, that’s why all five of these methods shouldn’t be looked at as a linear process. Creativity is an iterative process of ideation, testing, failure, learning, ideation, and more testing and failure. The best leaders know the goal isn’t to get it done, but to keep getting better. And that goes for the creative process, but also the team culture. The goal is to keep getting better until everyone can do their best work ever.

Image credit: Pexels

Originally published at https://davidburkus.com on May 24, 2022.

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Rapid Prototyping: Bringing Ideas to Life Quickly

Rapid Prototyping: Bringing Ideas to Life Quickly

GUEST POST from Chateau G Pato

In the fast-paced world of innovation, speed is often synonymous with success. Rapid prototyping has emerged as a crucial strategy in bringing ideas to life promptly and efficiently. This methodology not only accelerates the design process but also significantly reduces the risk of failure by fostering an iterative and flexible approach to product development.

What is Rapid Prototyping?

Rapid prototyping is a group of techniques used to quickly fabricate a scale model of a physical part or assembly using three-dimensional computer-aided design (CAD) data. It enables innovators to explore and visualize concepts, test ideas, and gain timely feedback from stakeholders. The resulting prototypes can range from simple sketches to 3D-printed models, each providing valuable insights that inform future iterations.

Case Study 1: Revolutionizing Healthcare with 3D Printing

XYZ Medical Corp, a leading innovator in the healthcare industry, faced the challenge of designing custom prosthetics that were both affordable and efficient. By implementing rapid prototyping, they harnessed the power of 3D printing to create prosthetic models in a fraction of the time traditional methods would take.

Through iterative testing and feedback from patients, XYZ Medical Corp was able to refine their designs rapidly. This approach not only reduced production time but also increased the customization options available to patients, ultimately enhancing user experience and trust in the company’s products. This case demonstrates how rapid prototyping can lead to revolutionary advancements in product design and patient care.

Case Study 2: Transforming Automotive Design at FastCar Inc.

FastCar Inc., a pioneering name in the automotive sector, aimed to drastically enhance their vehicle design process. By adopting rapid prototyping, they were able to shift from traditional clay modeling to digital modeling and 3D printing.

FastCar Inc. utilized virtual reality and augmented reality to create immersive prototypes that allowed designers, engineers, and customers to interact with car models before physical production commenced. This deepened understanding highlighted design flaws and areas for improvement early on, ultimately cutting down development cycles by over 30%. This case highlights how rapid prototyping can adapt businesses to new market demands quicker, staying ahead in competitive industries.

The Impact of Rapid Prototyping

Rapid prototyping democratizes the innovation process, creating a more inclusive environment where cross-functional teams can collaborate effectively. By visualizing ideas early and often, teams can align more easily on goals and priorities. Furthermore, the ability to quickly test and iterate reduces risk and fosters a culture of learning and adaptation.

Whether it’s revolutionizing healthcare or transforming automotive design, rapid prototyping proves to be a powerful tool in the innovator’s toolkit. As industries continue to evolve and customer demands change, the capacity to bring ideas to life swiftly will mark the difference between leaders and followers in the market.

Embracing rapid prototyping is not just about keeping up with competition—it’s about setting a new pace for innovation. This forward momentum catalyzes creativity, encourages experimentation, and ultimately leads to products that not only meet but exceed user expectations.

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

Image credit: misterinnovation.com

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From Idea to Execution: Best Practices for Innovating Successfully

From Idea to Execution: Best Practices for Innovating SuccessfullyGUEST POST from Art Inteligencia

Innovation is at the heart of progress. It drives companies to new heights and fuels economic growth. However, transforming an idea into a successful reality requires careful planning, strategic thinking, and flawless execution. In this article, we will explore the best practices for innovating successfully by analyzing two inspiring case studies.

Case Study 1: Apple Inc.

Apple Inc. is renowned for its innovative products that have revolutionized entire industries. One of their most memorable successes was the launch of the iPhone in 2007. What made this innovation exceptional was not just the creation of a new smartphone but the integration of multiple functions in a single device. Apple not only developed a powerful touchscreen phone but also designed an intuitive operating system and an App Store ecosystem that allowed developers to create versatile applications.

