Ep.188 -The CEO Playbook: Start-Ups, Scale-Ups and Successful Exits
What is the primary challenge for employees transitioning from acquired small companies into larger organizations?
The real friction is not learning new systems or processes—it's the fundamental shift from direct control to influence-based leadership . In small companies, people make decisions directly and see immediate results. In larger organizations, their sphere of direct control shrinks, but they must learn to drive outcomes through influence, persuasion, and navigating complex organizational structures instead.
Controlling feels safer and more natural than influencing. When you work in a 10-person company, you can make a call and it gets done. You own the outcome directly. But as David Etchew explains in the episode , this doesn't scale past a certain size.
The challenge deepens when organizational culture itself operates differently. Larger organizations have established influence processes—stakeholder alignment, consensus-building, cross-functional buy-in—that feel slow and frustrating to people accustomed to autonomy. What feels like bureaucracy is actually the mechanism that allows a 1,500-person company to move coherently.
People don't naturally prefer influence over control. They would rather direct something themselves than convince someone else to do it their way. This psychological preference makes the transition a genuine identity shift, not just a skills upgrade. Etchew, who transitioned through companies of vastly different scales—from small ventures to the enterprise environment of General Electric—points out that this adjustment is one of the most underestimated barriers in post-acquisition integration.
"I could fail every day as long as I failed differently the day before I learned from it. The thing that drives me nuts is failing the same way twice."
David Etchew — CEO of Cyberbit, cybersecurity executive with over 20 years of experience building and scaling businesses from startups to major global organizations. His career spans senior roles at General Electric (where he led a $30 million business line as head of global security), Rapid7, Gemalto, and NISO, and includes CEO positions at Rangeforce before its acquisition by Cyberbit.
The paradox is that operating at greater scale actually increases impact , even if individual control shrinks. One decision at a 1,500-person company affects more people and markets than 10 individual decisions at a startup. But employees transitioning from acquisitions rarely frame it that way at first. They experience the loss of autonomy before they see the multiplied influence.
Etchew's perspective—learned through building businesses at every stage of growth and navigating this transition multiple times—is that organizations must actively help people reframe what success and decision-making look like. Without that reframing, talented people from acquired firms either leave, or they stay but spend years frustrated, a dynamic he explores in depth in this episode on scaling leadership .
How should organizations frame learning from unachieved goals and missed targets?
Shift the conversation away from whether targets were hit, and focus instead on what was learned. The real value of a missed goal lies in ensuring you never fail the same way twice —failing differently each time means progress, even when the original target wasn't achieved.
David Etchew implements this principle at board level through a structured quarterly presentation format. Each team presents three elements: what was accomplished, what was learned, and goals for the next quarter. The middle section—learning—is often overlooked in traditional board discussions, yet it's where the most important insights live.
When targets aren't achieved for substantive reasons—discovering unknown unknowns, encountering unexpected market shifts, or managing resource constraints—the learning becomes the primary outcome. As Etchew explains in the episode , organizations that treat missed goals as learning opportunities rather than failures cultivate resilience and adaptive capability.
Making learning the centerpiece of goal reviews
The difference between repeating failure and moving forward hinges on what Etchew emphasizes to his teams: "I could fail every day as long as I failed differently the day before and learned from it." This mindset reframes accountability away from rigid outcome targets toward intellectual rigor—did the team genuinely extract what could be learned from the attempt?
A goal that isn't achieved still has value if it generated insight. Unknown unknowns discovered during execution—market conditions that shifted, technical obstacles that surfaced, or dependencies that weren't anticipated—are legitimate learning outcomes. These insights directly inform strategy and planning for the next cycle, making them as valuable as hitting the original target.
The inverse problem, which Etchew names explicitly, is far more damaging: failing the same way twice. That pattern signals either that learning didn't occur, wasn't documented, or wasn't acted upon. A point discussed at length in the podcast is how high-performing organizations institutionalize this learning—making it visible, repeatable, and part of the quarterly cadence rather than a one-off conversation.
"I could fail every day as long as I failed differently the day before and learned from it. The thing that drives me nuts is failing the same way twice."
David Etchew — CEO of Cyberbit and cybersecurity executive with over 20 years of experience building, scaling, and leading businesses from startups to major global organizations. His career spans senior roles at GE (where he headed security globally and managed a $30 million business line), Rapid7, Gemalto, and CEO positions at NISO and Rangeforce before becoming CEO of Cyberbit following their acquisition of Rangeforce.
If you want to explore how this principle connects to team performance expectations, the full episode covers the relationship between acceptable failure rates and high-performing culture .
Structure quarterly reviews to explicitly address learning from unachieved goals, not just accomplishments and future targets.
Treat goals missed for substantive reasons—market shifts, unknown unknowns, resource changes—as legitimate learning outcomes.
The only failure that matters is repeating the same failure twice; differentiated failure with documented learning is progress.
Make learning visible and actionable at the board level so it informs strategy and prevents institutional blind spots.
What is the relationship between acceptable failure rates and high-performing team culture?
High-performing teams perform best with goals they have 80% confidence in achieving . At 100% confidence, goals are too easy and don't extract peak performance; at 50%, failure rates spike too high. With 80% confidence goals, one-fifth will inevitably fail—and this must not just be acceptable but actively rewarded in corporate culture.
The Confidence Paradox: Why Easy Goals Kill Performance
Setting goals your team is completely certain about achieving sounds safe, but it's a performance trap. When there's no risk of failure, there's no pressure to innovate or push boundaries . Teams coast instead of stretching. The goal itself becomes a floor rather than a challenge.
The opposite extreme is equally damaging. Goals where your team has only 50% confidence create chaos and demoralization. The failure rate becomes too high for psychological safety , and people stop believing in the objectives. Trust erodes when failure feels commonplace rather than exceptional.
The 80% Rule: Mathematically Embracing Failure
The sweet spot is 80% confidence—meaning one-fifth of goals will fail . This is the zone where teams are genuinely stretched, where they must think differently and execute at their best, yet where most objectives still succeed. As David Etchew explains in the episode , this statistical inevitability requires a cultural shift.
The math is clear, but the leadership implication is harder: leaders must actively accept risk on behalf of their teams . That means not just tolerating the 20% failure rate—it means rewarding it, learning from it, and building it into how the organization measures success.
"I could fail every day as long as I failed differently the day before I learned from it. The thing that drives me nuts is failing the same way twice."
David Etchew — CEO of Cyberbit. With over 20 years leading businesses from startups to global organizations at GE (where he ran a $30 million security business line), Rapid7, and other major enterprises, Etchew brings deep experience in scaling teams and navigating high-stakes decisions across diverse company stages.
Etchew's insight captures the core contract: failure is not the enemy—repeated failure of the same kind is. The culture must distinguish between productive failure (new learning) and reckless failure (ignoring past lessons) . This distinction is where the 80% rule becomes truly powerful. Discussed at length in this podcast , it's the difference between building a learning organization and a risk-averse one.
Why Corporate Culture Is the Real Constraint
The 80% confidence goal itself is a simple metric. The hard part is the culture that surrounds it. Most organizations are structurally wired to punish failure —even the productive kind. Bonuses, promotions, and reputations are built on success metrics that don't account for acceptable failure rates.
For the 80% rule to work, leaders must visibly reward teams that fail as long as they learned something new. Performance reviews must ask: "Did you attempt 80% goals? Did you fail differently than before?" This cultural inversion is explored in detail by David Etchew , who has implemented it across companies at different scales.
High-performing teams need 80% confidence goals—ambitious enough to extract peak performance, yet statistically likely to succeed four times out of five.
At 100% confidence, goals are too safe and don't drive innovation; at 50% confidence, failure rates undermine psychological safety.
With 80% confidence, one-fifth of goals will fail—and this must be accepted and rewarded, not punished.
The real challenge is building a corporate culture that distinguishes between productive failure (new learning) and reckless repetition of old mistakes.
How do large organizations like Amazon and AWS maintain innovation despite their enormous scale?
Large organizations stay innovative by applying the two-pizza rule—keeping teams small enough to feed with two pizzas (under 12 people) , a principle AWS used to launch S3 and transform cloud storage. Success also depends on writing the press release before building the product, granting autonomy between functions, and avoiding dependencies that slow decision-making.
Scale typically stifles innovation because bureaucracy, approval chains, and interdependencies slow execution. Yet companies like Amazon and AWS have cracked a different code: they treat innovation as a structural problem, not a cultural one. Etchew observed this firsthand while working with these organizations on encryption and cloud technologies.
