Category Archives: Creativity

Designing Work for Deep, Collaborative Focus

Flow State for Teams

Designing Work for Deep, Collaborative Focus

GUEST POST from Chateau G Pato
LAST UPDATED: January 7, 2026 at 12:26PM

In our current world, the noise of the digital world has reached a deafening crescendo. We have more tools than ever to “connect,” yet we find ourselves more fragmented than at any point in history. As an innovation speaker and practitioner of Human-Centered Innovation™, I consistently remind leaders that innovation is change with impact. However, impact is impossible if your team’s most valuable resource – their collective attention – is being harvested by the Corporate Antibody of constant interruption.

We have long understood individual “Flow” — that psychological state of optimal experience where time disappears and creativity peaks. But in 2026, the real competitive advantage lies in Team Flow. This is the ability of a group to synchronize their cognitive efforts, moving as a single, high-performance organism toward a shared outcome. To achieve this, we must stop leaving focus to chance and start designing for it as a core architectural requirement of the organization.

“Collective flow is the highest form of human-centered efficiency. When a team synchronizes their focus, they don’t just work faster; they inhabit the future together, turning the ‘useful seeds of invention’ into reality before the status quo even realizes the soil has been disturbed.” — Braden Kelley

The Architecture of Deep Collaboration

Many organizations fall into the Efficiency Trap, assuming that because information flows quickly through instant messaging and real-time dashboards, innovation must be happening. In reality, this “hyper-connectivity” often acts as a barrier to deep work. Team Flow requires a deliberate balancing act between high-bandwidth collaboration and uninterrupted cognitive solitude.

Now, the most successful firms are moving away from “Always-On” cultures toward “Rhythmic Focus” models. This involves aligning team schedules so that everyone enters deep work states at the same time, followed by structured, high-energy “bursts” of collaboration. By synchronizing the Cognitive (Thinking), Affective (Feeling), and Conative (Doing) domains like we do in Outcome-Driven Change, we reduce the friction of “context switching” that kills momentum.

Case Study 1: The “Silent Co-Creation” at Atlassian 2026

The Challenge: Despite being a leader in remote collaboration, Atlassian found that their cross-functional teams were suffering from “Meeting Fatigue,” where 70% of the day was spent discussing work rather than doing it.

The Human-Centered Shift: They implemented “Flow Blocks” — four-hour windows twice a week where all notifications are silenced, and teams engage in what they call “Silent Co-Creation.” During these blocks, team members work on a shared digital canvas without verbal interruption, using agentic AI to summarize changes in real-time for later review.

The Result: Project velocity increased by 45%. More importantly, employee engagement scores surged as engineers and designers felt they were finally being given the “permission to focus.” They successfully bypassed the Corporate Antibody of the “quick check-in” and fostered a culture of deep, impactful change.

Case Study 2: Designing Physical Focus at The LEGO Group

The Challenge: As LEGO expanded its digital services division, the physical open-office environment became a source of friction, preventing the deep concentration required for complex algorithmic and design work.

The Human-Centered Shift: Following the principles of Outcome-Driven Change, they redesigned their innovation hubs into “Library Zones” and “Marketplaces.” The Library Zones are zero-interruption areas designed for Group Flow, utilizing localized noise-canceling technology and visual signals to indicate when a sub-team is in a “Flow State.”

The Result: By physicalizing the boundaries of focus, LEGO reduced unintended interruptions by 60%. This environmental nudge helped teams move from transactional tasks to transformational innovation, ensuring that their useful seeds of invention had the quiet space necessary to take root.

Leading Companies and Startups to Watch in 2026

The infrastructure for Team Flow is being built by a new wave of visionary companies. Flow Club and Focusmate have evolved from individual tools into enterprise-grade “Deep Work Orchestrators,” using AI to match team members’ biological rhythms for peak focus. Humu, now more integrated than ever, uses behavioral science to “nudge” managers to protect their team’s flow windows. Keep a close eye on Reclaim.ai and Clockwise, which are shifting from simple calendar management to “Cognitive Load Balancing,” ensuring that no team is scheduled into a state of burnout. These organizations recognize that in the 2026 economy, attention is the ultimate currency.

Conclusion: Protecting the Human Heart of Focus

Ultimately, designing for Team Flow is an act of empathy. It is an acknowledgment that your people are not processors to be maximized, but creators to be protected. When we move beyond the Efficiency Trap and embrace Human-Centered Innovation™, we create environments where brilliance is not the exception, but the baseline.