The key lesson from Apple’s success is the importance of thinking holistically. Innovation should not be limited to individual features or products. Instead, organizations should strive to create an ecosystem that provides a seamless experience to customers. By considering the entire user journey and designing complementary products or services, companies can differentiate themselves and capture market share effectively.

Case Study 2: Airbnb

Another remarkable success story is Airbnb. Founded in 2008, this online marketplace disrupted the traditional accommodation sector by connecting travelers with homeowners renting out their properties. The company’s success can be attributed to its ability to understand and adapt to changing customer needs. Airbnb recognized that travelers were seeking unique and personalized experiences rather than conventional hotel stays.

To ensure successful execution, Airbnb built a platform that focused on trust and community. By establishing rigorous verification processes, providing accurate reviews, and fostering a sense of belonging among hosts and guests, the company created a strong foundation for growth. Moreover, Airbnb’s strategy of gradually expanding its offerings beyond accommodations, such as “Experiences,” further strengthened its position in the market.

The key lesson from Airbnb’s success lies in continuous adaptation and responding to evolving customer demands. Successful innovation requires companies to be agile and open to learning from feedback. By staying connected to their customers and actively seeking their input, organizations can develop offerings that cater to their changing needs.

Best Practices for Innovating Successfully

1. Foster a culture of innovation: Encourage employees to think creatively and provide them with the resources and support to explore new ideas. Innovation should be ingrained in the company’s DNA.

2. Identify customer pain points: Truly innovative solutions address real-world problems. Invest time in understanding your customers’ pain points and use them as a basis for your innovation efforts.

3. Focus on the user experience: Innovation should enhance the overall experience for customers. Design products and services that are intuitive, user-friendly, and seamlessly integrated.

4. Build cross-functional teams: Successful innovation requires collaboration across different departments and disciplines. Encourage diverse perspectives by assembling teams with varied skill sets and backgrounds.

5. Test and iterate: Embrace a mindset of continuous improvement. Test your innovations, collect feedback, and iterate based on the insights gained. Rapid prototyping and minimum viable products can help gauge market response before full-scale implementation.

6. Create a supportive ecosystem: Just as Apple and Airbnb understood the importance of building an ecosystem around their innovations, consider how your innovation fits into the broader customer experience. Develop partnerships and collaborations that reinforce the value proposition of your offering.

Conclusion

Innovation is an iterative process that requires a thorough understanding of customer needs, a holistic approach, and continuous adaptation. By drawing inspiration from successful case studies like Apple and Airbnb, organizations can enhance their innovation capabilities and bring groundbreaking ideas to life. Embrace the best practices outlined here, and unleash the potential of your organization to innovate successfully.

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

Image credit: Misterinnovation.com

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Why More Ideas Won’t Solve the Innovation Problem

Why More Ideas Won't Solve the Innovation Problem

GUEST POST from Chateau G Pato


I. Introduction: The Idea Factory Fallacy

Organizations facing growth stalls, market shifts, or emerging competitive threats almost always default to the same panic button: “We need more ideas.”

This widespread obsession with innovation theater—hackathons, massive suggestion portals, and endless brainstorming sessions—creates a dangerous misconception: that innovation is primarily a top-of-funnel volume problem. We treat ideation as an industrial pipeline where pouring in more raw material automatically yields better outcomes.

The truth is that more ideas do not solve the innovation problem. In fact, they often exacerbate it by generating noise, draining organizational resources, and paralyzing decision-making. True innovation is rarely starved of ideas—it is starved of focus, human-centered clarity, and the execution architecture required to turn insight into value.

II. The Pathology of Idea Overload

Flooding an organization with thousands of raw concepts does not accelerate progress; it creates a structural bottleneck that slows everything down. When the volume of ideas outpaces an organization’s capacity to process them, several critical points of failure emerge across the system.

