The Key to Enduring Growth is Strategic Transformation (Revisited)

Written By

Erich Fritz

Published On

June 16, 2025

Mark Leslie offers timeless insights into company lifecycles and the power of strategic transformation. Below, we distill key takeaways from his framework and illustrate them through contemporary examples from the technology sector.

To achieve enduring growth, companies must go through strategic transformations—shifts in their business model, product focus, or market positioning that allow them to escape stagnation and capitalize on new waves of demand. These transformations are proactive, not reactive, and often require reinventing the company's identity.

Three Growth Phases:

1. Initial Traction ("Ignition") - A company finds product-market fit and starts to scale rapidly.
2. Hyper-Growth - Revenue and market share expand quickly as the core offering dominates.
3. Flattening (or Decline) - Growth stalls. Without transformation, the company risks irrelevance.

Strategic Transformation: The Lifeline to Enduring Growth

To break through the plateau, companies must:

• Reassess their core mission and capabilities
• Identify new problems to solve or new markets to enter
• Reinvent products, services, or delivery models

Modern Examples of Strategic Transformations

Tech and Tech-enabled companies inherently must continually innovate to remain relevant in the face of a more rapid company lifecycle

• Organic innovation can be supported by fundraising, partnership formation, business model transformation (as-a-service), M&A and divestitures
• Within the last decade, several juggernauts have gone through strategic transformations (Apple, Oracle, NVIDIA, Autodesk, Adobe, Tesla, Meta)
• Some have been successful; others are still a work in progress
• It is much harder to transition once a business is in decline

OpenAI

• Ignition: Initially focused on open research in AGI and safety.
• Hyper-Growth: ChatGPT’s viral success led to massive consumer traction.
• Transformation: Pivoted from open research to a productized platform model—building ChatGPT, GPT-4, and APIs, now driving enterprise and developer ecosystems (e.g., ChatGPT Enterprise, GPT Store).
• Strategic Play: Shifted from a pure research lab to a commercial platform enabling businesses to build AI-native apps. OpenAI is also reshaping its identity through partnerships (e.g., with Microsoft) and growing developer adoption.
• Risks / Considerations: Cultural turbulence; Altman; Microsoft

NVIDIA

• Ignition: Dominated in graphics hardware.
• Hyper-Growth: Leveraged GPU parallelism for AI workloads.
• Transformation: Repositioned itself as the foundational compute layer for AI, with CUDA, DGX systems, and full-stack AI solutions—not just chips. Now a linchpin in global AI infrastructure.

Amazon

• Ignition: Online bookstore.
• Hyper-Growth: E-commerce giant.
• Transformation: Created AWS, turning internal infrastructure into a cloud juggernaut. Reinvented itself again with Alexa and logistics dominance.
• Result: Market cap > $3 trillion (2025), powered by AI boom.

Tesla

• Ignition: High-performance electric roadster.
• Hyper-Growth: Mass-market EVs (Model 3, Y).
• Transformation: Expanded into energy (Powerwall, Solar) and autonomy (FSD). Envisions itself not as a carmaker but as a robotics and energy company.

These companies avoided the growth plateau by:

• Proactively expanding their vision
• Leveraging strengths (tech, user base, brand) into new domains
• Creating new S-curves before the original curve flattened

Deep Dives for Emerging Companies

Anthropic

Framework Principle: Enduring growth requires building a new GTM model that eventually becomes the company’s new core, not just optimizing the current product or channel.

Current GTM Model (2023–2024)

• Model: API access to Claude (foundational model) + enterprise and partner integrations. Found success in focusing of software coding as a core use case of foundational models.
• Distribution: Primarily B2B, through cloud platforms (Amazon Bedrock, Google Cloud) and limited direct sales.
• Revenue Sources:
  • Claude subscriptions (via Claude.ai).
  • API usage.
  • Strategic partnerships (e.g., Amazon, Google investments in exchange for preferred access).

