Category Archives: Psychology

Measuring the Unmeasurable – Metrics for Curiosity, Trust, and Openness

LAST UPDATED: December 8, 2025 at 2:34PM

Measuring the Unmeasurable - Metrics for Curiosity, Trust, and Openness

GUEST POST from Chateau G Pato

In the relentless pursuit of Human-Centered Change and innovation, we face a critical paradox: the most impactful drivers of breakthrough ideas—things like curiosity, trust, and openness—are often dismissed as “soft” or “unmeasurable.” We diligently track KPIs related to output, revenue, and efficiency, yet overlook the very inputs that foster an environment where these outputs can thrive. This is a profound mistake. What gets measured gets managed. What isn’t measured often languishes.

To truly build resilient, innovative organizations, we must unlearn the rigid assumption that only direct, quantitative metrics hold value. Instead, we must embrace the art and science of inferential measurement, building a mosaic of data points that, together, illuminate the state of these crucial, yet intangible, human qualities. These are not about vanity metrics; they are about understanding the health of your innovation ecosystem.

Visual representation: An infographic illustrating how indirect metrics (e.g., questions asked, cross-functional collaboration, idea submissions) can be proxies for Curiosity, Trust, and Openness.

The Triangulation Approach: Unlocking Hidden Insights

Measuring the unmeasurable is not about finding a single, perfect number. It’s about triangulation: combining multiple, often indirect, indicators to create a robust picture. Here’s how we can approach curiosity, trust, and openness:

1. Measuring Curiosity: The Fuel for Exploration

Curiosity is the impulse to explore, learn, and question. It drives individuals to seek new solutions and challenge assumptions. To measure it, look for behavioral proxies:

“Why?” Question Frequency: In meetings, workshops, and project discussions, track the number of times individuals or teams ask fundamental “why” questions rather than just “how” or “what.” A higher frequency suggests deeper inquiry.
Cross-Departmental Inquiry: Track the number of informal (coffee chats) and formal (shadowing, interviews) information-seeking interactions employees initiate outside their immediate team or department. Tools like communication platforms or internal social networks can help monitor this.
Learning Resource Engagement: Monitor engagement with internal learning platforms, external courses, industry reports, and innovation labs. How many unique topics are explored? How many non-mandatory courses are completed?
Idea Submission Diversity: Beyond just the number of ideas, analyze the breadth of domains or problem spaces addressed in idea submissions. Are people exploring completely new territories, or just iterating on existing ones?

By combining these, you can gauge whether your culture is merely allowing curiosity or actively fostering it.

2. Measuring Trust: The Foundation of Collaboration

Trust is the belief that others will act in good faith and that one’s vulnerabilities will not be exploited. It is essential for sharing nascent ideas and taking risks. Proxies for trust include:

Psychological Safety Index: Utilize anonymous surveys (e.g., Google’s Project Aristotle model) to gauge employees’ comfort level with speaking up, admitting mistakes, and sharing unconventional ideas without fear of negative repercussions. Focus on statements like, “If I make a mistake on this team, it is not held against me.”
Feedback Loop Activity: Track the volume and bidirectional nature of constructive feedback. Are people giving and receiving candid feedback freely, or is it primarily top-down and formal? High-trust environments foster frequent, informal feedback exchanges.
Cross-Functional Resource Sharing: Beyond simple collaboration, look at the willingness to share sensitive information, critical resources, or even temporary team members between departments. This indicates a deeper level of inter-team trust.
Conflict Resolution Patterns: Observe how conflicts are resolved. Is it through formal escalation (low trust) or direct, informal discussion and negotiation (high trust)?

A thriving innovation culture cannot exist without strong inter-personal and inter-team trust. Building this foundation is not soft; it is strategic.

3. Measuring Openness: The Gateway to New Possibilities

Openness is the willingness to consider new ideas, approaches, and perspectives, even if they challenge existing paradigms. It’s about shedding cognitive biases and embracing ambiguity. Metrics for openness include:

Experimentation Rate: Track the number of small-scale experiments, MVPs, and pilots initiated monthly. More importantly, measure the learning cycle time—how quickly experiments are run, results analyzed, and decisions made.
Diversity of Input Sources: Where do new ideas originate? Are they solely internal, or is there a strong influx from external sources (customer co-creation, academic partnerships, competitor analysis, diverse new hires)?
Resistance-to-Change Index: Use pulse surveys or qualitative interviews to identify explicit and implicit resistance to new processes, technologies, or strategies. Look for patterns in objections—are they evidence-based, or fear-based?
Leadership Receptiveness: Assess how often leaders genuinely seek out dissenting opinions, actively listen to junior staff ideas, and publicly acknowledge when their own assumptions were challenged and proven incorrect. This sets the tone for the entire organization.

Ultimately, openness determines an organization’s capacity for true transformation, not just incremental improvement.

Case Study 1: Reinvigorating a Stagnant R&D Lab

Challenge: Declining Innovation Output in a Legacy R&D Division

A global pharmaceutical company (“PharmaCo”) noticed its once-pioneering R&D lab was becoming risk-averse, producing fewer novel compounds. Direct output metrics remained stable due to incremental improvements, but true breakthrough innovation had stalled.

Measurement Intervention: Curiosity & Openness Proxies

PharmaCo introduced new “soft” metrics alongside traditional KPIs:

Curiosity: Tracked participation in cross-disciplinary “Lunch & Learn” sessions (informal scientific sharing), internal publication of research outside one’s core specialty, and spontaneous “deep dive” requests to the central knowledge repository.
Openness: Monitored the number of “negative result” reports (failures leading to new insights), external collaboration proposals, and employee-initiated “exploratory project” pitches outside core mandates.

The Innovation Impact:

By explicitly measuring and rewarding these proxies, PharmaCo shifted its culture. Within two years, cross-disciplinary “Lunch & Learns” increased by 300%, and “negative result” reports (previously buried) became celebrated learning documents. This led to a 15% increase in novel drug candidate proposals from unexpected combinations of research, demonstrating that measuring inputs can drive groundbreaking outputs.

Case Study 2: Building Inter-Departmental Trust in a Tech Giant

Challenge: Siloed Teams and Blame Culture Post-Acquisition

A rapidly growing tech company (“MegaTech”) experienced significant friction and blame-shifting between its engineering and product teams following a major acquisition. This eroded trust, slowed development cycles, and increased employee turnover in critical roles.

Measurement Intervention: Trust & Openness Proxies

MegaTech launched a Human-Centered Change initiative focusing on trust. Metrics included:

Trust: Anonymous pulse surveys on psychological safety (e.g., “I feel safe disagreeing with my manager”), and “shadowing days” where engineers spent a day with product teams, and vice versa.
Openness: Tracked the number of “feedback sessions” where teams collectively reviewed each other’s work (not just managers), and the explicit mention of “lessons learned” in post-mortems, rather than just “root causes.”

The Innovation Impact:

Over 18 months, the psychological safety score increased by 25%. More importantly, the quality and speed of conflict resolution improved dramatically, and employee retention in critical engineering roles stabilized. By making trust and openness measurable, MegaTech systematically dismantled silos, fostering a culture where inter-team learning and mutual respect became the norm.

Conclusion: The Strategic Imperative of Intangible Metrics

Ignoring curiosity, trust, and openness as “unmeasurable” is a strategic blunder. These are not optional nice-to-haves; they are the fundamental operating system of an innovative enterprise. By adopting a triangulation approach—combining observable behaviors, qualitative insights, and intelligent proxies—leaders can gain unprecedented visibility into the health of their innovation culture. This shift from purely output-driven metrics to input-driven insights is the next frontier of Human-Centered Change. Start measuring these “unmeasurables” today, and watch your innovation capacity soar.

“If you only measure the easy things, you’ll miss the most important things.” — Braden Kelley

Frequently Asked Questions About Measuring Intangible Metrics

1. Why are curiosity, trust, and openness considered “unmeasurable”?

They are often considered unmeasurable because they are subjective human qualities that cannot be directly counted or quantified in a simple numerical way. Traditional metrics focus on outputs (e.g., sales, production), whereas these are inputs that describe psychological states and behaviors, requiring more nuanced, indirect measurement approaches.

2. What is the “triangulation approach” to measurement?

The triangulation approach involves using multiple, different data sources and types (e.g., surveys, behavioral observations, usage logs) to gain a comprehensive understanding of an intangible quality. Instead of relying on a single “perfect” metric, it combines several indirect indicators to form a more robust and reliable picture.

