Disrupt Yourself

How do you continue growing in a world that rewards comfort and punishes change? In her book on personal disruption, Whitney Johnson argues that growth demands deliberate self-disruption—choosing to leave the familiar S-curve of mastery to begin climbing a new one. She reframes reinvention not as chaos but as a disciplined cycle of experimentation, courage, and learning. This framework draws from Clayton Christensen’s theory of disruptive innovation and applies it to individuals and teams.

According to Johnson, you move through three predictable phases on every learning curve: the slow and uncertain launch, the exhilarating steep climb, and the comfortable plateau where growth taps out. To keep advancing, you must repeatedly jump to new curves at the moment of mastery. Each transition—though uncomfortable—is essential for sustained relevance and vitality.

The S-Curve as a Map of Growth

The S-curve, borrowed from diffusion of innovation theory, models both corporate and personal growth. At the base, progress feels glacial: you’re forming new neural pathways, not seeing visible results. Persistence and feedback move you into the steep acceleration phase where learning compounds. Eventually, incremental improvement tapers off as the brain automates what you’ve mastered. That plateau is the signal—not failure—that it’s time to disrupt yourself again. Neuroscience supports this: as the basal ganglia automates routines, the brain seeks novelty for renewed engagement.

Disruption as an Iterative Experiment

Personal disruption integrates seven intertwined levers: (1) start on the right learning curve, (2) play to your distinctive strengths, (3) embrace market—not competitive—risk, (4) use constraints to catalyze creativity, (5) battle entitlement, (6) step back to slingshot forward, and (7) be driven by discovery rather than rigid planning. Together, these form a system where progress comes from deliberate design, not luck. Each lever reinforces the others: strengths clarify where you should take risk, constraints accelerate feedback, and humility keeps you open to learning.

From Wall Street to Reinvention

Johnson’s own story illustrates this arc. Leaving her successful Wall Street analyst job, she plunged to the bottom of a new curve, launching a magazine and later joining Clayton Christensen’s investment firm. Early ventures failed but delivered the insights, networks, and purpose that fueled her later success as a thought leader on disruption. Her journey demonstrates that right risks (experiments designed for learning) are microdisruptions that compound into significant reinvention.

The Function and the Emotion of Growth

Behind every shift lies a dual motivation: the functional job of earning or advancing, and the emotional job of feeling valued, purposeful, or alive. Many stagnate not because they’re underpaid but because their emotional job is unfilled. Clarifying both before you leap ensures disruption serves both your head and heart. This framing—adapted from Clayton Christensen’s Jobs to Be Done theory—helps you evaluate whether a move truly aligns with what you’re “hiring” it to do.

Learning to See Failure and Constraint as Fuel

Across stories—from Kay Koplovitz founding USA Network to Linda Descano reimagining her path from geology to finance—failure and constraint emerge not as setbacks but as creative accelerants. When resources, time, or status are limited, the brain engages differently, generating novel solutions. Conversely, entitlement—the expectation that rewards should continue without learning—kills innovation. Gratitude, humility, and curiosity keep people adaptive across disruptions.

Ultimately, personal disruption is the lifelong skill of re-creation. It’s less about risk-taking heroics than about mastering the science of adaptation: defining the right curve, testing assumptions quickly, measuring progress by learning velocity, and showing up consistently enough for compounding growth to take hold. Johnson’s framework merges psychology, neuroscience, and business strategy into a roadmap for those who choose evolution over inertia.

Every journey of reinvention starts at the bottom of an S-curve. Here, progress feels nonexistent, effort high, and confidence low. Whitney Johnson compares this to learning a new language or role—your brain is wiring new circuits, and every action feels like swimming upstream. Recognizing this phase as normal prevents premature quitting. Neuroscience shows that as your brain chunks patterns via the basal ganglia, execution accelerates exponentially until mastery flattens growth at the top.

The Three Phases of the Curve

• Launch phase (bottom): full of uncertainty. Measure learning, not output.
• Acceleration phase (middle): growth compounds; experiments yield confidence.
• Mastery phase (top): comfortable but stagnant; plateau invites the next disruption.