We can and should be dedicated to helping our teams build a future where focus is the foundation of every breakthrough. We don’t just change for the sake of change; we change to create a world that works for humans.

Frequently Asked Questions

1. How do you prevent Team Flow from becoming “groupthink”?

Team Flow is about the process of concentration, not the homogenization of ideas. By ensuring high levels of psychological safety and diverse perspectives before entering the flow state, the period of deep focus actually amplifies the unique contributions of each member rather than suppressing them.

2. Can Team Flow work in a fully remote or hybrid environment?

Yes, but it requires digital discipline. Remote teams must use “digital boundaries” — dedicated focus channels, synchronized Do Not Disturb modes, and “Office Hours” for interruptions. The technology must serve the focus, not the other way around.

3. What is the biggest barrier to achieving Group Flow?

The Corporate Antibody. This is the organizational reflex to prioritize immediate visibility and “busy-ness” over long-term impact. Leaders must be willing to sacrifice the illusion of constant accessibility to gain the reality of profound innovation.

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

Image credits: Google Gemini

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The Neuroscience of Unlearning

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Making Room for New Operating Systems

Why unlearning is the hidden challenge of transformation and how leaders can design environments that enable cognitive renewal.

The Neuroscience of Unlearning

GUEST POST from Chateau G Pato
LAST UPDATED: January 1, 2026 at 12:54PM

In our current world, we are witnessing a phenomenon that most traditional business models were never designed to handle: the absolute necessity of erasure. For decades, the mantra of the corporate world was “continuous learning.” We built massive infrastructures dedicated to upskilling, reskilling, and the acquisition of new knowledge. But in 2026, as agentic AI and autonomous systems begin to handle the transactional “grunt work” of innovation, we are discovering that the true bottleneck to progress isn’t a lack of new information. It is the overwhelming presence of old information.

To move forward, we must understand the Neuroscience of Unlearning. We aren’t just updating software; we are attempting to overwrite deeply encoded biological “operating systems” that have been reinforced by years of success, survival, and habit. As a globally recognized innovation speaker, I frequently remind my audiences that innovation is change with impact, and you cannot have impact if your mental real estate is fully occupied by the ghosts of yesterday’s best practices.

“The hardest part of innovation is not the learning of new things, but the unlearning of old ones. We are trying to run a 2026 AI-driven OS on a 1995 hierarchical mindset, and the biological friction is what we misinterpret as resistance to change.” — Braden Kelley

The Biology of Cognitive Inertia

Our brains are masterpieces of efficiency. Through a process called Long-Term Potentiation (LTP), the neural pathways we use most frequently become “paved” with myelin, a fatty substance that speeds up electrical signals. This is why a seasoned executive can make a complex decision in seconds—their brain has built a high-speed expressway for that specific pattern of thought. However, this efficiency is also a cage. When the environment changes—as it has so drastically with the rise of decentralized work and generative collaboration—those expressways lead to the wrong destination.

Unlearning requires Long-Term Depression (LTD), the biological process of weakening synaptic connections. Unlike learning, which feels additive and exciting, unlearning feels like a loss. It is metabolically expensive and emotionally taxing. It requires us to activate our metacognition—our ability to think about our thinking—and consciously inhibit the dominant neural networks that tell us, “this is how we’ve always done it.” This is where the Corporate Antibody lives; it isn’t just a cultural problem, it is a neurological one.

Case Study 1: The Kodak “Comfort Trap”

The Challenge: Despite inventing the first digital camera in 1975, Kodak famously failed to capitalize on the technology, eventually filing for bankruptcy in 2012. Many attribute this to a lack of technical foresight, but the root cause was a failure of unlearning.

The Cognitive Friction: Kodak’s “Operating System” was built on the chemical process of film and the high-margin razor-and-blade model of silver-halide paper. Their leaders were neurologically “wired” to see the world through the lens of physical consumables. Digital photography wasn’t just a new tool; it required unlearning the very definition of their business. They couldn’t “depress” the neural pathways associated with film fast enough to make room for the digital ecosystem.

The Lesson: Knowledge is a power, but it can also create blind spots. Kodak’s experts were so good at the old game that they were biologically incapable of playing a new one.