3. How can I start measuring these in my own team?

Start small with a single proxy. For curiosity, try tracking “why” questions in team meetings. For trust, implement a quick, anonymous psychological safety pulse survey. For openness, monitor the diversity of idea sources. The key is to pick observable behaviors or simple self-reports and consistently track changes over time, then discuss the insights with your team.

Your first step toward measuring the unmeasurable: Convene your innovation leadership team. Instead of asking, “What new products did we launch?” ask, “What new questions did our team ask last month that challenged our core assumptions?” Document these, and you’ve begun to measure curiosity.

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.

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The Secret Skill of the Modern Innovator

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Psychological Flexibility

LAST UPDATED: December 7, 2025 at 12:43AM

The Secret Skill of the Modern Innovator - Psychological Flexibility

GUEST POST from Chateau G Pato

We celebrate the external skills of the innovator: the design thinking workshops, the pitch decks, the engineering prowess. But the greatest innovation hurdle is not external; it is internal. It is the human brain’s innate desire for certainty and comfort. Innovation, by definition, requires uncertainty, risk, and repeated failure. The skill that allows an individual and an organization to navigate this emotional terrain is Psychological Flexibility.

Psychological Flexibility is the ability to fully contact the present moment—including undesirable thoughts, feelings, and sensations—and, depending on what the situation affords, persist or change behavior in the service of chosen values. It’s the opposite of rigidity. Rigidity manifests in the innovation space as Idea Attachment (holding onto a failed concept too long) or Emotional Avoidance (shying away from projects that induce fear of failure). True Human-Centered Change demands that we unlearn avoidance and embrace the discomfort as a necessary input for growth.

Visual representation: A diagram illustrating the key components of Psychological Flexibility: Acceptance, Cognitive Defusion, Contact with the Present Moment, Self-as-Context, Values, and Committed Action.

The Four Practices of the Flexible Innovator

To cultivate this internal agility, innovators must master four practices adapted from Acceptance and Commitment Therapy (ACT):

1. Cognitive Defusion (Disentangling from Thoughts)

Innovation is besieged by self-doubt: “This idea is stupid,” “The market will never accept this,” or “I’m going to lose my job.” Cognitive Defusion is the practice of seeing thoughts not as literal truths, but as mere words or mental events. The flexible innovator does not try to fight or suppress the negative thought; they simply observe it and continue acting in alignment with their goal. The key phrase is, “I am having the thought that I will fail,” instead of “I will fail.” This distance creates mental space for bold action.

2. Values Clarity (Knowing the North Star)

Change often feels chaotic. Psychological Flexibility requires a clear, defined sense of Values Clarity. Why are we innovating? Is it to enhance customer dignity, improve planetary health, or simplify an essential process? When the inevitable setback occurs (a failed MVP, a budget cut), the innovator relies on their North Star values to guide the next move. They don’t pivot arbitrarily; they pivot toward the value, not away from the pain. This turns a moment of crisis into a Commitment Test.

3. Acceptance (Embracing the Error)

Innovation failure is data, but emotionally, it feels like rejection. Acceptance is not resignation; it is the active, non-judgmental embrace of uncomfortable emotions (frustration, anger, sadness) and market realities (the product is flawed). The rigid innovator wastes energy trying to rationalize or ignore the failure. The flexible innovator accepts the emotional hit, processes the data, and redirects that saved energy into Course Correction. This radically accelerates the Build-Measure-Learn loop.

4. Self-as-Context (Fluid Identity)

Many innovators tie their personal worth to the success of their project. When the project fails, their self-esteem is crushed. Self-as-Context means recognizing that one’s identity is the container holding all experiences, not the experiences themselves. The failure of Project X does not mean “I am a failure.” It means “The container is holding the experience of a failed project.” This internal decoupling protects the innovator’s psychological resources, allowing them to remain resilient and return to the challenge without the debilitating fear of identity loss.

Case Study 1: The Media Company’s Content Pivot

Challenge: Market Collapse of Traditional Revenue Stream

A mid-sized media conglomerate (“GlobalNews”) saw its core print advertising revenue rapidly evaporate. The leadership team had spent years successfully managing a highly stable business, and the sudden shift induced profound anxiety and Cognitive Fusion with limiting beliefs (“We are print people,” “Digital is too chaotic”).

Flexibility Intervention: Values-Driven Defusion

The CEO mandated a Human-Centered Change program focusing on psychological skills. The team practiced Cognitive Defusion to observe their limiting thoughts without acting on them. The core value was redefined from Delivering Print to Delivering Trusted Information. They accepted the pain of losing their old model (Acceptance) and used the value of Trusted Information to pivot.

The pivot was towards building a paywalled, high-fidelity data analytics service for businesses, not just a news website.
The value (Trust) defined the new product’s identity and its business model, moving them out of the volatile ad market.

The Innovation Impact:

By using their core value as the flexible guide and practicing defusion, the team avoided the rigid response of simply cutting costs or doubling down on failed strategies. They achieved a strategic pivot within 18 months, leveraging their expertise in a new, high-growth format, driven entirely by their newfound psychological tolerance for market upheaval.

Case Study 2: The Software Team’s Feature Kill

Challenge: Attachment to a High-Cost, Low-Value Feature

A software development team (“HelixTech”) spent six months and significant budget on a highly complex, technically impressive new feature. Upon launch, Big Data revealed near-zero user adoption. The product manager, having personally championed the feature, experienced intense Idea Attachment and resisted the recommendation to “kill” the feature.

Flexibility Intervention: Acceptance and Self-as-Context

The leadership team intervened by applying the Acceptance and Self-as-Context practices. They explicitly coached the manager: “The failure of Feature Z is not a failure of your competence. It is data showing an unmet customer need.” They asked the manager to practice accepting the data and the resulting negative emotion (frustration/embarrassment) as temporary states, not definitions of self.

The manager was then empowered to lead the decommissioning project, re-framing the effort as cleaning up the roadmap (a new valued action).
The time saved was immediately reinvested in a small, customer-validated MVP, allowing the manager to instantly re-engage in creative work.

The Innovation Impact:

By separating the innovator’s identity from the idea’s outcome, HelixTech avoided the common inertia where teams waste months supporting defunct features. The quick Acceptance and re-framed Committed Action allowed the team to recover the initial investment of time and maintain high morale, reinforcing the organizational value that failure is simply a learning input.

Conclusion: Building Resilient Organizations

Psychological Flexibility is not a soft skill; it is the hardest skill in innovation. It is the prerequisite for speed, resilience, and true market responsiveness. Organizations focused on Human-Centered Change must recognize that the biggest brake on progress is the collective rigidity of their people, fueled by fear and the desire for emotional comfort. By embedding the practices of Cognitive Defusion, Values Clarity, Acceptance, and Self-as-Context, leaders don’t just build resilient innovators; they build resilient organizations capable of navigating any disruptive shift.

“Innovation is a contact sport. You must be willing to feel the pain of rejection and keep moving towards successful value creation that can overcome market inertia.” — Braden Kelley

Frequently Asked Questions About Psychological Flexibility

1. How does Psychological Flexibility differ from simple Resilience?

Resilience is typically defined as the ability to bounce back from adversity. Psychological Flexibility is a broader, active skill set: the ability to engage fully with painful or undesirable thoughts and feelings (Acceptance) while simultaneously taking effective action aligned with one’s values. It’s about adapting behavior in the face of internal discomfort, not just enduring it.

2. What is “Cognitive Fusion” and why does it stop innovation?

Cognitive Fusion is when a person believes their thoughts are literal truths that must be acted upon or obeyed (e.g., “I am stupid” means I cannot try the hard project). This stops innovation because it prevents the individual from taking valued risks when the inevitable, self-critical thoughts arise. Cognitive Defusion is the opposite skill, allowing the innovator to observe the thought without obeying it.

3. How can a team encourage the practice of “Acceptance”?

Teams encourage Acceptance by making failure an explicit, non-punitive data event. This involves celebrating the learning derived from a failed experiment, publicly discussing the difficult emotions that arose, and immediately reassigning resources to the next valued action. It shifts the culture from failure avoidance to learning acceleration.

Your first step toward cultivating Psychological Flexibility: The next time a new project feels overwhelming or terrifying, pause. Don’t fight the fear. Simply acknowledge it by saying internally, “I am having the feeling of fear, and I choose to start the first task anyway.” Use your values, not your feelings, to guide your immediate action.