The two-pizza rule emerged as a core organizing principle inside AWS. As explained in the episode , when AWS launched S3—arguably the foundational service that enabled modern cloud computing—they did it with only 12 people on the core team . That constraint forced clarity: what's essential, and what isn't? Small teams make faster decisions, own accountability completely, and sidestep the lengthy consensus-building that hamstrings larger groups.
Writing the press release before building the product
Another counterintuitive practice Etchew highlighted is beginning with the customer perspective. Instead of building first and writing marketing copy second, teams write the press release—the public-facing narrative of what the customer will experience—before a single line of code is written.
This disciplines the entire effort around what actually matters to the user , not what's easiest to build internally. It forces honest conversations: Is this feature worth building? Does it solve the problem we claim it solves? A product built backward from the customer promise is less likely to be a technical achievement that nobody wants.
The practice also acts as a forcing function for simplicity. A press release cannot dance around complexity or hide behind jargon—if you can't explain the value clearly in a paragraph, you haven't understood it yet.
Autonomy and minimal dependencies
At the organizational level, large companies often suffer from function-to-function dependencies that create chokepoints. One team needs approval from another, which needs input from a third, and the whole system grinds to a halt. AWS broke this by granting genuine autonomy between teams and business units , minimizing the need for cross-team coordination on every decision.
This doesn't mean chaos. It means each team owns its domain fully—including its failures. A team can choose its technology stack, decide its roadmap, and ship without waiting for central alignment, as long as they respect the contract they made with the customer (the press release) and don't break upstream services.
"I could fail every day as long as I failed differently the day before I learned from it. The thing that drives me nuts is failing the same way twice."
David Etchew — CEO, Cyberbit. A cybersecurity executive with over 20 years leading businesses from startups to major global organizations, Etchew has held senior roles at GE (where he ran a $30 million business line and served as head of security globally), Rapid7, Gemalto, and led transformations at NISO and Rangeforce before assuming the CEO role at Cyberbit following their acquisition of Rangeforce.
This philosophy underscores why large organizations don't have to sacrifice speed. The constraint isn't size—it's structure. The episode goes deeper into how teams navigate failure and learning , showing that even inside organizations with thousands of employees, individual teams operate more like startups than departments.
These principles—small team size, customer-first thinking, and functional autonomy—apply regardless of company scale. A five-person startup and a 50,000-person corporation can both benefit from the two-pizza rule if they respect the discipline it demands. Etchew shares concrete examples of how these practices play out in practice , including the tension between scaling and staying nimble.
What operational capabilities do small companies have relative to larger enterprises?
Small companies win through agility, closeness to customers, and faster decision-making . Large enterprises, by contrast, are built to execute their core operations at scale with exceptional reliability—because when you serve thousands or millions of customers, uptime and consistency become survival requirements, not nice-to-haves.
The operational advantage of small companies lies in their inherent flexibility. A startup can pivot its strategy in days; a global corporation with entrenched processes takes months. This speed translates directly into market responsiveness—small teams can adapt products, pricing, or positioning based on real-time customer feedback without navigating layers of approval.
Customer proximity—another small-company edge—means decision-makers hear directly from end users. As David Etchew discusses in The Conference Room episode , this direct line eliminates the distortion that occurs when feedback travels through multiple organizational layers in large companies. A small team can understand a customer's pain point in an afternoon meeting; a large company needs formal market research and stakeholder consensus.
Why Scale Demands a Different Operating Model
Large enterprises cannot operate with the same fluidity as startups—and that's by design. When a single software update reaches millions of users or a pricing change affects thousands of contracts across 56 countries, reliability becomes non-negotiable . One outage costs more than most startups earn in a quarter.
This structural reality forces large companies to build processes that can run the same operation thousands or millions of times with identical results. They invest heavily in governance, testing, and change management—not from bureaucratic impulse, but because the cost of failure scales with their customer base. A price book change at a major enterprise can take 90 days to roll out globally not because the organization moves slowly, but because that timeline reflects the rigor required to avoid errors across so many touchpoints.
The trade-off is explicit: consistency over speed . Large companies excel when execution at scale is the competitive advantage. They can serve markets where reliability, contractual precision, and regulatory compliance matter more than innovation velocity. But they cannot match the adaptability that keeps small companies alive in uncertain environments.
"I could fail every day as long as I failed differently the day before I learned from it. The thing that drives me nuts is failing the same way twice."
David Etchew — CEO of Cyberbit, cybersecurity executive with over 20 years building, scaling, and leading businesses across startups, high-growth companies, and major global organizations including GE, Rapid7, and Gemalto. His experience spans the full spectrum: from 10-person teams to enterprises running $30 million business lines, and from scaling through acquisition to managing organizational transformation at scale.
This philosophy—learning from every failure, never repeating the same mistake—captures the operational mindset that separates small companies from large ones. A small company can experiment, fail, iterate, and move forward in a single sprint. The full episode explores how leaders navigate these completely different operating environments as they move between organizations of vastly different sizes.
Neither model is inherently superior—each is optimized for a different reality. The startup wins by moving first; the enterprise wins by moving reliably. The key insight for leaders is recognizing which capability matters for their current stage and market position, rather than trying to force small-company agility into an enterprise structure (or enterprise discipline into a startup that needs to survive by pivoting).
Interestingly, the conversation goes deeper into how Amazon used the two-pizza rule to maintain small-team agility even inside a giant organization —a rare example of a company that has managed to blend both advantages.
What advantages does cross-functional leadership experience provide compared to deep specialization in a single domain?
Deep expertise in one area may open doors faster, but cross-functional experience builds context and empathy across teams —revealing that most friction between departments stems not from unwillingness to collaborate but from simple misunderstanding. A CEO's job is to ensure strategy and create conditions where people perform their best; that becomes possible only when leaders understand how different functions actually think.
Getting deep experience early in your career feels like the safest path. You master one domain, become indispensable, and doors open. But David Etchew's career tells a different story. After studying finance and economics with a strong technical inclination, he wanted to become a CIO—the classic specialist track. Instead, at GE's IT leadership program, he got exposed to the full breadth of how large companies work. That breadth changed everything.
The advantage isn't just knowing more; it's understanding why people in other functions make the choices they do . When a sales team resists a security requirement, or engineering pushes back on marketing timelines, the problem rarely is that one side doesn't care about success. As Etchew explains in the episode , dysfunction between functions almost always signals a gap in context—each side operating from different information, constraints, or assumptions.
That insight transforms leadership. When you've worked across functions, you don't assume malice or incompetence; you ask what context is missing. You build bridges faster because you can speak each team's language and explain to one side why the other side's concerns are legitimate. This empathy across silos is what separates functional leaders from leaders who scale.
"I could fail every day as long as I failed differently the day before I learned from it. The thing that drives me nuts is failing the same way twice."
David Etchew — CEO of Cyberbit, cybersecurity executive with over 20 years building and scaling businesses from startups to global organizations. Previously held senior roles at GE (where he ran a $30 million business line and served as head of security globally), Rapid7, Blue Voyance, and Gemalto, and led NISO and Rangeforce as CEO before joining Cyberbit following its acquisition of Rangeforce.
The specifics matter here. At GE, Etchew ran a large business unit and learned how decisions ripple across the organization. Later, when he ran a 10-person startup, he wore every hat. Then he scaled to 1,500-person companies, where organizational design itself becomes strategy. Each stage taught him not just skills but how different parts of a business think and operate . When he joined Cyberbit, those lessons let him move faster because he wasn't learning the basics of cross-functional tension for the first time.
There's also a hidden advantage for career progression. A specialist can get stuck—deep expertise in a narrow domain may limit where you can go. But cross-functional exposure keeps doors open. As discussed at length in this podcast , companies looking for leaders want people who can see the whole system, not just optimize one corner of it.
The trade-off is real: deep specialists may get certain technical jobs faster, and there are absolutely roles where deep expertise is non-negotiable. But for leadership—especially at the executive level—breadth of understanding becomes the limiting factor long before depth of knowledge.
To hear more about how Etchew navigated these transitions and what he learned about leading through scale and acquisition, listen to the full episode .
Ep.183 -Bringing Structure and Systems to Accidental CEOs
What first step should leadership take to support an accidental CEO or newly promoted operations manager in their transformation?