The Funnel Choke

When ideation portals and open calls generate an avalanche of submissions, evaluation mechanisms break down. Review committees become overwhelmed, triage criteria blur, and decision-making grinds to a halt. In the chaotic noise of hundreds of unvetted suggestions, high-potential concepts are frequently overlooked or discarded, while mediocre, easy-to-understand ideas slip through simply because they require less effort to evaluate.

Innovation Fatigue and Disengagement

Collecting ideas without a clear, responsive path forward carries a high human cost. When employees enthusiastically submit concepts only to watch them disappear into an opaque corporate “black hole,” cynicism rapidly sets in. Rather than fostering a dynamic culture of participation, unmanaged volume breeds innovation fatigue, eroding trust and discouraging employees from contributing their best insights in the future.

The Sunk Cost of Filtering

Categorizing, reviewing, and politely rejecting thousands of unviable ideas consumes an enormous amount of organizational energy and capital. This effort represents a significant opportunity cost: the precious time, bandwidth, and budget spent sifting through an ocean of random suggestions are resources taken directly away from deep customer research, rapid prototyping, and meaningful field experimentation.

III. The Real Bottlenecks in the Innovation Ecosystem

If an abundance of ideas isn’t driving results, where is the friction actually occurring? When we examine the end-to-end innovation ecosystem through a human-centered lens, we find that the primary constraints exist far downstream from ideation.

Problem Definition vs. Idea Generation

Organizations are extraordinarily proficient at generating clever solutions to poorly defined problems. Innovation initiatives frequently fail not because teams lack answers, but because they are enthusiastically answering the wrong questions. Without rigorous framing and strategic clarity, a flood of ideas simply produces faster routes to destinations no one wants to go.

The Empathy Deficit

Ideas generated in a vacuum—isolated from genuine human needs, emotional triggers, and real-world behavioral friction—are little more than structured educated guesses. When teams focus on volume over empathy, they produce incremental feature tweaks or superficial gimmicks rather than transformative value. True breakthrough moments stem from deep customer intimacy, not crowded whiteboards.

Cultural Antibodies and Organizational Resistance

Leaders often seek technological or operational quick fixes—such as deploying new brainstorming software or launching internal pitch competitions—while leaving the underlying corporate immune system untouched. Deep-seated fear of failure, rigid hierarchical silos, and short-term efficiency metrics act as cultural antibodies that systematically eliminate novel concepts long before they reach market testing.

IV. Shifting from Quantity to Clarity: A Human-Centered Approach

To break free from the cycle of superficial brainstorming, organizations must pivot from collecting random ideas to cultivating strategic clarity. Shifting toward a human-centered innovation model requires reframing how we invite contributions, design the participant experience, and support concepts after they emerge.

Constraint as a Catalyst

Unconstrained ideation often leads to vague, impractical concepts that rarely align with strategic goals. True creativity requires boundaries. By replacing open-ended calls for “any good idea” with tightly framed challenge statements grounded in specific organizational constraints and human needs, teams can channel their problem-solving energy into high-value, actionable outcomes.

Designing the Experience of Innovation

Innovation is not a solitary event; it is an end-to-end experience for both the people generating solutions and the stakeholders evaluating them. Rather than treating innovation as a transactional suggestion box, organizations must design collaborative, relational experiences that respect people’s time, provide immediate feedback, and nurture psychological safety throughout the creative process.

Building an Execution Architecture

An idea represents only a small fraction of the innovation lifecycle. Without a robust execution architecture—encompassing rapid prototyping, structured experimentation, clear stage-gates, and resource allocation—even the most brilliant concept will stagnate. Sustainable success depends on building the systemic infrastructure necessary to test, learn, iterate, and scale ideas with speed and discipline.

V. Actionable Framework: What to Do Instead of Running Another Brainstorm

Moving beyond the idea factory mentality requires a deliberate pivot toward strategic discipline and human-centered design. Rather than launching another open ideation campaign, organizational leaders should implement a structured approach built around focus, rigor, and rapid learning.

1. Fall in Love with the Problem

Dedicate the majority of your energy to deeply understanding and framing the problem before attempting to solve it. Spend time observing user behavior, conducting empathetic field research, and mapping unarticulated pain points. A thoroughly understood, well-framed challenge statement yields far higher-quality solutions than hours of unfocused brainstorming.