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The End of the Lone Genius Myth

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Building Collective Confidence

The End of the Lone Genius Myth

LAST UPDATED: December 1, 2025 at 5:55PM

GUEST POST from Chateau G Pato

Innovation is rarely a bolt of lightning striking a solitary mind. Look closer at history’s greatest inventions, and you’ll find a network of collaborators, financiers, critics, and technical experts. Yet, in business, we persistently mythologize the Lone Genius — the charismatic individual who will single-handedly disrupt the market. This myth is more than just bad history; it’s bad strategy, creating fragile, single-point-of-failure dependencies and actively diminishing the potential of entire workforces.

The human-centered change leader knows that sustainable, continuous innovation flows from Collective Confidence — the shared belief among team members that their group is competent, capable of generating novel solutions, and resilient enough to overcome inevitable failures. It is the core mechanism that allows an organization to embrace ambiguity and initiate radical change without succumbing to fear or internal politics.

Individual confidence is essential, but it is Collective Confidence that translates great ideas into scaled reality. This is the difference between a brilliant patent and a world-changing product pipeline.

The Three Pillars of Collective Confidence

Collective confidence is not built through motivational posters or annual retreats; it is engineered through three core, systemic pillars:

1. Engineered Psychological Safety

The single most powerful predictor of team effectiveness is Psychological Safety — the shared belief that the team is safe for interpersonal risk-taking. If an engineer fears ridicule for suggesting a crazy idea, or if a junior employee risks reprisal for questioning a flawed decision, innovation dies. Collective Confidence requires institutionalizing safety through: a) Leadership modeling vulnerability and failure; and b) Process design that frames experiments as learning opportunities, not judgment opportunities. When teams know they can fail safely, they will dare to succeed boldly.

2. Shared Context and Innovation Language

Confidence is impossible without clarity. Teams cannot feel confident about solving a complex problem if they don’t share a common language for defining the problem, measuring progress, and articulating risk. This means moving beyond departmental jargon to create a common, human-centered language (e.g., using “minimum viable product” and “discovery phase” consistently across engineering, marketing, and finance). This shared context minimizes miscommunication, builds trust, and ensures everyone is confidently pulling in the same direction — even if the path forward is ambiguous.

3. Reciprocal Accountability, Not Individual Blame

In the Lone Genius model, if a project fails, a single person is blamed and removed. In the Collective Confidence model, accountability is reciprocal. It is a shared responsibility to ensure success and to support the process of learning from failure. When a project hits a roadblock, the question shifts from “Who made the mistake?” to “What did our process allow to happen, and how can we, as a team, strengthen our controls for the next iteration?” This shared burden of responsibility reinforces trust and encourages team members to speak up early when risks are identified.

Case Study 1: The Manufacturing Firm’s Quality Transformation

Challenge: Inconsistent Quality Control and Blame Culture

A precision parts manufacturing firm (“PrecisionCo”) struggled with unacceptable error rates. Their existing culture relied on a “Quality Genius” — a single, highly experienced supervisor responsible for final sign-off. When failures occurred, the supervisor was blamed, which led the rest of the team to practice defensive mediocrity — avoiding responsibility and relying solely on the genius’s final check.

The Collective Confidence Intervention: Decentralizing Quality Ownership

PrecisionCo decided to deliberately dismantle the Quality Genius role. Instead, they:

Implemented mandatory cross-functional training, teaching every line worker not just their task, but the context of the next person’s task.
Introduced a rule: Errors were investigated, not to find the individual responsible, but to identify the process step that failed.
Empowered every team member with the stop work authority, encouraging them to halt production if a process felt wrong, making their voice a valued tool, not a potential liability.

The Human-Centered Lesson:

The shift was profound. By building Collective Confidence in the process and in each other, error rates dropped dramatically. The value was not in creating 100 individual geniuses, but in creating a system where the collective capability of the team — backed by psychological safety — eliminated the need for a single hero.

Case Study 2: The Design Agency’s Client Pitch Success

Challenge: Dependence on the Principal Designer for High-Stakes Pitches

A renowned digital design agency (“DesignPro”) often won major contracts, but only when the celebrated Principal Designer (the “Genius”) led the pitch. Junior designers, fearing the Principal’s perfectionism, rarely contributed their best work until it was safe, resulting in bottlenecks and burnout for the lone star.

The Collective Confidence Intervention: Structured Co-Creation and ‘Shitty First Drafts’

DesignPro focused on teaching the team to confidently engage with ambiguity early. They instituted:

The “Shitty First Draft” (SFD) ritual: Every project phase required a deliberately low-fidelity, unfinished draft from every team member to normalize imperfection and minimize the fear of judgment.
Reciprocal Feedback Systems: Instead of the Principal critiquing down, junior members were mandated to lead critique sessions for the Principal’s work, encouraging Psychological Safety and flattening the expertise hierarchy.

The Human-Centered Lesson:

The result was a dramatic decrease in the Principal Designer’s pitch lead rate, and a massive increase in overall client pitch wins led by various team members. The Collective Confidence enabled the entire firm to innovate consistently. The Principal Designer, freed from the necessity of being the lone hero, shifted into a strategic coaching role, enhancing the firm’s overall innovation capacity.

The Call to Action for Human-Centered Leaders

Stop searching for the next Lone Genius. The genius is already within your walls, diffused across your teams, waiting for the right conditions to emerge. Your role as a leader is to stop rewarding individual heroism and start engineering the systems that build Collective Confidence.

This means moving from a culture of individual brilliance to a culture of systemic capability. The breakthroughs you need won’t come from a single hero’s desk, but from the collaborative, confidently ambiguous work of teams that trust their process and, most importantly, trust each other.

“Individual brilliance gets you a great idea. Collective Confidence gets you a sustainable organization capable of perpetual innovation.”

Frequently Asked Questions About Collective Confidence

1. What is the difference between Individual and Collective Confidence?

Individual confidence is a person’s belief in their own capability to perform a task. Collective Confidence (or team efficacy) is the shared, reciprocal belief among team members that their group, as a whole, can successfully organize and execute the courses of action required to produce given levels of attainment, especially when facing ambiguous or complex problems.

2. How does the “Lone Genius” myth harm organizational innovation?

The myth harms innovation by creating single points of failure, suppressing employee voice (lowering psychological safety), and encouraging “defensive mediocrity” where employees avoid responsibility and rely on the identified “genius” instead of contributing their own creative input. This slows down learning and reduces organizational resilience.

3. How do you “engineer” Psychological Safety?

Psychological Safety is engineered, not wished into existence, through formal processes: 1) Leadership explicitly modeling vulnerability and admitting mistakes; 2) Implementing formal feedback loops that focus on process learning instead of individual blame; and 3) Decentralizing decision-making (like the “stop work” authority) to empower all voices equally.

Your first step toward building Collective Confidence: Next time an experiment fails, deliberately avoid asking, “Who was responsible?” Instead, ask the entire team, “What weakness in our shared process or communication enabled this outcome? And what will we change next time?”

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Ethnography for Innovators

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Uncovering the Unmet Needs People Cannot Articulate

LAST UPDATED: November 25, 2025 at 6:43PM

Ethnography for Innovators

GUEST POST from Chateau G Pato

In our data-driven world, companies invest millions in surveys, focus groups, and A/B testing. Yet, these methods often only illuminate articulated needs—the problems people know they have and can describe. If you rely solely on these methods, you will, by definition, only produce incremental improvements on existing products.

The true gold standard of innovation—the breakthrough idea—lies in the unmet needs: the pervasive frictions, latent desires, or emotional compromises that people have simply grown used to and can no longer identify as problems. They are the invisible pain points that exist outside the structured environment of a corporate interview. The human-centered discipline that unlocks this insight is Ethnography.

Ethnography, borrowed from anthropology, is the practice of immersing oneself in the user’s natural environment to observe behavior, context, and culture. It is the shift from asking “What do you want?” to observing “What do you actually do, and why do you do it that way?” For the innovator, this shift transforms research from a validation exercise into an Exploration Engine.

The Three Fallacies Ethnography Corrects

Ethnography is essential because it bypasses three inherent flaws in traditional market research:

The Articulation Fallacy: People are experts at solving their own problems locally, often through complex workarounds they don’t even recognize as inefficient. They cannot articulate a solution they haven’t seen.
The Context Fallacy: Behavior changes when people know they are being observed in an artificial setting (the focus group room). Ethnography ensures observations happen in the flow of life, where real compromise and decision-making occur.
The Rationalization Fallacy: People often explain why they do something based on rational logic, while the true driver is deep-seated emotion, habit, or social pressure. Ethnography observes the action and then asks “Show me the workaround,” exposing the gap between what they say and what they do.