Leadership must slow down and bring the entire leadership team together to design the organizational chart jointly , rather than rushing to fill seats with the wrong people. This means explicitly defining what each seat holds—its responsibilities, accountabilities, required skills, mindset and capacity—before deciding who should occupy it.
When a high-performing specialist becomes a CEO or operations manager by accident, they often inherit both a business and immediate pressure to perform. But the instinct to act fast can backfire. As Val Coyne explains in the episode , the critical first move is not to solve today's problem, but to design tomorrow's structure.
This begins with a deliberate, collective conversation. Bring the leadership team into the conference room—literally and metaphorically—and ask hard questions together: What seats do we actually need? What does each role own? What skills, mindset and capacity does each person bring? Only after this clarity can you match the right people to the right seats.
Why clarity on seats comes before placement
Many organizations skip this step and pay for it later. When seats are not explicitly defined, accountability becomes murky. Two people may think they own the same responsibility, or nobody thinks they own it at all. This ambiguity compounds as the business scales.
By defining seats first—before you worry about who fills them—you create a shared map of the organization that everyone agrees on . This map becomes the reference point for every future hire, every delegation, and every performance conversation. It also reveals whether the right people are in the right chairs, or whether gaps exist that need to be filled from outside.
For an accidental CEO or new operations manager, this process is doubly important. It signals to the team that you're not just reacting to crisis; you're building a sustainable foundation. A point detailed in this podcast episode is that this deliberation also buys trust: the leadership team feels heard, and the new leader feels supported by clarity rather than alone with ambiguity.
"Technology always, always, always comes last. Typically, first comes process, second comes people, and third comes technology."
Val Coyne — Systems and Technology Strategist, Digital Transformation Advisory Consultancy. Val began her career in hospitality, managing a family restaurant in Italy before building and scaling a chain of restaurants, bistros, bars and bakeries in Australia's Sunshine Coast. She co-founded a software startup serving the disability sector, where she mastered systems-building in rapid growth, then launched her current consultancy. She now works with C-suite executives and new CEOs to align technology, people and process into coherent operating systems.
This principle applies directly to organizational design. Before you can assign roles and responsibilities effectively, you need clarity on your processes—what your business actually does and how it flows. Then you need to know your people—their strengths and gaps. Only then does technology, tools and systems design fall into place. Jumping to structural decisions without this foundation almost always leads to misfits.
The real value of slowing down lies in preventing costly restarts later. Organizations that rush to fill seats often find themselves reorganizing within six to twelve months, which erodes team morale and creates churn. A deliberate, upfront investment in seat clarity saves time and trust in the long run. To explore more about how new leaders can build robust systems once the structure is clear, listen to the full episode on Listenly .
What are the common challenges that accidental CEOs face when scaling their businesses?
Accidental CEOs—often high-performing specialists suddenly promoted to the top—suffer from lack of clarity, structure, and follow-through . They resist the systems and guardrails that scaling demands, and frequently sabotage transformation efforts without realizing it. Operations managers and COOs stepping up face a parallel trap: they keep wearing multiple hats from their previous roles instead of stepping fully into their new leadership identity.
The Three-Layer Problem of Accidental Leadership
The core issue is not incompetence—it's identity friction. When a strong individual contributor or specialist is thrust into the CEO seat, they remain psychologically attached to problem-solving on the front line . Delegation feels like abandonment. Systems feel like bureaucracy. As Val Coyne explains in the episode , this creates a shadow resistance: the accidental CEO consciously wants the company to scale, but unconsciously undermines the very structures that would make it possible.
The second layer affects COOs and operations managers stepping into leadership for the first time. They inherit a title but keep operating from their old role's playbook —still solving day-to-day fires, still being everyone's first point of contact. They wear too many hats to ever step into the full CEO's chair, and their team never learns to own their own problems.
The third layer is structural: most accidental CEOs have never been taught what a scaled organization actually looks like. They model what they've always known—the scrappy, founder-driven, high-touch approach that worked at $2 million in revenue. That exact approach becomes the ceiling at $20 million. Coyne walks through real examples in the full episode where process maps revealed 27 steps where three would do —a symptom of accumulated workarounds, not intentional design.
"Technology always, always, always comes last. Typically, first comes process, second comes people, and third comes technology."
Val Coyne — Systems and Technology Strategist, founder of a digital transformation advisory consultancy. She began her career managing hospitality operations across Italy and Australia's Sunshine Coast before transitioning into software development as a founding member of a disability-sector tech startup. She now works directly with CEOs and COOs to redesign operations for sustainable growth, starting always with people and process, never technology.
Where Resistance Hides
Accidental CEOs often frame their resistance as pragmatism: "We can't afford to slow down for process redesign" or "Our people won't accept all this structure." In reality, the resistance is usually unconscious self-protection . The founder or specialist fears that putting systems in place means they're no longer essential. If anyone can do the work, are they still needed?
This fear is often rooted in identity, not logic. The promoted executive has spent years building their reputation as the person who solves problems, ships fast, and gets things done. Stepping into a systems-thinking role feels like admitting defeat. Coyne discusses how to recognize and name this dynamic so teams can move past it together.
The software and tech stack often becomes a proxy battleground. Growing companies accumulate 30, 40, or even 50 different software platforms over three to six years—each one solving a real problem at the time it was added, but few ever integrated or audited. Accidental CEOs either resist consolidation ("We need all of these") or approve new purchases without ever decommissioning the old ones. Neither approach builds a coherent operating infrastructure.
Accidental CEOs stay psychologically attached to front-line problem-solving even after promotion, unconsciously resisting the systems that enable scale.
COOs and promoted operations managers fail to shed their old roles, continuing to wear multiple hats instead of stepping fully into leadership.
Process complexity grows unchecked—27 steps where three would suffice—because there's no structured review cycle or ownership of operational redesign.
Technology accumulation becomes a symptom of deeper resistance to governance and process discipline across the organization.
What is the responsibility framework for managing technology redundancy and software audits in growing organizations?
Technology sprawl is not a personal failing—it's a natural byproduct of business growth. The solution is assigning explicit accountability to a single owner (typically a finance or operations manager) who conducts annual software audits and quarterly reviews to track licenses, costs, usage, and feature changes across all departments.
As organizations scale, tools accumulate without governance. Growing businesses often end up with 30 to 50 different software platforms layered on top of each other, many running parallel to existing systems or purchased for features that emerge months or years after initial deployment.
The challenge intensifies because software vendors regularly roll out new capabilities. A tool purchased three to six years ago may now include 10 additional features that no one in the organization knows about—duplicating functionality already licensed elsewhere or solving problems the team thought they needed a separate tool to address.
Creating the Organizational Structure for Tech Accountability
The first step is to establish a clear organizational chart with defined roles and responsibilities . This isn't about blame; it's about clarity. Someone needs to own the software ecosystem across all departments, seeing patterns that individual teams miss because they operate in silos.
This owner is typically a finance manager or operations manager—someone who already has visibility across departments and understands both spending and operational workflow. They become the single point of accountability, preventing duplicate purchases and ensuring tools align with actual business needs. As discussed in the episode , this structural clarity transforms tech from a cost center chaos into an auditable operational layer.
The Rhythm of Software Audits: Annual and Quarterly Cycles
Accountability requires two distinct audit rhythms . The annual stock-take is comprehensive: audit every software subscription, license agreement, cost, and actual usage across the entire organization. This baseline reveals redundancy, unused tools, and opportunities to consolidate platforms.
The quarterly check is lighter but critical. It reviews whether new software has been purchased, what features or changes have occurred in existing tools, and whether usage patterns have shifted. This prevents the three-to-six-year drift where a tool evolves silently and the organization doesn't realize it's solving problems already addressed elsewhere.
Val Coyne emphasizes in this discussion that without this rhythm, organizations default to reactive firefighting—discovering redundancy only when budgets balloon or integration attempts fail.
"Technology always, always, always comes last. Typically, first comes process, second comes people, and third comes technology."
Val Coyne — Systems and Technology Strategist, Digital Transformation Advisory Consultancy. Val began her career in hospitality, managing a family restaurant in Italy and later a chain of restaurants, bistros, bars and bakeries in Australia's Sunshine Coast. She transitioned into technology as a founding member of a startup building software for the disability sector, where she learned to build systems in growing companies. She now works with C-suite executives and COOs to align technology, people, and process.
