How To Avoid Tech Leadership Mistakes During Rapid Growth

gettyRapid growth can force technology leaders to rethink practices that worked well when a company was smaller. Processes meant to create consistency and control can become bottlenecks at scale, while decisions made for short-term speed can create technical debt, security risks or organizational challenges down the road.

The challenge is knowing when a proven practice is no longer serving the business and what should take its place. Here, members of Forbes Technology Council identify technology leadership practices that can become liabilities during rapid growth and share more scalable approaches leaders can adopt instead.

Hiring for culture fit feels efficient; everyone is aligned and decisions move fast. But it manufactures groupthink at the exact moment growth demands more perspectives, not fewer. Hire for cognitive diversity instead: different backgrounds, different blind spots. Consensus is comfortable. It’s also how fast-growing companies miss the thing nobody in the room saw coming. - Joseph Byrum, Big House Enterprise

Centralizing every technology decision can create consistency, but during rapid growth it becomes a launch bottleneck. Instead, establish clear architectural guardrails, security standards and decision rights, then let teams choose how to execute within them. Mission control defines the safe flight envelope; it does not fly every subsystem. Scale comes from aligned autonomy—shared direction without centralized delay. Guardrails enable smarter growth. - Shelli Brunswick, SB Global LLC

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What backfires is adopting AI before anyone has mapped what it touches. As AI connects to more critical systems and data, gaps in access controls or oversight compound quickly. Leaders who build governance from day one will ultimately enable their teams to move faster because they won’t be inheriting a mess they’ll have to unwind later. - Linus Hakansson, Gravitee

Consolidating into an all-in-one platform can backfire when growth outpaces the original use case. Teams may end up paying for complexity and features they rarely use. Leaders should choose technology based on the core workflows and outcomes they actually need, then expand only when there is a clear business case. - Judit Sharon, OnPage Corporation

A best practice that can backfire is making rapid product decisions based solely on early customer surveys. Initial feedback captures intent, not always behavior. Leaders should pair customer input with adoption patterns and examine how features perform as the product evolves and interacts with other capabilities. In fast growth, decisions should be data-informed and iterative, not driven by the first signal. - Subasini Periyakaruppan, Cadmus Group

Don’t institutionalize every workaround that helped at one stage of growth. Regularly ask whether a process still reduces risk or just adds friction. Keep the controls that protect the business, simplify the rest and make ownership clear enough that people can exercise judgment. - Cheryl Johnson, Betterworks

Flattening an organization and having managers serve as player-coaches looks like efficiency, but it places coordination costs on people with no time budget. A 2026 Gallup analysis found that 97% of U.S. managers have individual contributor responsibilities, spending a median 40% of their time on that work. At the same time, the average number of direct reports rose to 12.1 in 2025 (with a minority of very large teams pulling the average higher). Cap managers’ IC loads in writing and set spans of control based on decisions per week, not headcount. - Nikhil Jathar, AvanSaber Technologies

While customer-centricity is essential, excessive tailoring can create technical debt, product fragmentation and a roadmap driven by a few voices rather than market needs. Instead, leaders should focus on identifying common customer patterns and building scalable, configurable solutions that serve a broader market while preserving long-term agility and growth. - Nalini Garg, Deloitte

One practice that backfires is enforcing heavy processes—like detailed roadmaps, sign-offs or standardized tooling—too early. It creates false stability while also slowing decisions and driving away builders who joined for speed. Instead, keep decision-making fast and reversible. Set a few nonnegotiables—security, data integrity—and let teams choose their tools and approaches otherwise. Add processes only when a specific pain repeats. - Kameshwar Singh, Cohesity

Standardizing on a framework or platform layer too early, before you are ready to scale, can backfire. When the product still changes weekly, the abstraction ages faster than the code it wraps, and you inherit a migration you never budgeted for. Keep the seams obvious and the dependencies shallow until the workload stops moving. - Neo Lee, Imagine AI

Giving teams too much autonomy in the name of moving quickly can create unnecessary risk and complexity as a company scales. Rather than slowing innovation, leaders should pair autonomy with clear standards, governance and accountability. The right guardrails enable teams to move quickly and make decisions independently without sacrificing security, consistency or long-term scalability. - Rodrigo Madanes, EY

Consensus-driven decision-making is praised as a healthy culture, but at high-growth speed, it just delays everything. Leaders should name a single owner for each decision and let debate happen before, not instead of, making a call. - Aruna Veerappan, Upwork

In my recent startup experience, we deferred the engineering efficiency of our production workloads, prioritizing faster builds and shipping more features to customers. This resulted in several service outage incidents, leading to customer dissatisfaction. Ship your product only if it can perform reliably, producing the best customer experience, even if you ship fewer features. - Balaji Soundararajan, PayRiva Inc.

Hiring specialists early is standard advice, but it backfires in high-growth companies because specialists optimize narrow problems while the organization’s actual bottlenecks keep moving. You end up with a brilliant data engineer and no one who can talk to customers. Hire generalists who can absorb ambiguity first, then specialize once the problem you’re solving stops changing every quarter. - Harsh Jangid, Coozmoo Digital Solutions

The “one North Star metric” mantra backfires when growth compounds; teams optimize the number and quietly degrade everything around it: quality, retention and brand trust. Instead, pair every North Star with one or two counter-metrics that must not fall. You get focus with a built-in alarm for when growth starts cannibalizing itself. - Mudit Singh, TestMu AI (LambdaTest)

A “best practice” that can backfire is adding too many approval layers for control. During rapid growth, this slows decisions and pushes accountability upward. Leaders should set clear guardrails, decision rights and escalation thresholds—then empower teams to act quickly within them. - Dr. Sanjay Kumar, JP Morgan Chase

Promoting your best individual contributors into management the moment the team doubles is not a simple task; it may feel like a reward and continuity, but coding or sales skills don’t predict management skills, and you lose your strongest builder while gaining a struggling manager. Instead, create a parallel senior IC track so top performers can gain influence and pay without being forced into people management. Technical and leadership skills are separate skills. - Dan Sorensen, Nexus Security Advisors

Buying a best-of-breed tool for every new problem can backfire. Each system gets better at its own job but none of them know about the others’ data. When something breaks, your best people spend hours connecting what the tools aren’t connecting. Leaders should fund the connections between systems with the same seriousness that they fund the systems themselves. - Sanjay Gidwani, KOSMOS

A common mistake is “move fast, govern data later,” piling on new data sources and AI pilots while treating unstructured data hygiene as tomorrow’s problem—until no one can say what’s sensitive or redundant or even where it lives. Instead, leaders should build the intelligence and orchestration layer for unstructured data before scaling AI, treating governance as a growth enabler rather than a brake on speed. - Carl D’Halluin, Datadobi

Fast-growing companies often respond to every failure by creating a new rule, approval or process. Eventually, yesterday’s mistakes become today’s bureaucracy. Leaders should regularly delete processes and accept that preventing every possible mistake is more expensive than allowing some reversible ones. - Benedetto Biondi, Folks Finance