The Four Pillars of Ethnographic Innovation

To successfully leverage ethnographic insight, innovators must focus on four key areas:

1. The Focus: Extremity Over Average

Do not study the average user; study the extreme user. The people who are bending, breaking, or hacking your product or process reveal the highest friction points and the most intense needs. Observing a power-user or an anti-user provides disproportionate insights compared to surveying the typical majority. The solution that works for the edge case often provides a superior experience for everyone.

2. The Method: Deep Hanging Out

This is the core of the practice. Instead of brief, formal interviews, innovators must practice Deep Hanging Out—spending hours or even days immersed in the user’s native context (their home, office, factory floor). The goal is not merely data collection; it is insight generation by understanding the culture, the tools, the interruptions, and the social contracts that surround the task.

3. The Lens: Observation over Interview

Prioritize observation. Use the interview to fill in the why, not to collect the initial what. For instance, instead of asking, “How do you manage your medication?” observe the user’s routine, the pile of bottles, the post-it notes, the compromises, and the moments of confusion. Then, ask: “Tell me about this sticker you put on the bottle.” That sticker often holds the key to the unmet need.

4. The Synthesis: Insight Teams

Ethnographic data must be synthesized by a diverse, cross-functional team. Insights are most powerful when a Marketing leader, a Data Scientist, and an Engineer all observe the same human behavior. The Engineer sees the technical gap, the Data Scientist sees the behavioral anomaly, and the Marketing leader sees the emotional driver. This co-synthesis prevents organizational bias from distorting the human reality observed.

Case Study 1: The Kitchen Appliance Manufacturer and the Latent Mess

Challenge: Stagnant Blender Market and Incremental Features

A major appliance manufacturer was struggling to innovate beyond faster motors and bigger jugs. Traditional research asked consumers, who invariably replied: “Make it more powerful.”

Ethnographic Intervention: Observing the Aftermath

The innovation team employed ethnography by installing cameras and observing users making smoothies in their homes, focusing not on the blending itself, but on the post-use clean-up routine (the latent pain). They observed:

Users immediately rushing to rinse the blender to prevent food from sticking.
The awkward balancing act of cleaning around the sharp blades.
The subsequent mess in the sink and the counter area.

The Innovation Insight:

The team realized the true, unarticulated pain wasn’t a lack of power, but the messy, time-consuming chore of cleaning. The resulting innovation was a product designed with self-cleaning capabilities and blade structures optimized for rinsing, effectively changing the job-to-be-done from “make a smooth drink” to “make a smooth drink with zero clean-up friction.” This insight could never have been generated by a focus group asking, “What new features do you want?”

Case Study 2: The Financial Services Firm and the Unspoken Anxiety

Challenge: Low Adoption of Retirement Planning Tools by Younger Clients

A financial firm offered robust digital retirement planning tools, but young clients ignored them. Traditional research revealed only surface-level reasons: “It’s too complicated” or “I don’t have enough money yet.”

Ethnographic Intervention: Contextual Mapping of Financial Stress

Innovators spent time with young professionals, observing how they managed money in context (paying bills, checking bank apps, discussing finances with partners). The team wasn’t just observing transactions; they were looking for emotional cues and physical workarounds.

They observed clients constantly checking their immediate bank balance (fear of overdraft) but never checking their long-term retirement accounts.
They noted that talking about retirement planning was socially taboo or anxiety-inducing, leading to procrastination.
The friction point was not complexity, but the psychological distance between the present need (pay rent) and the future goal (retirement).

The Innovation Insight:

The firm realized that the tool had to address the anxiety, not just the calculation. The innovation was a shift to automatic, small-scale savings triggered by behavioral cues (e.g., automatically save $5 every time you use a ride-share app). The tool made the savings process invisible and non-anxiety-inducing, successfully linking the immediate, observed behavior with the long-term, unarticulated goal. The breakthrough was finding the latent emotional trigger, not fixing the interface.

The Human-Centered Call to Action

Quantitative data tells you what is happening; Ethnography tells you why it’s happening. If your innovation effort is stalled, it’s not because you lack data—it’s because you lack deep, human insight.

To move beyond incremental improvement, you must mandate that innovation teams leave the building. They must become anthropologists of the modern world, actively seeking the compromises and workarounds that signal an unmet need. This is how you transform a good idea into a market-defining breakthrough.

“If your customers could tell you what they wanted, you wouldn’t need an innovation strategy; you would need a fulfillment strategy. Breakthroughs hide in the unarticulated.”

Frequently Asked Questions About Ethnography for Innovation

1. What is the main goal of using ethnography in innovation?

The main goal is to uncover “unmet needs”—the latent pains, desires, and emotional compromises that users have grown accustomed to and cannot articulate in a traditional interview. This deeper, contextual insight is necessary for disruptive, non-incremental innovation.

2. Why is studying the “extreme user” more valuable than studying the average user?

Extreme users (power-users, frequent hackers, or even non-users) experience the friction points and limitations of a product or process most intensely. Their extreme workarounds and frustrations often reveal critical system flaws and latent needs that apply to the average user, but are simply less visible.

3. What is the “Articulation Fallacy” and how does ethnography overcome it?

The Articulation Fallacy is the idea that people can accurately describe the best solution to their own problem. Ethnography overcomes this by focusing on observation (What they *do*) over interview (What they *say*), allowing innovators to design solutions for compromises and workarounds that the user is no longer conscious of.

Your first step toward Ethnographic Innovation: Do not commission a survey. Instead, mandate that every member of your next innovation team (including the finance analyst and the engineer) spends three hours observing a customer, not in a conference room, but in their natural environment (their desk, their home, or their point of interaction with your product). Instruct them to document five non-obvious workarounds they observe. Use those workarounds, not stated desires, as the starting point for your next design sprint.

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Decoupling Failure to Build the Psychological Safety Net for Risk-Taking

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LAST UPDATED: November 22, 2025 at 9:25AM

Decoupling Failure to Build the Psychological Safety Net for Risk-Taking

GUEST POST from Chateau G Pato

Every organization proudly declares its commitment to innovation. Yet, when you look closely at the annual performance review process, the budgeting models, and the criteria for promotion, you often find a subtle, yet powerful, mechanism for punishing mistakes. This disconnect is the single greatest inhibitor of meaningful change. The moment an employee realizes that an experiment that fails translates into a personal failure on their record, they will immediately stop taking the calculated risks necessary for true breakthrough innovation.

The solution is not just to tolerate failure — that’s passive and often meaningless in practice. The solution is to actively Decouple Failure. This is the deliberate organizational practice of separating the inevitable, often beneficial, negative outcome of a well-executed innovation experiment from the professional integrity, compensation, and career trajectory of the team and individuals who ran it. It’s about building a Psychological Safety Net beneath every strategic risk, ensuring that the person is protected even when the hypothesis is invalidated.

If we treat every “failure” as a crucial, expensive data point, then the team that generated that data point successfully performed their job. This human-centered perspective shifts the focus from avoiding mistakes to maximizing learning velocity — the speed at which we gain definitive, actionable knowledge.

The Three Pillars of Decoupling Failure

To institutionalize this psychological safety net, organizations must implement changes across three core cultural and structural pillars:

1. The Language Pillar: From Failure to Learning

The words leaders use shape the culture of risk. Leaders must banish language that equates an unsuccessful result with incompetence. Instead of asking, “Why did this initiative fail?” ask, “What definitive market or technical data did we learn from this prototype, and what is the cheapest next step?” We must formalize the “failure report” not as a punitive document, but as a Learning Dividend Document, celebrating the knowledge gained and the hypothesis invalidated. Crucially, leaders must clearly distinguish between a failure of hypothesis (good, valuable data) and a failure of process (negligence or carelessness, which remains unacceptable).

2. The Structural Pillar: Budgeting for Learning Capital

Innovation budgets must be structured not as rigid spending plans, but as pools of learning capital. Allocate specific, defined, and ring-fenced funds purely for experimentation where a negative outcome is anticipated and acceptable — the “safe-to-fail” zone. Critically, these expenditures should be accounted for as R&D Learning Costs, not Project Overruns or Losses, thus permanently decoupling them from operational P&L performance metrics that determine bonuses and budget health.