This principle directly informs the responsibility framework. Technology audits fail when organizations treat them as IT problems rather than operational and financial governance issues. The finance or operations owner isn't building or configuring systems—they're ensuring the organization has visibility and control over what's actually running, at what cost, and whether it's serving its original purpose.
The quarterly check also surfaces another layer: Has a tool added new features that the team didn't know existed? If Salesforce, Xero, or Google Drive rolled out an integration or capability that month, does it eliminate the need for a separate tool the organization is also paying for? This pattern recognition only happens with structured review cycles , not ad hoc complaints.
Assign accountability to a single finance or operations manager who owns the entire software ecosystem and reports on it regularly.
Conduct an annual comprehensive audit of all software subscriptions, licenses, costs, and usage patterns across departments.
Run quarterly reviews to catch new software purchases, feature releases, and changes in usage that might eliminate redundancy.
Remember that technology redundancy is a structural issue inherent to growth, not a failure of individual teams—the solution is organizational clarity and accountability.
How should organizations assess whether their technology stack actually supports their growth stage?
First, identify your growth stage —startup, grow up, scale up, established, or hyper growth—and match your tools to that phase, not the reverse. A startup doesn't need enterprise software like Salesforce because processes are still fluid. Second, audit how many software platforms you actually use and whether teams are truly using them; most organizations accumulate 30 to 50 different pieces of software without realizing existing platforms already contain the features they need.
Stage-First Assessment: The Foundation
The biggest mistake organizations make is selecting technology based on what competitors use or what the industry expects. Your tools must reflect where you are , not where you aspire to be in five years. A startup with founder-led operations has different needs than an established business with formal processes and multiple departments.
As Val Coyne explains in the episode , early-stage businesses often have agility as their competitive advantage. Implementing rigid enterprise systems too early locks you into structures that may not match how you actually operate. The flexibility to pivot and adapt—something easier with lighter software—disappears once you're invested in a massive platform.
The Hidden Software Audit: What You Don't Know
Most organizations don't know how much software they've accumulated. Conducting a full inventory reveals redundancy that consumes budget and creates confusion . Businesses often discover teams using Google Drive for what another department does with a paid platform, or realizing a feature built into existing software handles a problem they thought required a separate tool.
The pattern is consistent: software platforms gain 10 or more new features over 3 to 6 years that users never discover. This happens because teams don't revisit platform capabilities once deployment is complete. A quarterly check-in of your software inventory paired with one full annual audit prevents this waste, as detailed in this podcast .
"Technology always, always, always comes last. Typically, first comes process, second comes people, and third comes technology."
Val Coyne — Systems and Technology Strategist. Val brings over a decade of experience helping C-suite executives and accidental CEOs align their operations. She began her career building systems in hospitality, managing a family restaurant in Italy and later a chain across Australia's Sunshine Coast, before transitioning to technology as a founding member of a disability-sector software startup. She now consults with CEOs and COOs to ensure technology, people, and process work together as one integrated system.
This principle anchors the entire assessment. If you select technology first and then try to fit your people and processes around it, you've already lost. Process design and team structure must come first ; technology is the enabler that follows, not the foundation.
For a more detailed exploration of why this sequencing matters and how it transforms organizational outcomes, listen to the full conversation between Simon Lader and Val Coyne.
Align your technology to your current growth stage (startup, scale up, established, hyper growth) rather than choosing tools based on industry norms or future aspirations.
Most organizations carry 30 to 50 overlapping software platforms; auditing your inventory reveals redundancy and hidden feature overlap.
Software platforms accumulate features over years that users never discover; quarterly check-ins and annual full audits prevent budget waste.
Technology must follow process and people decisions, never precede them—selecting software first forces you into misaligned operations.
Why should process and people considerations come before technology in organizational transformation?
If you start with technology alone, you simply replicate your current inefficiencies with software and call it automation—but you haven't actually improved. Starting from process allows you to identify the person who knows how things actually work and where real improvements are needed , so you can introduce technology to support those refined operations rather than codify the broken ones.
Most organizations rush to implement software solutions without first examining how their work actually flows. You end up automating waste, building digital versions of broken processes, and creating more complexity than you had before.
The right sequence is deliberate: process first, people second, technology third. When you start with process, you're forced to ask hard questions about why a step exists at all. Is it necessary? Can it be simplified? Does it add value? This is where domain expertise becomes crucial.
As Val Coyne explains in the episode , the person doing the work every day—not the executive suite—often holds the answers to how operations can be refined. They understand the informal workarounds, the missing steps in documentation, and where bottlenecks really exist.
Process clarity reveals where people create value
When you map process first, you uncover who the actual experts are within your organization. A receptionist might be handling five undocumented tasks that no system captures. A warehouse supervisor knows three ways to accelerate packing that never made it into the manual. These insights only surface when you examine process before technology.
Once you understand the refined, optimized process and you've identified the people who'll drive it, only then do you select technology that supports those operations. A point detailed in this podcast is that many organizations accumulate 30, 40, or even 50 different software platforms without ever stopping to ask whether they're solving actual process problems or just piling on tools.
Technology should be the servant of your process and your people, not the driver of your transformation. When sequence is reversed, you end up with expensive systems that no one uses effectively, because they weren't designed around how work actually happens.
"Technology always, always, always comes last. Typically, first comes process, second comes people, and third comes technology."
Val Coyne — Systems and Technology Strategist at Digital Transformation Advisory Consultancy. After building restaurants and hospitality operations in Italy and Australia's Sunshine Coast, Coyne transitioned into technology as a founding member of a disability sector software startup. Her consultancy now works with C-suite executives and CEOs to align technology, people, and process in growing organizations.
The real cost of getting this wrong is hidden in accumulation. Over 3, 5, or even 6 years, a piece of software may gain 10 additional features that nobody on your team knows about—features you might have paid extra for that could solve problems you're still handling manually. But those features sit dormant because no one examined whether the software actually matched your refined process.
Val Coyne recommends a structured approach: conduct one full audit of your technology inventory and usage annually, with a smaller quarterly check in between. This keeps you honest about whether your tools are still serving your people and processes, or whether they've become legacy bloat.
Want to hear more about how to structure this transformation rhythm and avoid the trap of accidental CEO decision-making in growth? Listen to the full episode on Listenly .
Starting with technology alone replicates current inefficiencies with software instead of actually improving them.
Mapping process first reveals the people who hold crucial domain expertise and understand where real improvements are needed.
Technology should only be introduced after process is refined and the right people are identified to support it.
Most growing organizations accumulate 30–50 unintegrated software platforms without examining whether they solve actual process problems.
Conduct at least one full annual audit and quarterly check-ins to ensure technology continues to serve your refined processes.
What is the true definition of digital transformation beyond simply implementing software?
Digital transformation is not about buying new software—it's about examining and streamlining your actual operations first . If a process takes 27 steps, you need to simplify it before digitizing it; otherwise, you're just automating a broken workflow.
Most organizations approach transformation backward. They identify a problem, buy software, and expect the issue to vanish. Instead, what happens is a messy manual process gets replicated exactly in digital form , complete with all its original inefficiencies.
The correct sequence, as explained in the episode , is deliberate: process first, then people, then technology. You must step back and ask hard questions about why a task requires so many steps in the first place.
Why technology always comes last
Many accidental CEOs and growing businesses accumulate 30, 40, or even 50 different software platforms without ever auditing whether they actually use them or if they serve their real needs. Technology decisions get made in isolation, without a clear understanding of the underlying process that needs to be supported.
Val Coyne recommends a structured rhythm: one full software audit annually and quarterly check-ins to track inventory and actual usage. This prevents the common trap where a business subscribes to a tool years ago and loses track of it—or discovers that the software has added 10 new features that no one in the organization knows exist or uses.
As Val Coyne observes, "Technology always, always, always comes last. Typically, first comes process, second comes people, and third comes technology." This principle cuts through the noise of vendor pitches and marketing hype.
"Technology always, always, always comes last. Typically, first comes process, second comes people, and third comes technology."
Val Coyne — Systems and Technology Strategist. Val began her career in hospitality, managing a family restaurant in Italy and later a chain of restaurants, bistros, bars and bakeries on Australia's Sunshine Coast. She transitioned into technology as a founding member of a startup building software for the disability sector, where she first learned to build scalable systems. She now works with C-suite executives to align technology, people, and process.
The real work of digital transformation happens before any software license is purchased. It's the unglamorous work of mapping workflows, identifying redundancy, and redesigning operations for clarity. Only when that foundation is solid does technology become an accelerant rather than a burden.