Upgrading the Human OS

In 2026, the shift is even more profound. We are unlearning the concept of “work as a location” and “management as oversight.” Leading organizations are now focusing on Human-AI Teaming, where the human role shifts from originator to curator. This requires a radical unlearning of individual ego. To succeed today, a leader must unlearn the need to be the “smartest person in the room” and instead become the most “connective person in the network.”

Case Study 2: Microsoft’s Growth Mindset Transformation

The Challenge: Prior to Satya Nadella’s tenure, Microsoft was defined by a “know-it-all” culture. Internal competition was fierce, and silos were reinforced by a psychological contract that rewarded individual brilliance over collective innovation.

The Unlearning Strategy: Nadella didn’t just introduce new products; he mandated a shift to a “learn-it-all” (and “unlearn-it-all”) philosophy. This was a Human-Centered Change masterclass. By prioritizing psychological safety, he allowed employees to admit what they didn’t know. This lowered the “threat response” in the brain, making it neurologically possible for employees to dismantle old competitive habits and embrace a cloud-first, collaborative mindset.

The Result: By unlearning the “Windows-only” worldview, Microsoft reclaimed its position as a market leader, proving that cultural transformation is, at its heart, a massive exercise in neural rewiring.

Leading Companies and Startups to Watch

As we navigate 2026, watch companies like Anthropic, whose “Constitutional AI” approach is forcing us to unlearn traditional prompt engineering in favor of ethical alignment. BetterUp is another key player, using behavioral science and coaching to help employees “unlearn” burnout-inducing habits. In the productivity space, Atlassian is leading the way by unlearning the traditional office-centric model and replacing it with “Intentional Togetherness,” a framework that uses data to determine when physical presence actually drives value. Also, keep an eye on startups like Tessl and Vapi, which are redefining the “OS of work” by automating the transactional, forcing us to unlearn our reliance on manual task management and focus instead on high-value human creativity.

“Unlearning feels like failure to the brain, even when it is the smartest move available.” — Braden Kelley

Conclusion: Making Room for the Future

To get to the future first, you must be willing to travel light. The “useful seeds of invention” are often buried under the weeds of outdated assumptions. As you look at your own organization or career, ask yourself: What am I holding onto because it made me successful in 2020? What “best practices” have become “worst habits” in a 2026 economy? The Neuroscience of Unlearning tells us that while it is difficult to change, it is biologically possible. We simply need to provide our brains—and our teams—with the safety, time, and intentionality required to clear the path for a new operating system.

Frequently Asked Questions

Why is unlearning harder than learning?

Learning is additive and often triggers the reward centers of the brain. Unlearning requires weakening existing, myelinated neural pathways (Long-Term Depression), which the brain perceives as a loss or a threat. It is more metabolically expensive and emotionally difficult to “delete” than to “save.”

What is a “Corporate Antibody”?

It is the natural organizational resistance to change. Just as a biological antibody attacks a foreign virus, an organization’s existing culture, processes, and “successful” mental models will attack new ideas that threaten the status quo. Successful unlearning requires “disarming” these antibodies through psychological safety.

How can a leader encourage unlearning in their team?

Leaders must model vulnerability. By moving from a “know-it-all” to a “learn-it-all” mindset, they create a safe space for others to question outdated habits. Using frameworks like the Change Planning Toolkit™ helps make this transition structured rather than chaotic.

Image credits: Google Gemini

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Future-Proofing Human Creativity in the Age of Algorithmic Output

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LAST UPDATED: December 30, 2025 at 2:51PM

Future-Proofing Human Creativity in the Age of Algorithmic Output

GUEST POST from Chateau G Pato

Innovation has always been about change with impact. But as we navigate the late 2025 landscape, a new threat has emerged: the AI Creativity Trap. Organizations are rushing to replace human ideation with algorithmic output, lured by the siren song of “infinite content” and “zero-cost drafts.” However, we must be vigilant. If we are not intentional, a myopic focus on this technology will take us down the path of least resistance — the path where our creative energy moves to where it is easiest to go, rather than where it is most meaningful.

The truth is that Artificial Intelligence is superhuman at pattern recognition but fundamentally “backward-looking.” It is trained on yesterday’s data. To get to the future first, we need analogical thinking — the ability to connect unrelated domains and find the “Aha!” moments that a database of the past simply cannot predict. We are not just building tools; we are managing a transition of the human spirit.