3. The Leadership Pillar: Rewarding Process Over Outcome

Leaders must stop rewarding heroic, chance-driven successes and start rewarding rigorous process and high integrity. The highest praise should go to the team that identified an unnecessary risk early, stopped the experiment before it became too expensive (the concept of failing fast), and clearly articulated the market or technical insight gained. When promotion or compensation is tied to demonstrating intentional risk-taking and disciplined, transparent learning, the culture begins to shift from passive avoidance to active, scientific exploration.

Key Benefits of Decoupling Failure

When an organization successfully decouples failure, the following powerful advantages emerge, driving both innovation and employee trust:

Increased Risk Appetite: Teams are emboldened to test truly disruptive ideas (the 10X ideas), knowing the career consequences are strictly limited to the budget of the experiment itself, not their professional standing.
Accelerated Time-to-Insight: By actively celebrating early stopping, teams gain crucial market data much sooner, preventing months or years of expensive investment in projects that were flawed from the start.
Enhanced Psychological Safety: Trust dramatically increases, leading to more open communication, better transparency around potential problems, and the earlier flagging of risks to leadership.
Improved Talent Retention: High-potential employees who seek challenging, exploratory work are far more likely to stay in an environment where disciplined risk-taking is valued and career trajectories are protected.
Reduced Cognitive Load: Employees spend less time managing their internal career risk profile and more time focusing creative energy on solving complex customer problems.

Case Study 1: The Fortune 500 Bank and the Innovation Sandbox

Challenge: Stagnant Digital Offerings Due to Internal Risk Aversion

A major bank recognized that its internal approval processes and metrics were meticulously designed for loss prevention, not innovation. Any project that failed to generate positive ROI in its first year was subject to intense scrutiny, directly impacting the managing director’s bonus and future career prospects. This culture led to teams exclusively pursuing incremental, safe projects (e.g., small app updates) and actively avoiding disruptive fintech ideas (e.g., blockchain applications).

Intervention: Decoupling via the “Innovation Sandbox”

The bank established an Innovation Sandbox, a ring-fenced organizational unit given a specific annual budget for Proof-of-Concept (POC) Experiments. Key characteristics included:

Clear Mandate: The Sandbox’s official goal was defined as “Generate 10 critical learning dividends (POC successes or failures) with a maximum investment of $50,000 each.” The goal was not profit or revenue generation, but knowledge acquisition.
Decoupled Metrics: The success of the Sandbox director was measured entirely on the quality of the insights gained and the speed of the failure (the lower the cost of the unsuccessful POC, the better the performance rating).
Personnel Protection: Employees seconded to the Sandbox were guaranteed in writing that the P&L results of their experiments would not factor into their annual review, bonus calculation, or promotion track.

The Human-Centered Lesson:

The Sandbox rapidly became a hotbed of experimental activity. Within 18 months, the team ran 30 experiments, yielding 25 “failures” that provided invaluable, cheap data on consumer reaction to new payment methods and blockchain applications. Because the failures were decoupled from career punishment, teams enthusiastically killed bad ideas early, saving the bank significant resources. The five successes, fueled by the learning from the failures, led to the bank’s first genuinely disruptive digital product in a decade, demonstrating that protection of the innovator is the key to breakthrough success.

Case Study 2: The Manufacturing Firm and the R&D Post-Mortem

Challenge: High Cost of Delayed Failure in Product Development

A large industrial manufacturer suffered from a cultural affliction: R&D teams often knew months in advance that a new, complex product design had major technical flaws, but they feared reporting the bad news to senior leadership. Instead of stopping, teams would “over-engineer” costly workarounds and delay acknowledging the failure, resulting in millions of dollars wasted before the project was finally cancelled late in the cycle (a classic failure of process driven by fear).

Intervention: Decoupling via the “Learning Credit” System

The firm formalized a Learning Credit System and redesigned its mandatory post-mortem process into a Learning Review.

Learning Review Process: Any project officially cancelled before reaching Stage Gate 3 received an automatic “Learning Review” (not a punitive audit). The team was publicly celebrated if they could prove they saved the company money and time by failing fast and clearly articulating the data-driven reason for stopping.
Credit System: Team leaders and core members received “Learning Credits” toward professional development or additional small-scale experiments, specifically for demonstrating early, high-integrity reporting of a failure of hypothesis.
Leadership Modeling: The CTO began publicly and formally celebrating (via internal video and memos) the project leads who delivered the most actionable negative data, reinforcing that the value lay in the rigor and timing of the testing, not the positive result.

The Human-Centered Lesson:

The cultural shift was dramatic and immediate. Teams started reporting bad news weeks or months earlier. The culture transformed from one of “cover up the flaw” to one of “document the data and save the capital.” The decoupling allowed engineers to act with high integrity — they were now rewarded for saving the company money and intellectual capital by stopping a flawed project quickly. The result was a 40% reduction in costly late-stage project cancellations and a significant boost in employee engagement and trust.

Frequently Asked Questions About Decoupling Failure

1. What is the fundamental concept of Decoupling Failure?

Decoupling Failure is the deliberate strategic practice of separating the negative outcome of an innovation experiment (the failed test, prototype, or idea) from the professional evaluation, compensation, and career trajectory of the innovator or team that conducted the experiment.

2. How is Decoupling Failure different from simply “tolerating” mistakes?

Tolerating mistakes is passive; it accepts an error after it happens. Decoupling is active and intentional. It structures the organization (through budgets, language, and performance metrics) to expect, fund, and reward learning generated from calculated risk-taking, turning a negative outcome into a valuable, protected asset (a “Learning Dividend”).

3. Does this model encourage carelessness or recklessness?

No. Decoupling failure rewards intentional risk-taking and rigorous process, not carelessness. Leaders must clearly distinguish between a failure of process (sloppiness, negligence, ethical lapse) which is always unacceptable, and a failure of hypothesis (a well-designed test proving the idea won’t work), which is highly valuable and protected.

The Human-Centered Call to Action

Innovation is inherently messy, unpredictable, and often wasteful — if you only measure success. But if you measure learning velocity and integrity of testing, that perceived waste becomes a highly efficient investment in future success. The most potent tool a human-centered change leader has is not a spreadsheet, but a culture built on trust and psychological safety.

By actively decoupling the experiment’s outcome from the innovator’s fate, you give your teams the greatest permission slip of all: the freedom to try and the psychological safety to stop when the data demands it. This is how you transform a risk-averse culture into an Exponential Learning Engine.

“If you want breakthrough success, you must first design a system that protects the people who deliver the necessary data of failure.”

Your first step toward Decoupling Failure: Identify a specific, small-scale innovation initiative currently underway (a prototype, a pilot, a market test). Review the budget line for that project and ask: “Is this expenditure treated as a cost that must result in profit, or is it treated as a budgeted cost of learning?” If the answer is the former, work immediately with finance to ring-fence a portion of that spending as “Learning Capital,” and publicly state that the success of the project manager will be measured by the rigor and speed of their testing, not the P&L result. Document the key learning gained from the next negative outcome as a formal “Learning Dividend.”

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Augmented Ingenuity

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How AI Elevates the Art of Human Questioning

LAST UPDATED: November 20, 2025 at 12:37PM

Augmented Ingenuity

GUEST POST from Chateau G Pato

In the vast landscape of innovation, the quality of the answer is always constrained by the quality of the question. For centuries, breakthrough ideas — from the theory of relativity to the invention of the internet — began not with an answer, but with a profoundly insightful question. Now, as Artificial Intelligence (AI) permeates every layer of the enterprise, we face a critical choice: Will we delegate our thinking to AI, or will we leverage AI to make us profoundly better thinkers?

The Human-Centered Change leader recognizes that AI’s primary value is not as a standalone solution provider, but as a colossal questioning amplifier. AI can process, connect, and synthesize data across domains faster than any human team, allowing us to move beyond simple data retrieval and focus on the meta-questions, the ethical challenges, and the non-obvious connections that drive true ingenuity. It transforms our human role from seeking answers to formulating brilliant prompts.

This is Augmented Ingenuity: the essential synergy between AI’s processing power and human curiosity, judgment, and empathy. It’s the next evolution of innovation, shifting the competitive edge back to the organizations that master the art of asking the most creative, complex, and impactful questions of themselves and their machine partners.