To hear more about how to structure this transformation at scale, and the specific methods Val Coyne uses with her clients, listen to the full episode .
Digital transformation requires process simplification before technology implementation, not the reverse.
Growing businesses often accumulate 30–50 software platforms without auditing actual usage or relevance.
A structured rhythm of annual full audits and quarterly check-ins prevents software waste and keeps your tech stack aligned with real needs.
Technology is the third step—process comes first, people second—and acting on this sequence separates real transformation from costly automation of broken workflows.
Ep.186 -A Founder's Story: Building a Biotech Company From the Ground Up
What early challenges did Dr. Sherry Zhang face as an immigrant pursuing higher education in the United States?
Dr. Zhang's visa was rejected three times before she could start her PhD at Marquette University in Wisconsin; she arrived late for her start date, but her…
What is the vision behind the new AI-native health platform Dr. Sherry Zhang is building at Buck Institute?
Rather than asking the reactive question 'What's wrong with you today,' the platform asks proactive questions like 'Where is your health headed?' and…
How should founders structure internal communication to avoid meeting overload while maintaining alignment?
Dr. Zhang implements a cadenced communication structure: daily standups of 15 minutes for urgent issues and blockers; weekly touchbase meetings around the…
What is the minimum viable product strategy for early-stage biotech companies?
Listen deeply to your first and second customer personas to identify the one thing customers care about most , then build a lean product that addresses exactly that—nothing more. Avoid feature bloat and over-engineering before validating core customer needs; the MVP strategy is about focus, not compromise.
The foundation of product strategy for early-stage biotech founders rests on understanding customer urgency. Rather than guessing what features matter, founders must conduct structured conversations with potential customers to uncover their actual pain points. This isn't theoretical market research—it's direct, actionable feedback that shapes every engineering decision.
When Dr. Sherry Zhang built Genopalate, her personalized nutrition company that has since served more than 170,000 customers , she applied this principle rigorously. She focused on what was scientifically sound and commercially viable, avoiding the trap that catches many biotech founders: adding capabilities that sound impressive but don't drive revenue or solve the core problem.
Build a system to prioritize what absolutely matters
Early-stage biotech faces a unique pressure: the science is complex, the regulatory landscape is strict, and founders are often tempted to showcase their technical sophistication. This leads to over-engineering—adding features, running extra studies, or pursuing tangential innovations before the core product has proven its value.
Dr. Zhang emphasizes developing a system to focus on what absolutely matters for revenue generation and nothing else. This means saying no to secondary features, even good ones. It means resisting the urge to perfect every aspect before launch. The MVP strategy for biotech is not about shipping something incomplete; it's about shipping something focused.
As explored in detail in the full episode on Listenly , this discipline requires founders to make difficult choices about scope and trade-offs early on, before capital, team time, and scientific effort are sunk into features customers don't need.
"This drive in me to deliver world-class science and translate that into something useful and practical for everyday people is so strong that I think that will motivate me to learn new skills, to meet new people, to get on stage that I'll be nervous for, and raise funding."
Sherry Zhang — Executive Director of External Strategy and Partnerships at the Price Lab, Buck Institute for Research on Aging, and founder of Genopalate. Dr. Zhang is a first-generation immigrant scientist who arrived in the United States from China with three bags and $3,000. She earned her PhD in molecular biology from Marquette University and conducted obesity genomics research at Medical College of Wisconsin (MCW) under Dr. Ahmed Kaseba, who coined the concept of metabolic syndrome. Her commitment to translating rigorous science into practical solutions has shaped both her founding approach and her ongoing work in longevity and preventive health optimization.
One often-overlooked aspect of MVP strategy in biotech is the founder's own role in execution. Dr. Zhang ran Genopalate while maintaining a full-time faculty position, which forced ruthless prioritization. This constraint, while demanding, also prevented scope creep— a principle she discusses in depth on the podcast , revealing how resource limitation can paradoxically lead to stronger product-market fit.
Conduct structured customer conversations with your first and second personas to identify their single most urgent need before building anything.
Develop a decision-making system that ruthlessly prioritizes revenue-generating features and eliminates everything else—feature creep is the enemy of early-stage validation.
Avoid over-engineering and secondary innovations until the core MVP has proven traction with real customers.
Accept that resource constraints (time, capital, team size) can be a powerful forcing function for product focus and faster market validation.
How does leadership differ between academic research, startup founding, and established research institutions?
Scientists are trained to reduce uncertainty through data and hypotheses , while founders must navigate uncertainty as a constant reality. Dr. Sherry Zhang combines both skill sets to ask more audacious questions and build bigger ecosystems, applying scientific rigor to forecast health trajectories while remaining responsive to customer feedback and the complex, non-linear nature of real-world health journeys.
The scientist's approach versus the founder's mindset
In academia, leadership is anchored in hypothesis testing and peer validation. You design an experiment, collect data, reduce variables, and publish findings—each step builds on proven knowledge. This systematic approach creates confidence in decisions, but it can also slow innovation when real-world complexity demands speed .
Founding a startup inverts this model entirely. As a founder, you operate in perpetual ambiguity: your product may not exist yet, your market may shift weekly, and your team may change before you find product-market fit. Uncertainty becomes your default state, not a problem to solve first . You make decisions with 60% of the information, knowing you'll course-correct once you learn more from customers.
Zhang's experience bridges both worlds. When she founded Genopalate with a mission to help more than 170,000 customers make personalized nutrition decisions based on their DNA, she applied rigorous genomics knowledge from her PhD research at Marquette University while simultaneously learning to iterate fast based on market feedback. As she explains in the episode , her drive to "deliver world-class science and translate that into something useful and practical for everyday people" meant developing skills far beyond the laboratory.
Building ecosystems at Buck Institute
Now leading external strategy and partnerships at the Price Lab at Buck Institute for Research on Aging, Zhang demonstrates how hybrid leadership scales. Her current work applies scientific rigor to forecast individual health trajectories while building an AI-native platform that listens to customer needs and adapts to the messy reality of how people actually manage their health over time.
This isn't academia avoiding commercial reality, nor is it a startup sacrificing scientific integrity for speed. It's a deliberate fusion: the patience of peer review combined with the agility of startup iteration, the credibility of a PhD combined with the humility to learn from users. A point detailed in this podcast is that effective leaders across all three environments—academia, startups, and established research institutions—must ultimately ask the same question: How do I create value for the people I serve?
"This drive in me to deliver world-class science and translate that into something useful and practical for everyday people is so strong that I think that will motivate me to learn new skills, to meet new people, to get on stage that I'll be nervous for, and raise funding."
Sherry Zhang — Executive Director of External Strategy and Partnerships at Price Lab, Buck Institute for Research on Aging. Dr. Zhang is a first-generation immigrant scientist who arrived in the United States from China with three bags and $3,000. She earned her PhD in molecular biology from Marquette University in Wisconsin, conducted obesity genomics research at Medical College of Wisconsin (MCW) under Dr. Ahmed Kaseba (who coined the concept of metabolic syndrome), and founded Genopalate, a personalized nutrition company that has served more than 170,000 customers. She now leads AI-driven approaches to extending human lifespan and preventive health optimization.
If you want to hear more about how Zhang navigated the specific challenges of building a biotech company from zero—from visa rejections to running Genopalate while working as faculty at MCW to managing investor relationships— the full conversation on Listenly covers her complete founder journey and the lessons that shaped her leadership across all three environments.
Academic leaders reduce uncertainty through data; startup founders accept uncertainty as permanent and make decisions with incomplete information.
The hybrid approach—combining scientific rigor with startup agility—enables leaders to ask bolder questions and scale impact faster.
Translating science into practical value requires learning skills beyond your original discipline: marketing, fundraising, customer feedback loops, and rapid iteration.
Established research institutions benefit most when they adopt startup-like responsiveness to real-world complexity while maintaining scientific credibility.
What are the core mistakes first-time biotech founders make in team building and partnerships?
First-time founders must surround themselves with people who share their dream and align with their core principles and values , even when disagreeing on approach. A critical mistake is hesitating to terminate relationships that aren't working—dragging along misaligned team members or vendors rather than cutting ties quickly once the dysfunction becomes clear.
The foundation must be solid from the start
Building a biotech company requires making hard decisions about who stays and who goes. The instinct to salvage relationships or give people second chances can be costly. As Dr. Zhang explains in the episode , a company cannot be sustainable if built on a cracking foundation—and that foundation is the alignment of values and principles among core team members.