“The algorithm can find the pattern, but only the human can find the purpose. Innovation isn’t just about what is possible; it is about what is purposeful and how it transforms the quality of people’s lives in ways they cherish.”

— Braden Kelley

The Corporate Antibody vs. The Generative Ally

When we introduce AI into the creative workflow, the corporate antibody — the natural organizational resistance to disruption — often manifests in two ways: total rejection or total abdication. Both are fatal. Future-proofing your organization requires Human-AI Teaming, where the machine handles the computational complexity and the human provides the emotional resonance and cultural nuance.

Case Study 1: The Empathy Engine in Global Contact Centers

The Challenge: A major global utility provider was seeing a “Trust Deficit” as their automated IVR systems frustrated customers, leading to high churn. Their initial instinct was to use Generative AI to replace agents entirely to save costs.

The Human-Centered Solution: Following the Cautious Adoption Framework, they shifted strategy. Instead of replacing agents, they deployed AI as a “Co-Pilot” that synthesized customer history and emotional sentiment in real-time. When a customer called in frustrated, the AI didn’t speak for the agent; it provided the agent with a three-bullet emotional dossier and suggested empathetic pathways. The Result: Resolution speed increased by 30%, but more importantly, agent job satisfaction rose because they were empowered to solve complex human problems rather than digging through data. They moved from being transactional clerks to high-value relationship managers.

Case Study 2: Breaking the ‘Average’ in Architectural Design

The Challenge: An urban planning firm found that using standard AI design tools led to “Architectural Homogenization” — every building proposal started to look like a blend of the most popular designs from the last five years. Their creative edge was evaporating into the “commodity of the average.”

The FutureHacking™ Approach: The firm implemented a rule: AI could only be used for stress-testing and rapid iteration, never for the initial “seed” of the idea. Architects were tasked with finding analogies from biology and music to create the initial concept. Only after the human “soul” of the building was defined did the AI step in to optimize for structural integrity and light efficiency. The Result: They won three consecutive international competitions because their designs possessed a distinctive cultural thumbprint that purely algorithmic competitors lacked. They proved that AI “collapses” when context changes, but human intuition thrives in the cracks of the unknown.

Leading Companies and Startups to Watch

In the current 2025 landscape, we must look beyond the “Big Tech” giants to find the true architects of human-AI collaboration. Anthropic continues to lead with their “Constitutional AI” approach, ensuring Claude remains aligned with human ethical frameworks. Adobe has set the gold standard for IP-friendly creativity with the Firefly Video Model, which empowers creators rather than scraping them. Startups like Anysphere (the team behind Cursor) are redefining “vibe coding,” allowing developers to stay in a flow state while the AI handles the boilerplate. Meanwhile, Cerebras Systems is building the “wafer-scale” hardware that will allow us to move beyond the limitations of current GPUs, potentially opening the door for AI that understands physics and three-dimensional context more deeply than ever before.

Architecting the Future Present

Success in this age will not be defined by who has the most powerful LLM, but by who has the most resilient creative culture. We must tell our employees the truth: technology will change your job, but it doesn’t have to eliminate your value. By focusing on experience design and empathy-driven innovation, we can ensure that we aren’t just optimizing for obsolescence, but building a world where technology serves the human spark, not the other way around.

Frequently Asked Questions

How do we prevent AI from making all creative work look the same?

The key is to use AI as an iterative partner rather than an originative source. By forcing the “initial seed” of a project to come from human analogical thinking — finding connections across unrelated domains — you ensure the output has a unique “soul” that a pattern-matching algorithm cannot replicate.

What is the biggest risk of over-automating creativity?

I call this the AI Creativity Trap. When teams rely too heavily on AI for ideation, their “creative muscles” atrophy. Research shows that when context or constraints change unexpectedly, purely AI-driven solutions often “collapse,” whereas human-led teams can flex and adapt using their unique emotional intelligence.

How can leaders build trust during AI transitions?

Trust is built through behavior, not just words. Leaders must be transparent about why the change is happening and involve employees early in defining how the tools will be used. Following a Cautious Adoption Framework — starting with low-risk, high-utility tasks — helps people see the AI as an ally that removes “grunt work” to free them up for “soul work.”