The Three-Part Partnership of AI and Inquiry

AI elevates human questioning by fulfilling three distinct, interconnected roles in the innovation cycle:

1. The Data Synthesizer: Eliminating Obvious Questions

AI’s first job is to eliminate the need for humans to ask — and answer — the simple, quantitative, or repetitive questions. AI rapidly sifts through vast, complex datasets (customer feedback, market trends, performance metrics) to summarize the “what” of a situation. This frees human teams from tedious compilation and analytical bottlenecks, allowing them to jump straight to the high-value, strategic “why” and “what if” questions that require human empathy and foresight.

2. The Cognitive Challenger: Uncovering Blind Spots

Because AI processes information without the constraints of human bias or organizational orthodoxies, it excels at challenging our assumptions. By analyzing historical innovation failures, cross-industry patterns, or even ethical frameworks, AI can generate adversarial or non-obvious questions that we would never naturally think to ask. It provides an essential friction — a digital devil’s advocate — to ensure our proposed solutions are robust, our strategies are resilient, and our underlying assumptions are soundly tested.

3. The Creative Catalyst: Expanding the Scope

AI excels at taking a foundational question (e.g., “How can we improve customer checkout?”) and rapidly generating hundreds of related, increasingly distant, or analogy-based questions (e.g., “What checkout processes succeed in gaming? What friction points did early libraries face? How do autonomous vehicle transactions work?”). This exponential expansion forces human teams out of their functional silos and into adjacent creative spaces, turning a tactical query into a strategic, multi-disciplinary innovation challenge.

Key Benefits of Augmented Ingenuity

When organizations successfully embrace AI as a questioning partner, they fundamentally enhance their innovation capability, unlocking powerful, human-centered advantages:

Accelerated Insight Velocity: The time from initial problem definition to the formulation of an actionable, insightful, and strategic question is drastically reduced, shortening the front-end of the innovation funnel.
Reduced Cognitive Load: Human experts and leaders spend significantly less time compiling and organizing basic data, dedicating more time to applying their unique empathy, judgment, and Contextual Intelligence to high-level strategic challenges.
De-biased Innovation: AI challenges existing organizational orthodoxies and human cognitive biases, leading to the creation of more diverse, ethically considered, and resilient solutions.
Wider Opportunity Mapping: AI connects seemingly disparate market signals or scientific principles across sectors, revealing non-obvious innovation white space and emerging opportunities that would be invisible to siloed human teams.
Enhanced Human Skills: By training humans to interact effectively with AI (crafting brilliant prompts, providing critical feedback), we sharpen the fundamental human skills of questioning, critical thinking, and synthesizing complexity.

Case Study 1: Pharma Research and the Question Generator

Challenge: Stalled Drug Discovery in a Niche Field

A major pharmaceutical company was stuck in a rut trying to find a novel drug target for a rare neurological disease. Human researchers were constantly asking variations of the same 50 questions, constrained by historical biomedical literature. The sheer volume of new genomics and proteomics data was too vast for the team to synthesize and connect to peripheral fields like materials science or computational physics.

AI Intervention:

The research team implemented a custom AI model focused on Question Generation. The model ingested all relevant public and internal data (genomics, clinical trials, and, crucially, cross-disciplinary literature). The AI’s task was not to propose drug targets, but to generate novel questions based on its synthesis. For example, instead of asking “Which gene is responsible for this mutation?” the AI posed: “What non-biological delivery system, currently used in nanotechnology or deep-sea exploration, could bypass the blood-brain barrier given this compound’s unique mass and charge?”

The Human-Centered Lesson:

The AI served as the Creative Catalyst. Its machine-generated questions led the human team down an entirely new, external path, linking the disease to a concept from materials science. The human researchers, freed from basic literature review, applied their deep biological intuition and ethical judgment to vet the AI’s prompts and refine the resulting hypotheses. This synergy led to the identification of a promising new delivery mechanism and significantly accelerated the drug’s path to clinical trials, proving that AI’s greatest contribution can be sparking a human moment of “Aha!” by asking the impossible question.

Case Study 2: The Retailer and the Customer Empathy Engine

Challenge: Decreasing Customer Loyalty Despite High Satisfaction Scores

A national retailer had excellent customer service metrics (CSAT, NPS), but their repeat purchase rates and loyalty were steadily declining. Their quantitative dashboards told them “what” was happening (low loyalty) but couldn’t explain the “why.” Human teams were struggling to move past the positive, surface-level survey data.

AI Intervention:

The retailer used an AI platform as a Data Synthesizer and Cognitive Challenger. The model ingested massive amounts of unstructured data: call transcripts, social media comments, chatbot logs, and product reviews. The AI was tasked with finding contradictions and unspoken needs. It didn’t output an answer; it output questions like: “Why do customers highly rate the product quality but use language associated with ‘stress’ and ‘fear’ during the checkout and returns process?” and “Why is the highest volume of negative sentiment related to products they didn’t buy, but considered?”

The Human-Centered Lesson:

The AI’s contradictory questions forced the human team to re-examine their assumptions about what drives loyalty. They realized customers weren’t loyal because the purchasing journey was stressful (returns ambiguity, complex filtering). The “stress” language was a key human insight the AI extracted. The team used this AI-generated question to conduct targeted qualitative research, finding that the highest loyalty was generated not by the initial purchase, but by the confidence of a smooth, frictionless return. This led to a complete, empathetic redesign of the returns policy and interface, which was marketed aggressively. Loyalty stabilized and then rose, demonstrating that AI can shine a spotlight on the hidden human dimension of a problem, enabling humans to design the empathetic, sustainable solution.

The Future of Leadership: Mastering the Prompt

The rise of AI fundamentally shifts the skills required for human-centered change leadership. Our value moves from having the answers to possessing the Contextual Intelligence — the knowledge of our customers, our culture, and our ethics — to ask the right questions. We must train ourselves and our teams to:

Be Specific and Strategic: Move beyond generic searches to asking multi-layered, hypothesis-driven questions of the AI, defining the guardrails of the inquiry.
Embrace Paradox: Use AI to generate contradictory hypotheses and explore them rigorously, leveraging machine-generated friction for deeper thought.
Filter with Empathy: Apply human judgment, ethical considerations, and cultural nuance to the AI’s generated prompts. We remain the ultimate arbiters of value.

AI handles the calculus of data; we handle the calculus of humanity. By consciously combining the machine’s ability to process everything with our innate human ability to question anything, we unleash Augmented Ingenuity, ensuring that the next great breakthroughs are born not of automation, but of amplified human curiosity.

“AI won’t steal your job, but a person who knows how to ask brilliant questions of AI will.” — Braden Kelley

Your first step toward Augmented Ingenuity: Take the most pressing challenge facing your team right now (e.g., improving a specific metric, reducing a particular risk). Instead of jumping to solutions, spend 30 minutes using an AI tool to generate 10 questions that challenge the underlying assumptions of that problem. Which of those 10 questions would you never have asked on your own, and why? That non-obvious, often uncomfortable, question is your starting point for breakthrough human innovation.

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Fix the Problem or Design it Out?

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Fix the Problem or Design it Out?

Let’s start with the problem.

According to The Plastic Pollution Coalition (January 3, 2017) – “It’s National Drinking Straw Day! Each day, more than 500 million plastic straws are used and discarded in the U.S. alone. Plastic straws consistently make the top ten list of items found, according to Ocean Conservancy’s International Coastal Cleanup data. In the last three years, plastic straws have climbed the list to the Number 5 spot.”

The Paper Straw Movement

In response to this growing problem, in January California made it illegal to give customers plastic straws unless they expressly request one.

Another way some restaurants have tried to to fix this problem has been to replace plastic straws with paper straws.

Or then there is the tasty fix to the problem, the cookie straw.

Starbucks Cookie Straw

But there is another way to approach problem solving, and that is to design out the problem instead of trying to fix it.

Recently a barista at Starbucks accidentally gave me a lid on my water cup that I wasn’t expecting.

I had heard that Starbucks was planning to reduce their use of the iconic green plastic straw, but I kind of assumed that meant they were shifting to paper straws like some other quick serve restaurants, but that is not what they have in mind at all.

Starbucks is instead planning to eliminate the plastic straw.

Instead of focusing on the straw they instead chose to focus on the lid and design it in a way that a straw isn’t even necessary.

Starbucks Sippy Cup

So, next time you’re wrestling with a problem and trying to solve it, look at it in a slightly different way just for fun, try asking yourself how you could design the product, service, or experience (or all three) in order to design out the problem.

You may or may not get to a more viable, desirable, and feasible solution than trying to fix the problem.

But, looking at the problem from a range of different perspectives is always worth the effort.

Keep innovating!