2. Curate, Don’t Accumulate

Replace massive, open-ended suggestion drives with targeted, mission-driven innovation challenges. Align every call for solutions directly with strategic business priorities, explicit operational constraints, and pressing customer friction points. Quality and relevance must take precedence over raw volume.

3. Establish Clear Decision Gates

Build transparent, lightweight validation loops that move concepts quickly from theory to testing. Define clear criteria for progress at every stage so that promising initiatives gain rapid momentum, while unviable concepts are retired quickly and constructively, preserving organizational energy for high-potential ideas.

4. Empower Change Champions

Tools and portals do not drive transformation—people do. Cultivate skilled change leaders across the organization who can navigate complex internal dynamics, build cross-functional support, and guide promising concepts past corporate resistance and toward successful execution.

VI. Conclusion: Stop Collecting Dots, Start Connecting Them

In modern innovation management, idea volume is merely a vanity metric. Generating hundreds of raw concepts creates an illusion of progress, but without deep human empathy, strategic focus, and a resilient path to execution, it simply generates organizational friction and fatigue.

The future does not belong to the organization that can collect the most ideas. It belongs to the one that can cultivate deep insight into human needs, frame the right problems with precision, and build the organizational muscle needed to turn meaningful insights into lasting value.

Frequently Asked Questions

Why is generating more ideas harmful to the innovation process?

Generating an overwhelming volume of unvetted ideas creates an organizational bottleneck, known as “funnel choke.” It drains resources, demoralizes employees whose suggestions disappear into black holes, and makes it harder to identify and execute truly high-potential concepts.

What should organizations focus on instead of idea generation?

Organizations should prioritize deep problem definition, human-centered empathy, and a strong execution architecture. Framing clear, constrained challenge statements and understanding real user friction points yields far better outcomes than unconstrained brainstorming.

How can teams shift from idea quantity to strategic clarity?

Teams can shift to strategic clarity by launching targeted, mission-driven innovation challenges tied directly to strategic goals, establishing rapid decision gates to validate concepts early, and empowering change champions to navigate internal corporate resistance.


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

Image credit: 1 of 1,550+ FREE quotes for your presentations at http://misterinnovation.com

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The Cognitive Value Chain

Structuring Teams to Take Ideas from Conception to Scale

The Cognitive Value Chain

GUEST POST from Art Inteligencia


Executive Summary: The Cognitive Value Chain

Most organizations do not suffer from a shortage of great ideas—they suffer from a systemic inability to move those ideas from initial spark to sustained, enterprise-scale impact.

Traditional innovation approaches treat ideation and execution as binary states. The Cognitive Value Chain redefines innovation as a continuous, human-centered assembly line of distinct cognitive modes. By aligning specific mindsets, team structures, and experience design principles to distinct phases of value creation, leaders can bridge the execution gap and turn friction into momentum.

Core Thesis

Scaling innovation is fundamentally a human-centered change challenge. Success requires intentionally orchestrating four cognitive transitions: shifting from Explorers identifying human needs, to Architects prototyping value, to Integrators building organizational readiness, and finally to Optimizers realizing value at scale.

Key Strategic Takeaways

  • Eliminate the Handoff Friction: Great ideas die in the seams between teams. Structuring early integration loops prevents the “Not Invented Here” syndrome before scaling begins.
  • Align Mindset to Stage: Assigning execution-oriented mindsets too early stifles discovery, while keeping exploratory mindsets too late prevents operationalization.
  • Human-Centered Integration: Change management and experience design cannot be downstream afterthoughts—they must be woven into the fabric of product and service architecture from Day 1.

Phase 1: Context & Discovery (Insight Generation)

Every scalable innovation begins not with a solution, but with deep curiosity and a relentless commitment to understanding human needs and market shifts.

Phase 1 lays the foundation of the Cognitive Value Chain by framing the right problems before jumping to answers. Instead of brainstorming in a vacuum, teams engage in Human-Centered Sensing—evaluating the broader landscape through the dual lenses of customer and employee experience design to uncover latent friction, unarticulated desires, and strategic opportunities.