Image credits: Google Gemini

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Anchors & Biases – How Cognitive Shortcuts Kill New Ideas

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LAST UPDATED: December 10, 2025 at 12:12PM

Anchors & Biases - How Cognitive Shortcuts Kill New Ideas

GUEST POST from Chateau G Pato

Innovation is inherently messy, uncertain, and challenging. To navigate this complexity, our brains rely on cognitive shortcuts – heuristics — to save time and energy. While these shortcuts are useful for avoiding immediate danger or making routine decisions, they become the primary internal roadblocks when attempting to generate or evaluate truly novel ideas. These shortcuts are our anchors and biases, and they consistently pull us back to the familiar, the safe, and the incremental.

In the context of Human-Centered Innovation, we must shift our focus from just generating innovation to protecting it from these internal threats. The key is to recognize the most common biases that derail novel concepts and build specific, deliberate processes to counteract them. We must unlearn the assumption of pure rationality and embrace the fact that all decision-making, especially concerning risk and novelty, is tainted by predictable cognitive errors. This recognition is the first step toward building a truly bias-aware innovation ecosystem.

Anchors & Biases - How Cognitive Shortcuts Kill New Ideas

Visual representation: A diagram illustrating the innovation funnel being constricted at different stages (Ideation, Evaluation, Funding) by three key cognitive biases: Anchoring, Confirmation Bias, and Status Quo Bias.

Three Innovation Killers and How to Disarm Them

While hundreds of biases exist, three are particularly lethal to the innovation process:

1. Anchoring Bias: The Tyranny of the First Number

The Anchoring Bias occurs when people rely too heavily on the first piece of information offered (the “anchor”) when making decisions. In innovation, the anchor is often the budget of the last project, the timeline of the most recent success, or the projected ROI of the initial idea submission. This anchor skews all subsequent analysis, making it nearly impossible to objectively evaluate ideas that fall far outside that initial range.

The Killer: A disruptive idea requiring a tenfold increase in budget compared to the anchor will be instantly dismissed as “too expensive,” even if the potential ROI is twentyfold.
The Disarmer: Use Premortem Analysis (imagining the project failed and listing the causes) before assigning any financial figures. Also, use Three-Point Estimates (optimistic, pessimistic, and most likely) to establish a range, preventing a single number from becoming the dominant anchor.

2. Confirmation Bias: Seeking Proof, Not Truth

The Confirmation Bias is the tendency to search for, interpret, favor, and recall information that confirms or supports one’s prior beliefs or values. In innovation, this leads teams to design market research that validates their pet idea and ignore data that challenges it. This results in the pursuit of solutions nobody wants, but which the team believes they want.

The Killer: A team falls in love with a solution and only interviews customers who fit their narrow ideal profile, ignoring a critical segment whose objections would save the project from failure.
The Disarmer: Institute a Red Team/Blue Team structure. Assign a dedicated “Red Team” whose only job is to rigorously critique the idea and actively seek disconfirming evidence and data. Leadership must reward the Red Team for finding flaws, not just for confirming the status quo.

3. Status Quo Bias: The Comfort of the Familiar

The Status Quo Bias is the preference for the current state of affairs. Any change from the baseline is perceived as a loss, and the pain of potential loss outweighs the potential gain of the new idea. This is the organizational immune system fighting off innovation. It’s why companies often choose to incrementally improve a dying product rather than commit to a disruptive new platform.

The Killer: A new business model that could unlock 5x revenue is rejected because it requires decommissioning a legacy product that currently contributes 10% of profit, even though that product is in terminal decline. The perceived certainty of the 10% trumps the uncertainty of the 5x.
The Disarmer: Employ Zero-Based Budgeting for Ideas. Force teams to justify the existence of current processes or products as if they were a new idea competing for resources. Ask: “If we didn’t offer this product today, would we launch it now?” If the answer is no, the status quo must be challenged.

Case Study 1: The Anchor That Sank the Startup

Challenge: Undervaluing Disruptive Potential Due to Legacy Pricing

A B2B SaaS startup (“DataFlow”) developed an AI tool that automated a complex, manual compliance reporting process, reducing the time required from 40 hours per month to 2 hours. The initial team, anchored to the price of the legacy human labor (which cost clients approximately $4,000/month), decided to price their software at a conservative $300/month.

Bias in Action: Anchoring Bias

The team failed to anchor their pricing to the value delivered (time savings, error reduction, regulatory certainty) and instead anchored it to the legacy cost structure. Their $300 price point led potential high-value clients to view the product as a minor utility, not a mission-critical tool, because the price was too low relative to the problem solved. They were competing on cost, not value.