Accelerate your change and transformation success

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Why Change is Accelerating

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Why Change is Accelerating

In previous articles I’ve spoken about how the pace of change is accelerating, and how for many people (and organizations) things are changing so fast that they feel overwhelmed and that things may be changing faster than some of us humans are able to absorb. I’ve spoken about how we are in the middle of a period of discontinuity thrust upon us by the rapid advances in computing and mobile connectivity that have put a supercomputer in everyone’s pocket and a target on most organizations’ backs.

Why are things changing so fast?

Is it that we’ve hit some sort of inflection point never achieved before in human history that is allowing us to innovate and displace the status quo faster than ever before?

Maybe.

Have we reached some sort of perfect storm where the innovation curve has gone vertical and the singularity will be here tomorrow?

Probably not.

So if we are not necessarily innovating faster than ever before or destined to reach the singularity tomorrow and become one with machines, then what is creating the feeling that things are changing more rapidly?

One word…

“Expectations”

Changing Customer Expectations

It feels as if the world is changing faster than ever before because the expectations of our customers and our expectations as customers are changing faster than ever before. Why?

Because we as consumers are seeing better customer experiences enabled by digital technologies in parts of our personal lives and more efficient and effective business processes in parts of our business lives, we are now expecting every organization (not just companies) and every aspect of that organization to deliver an efficient, effective experience and information exchange in whatever channel we choose, whenever we want to experience it.

This incredible change in expectations is being thrust upon all organizations simultaneously and threatening the very existence of entities that have existed for dozens or even hundreds of years. This discontinuity has created immense technical debt for organizations large and small to overcome and the only way for an incumbent organization to recover and to survive in this new digital age will be to undergo a complete digital transformation.

This doesn’t mean creating a digital strategy to address one part of the organization or a single constituency, but a path to a complete transformation that brings digital approaches to both every part of the organization and its operations, but also to all of its constituencies, at the same time. This means re-imagining every system, every policy, every procedure, and every process as a digital native organization looking to enter and disrupt your industry might, and then make a plan for transforming yourself. This will require IMMENSE amounts of change, and is no small task given the 70% change failure rate, but it is the key to your organization’s survival.

The problem is that the organizational change thought leadership status quo isn’t up to the task of planning and executing the scope and scale of change required for existing organizations to survive the digital evolution underway. A new set of tools is needed. My new book Charting Change and the accompanying Change Planning Toolkit™ were designed to inspire a change revolution to free people from the tyranny of the blank word document and poorly planned change efforts.

Why the Pace of Change is Accelerating

Economics 101

Because the challenge we face is not a static one. Organizations that focus on catching up to where the customer is today and wedging their efforts into existing budget constraints are those that will find themselves falling further behind the curve of changing customer expectations.

No longer is it a victory to be seen by customers as ‘best in class’. No, now customers are expecting every organization to be ‘world class’. This means that increasingly customer satisfaction will be achieved only by providing one of the best experiences in the world. Talk about changing expectations!

And so given the time to develop new technology solutions, you should be aiming not to incrementally improve your current experience to get closer to the leaders in your industry, but instead investing in a solution that will anticipate what the best customer experience allowed by technology 12-18 months from now and start building that instead.

It’s Economics 101 all over again. In today’s reality, as most organizations seek to move up the customer experience supply curve, the customer experience demand curve is constantly shifting outward, leading your share of the market to wither and die unless you make the strategic investment required to actually shift your customer experience (CX) supply curve outward as well.

I’ve tried to capture the scenario in the figure above titled ‘Why the Pace of Change is Accelerating’. Most organizations when they see at Time⁰ that their level of customer experience is below Customer Expectations⁰ they invest in projects to increase their CX Supply⁰ up the CX Supply curve to CX Supply¹ thinking that they will then be meeting the customers’ level of expectations at Time¹. But that’s not how it works in the digital world of today, as customer expectations are changing (shifting upward) just as fast as the technology used to create better customer experiences. So, organizations that invest in moving up the CX Supply curve to catch up with current customer expectations find themselves continuously falling short of future customer expectations.

Conclusion

The reason nearly every organization follows this approach of climbing the CX Supply curve to close the gap on customer expectations is usually financial. Most managers are forced (or compelled) to try and close the gap with existing budgetary resources and by creating a digital strategy as part of these efforts. Very few organizations have visionary leaders willing to invest in a digital transformation and fundamentally re-think the architecture and capabilities the organization needs to successfully compete in a digital age. Very few organizations see how to properly use technology to fulfill the mission of the organization and to exceed customer expectations, and as a result create a shift outwards in the CX Supply Curve itself.

Choosing not to digitally transform your organization, creates the space in the market for new digital native organizations to enter and establish a beachhead and attack the incumbents.

At the same time, as our world and organizations continue to digitize this will result in decreasing variable costs and increasing fixed costs, leading to increased consolidation in many fragmented industries. Those organizations bold enough to invest in shifting their customer experience supply curves outward by undergoing a true digital transformation will improve their position to be a buyer instead of a seller as this consolidation occurs. So the real question is…

If we are living in an era of survival of the digital fittest, which side of the digital evolution do you want to be on?

I hope you’ll join the change revolution, get your copy of Charting Change today and check out the Change Planning Toolkit™!

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Measuring Change Readiness

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Measuring Change Readiness Are you and your organization ready for change?

Too often organizations define the change effort they want to pursue without first identifying whether there are people, resources, legislation, etc. present that must be in place before the change effort can begin. We will explore the circumstances you may want to explore before beginning any change effort and the areas to explore as potential prerequisites to the change program and its eventual success.

During the course of any change initiative many different challenges will appear, and the most successful change efforts will anticipate those challenges and have a plan for dealing with them. Part of that anticipation begins with identifying how ready the organization is for change.

The Change Planning Toolkit™ is designed to assist your change planning team by making the planning process easier with its collection of 50+ frameworks, methodologies and other tools.

One of the keys to change planning success is carefully identifying the prerequisites for change, including:

What must we know? (Knowledge)
What must we have? (Tools)
What must be completed? (Foundation)

This information is captured in one of the worksheets in the toolkit.

One other concept we should stop and discuss briefly is the idea of change saturation. This concept captures the idea that organizations in general, and certain individuals in specific, can only absorb so much change at one time. One frequent occurrence with change efforts is the situation where more than one project or larger change effort may require the same human, financial, physical, information or other resources at the same time. To become aware of this situation and to enable you to work to mitigate the effects of change saturation, you will want to build a heat map identifying the different timing, duration, and intensity of the different requirements all of the different projects and change efforts will place on the different types of resources within the organization. This too is a prerequisite.

Another prerequisite for change is having a deep understanding for what the current state looks like, including having answers for the following:

Who is feeling the pain? Pushing for the change?
What is the pain caused by the current state?
Where is the bulk of the change likely to take place?
When did the current state start causing pain?
Why is the change being pursued

These questions can be asked and answered during your change planning session, but they must be asked and the answers must be integrated into your examination of your readiness for this change BEFORE you actually begin the change.

An additional prerequisite for change is also having a deep understanding for what the desired state will look like, including answers for the following:

Who are we making this change for? Who will feel the greatest benefit from this change?
Where will the resources and support come from?
When do we need/want to complete the change process by? Is there a legal deadline?
What solution would we like to see in place?
Why is this solution better than the status quo?

Finally, to be ready to pursue a change the organization must have people in place to look after each of the Five Keys to Successful Change and should be familiar with both the Architecting the Organization for Change framework and my PCC Change Readiness Framework (these are three of the free downloads from the toolkit).

My PCC Change Readiness Framework focuses on the psychology of key groups surrounding the identified change, the capabilities needed to successfully execute the change, and the organization’s capacity to tackle this change effort (along with everything else).

You will notice that I don’t speak about organizational psychology or culture in my PCC Change Readiness Framework. The reason I don’t highlight culture in the same way that many other people do is that in today’s more social, customer-centric business, we must look more broadly than the typical inward focus of company culture when it comes to identifying the readiness of not only employees, but leaders, customers, and partners too. Inevitably many of our change efforts will have some impact on one or more external groups (possibly even non-profit entities and one or more governments).

You will notice that within the PSYCHOLOGY box there is a common focus on the mindsets, attitudes, beliefs and expectations of the individuals. Culture is incorporated into the psychology realm by focusing on what the shared understandings are around the potential change, but more broadly too. And, finally you will notice that my PCC Change Readiness Framework highlights the need for successful change efforts to move towards gaining commitment to the change from leadership, acceptance of the change by employees, and a desire for the change from customers and partners.