When you delay removing someone whose values don't align with the company's mission, you risk creating a culture where compromise on core principles becomes normalized. This cascades through hiring decisions, how you treat customers, and ultimately how you approach your science or product. Speed in terminating non-working relationships is not coldness; it's respect—both for the person and for the company's future.
The challenge many first-time founders face is emotional attachment or a sense of loyalty that outweighs objective assessment. Yet Dr. Zhang's experience building Genopalate, which served more than 170,000 customers making nutrition decisions based on DNA analysis, showed her that difficult personnel decisions early are infinitely easier than organizational dysfunction later.
"This drive in me to deliver world-class science and translate that into something useful and practical for everyday people is so strong that I think that will motivate me to learn new skills, to meet new people, to get on stage that I'll be nervous for, and raise funding."
Sherry Zhang — Executive Director of External Strategy and Partnerships at Price Lab, Buck Institute for Research on Aging. Dr. Zhang is a first-generation immigrant scientist who arrived in the United States from China with $3,000, earned her PhD in molecular biology from Marquette University, and founded Genopalate, a personalized nutrition company that has served more than 170,000 customers. She now leads AI-driven approaches to longevity research at one of the world's leading aging research institutions.
What makes this principle-alignment test truly valuable is that it surfaces disagreements early. In the full episode , Dr. Zhang emphasizes that people on your team don't need to agree on every tactic or strategy—but they must be united on why the company exists and what it stands for. That shared "why" makes navigating conflict productive rather than destructive.
Prioritize principle and value alignment over skills fit when building your core team; misaligned values compound over time.
Hesitation to terminate relationships that aren't working is a common costly mistake for first-time founders.
A company built on misaligned foundations cannot be sustainable—act quickly and decisively when dysfunction emerges.
Disagreement on approach is acceptable; disagreement on principles and core values is a warning sign.
How should biotech founders approach fundraising and investor relationships?
Trust building and finding aligned investors matter far more than speed in biotech fundraising. Rather than accepting funding too quickly, founders should conduct numerous coffee talks, test pitches repeatedly, and develop a system to filter what matters to both parties—because the number one job of a founder CEO is raising capital while maintaining relationships they won't regret later.
Why urgency can destroy biotech deals
Biotech companies face a unique financial pressure that most other startups do not. Funding requirements are far steeper —not just for research equipment and genome sequencing, but especially for talent with higher payroll expectations in specialized science roles. This constant tension between the need to generate revenue quickly and the need to avoid damaging long-term partnerships is what Zhang emphasizes as the central paradox of biotech fundraising.
Rushing into investor relationships out of desperation often leads to misalignment later. As Zhang explains in the episode , founders who prioritize speed over fit end up working with backers whose incentives, timelines, or expectations fundamentally conflict with the science itself.
The coffee-talk method: Testing before committing
Zhang advocates for a deliberate, low-pressure approach to investor conversations. Rather than formal pitch decks from day one, she recommends conducting numerous casual coffee talks where both founder and investor can speak candidly about goals, risk tolerance, and vision alignment. These conversations serve as a filter on both sides.
The founder learns whether an investor truly understands biotech timelines, scientific uncertainty, and the regulatory landscape. The investor gauges whether the founder has the resilience, clarity of purpose, and adaptability required to navigate a multiyear, capital-intensive journey. This mutual evaluation happens naturally in informal settings before either party commits.
Pitching repeatedly—to different investors, in different formats—also refines the founder's own thinking. Zhang's story shows that each conversation shapes how she articulates her science and its value, which strengthens her positioning for genuine partners later.
"This drive in me to deliver world-class science and translate that into something useful and practical for everyday people is so strong that I think that will motivate me to learn new skills, to meet new people, to get on stage that I'll be nervous for, and raise funding."
Sherry Zhang — Executive Director of External Strategy and Partnerships at Buck Institute for Research on Aging, and founder of Genopalate. Zhang is a first-generation immigrant scientist from China who arrived in the U.S. with three bags and $3,000. She holds a PhD in molecular biology from Marquette University and founded Genopalate, a personalized nutrition company based on DNA analysis that has served more than 170,000 customers. She now leads AI-driven approaches to extending human lifespan at Buck Institute.
Building a filtering system, not just a pipeline
The key insight from Zhang's experience is that investor selection is as rigorous as scientific methodology . Founders should establish clear criteria for what an aligned investor looks like: Do they understand delayed ROI? Do they respect the founder's scientific judgment? Do they add value beyond capital—networks, technical expertise, regulatory guidance?
This filtering happens through conversations, reference checks with past founders, and observing how an investor responds to tough questions or bad news. A detailed exploration of this selection process is available in Zhang's full episode , where she describes how she evaluates investor fit for her current work in longevity science.
The payoff for this deliberate approach is significant: founders avoid being trapped in misaligned partnerships that drain energy, slow progress, or force compromises on science quality. They also build a network of investors who become genuine partners in the long, uncertain journey of biotech innovation.
What drives a scientist to transition from academic research into founding a biotech company?
The transition from academia to founding a biotech company hinges on two converging moments: discovering scientific insights so actionable they demand real-world application , and recognizing that an enabling market ecosystem already exists to absorb them. For Dr. Sherry Zhang, this meant identifying FTO gene variants that directly explained her family's weight loss outcomes, while realizing that consumer genomics platforms like Ancestry.com and 23andMe had already primed the public to understand and act on genetic data.
A problem lived, then recognized as solvable
Zhang's journey began not with a business plan, but with a personal realization. While conducting obesity genomics research at the Medical College of Wisconsin under Dr. Ahmed Kaseba—the physician who coined the concept of metabolic syndrome—she discovered that FTO gene variants significantly predicted how individuals would respond to weight loss interventions . The insight was academically rigorous, but it sat confined to peer-reviewed journals.
She wanted her own family members to understand their genetic risks and make informed nutrition decisions based on their DNA. That gap between knowledge and application became the seed of Genopalate. As Zhang explains in the podcast episode , the realization crystallized: world-class science developed in universities was never reaching the people who needed it most.
The market window was already open
What made the moment ripe for founding was not the science itself—that had existed for years—but the emergence of consumer genomics as a mainstream category . Companies like 23andMe, Ancestry.com, and MyHeritage had already shifted public perception: millions of people understood they could access their genetic data and that it held practical value.
Zhang recognized this was not a market she had to build from scratch. The consumer appetite, the technical infrastructure, and the regulatory precedents were already in place. What was missing was the translation layer—the bridge between raw genetic data and actionable nutrition guidance. This combination of scientific knowledge waiting to be translated and a market ready to receive it , as discussed in the episode, became the real catalyst for her decision to found Genopalate, which would eventually serve more than 170,000 customers making nutrition decisions based on their DNA.
"This drive in me to deliver world-class science and translate that into something useful and practical for everyday people is so strong that I think that will motivate me to learn new skills, to meet new people, to get on stage that I'll be nervous for, and raise funding."
Sherry Zhang — Executive Director of External Strategy and Partnerships at the Price Lab, Buck Institute for Research on Aging, and founder of Genopalate. A first-generation immigrant scientist who arrived in the United States from China with three bags and $3,000, Zhang earned her PhD in molecular biology from Marquette University in Wisconsin and spent years conducting obesity genomics research. Her drive to translate academic discoveries into tools for everyday people led her to found Genopalate, which has now guided over 170,000 customers in making DNA-informed nutrition decisions, and is now building AI-native health platforms focused on longevity and preventive optimization.
Beyond the personal motivation and market timing, Zhang's transition also reflects a deeper philosophical shift in how modern scientists view their responsibility. For decades, the academic career path rewarded publication and prestige within institutional walls. But Zhang represents a growing cohort of researchers who see founding a company not as abandoning science, but as completing it—extending the laboratory's reach into real lives , a theme that runs through her conversation on the podcast.
Scientific breakthroughs alone are insufficient to drive the leap into founding; the founder must personally witness the gap between knowledge and application.
A functioning market ecosystem—where consumers already understand the value of genomic data—removes the largest barrier to entry and validates the business opportunity.
The strongest biotech founders are often motivated by translation: the desire to move knowledge from academic journals into practical tools that solve real problems for real people.
Timing combines personal insight (discovering actionable science) with market readiness (an audience prepared to act on that science).
Ep.185 -The Fortune Hidden in the Follow Up
What is the philosophical principle behind Ali's follow-up approach regarding time and deal progression?