Phase Blueprint

  • Primary Objective: Uncover high-value insights and establish strategic problem-solution fit.
  • Cognitive Mode: Divergent, inquisitive, empathetic, and challenge-driven.
  • Key Deliverable: Formulated problem statements and customer experience gap analyses.

Team Dynamic: Explorers & Empaths

To succeed in this initial phase, team structures must prioritize cognitive diversity that thrives on ambiguity. The ideal team composition combines:

  • Explorers: Individuals who scan horizon trends, challenge long-held organizational assumptions, and connect disparate dots across industries.
  • Empaths: Experience design practitioners who listen deeply to users, mapping emotional journeys and uncovering hidden behavioral pain points.

Tooling & Methodology

Insight generation relies on structured inquiry rather than ad-hoc ideation. Teams leverage problem-framing canvases, contextual inquiry, and experience mapping to align organizational strategy directly with authentic market demands. By establishing a rigorous foundation here, organizations ensure that downstream investments are built on validated human value rather than internal guesswork.

Phase 2: Synthesis & Prototyping (Value Design)

Raw insights hold little enterprise value until they are translated into tangible, testable architectures designed for both human desirability and operational viability.

Phase 2 pivots the Cognitive Value Chain from open-ended exploration to purposeful convergence. Here, teams synthesize raw customer and employee insights into initial service models, experience blueprints, and business concepts. Through continuous feedback loops, early designs are de-risked long before capital-intensive deployment begins.

Phase Blueprint

  • Primary Objective: Convert raw insights into validated, low-fidelity prototypes and scalable experience architectures.
  • Cognitive Mode: Convergent, constructive, analytical, and iterative.
  • Key Deliverable: Tested prototypes, experience blueprints, and initial business model hypotheses.

Team Dynamic: Architects & Designers

This phase requires a transition in cognitive posture—moving from open inquiry to systemic construction. The team structure centers on:

  • Architects: Strategic thinkers who evaluate technical feasibility, value proposition sustainability, and broader ecosystem integration.
  • Designers: Experience specialists who craft user interfaces, touchpoints, and interaction flows to ensure intuitive adoption.

Tooling & Methodology

Rapid experimentation is the cornerstone of value design. Teams utilize experience prototyping, visual charters, and experiment canvases to stress-test assumptions. By measuring real human reactions to early concepts, organizations identify potential friction points and refine the solution while the cost of modification remains low.

Phase 3: Change Readiness & Operationalization (System Alignment)

The greatest threat to a brilliant innovation is not market rejection—it is internal organizational inertia and systemic resistance to change.

Phase 3 bridges the critical chasm between a validated prototype and an enterprise-wide rollout. Instead of treating change management as a late-stage announcement, the Cognitive Value Chain integrates human-centered change design directly into operational planning. This ensures that organizational culture, incentives, governance, and capabilities are aligned long before scaling begins.

Phase Blueprint

  • Primary Objective: Overcome organizational friction, build institutional capability, and prepare systems for enterprise adoption.
  • Cognitive Mode: Relational, integrative, strategic, and capability-focused.
  • Key Deliverable: Change architecture plans, stakeholder engagement roadmaps, and operational transition frameworks.

Team Dynamic: Change Champions & Integrators

Navigating the organizational handoff demands mindsets skilled in empathy, negotiation, and systems thinking. Primary roles include:

  • Change Champions: Influencers and leaders across departments who build cross-functional coalition, communicate purpose, and drive cultural buy-in.
  • Integrators: Operations and systems experts who reconfigure workflows, update governance structures, and align IT/process architectures with the new experience.

Tooling & Methodology

Success in this phase relies on structured change planning tools, organizational agility frameworks, and stakeholder impact mapping. By proactively diagnosing risk and addressing the human element of change early, teams dismantle the “Not Invented Here” bias and establish frictionless pathways for enterprise scaling.

Phase 4: Scaling & Continuous Evolution (Value Realization)

Innovation reaches its full potential only when scalable delivery is paired with an ongoing commitment to continuous experience refinement.