The Correction: External consultants forced the team to re-anchor based on the avoided regulatory fine risk (a $100k-$500k loss). They repositioned the product as an insurance policy rather than a software license and successfully raised the price to $2,500/month, radically improving their perceived value, sales pipeline, and runway.

The Innovation Impact:

By identifying and aggressively correcting the anchoring bias, DataFlow unlocked its true market value. The innovation was technical, but the success was achieved through cognitive clarity in pricing strategy.

Case Study 2: The Confirmation Loop That Killed the Feature

Challenge: Launching a Feature Based on Internal Enthusiasm, Not Customer Need

A social media platform (“ConnectAll”) decided to integrate a complex 3D-modeling feature based on the CEO’s enthusiasm and anecdotal data from a few early-adopter focus groups. The development team, driven by Confirmation Bias, only sought feedback that praised the technical complexity and novelty of the feature.

Bias in Action: Confirmation Bias & Sunk Cost

The internal team, having invested six months of work (Sunk Cost Fallacy), refused to pivot when the initial Beta tests showed confusion and low usage. They argued that users simply needed more training. When the feature launched, user adoption was near zero, and the feature became a maintenance drain, detracting resources from core product improvements.

The Correction: Post-mortem analysis showed the team needed Formal Disconfirmation. The new innovation process mandates that market testing must include a structured interview block where testers are paid to actively try and break the new feature, list its flaws, and articulate why they wouldn’t use it.

The Innovation Impact:

ConnectAll learned that the purpose of testing is not to confirm success, but to disconfirm failure. By forcing teams to seek and respect evidence that contradicts their initial beliefs, they now kill flawed ideas faster and redirect resources to validated, human-centered needs.

Conclusion: Bias-Awareness is the New Innovation Metric

The greatest barrier to radical innovation isn’t a lack of ideas or funding; it’s the predictability of human psychology. Cognitive biases like Anchoring, Confirmation Bias, and Status Quo Bias act as unconscious filters, ensuring that only the incremental and familiar survive the evaluation process. Organizations committed to Human-Centered Innovation must make bias-awareness a core competency. By building systematic checks (Premortems, Red Teams, Zero-Based Thinking) into every stage of the innovation pipeline, leaders transform cognitive shortcuts from fatal flaws into predictable inputs that can be managed. To innovate boldly, you must first think clearly.

“The mind is not a vessel to be filled, but a fire to be kindled — and often, that fire is choked by the ashes of old assumptions.” — Braden Kelley

Frequently Asked Questions About Cognitive Biases in Innovation

1. What is the difference between a heuristic and a cognitive bias?

A heuristic is a mental shortcut used to solve problems quickly and efficiently — it is the process. A cognitive bias is a systematic pattern of deviation from norm or rationality in judgment — it is the predictable error resulting from the heuristic. Biases are the consequences of using mental shortcuts (heuristics) in inappropriate contexts, such as innovation evaluation.

2. How does the Status Quo Bias relate to the Sunk Cost Fallacy?

The Status Quo Bias is a preference for the current state (a passive resistance to change). The Sunk Cost Fallacy is the resistance to changing a current course of action because of resources already invested (an active commitment to past expenditure). Both work together to kill new ideas: the Status Quo protects the legacy product, and Sunk Cost Fallacy protects the legacy project that failed to deliver.

3. Can AI help eliminate human cognitive biases in decision-making?

Yes. AI can be a powerful tool to mitigate human bias by acting as an objective “Red Team.” AI can be prompted to ignore anchors (e.g., “Analyze this idea assuming zero prior investment”), actively seek disconfirming data, and simulate scenarios free of human emotional attachment, providing a rational baseline for decision-making and challenging the human team’s assumptions.

Your first step toward mitigating bias: Before your next innovation meeting, ask everyone to write down the largest successful project budget from the last year. Collect these, then start the discussion on the new idea’s budget by referencing the highest and lowest numbers submitted. This simple act of introducing multiple anchors diffuses the power of any single number and forces a broader discussion.

Image credit: Pexels

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Innovation vs. Invention vs. Creativity

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Innovation vs. Invention vs. Creativity

by Braden Kelley

There is so much talk about innovation these days, it’s hard to sometimes distinguish the signal from the noise.

In fact, the word innovation gets thrown around so much that it leaves people wondering:

What’s really innovative?