It's not time that kills deals—it's lack of proximity. Salespeople often abandon prospects too quickly, but if someone has genuine integrity and real constraints like needing partner approval or arranging finances, they deserve consistent, valuable touchpoints until they're ready to move forward.
This principle flips conventional sales wisdom on its head. Most teams operate under the assumption that a quiet prospect after 30 days is a lost cause. But Ali Samaha's mentor taught him that deals naturally take time , and writing them off simply because weeks have passed ignores the reality of how decisions actually get made in business.
The distinction matters. Many prospects don't abandon deals because they lost interest—they pause because circumstances genuinely require it. A CFO may need buy-in from a board. A small business owner might be arranging capital. A team lead has to align three departments. None of these situations means the deal is dead; it means the prospect still needs reasons to stay engaged while their constraints resolve.
Proximity as the Active Ingredient in Follow-Up
Proximity, in Ali's framework, means staying present and relevant without being intrusive. It's not about bombarding someone with the same message; it's about providing genuinely useful information and resources that respect where they are in their decision timeline.
As explored in detail in the episode , this approach shifts the burden from the prospect's memory to the salesperson's discipline. Instead of hoping they remember your solution when they're finally ready, you show up with new insights, industry updates, or examples that keep the conversation alive and position you as a trusted advisor, not a pest.
"It's not time that kills deals. It's lack of proximity. So sometimes deals take time, Simon."
Ali Samaha — Founder, Samaha Consulting. Ali is widely known as the king of follow ups and helps founders, sales teams and business owners transform missed opportunities into revenue by creating structured, high impact follow up strategies. Through his consulting, content and coaching, he has helped thousands of professionals rethink how they build relationships, earn trust and create opportunities that others assume are lost.
The practical implication is stark: consistency over time beats novelty chasing. Rather than constantly hunting for new prospects to fill a pipeline, a sales team that masters proximity can turn stalled opportunities into closed deals. Ali's philosophy recognizes that 91% of your target audience isn't ready to buy right now—which means they all need ongoing proximity until circumstances shift.
For deeper insight into how Ali operationalizes this principle through structured messaging and qualified prospect focus, listen to the full conversation where he reveals the specific cadence and touchpoint strategy that keeps deals warm without adding busywork.
Lack of proximity, not elapsed time, is the actual deal-killer in sales follow-up.
Legitimate constraints like board approval or financing timelines are reasons to stay engaged, not signals to give up.
Proximity means delivering valuable information and resources that respect the prospect's timeline while keeping conversations alive.
Consistency and discipline through structured touchpoints outperform random prospecting in a growing pipeline.
How should follow-up messaging differ from standard sales pitches to feel more valuable and human?
Follow-up messages should open with humility and specificity , not assumptions—use Ali Samaha's "non-assumptive sandwich" approach: start with "I'm not sure this would interest you," place the prospect's exact pain point and your value in the middle, and close with warmth like "I know it's a bit last minute." Keep every message short and conversational, as if texting a friend, and always tie each touch point to a concrete value they requested or an obstacle they mentioned.
The Non-Assumptive Sandwich: Structure That Feels Human
The trap most salespeople fall into is writing follow-ups that sound like rejected sales pitches repeated. Instead, lead with vulnerability —"I'm not sure this would interest you"—which immediately signals you're not assuming they want what you're selling. This opening does real work: it disarms defensiveness and prepares them to actually listen.
The middle of the message is where you earn attention. Reference their specific pain point—the exact problem or goal they mentioned in your conversation—and explain how your solution addresses it. Then close the door gently: "I know it's a bit last minute" or similar language that acknowledges timing, uncertainty, or their position without pressure. This entire structure takes three to four sentences, maximum.
Every Touch Point Solves a Real Obstacle
The second critical shift is removing generic follow-ups entirely . As explained in the episode , every follow-up must respond to something real from the conversation. If they voiced certainty as an objection, send a testimonial or case study. If they mentioned needing partner alignment, send a two-minute Loom video walking them through implementation.
This approach transforms follow-up from noise into value delivery. The prospect sees you're listening and solving for their exact situation, not just rotating through a template. Keep the message itself short—never paragraphs—because the substance lives in the asset or detail you're attaching, not in flowery copy.
"It's not time that kills deals. It's lack of proximity. So sometimes deals take time, Simon."
Ali Samaha — Founder, Samaha Consulting. Ali is widely known as the king of follow ups and helps founders, sales teams and business owners transform missed opportunities into revenue by creating structured, high impact follow up strategies. Through his consulting, content and coaching, he has helped thousands of professionals rethink how they build relationships, earn trust and create opportunities that others assume are lost.
One specific detail that deepens this philosophy: as Ali discusses at length in this podcast , a rhythm of two to three touch points per week with adequate spacing keeps you in their world without feeling obsessive. The magic is that each one addresses a new dimension of their concern, rather than repeating the same offer.
Open with humility ("I'm not sure this would interest you") to disarm defensiveness and signal you're not making assumptions about their needs.
Anchor every follow-up to a specific obstacle or value they mentioned, not a generic template—send testimonials for certainty objections, Loom videos for alignment concerns.
Keep messages short and conversational; the substance lives in what you attach or reference, not in lengthy prose.
Maintain a two to three touch point per week cadence with proper spacing to stay present without feeling like harassment.
What role does AI and automation play in follow-up strategy according to Ali Samaha?
Use AI for low-touch, scalable activities—like sending AMA invitations to many prospects—but concentrate 80% of your custom effort on your five most qualified prospects closest to closing . The highest-impact work—personalized Looms and one-on-one conversations—must stay human. Follow-up is an energy management game, not a time game.
Why most teams misunderstand automation
When salespeople face a backlog of 300 prospects to follow up with, the instinct is immediate: automate everything. The reasoning sounds logical—there's no way to keep up manually. But this approach destroys the very relationships that turn prospects into revenue.
The problem is that broad automation dilutes your impact when applied to high-value prospects who expect personal attention. Automation works beautifully for reaching many people with minimal friction—sending invitations to group AMAs, for example. But the deals that close are won through custom effort: a personalized Loom video, a thoughtful email addressing their specific concern, or a genuine one-on-one conversation.
The 80-20 triage: qualify ruthlessly
Ali's framework is surgical: out of fifty prospects, identify the five most qualified and closest to a decision. As described in the episode , this requires real assessment—not wishful thinking. These five get your best energy: custom Looms addressing their specific objections, personal check-ins, and invitations to exclusive AMAs tailored to their needs.
The remaining forty-five? They receive strategic automation: templated invitations to group sessions, scheduled nurture sequences, and periodic value-adds that keep them warm without burning your time. This isn't neglect—it's intelligent prioritization.
The logic is simple: if only 9% of your target audience is ready to buy now, the other 91% need a different engagement model. Automation keeps them engaged until they're ready. Custom effort closes the deal when they're warm.
"It's not time that kills deals. It's lack of proximity. So sometimes deals take time, Simon."
Ali Samaha — Founder, Samaha Consulting. Ali is widely known as the king of follow ups and helps founders, sales teams and business owners transform missed opportunities into revenue by creating structured, high impact follow up strategies. Through his consulting, content and coaching, he has helped thousands of professionals rethink how they build relationships, earn trust and create opportunities that others assume are lost.
This insight cuts to the heart of why automation alone fails: a bot cannot establish proximity. Proximity is built through consistent, personal presence—and that requires human touch, even if it's a Loom video rather than a live call. The cadence matters too; as discussed in the podcast , a 72-hour interval between touch points maintains momentum without inducing fatigue.
To hear Ali elaborate on the specific workflows that separate deals that close from those that stall, and the exact metrics he uses to measure follow-up effectiveness, listen to the full episode on Listenly .
Automate low-touch activities (group AMA invitations, scheduled nurture flows) but reserve custom effort for your top five prospects out of fifty—those closest to decision.
The highest-impact work—personalized Looms, one-on-one conversations, custom value adds—must remain human to establish the proximity that actually closes deals.
Follow-up is energy management, not time management: allocate 80% of your effort to the most qualified segment and let automation handle the rest without guilt.
Proximity—not time—is what kills or saves deals; automation without human presence creates distance precisely when you need closeness most.
How should salespeople identify whether an objection is real or a delay tactic?
Ask the prospect to set the objection aside and confirm whether they genuinely want to move forward. If they say yes but still sound unsure, dig deeper by asking what's really behind the hesitation. Fake objections often mask real concerns about the product itself, so getting clarity on the true obstacle is essential before building a follow-up cadence.