Phase 4 represents the destination of the Cognitive Value Chain—embedding the innovation seamlessly into the core operating engine of the enterprise. True value realization requires industrializing delivery without losing the human-centered spirit that sparked the original vision. By establishing tight feedback loops, operational teams maintain delivery excellence while constantly feeding fresh signals back into Phase 1 for perpetual learning.

Phase Blueprint

  • Primary Objective: Achieve sustained enterprise scale, measure real-world impact, and institutionalize continuous feedback loops.
  • Cognitive Mode: Disciplined, analytical, systematic, and optimization-oriented.
  • Key Deliverable: Scaled operating models, experience level metrics, and ongoing continuous improvement cycles.

Team Dynamic: Operators & Optimizers

Scaling requires transition to execution-minded cognitive styles focused on consistency, efficiency, and governance. Key capabilities include:

  • Operators: Process and delivery leaders who manage day-to-day execution, maintain quality standards, and ensure operational resilience across all channels.
  • Optimizers: Data and analytics specialists who track adoption metrics, measure experience level outcomes, and fine-tune system performance.

Tooling & Methodology

Long-term success depends on robust measurement frameworks, experience management oversight, and operational governance dashboards. By continuously monitoring key performance and experience indicators, organizations ensure the value proposition remains vibrant and adaptable to evolving market forces over time.

Conclusion & Strategic Imperative

Innovation is not a solitary lightning strike—it is an orchestrated, human-centered journey from early insight to enterprise realization.

By mastering The Cognitive Value Chain, organizations move past the trap of random ideation and build a resilient capability for sustained value creation. The true bottleneck in modern business is rarely a lack of vision; it is the structural friction between how teams think, collaborate, and adapt across transitions.

The Leadership Call to Action

Leaders must step back from simply managing project outcomes and focus instead on designing the cognitive environment. Audit your organization to identify where your value chain leaks potential: Are you expecting Explorers to drive operational scale, or asking Optimizers to discover breakthrough insights?

Aligning the right cognitive modes, human-centered design practices, and change management principles to each stage of the journey ensures your best ideas don’t just survive the organization—they transform it.

Frequently Asked Questions

What is the primary difference between traditional innovation models and The Cognitive Value Chain?

Traditional models treat ideation and execution as binary steps, often leading to severe handoff friction. The Cognitive Value Chain redefines innovation as a continuous, four-stage human-centered assembly line, systematically aligning specific cognitive mindsets—Explorers, Architects, Integrators, and Optimizers—to each phase of value creation.

Why do great concepts usually fail during Phase 3 (Change Readiness & Operationalization)?

Most concepts stall during operationalization due to internal organizational inertia and the “Not Invented Here” syndrome. Phase 3 addresses this by integrating human-centered change design, organizational agility, and stakeholder alignment into the process before enterprise scaling begins, rather than treating change management as a late-stage afterthought.

How can leaders apply The Cognitive Value Chain to existing teams?

Leaders should conduct a cognitive audit of their innovation process to identify operational bottlenecks. Rather than expecting one team to manage the entire lifecycle, leaders must structure cross-functional transitions that match individuals’ natural cognitive strengths (discovery, architectural design, change integration, or operational optimization) to the appropriate stage of the innovation journey.


EDITOR’S NOTE: Braden Kelley’s Problem Finding Canvas can be a super useful starting point for doing design thinking or human-centered design.

“The Problem Finding Canvas should help you investigate a handful of areas to explore, choose the one most important to you, extract all of the potential challenges and opportunities and choose one to prioritize.”

Image credit: Gemini

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Get Social with Your Innovation

Get Social with Your InnovationIf your organization is struggling to sustain its innovation efforts, then I hope you will do the following things.

  • Find the purpose and passion that everyone can rally around.
  • Create the flexibility necessary to deal with the constant change that a focus on innovation requires for both customers and the organization.
  • Make innovation the social activity it truly must be for you to become successful.