Leaders like Linda Descano and Tom McGuire embody the principle. Both rotated through diverse roles—finance, communications, systems—to climb multiple curves, staying fresh by choosing discomfort repeatedly. Their stories emphasize patience and self-compassion in early struggle, and vigilance at the top where complacency lurks.

Practical Rule

If you feel bored or effortless, you’re at the top of your curve. Seek a new one.

How Managers Use the Curve

For leaders, S-curves map team composition. A healthy organization balances people at all stages—novices stretching, contributors accelerating, and experts plateauing. Managers should rotate top performers into new challenges before stagnation erodes engagement. The S-curve thus becomes a diagnostic for talent mobility and culture vitality.

(Johnson echoes Carol Dweck’s growth mindset here: learning thrives when effort is reframed as building capacity, not proof of failure.)

In short, every jump requires courage and design: define learning metrics, track small wins, and treat discomfort as data. When you internalize the S-curve logic—accepting the awkward launch and planning for the plateau—you turn disruption from a crisis into a repeatable pattern of renewal.

Disruption without discernment is recklessness. Johnson distinguishes between competitive risk—fighting incumbents in known markets—and market risk—creating new demand where none is certain. Counterintuitively, market risk is usually the safer play when you want a steep new learning curve. It offers room to test, learn, and lead without being crushed by established rivals.

Competitive vs. Market Risk

Competitive risk pits you against entrenched players with scale and resources. Market risk asks you to hypothesize new value and validate it. Christensen’s disk drive research found companies taking market risk succeeded six times more often than those tackling established markets. The same principle applies personally: Amy Jo Martin, for example, created the NBA’s first digital media role before anyone else imagined one, turning uncertainty into advantage.

How to Choose Smart Risk

• Frame the move as an experiment—state a clear hypothesis and success/failure signals.
• Bound the downside—calculate what loss is tolerable and reversible.
• Align with your strengths—risk should amplify your comparative advantage, not expose your gaps.
• Track learning, not vanity metrics—define milestones that reflect insight gained.

Johnson’s own leap from Wall Street followed these rules: her magazine and investing ventures failed financially but produced priceless learning about entrepreneurship, networks, and purpose. Each was a bounded, hypothesis-driven experiment that propelled her to the next curve.

Right risk, then, is not gambling—it’s designing for maximum learning per unit of loss. Done well, it accelerates discovery and compounds confidence, setting the tone for every future disruption.

Most people fixate on weaknesses. Johnson asserts you grow faster by doubling down on your distinctive strengths—the few capabilities that create disproportionate value. These are not merely things you’re good at but those you do uniquely well compared with peers. When matched with unmet needs, these strengths become the engine of rapid ascent.

Finding Your Edge

• Track your high-output moments over two weeks to identify where you create the biggest impact.
• Solicit “speedback” from colleagues for patterns of excellence you overlook (Karen May’s method at Google).
• Look for unique combinations—like empathy + analysis—that competitors can’t mimic.

Where Strengths Meet Unmet Needs

Linda Descano repeatedly leveraged analytic and storytelling strengths to move across professions—from geology to finance to corporate communications—each shift building on the last. Rachael Chong’s Catchafire paired professionals’ underused skills with nonprofits’ needs, creating a market that didn’t exist. In both, the fusion of personal capability and market vacuum produced exponential growth.

Core Idea

You move up the curve fastest where your rare strengths solve meaningful problems.

Once identified, reorder your schedule so your strengths dominate your energy use. This is not indulgent—it’s efficient evolution. As psychologist Benjamin Hardy notes, environments that amplify strengths yield confidence and momentum, key ingredients for successful disruption.

Two forces determine how you adapt to disruption: how you respond to constraint, and how you handle success. Constraints—time, money, skill—ignite creativity when embraced as design limits rather than excuses. Entitlement—the belief you deserve outcomes without continuous effort—kills growth by dulling curiosity and eroding trust. Johnson shows how both dynamics shape your innovation potential.