Testing genuine interest versus surface-level resistance
The first move is simple but direct: separate the stated objection from true intent . When a prospect raises an obstacle like "I need my partner's approval," don't accept it at face value. Ask them to mentally set that concern aside and answer the core question: "If that weren't an issue, would you genuinely want to move forward?"
Their answer and tone reveal everything. If they hesitate, pause, or give a lukewarm yes, that's a signal the objection is masking something deeper. As Ali Samaha explains in the episode , this is the moment to probe further, not retreat.
Uncovering the real concern beneath the surface objection
Once you suspect an objection is a delay tactic, the next step is asking open-ended questions that invite honesty . For example, if a prospect admits they're not even sure if their partner needs to approve, that's a confession—the objection was never real. The actual barrier might be doubt about the product, unclear ROI, or fear of change.
This distinction is critical. A real objection is specific, time-bound, and removes when resolved. A fake objection is vague, recurring, and disappears when questioned. The episode details practical examples of how to distinguish between the two and respond accordingly.
"It's not time that kills deals. It's lack of proximity. So sometimes deals take time, Simon."
Ali Samaha — Founder, Samaha Consulting. Widely recognized as the king of follow-ups, Samaha has helped thousands of founders, sales teams, and business owners transform missed opportunities into revenue through structured, high-impact follow-up strategies. His philosophy centers on outlasting the competition with genuine persistence, value, and discipline rather than relying on closing techniques alone.
Once you've identified the real obstacle, the podcast dives into how to build a follow-up cadence that addresses that specific concern, not the false objection. This precision transforms follow-up from random touchpoints into targeted, strategic persistence.
Ask prospects to temporarily ignore the stated objection and confirm genuine interest—hesitation signals a fake objection.
Dig deeper with open-ended questions to uncover the real obstacle, which is often a product doubt rather than an external blocker.
Real objections are specific and time-bound; fake objections are vague and recur when questioned.
Once you identify the true concern, build a follow-up cadence targeting that specific barrier, not the surface-level excuse.
At what point does persistence in follow-up become counterproductive annoyance?
A 72-hour cadence between touch points prevents badgering while maintaining momentum. The critical difference lies in ensuring each interaction adds genuine value and addresses specific obstacles discussed during your conversation, rather than sending generic check-ins that waste the prospect's time.
Value, not volume, decides the line
The point at which persistence becomes annoying isn't about frequency—it's about substance. Each touch point must either provide new information, remove a known barrier, or respect the prospect's stated timeline. Generic "just checking in" messages train prospects to ignore you, regardless of how long you wait between them.
Treating prospects like adults means being transparent about your intentions while prioritizing their objectives over your close date. When you do this consistently, the conversation stays alive far longer than your competition's , because you're demonstrating genuine interest in solving their problem, not solving your quota.
Persistence has limits. If a prospect refuses to clarify their position or timeline after multiple clear, value-driven attempts, a walk-out strategy becomes appropriate. This isn't giving up—it's respecting both their autonomy and your own time.
This is where Ali Samaha emphasizes the discipline of follow-up : knowing when to continue and when to step back separates professionals who build sustainable pipelines from those who burn out chasing dead leads.
"It's not time that kills deals. It's lack of proximity."
Ali Samaha — Founder, Samaha Consulting. Ali is widely known as the king of follow ups and helps founders, sales teams and business owners transform missed opportunities into revenue by creating structured, high impact follow up strategies. Through his consulting, content and coaching, he has helped thousands of professionals rethink how they build relationships, earn trust and create opportunities that others assume are lost.
To understand how proximity works in practice and explore the specific mechanics Ali uses to keep deals alive when 91% of your target audience isn't ready to buy, listen to the full episode on Listenly .
What is the recommended follow-up cadence between initial conversation and decision?
Follow up every 72 hours with two to three touch points per week. The first touch point should be a crystal-clear recap of your conversation, the second a testimonial addressing their specific obstacle, and the third an invitation to an AMA. Always book the next meeting from the current meeting itself.
Structure your follow-up around specific obstacles
The exact cadence depends on the specific constraint you identified during the initial call. You're not following up blindly—each touch point serves a precise purpose tied to what the prospect told you about their situation.
The principle is simple: lack of proximity kills deals , not time. Your prospect may need days or weeks to move forward, but they need to feel close to you throughout the process. As Ali Samaha explains in the episode , sometimes deals take time, but the proximity must remain constant.
Your first touchpoint recap is not a sales pitch—it's clarity on what was discussed . Write down what they told you, what they're trying to solve, and what next step was agreed. This removes friction and shows you were genuinely listening.
Your second touchpoint is addressing the exact obstacle they named . A testimonial from another founder or business owner who had the same challenge works far better than generic social proof. This is direct evidence that their constraint can be solved.
Your third touchpoint offers access to expertise —an AMA (Ask Me Anything) session or a group call where they can see how you think and get real answers. This builds confidence beyond the one-on-one conversation.
"It's not time that kills deals. It's lack of proximity. So sometimes deals take time, Simon."
Ali Samaha — Founder, Samaha Consulting. Ali is widely known as the king of follow ups and helps founders, sales teams and business owners transform missed opportunities into revenue by creating structured, high impact follow up strategies. Through his consulting, content and coaching, he has helped thousands of professionals rethink how they build relationships, earn trust and create opportunities that others assume are lost.
A deeper look at how to customize this cadence based on your specific sales context is explored in this conversation with Ali Samaha , where he walks through real examples of how different industries and deal sizes benefit from the same framework applied differently.
Follow up every 72 hours with two to three touch points per week, tailored to the specific obstacle they shared with you.
Structure each touch point for a distinct purpose: recap, targeted testimonial, and AMA invitation—not generic outreach.
Book the next meeting before the current call ends to eliminate scheduling friction and reinforce commitment.
Proximity matters more than time; the goal is to stay close and valuable while they make their decision.
Why do most salespeople stop following up after one or two attempts?
Most salespeople lack a structured follow-up system and resort to dehumanizing communication — long paragraphs and complicated messages that feel pushy. Without clarity on how to help prospects overcome specific obstacles, they eventually give up because they're operating from a scarcity mindset of "I need the sale" rather than "I want to serve."
The root problem isn't laziness or lack of effort — it's a fundamental misunderstanding of what follow-up actually requires. Many salespeople know they should follow up, but without a system to guide them, the process begins to feel like chasing or badgering prospects.
As Ali Samaha explains in The Conference Room with Simon Lader , salespeople often jump to automating follow-up because they feel overwhelmed by volume. Yet automation without the right foundation only amplifies the problem, turning a personal conversation into a transactional sequence.
The mindset trap that kills follow-up momentum
When salespeople operate from a place of self-interest — "I need this sale to hit my quota" — prospects sense it immediately. That desperation creeps into every message, making even a simple follow-up feel intrusive.
Contrast that with a service-first approach: "What specific obstacle is this prospect facing, and how can I help them solve it?" This mindset doesn't just improve the relationship — it gives the salesperson a reason to follow up that feels authentic, not forced.
As a result, follow-up stops feeling like an uncomfortable chore and becomes a natural extension of the sales conversation. Discussed at length in this podcast episode , this distinction explains why some salespeople can follow up twenty times and maintain respect, while others quit after two because the entire dynamic feels off.
Why systems matter more than willpower
A structured follow-up process removes the guesswork and emotion from the equation. Instead of wondering "Should I reach out again?" or "Am I being too pushy?", a salesperson with a clear system knows exactly when to touch base, what to say, and how to add value at each stage.
This is where persistence becomes discipline rather than desperation. Details on building that structure are covered in the full episode , where Samaha breaks down how to keep conversations alive long after most competitors have walked away.
"It's not time that kills deals. It's lack of proximity. So sometimes deals take time, Simon."
Ali Samaha — Founder, Samaha Consulting. Ali Samaha is widely known as the king of follow ups and helps founders, sales teams and business owners transform missed opportunities into revenue by creating structured, high impact follow-up strategies. Through his consulting, content and coaching, he has helped thousands of professionals rethink how they build relationships, earn trust and create opportunities that others assume are lost.
How did Ali Samaha develop his competitive advantage and brand as the king of follow ups?
For years, Ali followed conventional sales wisdom by packing his calendar and treating quiet prospects as lost. He realized he wanted to maximize…