If your organization has lost the courage to move innovation to its center and has gotten stuck in a project – focused, reactive innovation approach, then now is your chance to regain the higher ground and to refocus, not on having an innovation success but on building an innovation capability. Are you up to the challenge?

There is a great article “ Passion versus Obsession ” by John Hagel that explores the differences between passion and obsession. This is an important distinction to understand in order to make sure you are hiring people to power your innovation efforts who are passionate and not obsessive. Here are a few key quotes from the article:

“The first significant difference between passion and obsession is the role free will plays in each disposition: passionate people fight their way willingly to the edge to find places where they can pursue their passions more freely, while obsessive people (at best) passively drift there or (at worst) are exiled there.”

“It’s not an accident that we speak of an “object of obsession,” but the “subject of passion.” That’s because obsession tends towards highly specific focal points or goals, whereas passion is oriented toward networked, diversified spaces.”

More quotes from the John Hagel article:

“The subjects of passion invite and even demand connections with others who share the passion.”

“Because passionate people are driven to create as a way to grow and achieve their potential, they are constantly seeking out others who share their passion in a quest for collaboration, friction and inspiration . . . . The key difference between passion and obsession is fundamentally social: passion helps build relationships and obsession inhibits them.”

“It has been a long journey and it is far from over, but it has taught me that obsession confines while passion liberates.”

These quotes from John Hagel’s article are important because they reinforce the notion that innovation is a social activity. While many people give Thomas Edison, Alexander Graham Bell, and the modern-day equivalent, Dean Kamen, credit for being lone inventors, the fact is that the lone inventor myth is just that — a myth, one which caused me to create The Nine Innovation Roles.

The fact is that all of these gentlemen had labs full of people who shared their passion for creative pursuits. Innovation requires collaboration, either publicly or privately, and is realized as an outcome of three social activities.

1. Social Inputs

From the very beginning when an organization is seeking to identify key insights to base an innovation strategy or project on, organizations often use ethnographic research, focus groups, or other very social methods to get at the insights. Great innovators also make connections to other industries and other disciplines to help create the great in sights that inspire great solutions.

2. Social Evolution

We usually have innovation teams in organizations, not sole inventors, and so the activity of transforming the seeds of useful invention into a solution valued above every existing alternative is very social. It takes a village of passionate villagers to transform an idea into an innovation in the marketplace. Great innovators make connections inside the organization to the people who can ask the right questions, uncover the most important weaknesses, help solve the most difficult challenges, and help break down internal barriers within the organization — all in support of creating a better solution.

3. Social Execution

The same customer group that you may have spent time with, seeking to understand, now requires education to show them that they really need the solution that all of their actions and behaviors indicated they needed at the beginning of the process. This social execution includes social outputs like trials, beta programs, trade show booths, and more. Great innovators have the patience to allow a new market space to mature, and they know how to grow the demand while also identifying the key shortcomings with customers who are holding the solution back from mass acceptance.

Conclusion

When it comes to insights, these three activities are not completely discrete. Insights do not expose themselves only in the social inputs phase, but can also expose themselves in other phases — if you’re paying attention.

Flickr famously started out as a company producing a video game in the social inputs phase, but was astute enough during the social execution phase to recognize that the most used feature was one that allowed people to share photos. Recognizing that there was an unmet market need amongst customers for easy sharing of photos, Flickr reoriented its market solution from video game to photo sharing site and reaped millions of dollars in the process when they ultimately sold their site to Yahoo!.

Ultimately, action is more important than intent, and so as an innovator you must always be listening and watching to see what people do and not just what they say. Build your solution on the wrong insight and nobody will be beating a path to your door.

NOTE: This article is an adaptation of some of the great content in my five-star book Stoking Your Innovation Bonfire (available in many local libraries and fine booksellers everywhere).

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Planning to Spread

We’ve all seen the viral videos that seemingly come out of nowhere to garner millions of views on YouTube, videos like this one where five people play one guitar singing Gotye’s “Somebody That I Used to Know”, which as of this date has garnered more than 163 million video views:

And if you add up all of the other postings of this same video, the total number of video views goes much, much higher.