Well, most of the time that people talk about something being innovative, what they describe isn’t innovative, but instead inventive or creative. These three are all very different. Here is how I like to distinguish the differences between creativity, invention and innovation:

Creativity – creates something interesting
Invention – creates something useful
Innovation – creates something so valuable that it is widely adopted, replacing the existing solution in a majority of appropriate use cases

Very few creative sparks result in an invention and very few inventions become innovations.

And the painful truth is that many great inventions take 20-30 years to be realized. Timing your investment is the key to whether you waste a big wad of cash, or still have it to spend when the optimal time to invest in a potential innovation comes.

If you look at most technology-based innovations, whether it’s the mp3 or the VCR, they were invented 20-30 years before they reached wide adoption in the marketplace, and for Gorilla Glass we’re talking more like 50 years.

To further emphasize the importance of timing…

Look at Webvan vs. Amazon Fresh

Look at Pets.com vs. Chewy.com (acquired by Petsmart)

Now these aren’t innovations, but you get my point. You have to know where you are on the commercialization timeline…

And most importantly, sometimes you have to look BACKWARDS before you look forwards, so you know where on the commercialization timeline you are.

If you’re working on a potential innovation now, are you sure it’s a potential innovation?

Are you sure now is the time to go big?

Using Boredom to Help Students Learn

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Bored Game Teacher What do you get when you take the technology away from a group of 10 and 11 year olds and ask them to be creative with a handful of household objects?

Well, Thomas Fraser, a teacher at Crestwood Elementary School in Edmonton, Canada, troubled by the short attention spans of today’s youngsters endeavored to find out by creating what he calls the Bored Game, which involves giving students a handful of common household objects with the only instruction being to do something interesting with them.

The reaction at first from his group of always on youngsters were perplexed looks of how can I create something without an iPad, smartphone or a computer?

Then they started to get into it, and were sad when they didn’t get to play the Bored Game.

CTV recorded an interview about the Bored Game that you can watch here:

(sorry, video is no longer available)

My favorite part of the story is that they’re finding that the performance of the children in a range of subjects is increasing as the children have this periodic time to play and engage their creative problem solving skills.

So, maybe we need less technology in the classroom if we want to teach kids how to learn?

In my opinion, we focus too much on teaching kids to repeat activities, facts, and figures, focusing and what they’re able to memorize and regurgitate and not enough on actually teaching kids creative problem solving and how to learn. We don’t need a new generation of trivia experts, we need a new generation of problem solvers that can help repair the world.

We’ve all heard the saying “If you give a man a fish he’ll eat for a day, if you teach a man to finish he’ll never go hungry.”

If you want your child to be more successful, you have to do the same thing…

“Good teachers teach kids how to do well on the test, great teachers teach kids how to learn so they do well in life.”

For more, I encourage you to check out the Edmonton Journal Article (link expired)

Image credit: Edmonton Journal

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Where Does Value Come From?

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Where does value come from?

What makes people willing to pay $50 for a t-shirt that’s just like the one that ten other people are wearing in the club?

What makes people pay a premium for Apple products with features introduced by other companies months or years before?

If you are truly trying to be innovative, instead of creative or inventive, you MUST understand how your prospective customers assign value for the new solution you are about to introduce. This may require lots of customer interviews, ethnography, forced choices, and other upfront research, but it’s worth it, because if you don’t build your potential innovation on a new, unique insight then it has no chance of succeeding in the marketplace. And as I’ve said before, to achieve innovation you have to focus not just on creating value in the product or service itself, but all three sources of value:

Value Creation
Value Translation
Value Access

So, let’s get back to the $50 t-shirt…

Here in Seattle we are proud of Macklemore and Ryan Lewis, who became a chart topping rap music music act by choosing not to follow the traditional way of making it in the music business so they could not only maintain their creative freedom, but also to make more money. Their mega-hit “Thrift Shop” pokes fun at fashionistas and has helped to make thrift shopping cool instead of embarrassing. Thank you to their combination of skills, they’ve been able to do a lot of the hard work themselves to promote their music, including making this video:

By remaining independent, Macklemore and Ryan Lewis are free to collaborate with whomever they want, when they want, and with sponsors who add value in specific ways consistent with the current project they are working on, instead of a record company extracting a rent from all the artist’s activities (whether they are adding value or not). Here is one such project they undertook with another local artist, Fences, and sponsorship from a company headquartered here locally – T-Mobile USA. It’s a great song and a pretty cool video if you haven’t heard or seen it before:

I for one am grateful that Macklemore and Ryan Lewis didn’t sign a record deal, and record executives have candidly admitted that they would have totally ruined the act by forcing them to change to be more “marketable.” The success of Macklemore and Ryan Lewis (and others) serve to highlight the disruption in the music industry value chain that continues to occur, creating discontinuities that artists like Macklemore and Ryan Lewis can take advantage of. This is of course as long as they have the digital and social skills to get the word out and help their music spread.