Within the CAPABILITY box of my PCC Change Readiness Framework we must investigate whether our change effort has any regulatory or statutory implications and whether we are ready to adapt, adopt or influence the changes necessary in this sphere. We must also ask ourselves a series of questions:

“Do we need to get permission from anyone to do this?”
“What knowledge, skills, and abilities needed for this change do we already possess?”
“What knowledge, skills, and abilities needed for this change do we need to acquire?”
“What relationships do we possess that will be useful in advancing the change?”
“What relationships do we need to build to help advance the change?”
“What are the enablers of making this change successful?”

Within the CAPACITY box we have to look at where our resources are approaching, or have already achieved, change saturation. This means they are unable to productively participate in any more change efforts or adopt any more change. But we also have to look at the availability of our resources:

Human
Financial
Physical
Information
Executive Sponsors
Space in our desired communication channels

It is easy to take for granted that the organization will have the capacity to undertake your change effort, but often there are capacity constraints that you will run into, especially as the pace and volume of change increases inside an organization. The one that is easiest to overlook and fail to plan for, is making sure that you’re going to be able to communicate your change messages in your desired messaging channels (they may already be full).

There is a worksheet that goes with the PCC Change Readiness Framework that will help you capture information around the:

History
Capability
Capacity
Partners
Context
Leadership
Employees
Customers
Shared Understanding
Strategic Alignment (Commitment)
Cultural Alignment (Acceptance)
Brand Alignment (Desire)

EDITOR’S NOTE: I’ve gone ahead and created a free downloadable flipbook PDF for people to grab. It was inspired by Braden’s article titled Change the World – Step Two, which was the follow-up predictably to Change the World – Step One.

You will find these companion tools for the PCC Change Readiness Framework in the Change Planning Toolkit™ to download for printing and use in your collaborative exploration of your change readiness.

In my next book Charting Change we will investigate additional aspects of change readiness and have a special section from one of my invited guest experts in the book, Beth Montag Schmaltz of PeopleFirm looking at several topics including change fatigue, where the change threshold lies, why people resist change, how to reduce change fatigue, how to build change capability, what change capable employees look like, and how you can embed change behavior into the very fabric of your organization.

The book is available for pre-order, and has received several strong endorsements, so I hope you’ll pick up a copy (or one for each member of your team). You can find more information on the Charting Change book page.

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The Pyramid of Results, Motivation and Ability

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Changing Outcomes, Changing Behavior

Pyramid of Results, Motivation and Ability

by Braden Kelley

When engaging in a change effort it is important to focus not on outputs but on outcomes. The difference is sometimes subtle for people, but the biggest difference is that outputs are usually activity-based where outcomes are behavior-based.

There are several good behavior modification frameworks out there including the Six Boxes framework from Carl Binder, the Six Sources of Influence framework from VitalSmarts, and the Results Pyramid® from Partners in Leadership that start with the desired performance changes, results or outcome shifts and work backwards.

Six Boxes Approach - Carl Binder

Six Boxes Approach – Carl Binder

Potential Benefits of Using the Six Sources of Influence

The Six Sources of Influence framework from VitalSmarts, a framework designed for personal change has some usefulness as we look at organizational change. Here are some of my thoughts on how this personal change framework is relevant, centered on the fact that successful change happens one individual at a time. The Six Sources of Influence framework looks at motivation and ability on one axis, and how they are affected across three other variables, which include:

Personal
Social
Structural

Taken together they form the Six Sources of Influence (see the Motivation Ability Worksheet in Figure 1) and can be used to change behavior one individual at a time. And it is from these changes in behavior that the transitions towards the new way of doing things begin to happen.

Figure 1

To utilize personal ability to influence the change will require teaching people the new skills to be successful at the new way of doing things. Consider breaking up the learning into short intervals where you can give people immediate feedback and prepare for people to have regressions back to the status quo. Work to identify those moments where people will be most tempted to regress to the status quo and create strategies that reinforce the new way of doing things.

To influence the change through personal motivation will require visualizing the change for people and utilizing physical and other cues (including vivid storytelling) to help reinforce that the change is desirable. Help people see, feel and believe in the new way of doing things (the desired state).

Social motivation can be used to influence change adoption by turning accomplices (status quo advocates) into friends (people practicing and supporting the new way of doing things), while any attempt to use social ability as an influencer for change adoption will require open and honest conversations to transform people from accomplices into friends .

Finally, utilizing structural motivation will require selling the problem in a way that people are influenced to abandon the status quo (visualize it, prototype it, etc.) and structural ability can be used to motivate people by changing the physical environment to reinforce the change. Instead of using a stick to motivate people to change, consider using carrots and the threat of losing carrots. It’s a slight twist away from using a stick, but it’s a powerful one. Finally, reward small wins and use incentives (carrots) in combination and in moderation.

Devotees of the Six Sources of Influence may find the free Motivation Ability Worksheet useful.

Using the Results Pyramid® to Create New Results

The Results Pyramid® framework from Tom Smith and Roger Connors’ book titled Change the Culture, Change the Game focuses on the importance of building a culture of accountability. Leaders can accelerate the change and results that they seek by working with the bottom half of the pyramid (“beliefs” and “experiences”). The Results Pyramid® has four main components that I would love to show below in Figure 2 but can’t:

Figure 2 would have gone here

Transformational change is most often lasting and sustainable in achieving the desired new results when leaders work to change the beliefs and experiences that people have and ensuring that people begin having new experiences that lead to new beliefs that lead to new actions that ultimately support the desired new results.

I was trying to help bring additional readers to the authors via the Results Pyramid® Worksheet, but it didn’t quite work out, so you’ll have to do without the visuals and imagine how the tool from Change the Culture, Change the Game could be used to:

First focus on identifying the new results that the group wants to achieve after making the change.
Second, ask employees and partners what new experiences they think that people will need to have in order to not only begin to leave the old way of doing things behind, but to both support the new results you want to achieve AND to help them believe the organization is serious and committed to the new results and that the leadership can be trusted.
Third, ask what new beliefs they think that people will need to have in order to commit to leaving the old way of doing things behind and prepare them to take new actions.
Finally, ask what new actions they think that people will need to take in order to achieve the new results that you are hoping to have in the desired state.

In most cases you will find that your current set of experiences, beliefs, actions, and results have achieved a sort of equilibrium or alignment and that one of the keys to achieving successful change is to move from your current state of equilibrium or alignment to a new set of experiences, beliefs, and actions that create a new state of equilibrium centered around your new results. By identifying where you want to move the top of the pyramid, your can start moving the base of the pyramid followed sequentially be the layers above it, and in doing so, prevent the pyramid from toppling over.

Potential Benefits of Using the Results Pyramid®

The Results Pyramid® is based on the idea that too many organizations focus on the results they want to achieve in the shift from the current state to the desired state and that just by communicating the desired results that the organization will see these new results manifest. But, the reality that the Results Pyramid® captures is that in order to achieve a shift from the current state to the desired state, and to achieve a new set of results, you must do more than define the new results you want to achieve. And you must provide a new set of experiences, beliefs, and actions that will help you achieve those results. The other key component of the Results Pyramid® theory is that too often companies demand new actions to get new results, but the truth is that these four things (results, actions, beliefs, and experiences) are organized like a pyramid and you can’t just move the top of the pyramid without also moving the supporting layers as well.

Meaning, that to create a shift in results (or outcomes), you must create a new set of experiences that lead to a new set of beliefs that lead to a new set of actions that result in the new results that you are hoping for as a result of your change effort. And of course by planning out consciously the shift in results that you’re trying to achieve, you can work as a change planning team to identify the new experiences, beliefs, and actions that you need to create in order to achieve the new results

I find this a useful tool to consider using as you analyze the desired behavior changes and new outcomes you are seeking to achieve with your change effort as you go through your change planning meetings or off-site.

Devotees of the Results Pyramid® would have found the Results Pyramid® Worksheet useful but, sigh, you can’t see it.

Conclusion

In this article we looked at the role of changing behaviors in achieving changed outcomes, and how we might use a couple personal behavior modification frameworks, the Six Sources of Influence and the Results Pyramid® to help us organize our conscious attempts to modify the behavior of individuals as part of our attempts to achieve our desired group behavior change and to ultimately to achieve the intended successful outcomes of our change effort.

So, check out the work of Carl Binder and grab yourself copies of Change the Culture, Change the Game and Change Anything and get started!

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