Now, surely Gotye’s version of the song couldn’t have possibly garnered more views than this viral sensation that Walk Off the Earth’s cover created, could it?

Um, actually it did. To date Gotye’s official video has captured nearly 600 million video views, or nearly FIVE TIMES as many video views. So, it hasn’t turned out all bad for Gotye.

Now you might ask yourself, how could the huge success of the Walk Off the Earth viral campaign be trumped by traditional marketing if viral marketing is supposed to be the silver bullet?

Well, the truth is that whether you pursue traditional marketing and advertising or supposedly “viral” marketing activities, the goals are the same:

  1. Awareness
  2. Interest
  3. Desire
  4. Action

And it is within that first bullet point, that you find the viral component that any marketing activity or any evangelism activity (for innovation, for change, etc.) should always contain – spreadability.

Now, WordPress doesn’t seem to think that spreadability is a word, but let’s assume for a moment that it is and focus on the fact that most of the time, one of your goals in business (and your personal life) is spreadability. Ultimately, in many cases, success is determined by whether or not you can get your idea to spread.

This is true whether we are talking about an IT project, a Six Sigma continuous improvement effort, a change initiative, a Lean event, a marketing campaign, or a project commercializing an invention into a potential innovation.

So, can anyone guarantee that an idea or marketing campaign will spread?

The short answer is no.

Sorry, I wish I had better news for you, but the fact is that nobody can guarantee that your idea or your marketing campaign will go viral. Why?

You’re dealing with humans living in a complicated world. We’re not all built the same and the same person can have different reactions to the same stimulus (driven by mood and context among other things). This can result in a perfectly spreadable idea or message being stopped dead in its tracks, depriving you of all of the potential downstream sharing that you might have been hoping for or counting on.

Sorry, you can’t guarantee spreadability, despite what opportunistic marketing consultants claiming to know the magic formula might tell you.

Spreading ChangeBut, an idea can be built to spread.

And I’d like to share with you a simple framework, for free, that you can download and spread far and wide.

Click here to download the “Planning to Spread” starter worksheet as a PDF.

It’s based on the same priniciples as mind mapping and it will help you start either with a particular node in mind (someone you’d like to reach and influence) and work backwards, identifying both how to evolve your idea to best influence that particular node, and how you might be able to reach them (at the same time). Or you can work from the idea outwards. Focusing primarily on the WHO and the WHY as you move outward.

The key questions to consider as you are “Planning to Spread” your idea are the following:

  1. What is your idea or message? (Does it resonate with my target audience?)
  2. Who are you trying to reach?
  3. How will you reach them?
    • When will they be most receptive to the message or idea?
    • Where will they be most receptive to the message or idea?
  4. Why will they engage? (What value will they get?)
  5. Why will they share? (What value will they derive?)
  6. How will they share?

Working your way thoughtfully through these questions will increase the chances that your idea or message will spread, but they won’t guarantee it. Going through the process however will help you refine your idea or message, help you think through the mechanics of how you might encourage and increase engagement, and may even help you uncover flaws in your idea or message that you missed (and give you a chance to fix them).

Planning to Spread WorksheetHappy spreading!
(and please let me know in the comments below any things I might have missed)

So what am I trying to spread?

Well, in the run up to my second book (this time focusing on the best practices and next practices of organizational change), soon I will be releasing a new collaborative, visual change planning toolkit to help organizations work smarter by planning their change initiatives (and projects) in a less overwhelming, more human way that will help get everyone literally on the same page.

This is the idea that I will be spreading and there are many ways that you can benefit.

One way is by becoming a case study volunteer. I’m looking to select a handful of companies to teach how to use the toolkit for free and feature their experience in my next book on the best practices and next practices of organizational change. If you would like to get a jump on the competition by increasing your speed of change (and your ability to work smarter), register your interest here.

But there are several other ways you can benefit, and all of them can be found here (including upcoming chances for consultants to train on the methodology and boost their revenue and success as they work with their clients around the world to deliver positive change). I’ll be focusing on teaching and tools, not consulting.

What message or idea are you trying to spread?


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