Is there disruption happening in your industry’s value chain?

How can you take advantage of the discontinuities?

Please note the following licensing terms for Stikkee Situations cartoons:

1. BLOGS – Link back to https://bradenkelley.com/category/stikkees/ and you can embed them for free
2. PRESENTATIONS, please send $25 to me on PayPal by clicking the button	3. NEWSLETTERS & WEB SITES, please send me $50 on PayPal by clicking the button

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Making People Dance Instead of Jaywalk

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Making People Dance Instead of Jaywalk I love anything that is fun and investigates human psychology, especially crowd psychology, and the investigation of how you can use fun to potentially influence human behavior for social good (i.e. the piano stairs example I’ve shared before).

Nobody likes to wait at pedestrian crossings. Traffic lights can be dangerous for impatient pedestrians trying to save a few seconds to cross the street (and willing to risk their lives in the process).

The folks at Smart created The Dancing Traffic Light, an experiential marketing concept providing a fun and safe way to keep people from venturing too early into the street. They started by placing a dance room on a square in Lisbon, Portugal and invited random pedestrians to go into the box and dance. Their movements were then displayed on a few traffic lights in real time. This resulted in 81% more people stopping and waiting at those red lights.

It’s a genius marketing gimmick because it reinforces the brand value of fun by making people dance in a box that looks, imagine that, a bit like a smart car.

The question brought up by this example of a marketing campaign that claims that fun can be used to achieve social good, is that it claims a benefit, that without an extended test could be attributed to novelty…

Does the benefit hold up over time?

Or does it stop being fun and impactful after people have seen it once or twice or the live video component goes away and it becomes a recording? Do people then start jaywalking again at the normal rate?

What do you think?

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Improving Education for 20 Cents a Student

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I love examples of simple, inexpensive solutions that solve important problems. Solutions like the water bottle light, the gravity light, etc., and Mike Freeston was kind enough to send this most recent example that I will share with you today. Thank you Mike!

The video details the work of a Non-Governmental Organization (aka NGO), that was created as a Community Service Center for marginalized families in rural areas an urban slums. It’s called Aarambh, and they wanted to help students who don’t even have the basic facilities, to be more comfortable and productive at school.

Most schools in rural India have two basic problems:

Schools don’t have proper desks, which leads to poor eyesight, bad posture and bad writing.
Students don’t have school bags.

Aarambh came up with a solution which tackled both these problems with a single, thoughtful design.

Aarambh came up with a design for portable desks made using discarded cardboard boxes (aka cartons). This choice for raw materials is both economical, and easily available. The stencil design, when cut and folded, creates a desk suitable for use by students whom must sit on the floor AND it also can serve as a school bag.

Brilliant!

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Your Chance to Help Overworked Entrepreneurs

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Life for a busy entrepreneur regular working 60 hours a week can lead to a struggle with maintaining a healthy weight. You may find that you are eating out for convenience and getting to the gym very infrequently (if at all). This lifestyle may have been fine through your twenties and early thirties, but after 35, it gets difficult to keep active and you might find those few extra pounds you’ve put on every year are really starting to add up.

Have you had similar struggles?

If you have a way to help motivate overworked entrepreneurs to lay off the takeout and introduce more physical activity into their busy lives, we at Premera would love to hear about it.

Simply post your idea to Premera’s Facebook or Twitter page using the hashtag #IGNITEchange, or as a comment to their stories. You are then automatically entered into a drawing to win a $200 Amazon gift card. Best of all, you have the chance to impact a real person’s life. There will be four chances to win, once every week from now until September 8, 2014 (terms and conditions link expired).

Have a true game-changing idea that will spark families to make lasting, realistic improvements to their health?

Premera is rewarding that type of innovation as well through Premera’s Innovate to Motivate challenge (link expired), which offers a grand prize of $5,000!

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