Emerging Transformation Vectors

• Toward a Platform GTM:
  • Anthropic has started positioning Claude as a platform for enterprise AI, not just a model.
  • Building out Claude Teams, Claude for Business — stepping into productization beyond raw APIs.
  • Model Context Protocol (MCP) is a significant innovation that helps the API call business by facilitating agentic interaction.
• Multi-Cloud GTM Play:
  • Unlike OpenAI (tied closely to Microsoft), Anthropic is multi-cloud with AWS and Google.
  • This opens the door to a horizontal GTM model: being the foundational model layer across clouds and industries.
• Constitutional AI as Differentiator:
  • Marketing “Constitutional AI” as a trust, safety, and alignment moat — potentially a new GTM model for regulated or high-assurance industries (e.g., finance, healthcare, government).

Risks of Incomplete Transformation

• If Anthropic remains focused primarily on foundation model performance and API reselling, it may:
  • Encounter share grab from vertical SaaS companies building full-stack AI solutions (e.g., Notion, Canva, Salesforce AI).
  • Be disintermediated by cloud vendors who own customer relationships (mitigants: Google and Amazon are large shareholders; OpenAI’s / Microsoft’s rocky relationship providing an opening).
  • Face margin pressure as model commoditization increases.
  • Struggle with the requirements of raising incremental capital as revenue growth slows.

Strategic Transformation Potential

• Build a direct GTM motion targeting end-users with differentiated workflow tools (beyond chat).
• Monetize vertical-specific offerings (e.g., Claude for Legal, Claude for Pharma).
• Develop an ecosystem or app store around Claude, turning it from a model to a platform.
• Expand channel partnerships to reach new customer bases (e.g., SMBs, international markets).

Verdict:

Anthropic is in the early phase of building its first real GTM model. Its transformation will depend on whether it can evolve from a foundation model API vendor into a scalable platform business with multiple GTM engines. The groundwork is promising, but the strategic pivot is not yet fully realized.

Scale AI

Framework Principle: Long-term growth requires building new go-to-market (GTM) models that eventually become the core business, not just optimizing what already works.

Original GTM Model (2016–2022)

• Model: Data labeling as a service — high-quality training data for AI/ML teams.
• Target customers: Government agencies (DoD), self-driving car companies, big tech.
• Strengths:
  • Human-in-the-loop workflows.
  • Reputation for quality and security.
  • Landed key enterprise and defense contracts.

Strategic Transformation Underway

• New GTM Model (Post-2023):
  • AI infrastructure and model evaluation: Offers tools for model testing, red-teaming, safety evaluation (e.g., Scale Spellbook).
  • Developer-centric tools: Now selling to developers and model builders, not just enterprise ops teams.
  • Positioning as a foundational AI stack, not just a vendor of labeled data.
• Defense/National Security GTM:
  • Through Scale’s Government division, it's evolving into a core infrastructure player in defense AI applications — a strategic GTM vertical.
  • Competes to become the “Palantir of the AI age” — not just tooling, but critical operational infrastructure.
• Shift from services to platform:
  • Introducing APIs and SaaS-style platforms for data management, synthetic data generation, and model eval — a scalable, recurring revenue model.

Framework Analysis

Strategic Imperatives to Complete the Transformation

To fulfill Leslie’s model fully, Scale AI must:

• Turn tools into platforms — e.g., build proprietary developer ecosystems (like OpenAI plugins or HuggingFace).
• Win the enterprise GTM battle with unique IP in model eval, synthetic data, or high-assurance infrastructure.
• Outgrow defense dependence by creating widely adopted commercial solutions (e.g., Claude or OpenAI-style APIs).

Verdict:

Scale AI is in the midst of a strategic transformation. It has moved beyond its original GTM model (data labeling) and is actively constructing new infrastructure-layer GTMs in both the commercial and defense sectors. Success will depend on whether these new GTMs become scalable, recurring-revenue cores — not just add-ons to a services business.

Under the purview of a well-capitalized Meta ($15bn acquisition pending), Scale AI will be exposed to new possibilities and challenges.

SpaceX

Framework Principle: Enduring growth depends on building and scaling new GTM models that eventually become the company’s core — not just optimizing legacy ones.