Constraints as Creative Fuel

Borrowing from Adam Morgan’s A Beautiful Constraint, Johnson outlines how restrictions force prioritization and speed learning. Jaws became scarier when Spielberg’s mechanical shark failed. NASA’s LCROSS team found lunar water with leftover parts. Entrepreneurs like Kay Koplovitz turned setbacks—being excluded from equity profits—into missions to launch female-led accelerators. Each case shows limits can catalyze inventive problem-solving.

• Identify non-negotiables and cut the rest.
• Run low-cost experiments that yield fast data.
• If resources swell, impose artificial limits to maintain focus.

Fighting Entitlement with Humility

Entitlement manifests in small lapses—arriving unprepared, dismissing feedback, coveting recognition. Johnson draws from NASA’s Paul Hill and Harvard’s Donna Hicks to remind us that humility and gratitude are not moral niceties but strategic advantages. Teams thrive when members treat dignity and contribution as reciprocal currencies. Gratitude keeps learning loops open; entitlement shuts them down.

If constraints are accelerators and entitlement is a brake, mastering both determines your growth velocity. Transform lack into leverage, and privilege into responsibility; that dual mastery makes disruption sustainable.

The steepest growth curves often start with a step backward. Johnson calls this the slingshot principle: when you deliberately accept a lesser title, pay, or prestige to gain new capability or perspective, you preload momentum for greater future leaps. This reframes regression as investment.

Why Stepping Back Works

Leaders like Alissa Johnson, who left a higher-paying role to serve as Deputy CIO at the White House, prove the pattern. Her temporary pay cut yielded influence, network, and mission alignment that later translated into executive leadership. Similarly, companies like BRE Bank rebranded and reinvented themselves through side or backward moves to regain growth trajectories.

How to Evaluate a Downward Move

• Map learning outcomes and capabilities the move will build.
• Assess network expansion and exposure to decision-makers.
• Plan milestones and a clear horizon for reassessment.

Stepping back also means redefining metrics. The yardsticks of your last curve—salary, rank, recognition—mislead you when learning anew. Johnson urges people to track contribution, creativity, and consistency instead. The act of showing up daily becomes a proxy for future breakthroughs. Research backs this: volume of attempts predicts eventual success more reliably than confidence or early wins.

Key Metric

Measure learning velocity and presence—not titles or temporary performance spikes.

When you step back strategically and recalibrate what success means, every modest experiment counts as progress. You trade linear advancement for exponential learning—the hallmark of enduring disruptors.

Failure is the tuition of innovation. Johnson argues that giving failure its due—allowing space to grieve, debrief, and extract intelligence—is essential to sustaining disruption over time. Equally vital is cultivating a discovery-driven mindset where planning yields to testing, learning, and re-planning.

The Honest Psychology of Failure

Stories like consultant Elin Cherry’s firing, initially devastating, illustrate that setbacks often redirect energy toward healthier, more meaningful work. For Laura Hillenbrand, chronic illness became constraint-turned-gift: confinement deepened empathy and honed focus, producing bestsellers. Johnson insists these aren’t tidy success tales—they require curiosity and recovery rituals that turn pain into pattern recognition.

Discovery-Driven Growth

Borrowing from Rita McGrath’s strategy research, Johnson promotes discovery-driven planning: begin with assumptions, outline what must be true, test cheaply, and adapt. The Lewis and Clark expedition metaphor conveys it well—preparing but improvising en route. Data shows that 70% of successful ventures end up executing strategies different from what they planned, proving flexibility trumps prediction.

• Start with a reverse income statement—design the life or income you want, then test backward to feasibility.
• List key assumptions, define falsifiable tests, and track learnings at each milestone.
• View invalidated guesses not as shame but as data.

Leaders like Susan Cain (whose masterpiece Quiet emerged after endless revisions) and organizations like Southern New Hampshire University (which bet on online education long before competitors) embody discovery-driven execution. They learned and scaled by iterating, not adhering to predictions.

Ultimately, embracing failure and discovery transforms disruption from a series of leaps into a continuous feedback system. You stop chasing certainty and start optimizing for learning velocity—the truest sign you’re climbing, again, your next S-curve.