Original GTM Model (2002–2014): Launch Services

• Product: Falcon 1, then Falcon 9 and Falcon Heavy rockets.
• Customer base: NASA, commercial satellite companies, defense.
• Innovation: Lowered cost of launch through vertical integration and reusability.
• GTM model: Fixed-price launch contracts with government and commercial payload customers.

Result: Disrupted the aerospace incumbents (ULA, Arianespace). Dominated the global launch market.

First Strategic Transformation: Reusability & Cost Disruption

• New GTM: High-frequency, low-cost launch enabled by first-stage reusability.
• Result: Drove down cost per kg dramatically, created flywheel of reliability, cadence, and margin improvement.

Second Strategic Transformation: Starlink (2018–Present)

• New GTM model: Global broadband internet via LEO satellite constellation.
• Customer base: Consumers, enterprises, governments — recurring revenue.
• Distribution: Direct-to-consumer hardware kits + subscription internet.
• Business model shift: From project-based revenue to SaaS-like recurring revenue.

Starlink is poised to become the new core — a $10bn+ annual recurring revenue business with global scale.

Third Strategic Transformation: Starship + Space Infrastructure

• Product: Fully reusable heavy-lift vehicle (Starship).
• GTM model: Long-term: Mars colonization; near-term: ultra-heavy launches (e.g., Starlink Gen2, lunar missions).
• Potential new GTMs:
  • Orbital logistics
  • On-orbit refueling
  • Lunar cargo
  • Interplanetary infrastructure

Still early-stage, but could transform GTM yet again into the logistics provider of space infrastructure.

Framework Analysis for SpaceX

Strategic Transformation Strengths

• Clear product-market fit with each GTM.
• Leverages old GTM (low-cost launch) to enable the next (Starlink, Starship).
• Massive flywheel between verticals — Starlink revenue funds Starship; Starship enables cheaper Starlink launches.

Verdict:

SpaceX is a textbook example of strategic transformation. It built one dominant GTM (launch services), then invested heavily to create new engines of growth (Starlink, Starship), each with potential to become the next core business. Few companies in any industry demonstrate this level of transformation across hardware, infrastructure, and recurring services.

Anduril

Original Business Model (2017–2019): Autonomous Border Surveillance

• Focus: Launch AI-powered surveillance towers and drones for border security.
• Model: “Build-it-first” product development — self-funded R&D, then pitch to government.
• Outcome: Rapid pilot success (e.g., Sentry Towers caught 55 trespassers in 12 days) led to US Border Patrol backing.

Strategic Inflection Point (2019–2020): Expansion to Military-AI Systems

• Market Signal: Rising global concerns (e.g., drone threats in Saudi attacks, Ukraine) fueled demand for autonomous defense solutions.
• Transformation Move: Shift from fixed surveillance to offensive and networked defense:
  • Developed Lattice OS — central software platform integrating sensors, drones, and autonomous vehicles.
  • Introduced new hardware: Anvil (interceptor drone), Altius (loitering UAV), Fury/CCA fighter jet, Ghost Shark submarine.
• Contract Wins: Secured major defense deployments—US SOCOM, Air Force’s Advanced Battle Management System, Royal Navy — transitioning into full-spectrum defense.

Revised Business Model: Vertically Integrated Defense Tech

• Product-to-platform shift: Anduril now sells complete systems—sensor + AI software + autonomous vehicles—with software-defined contract pricing (fixed-price) rather than cost-plus models.
• Vertical integration: Acquired Area-I (drones), Dive Tech (UUVs), and Adranos (rocket motors) to internalize critical hardware.
• Manufacturing scale-up: Constructing Arsenal 1, a 5 million ft² factory to mass-produce autonomous weapons.

Transformational Outcome & Growth

• Explosive valuation:
  • 2022 Series E → $8.5bn.
  • 2024 Series F → $14bn.
  • 2025 Series G → $30.5bn.
• Revenue milestone: Surpassed $1bn in 2024.
• Business model impact:
  • Transitioned from narrow surveillance to aiming for “trillion dollar” defense market share (fighter jets, ISR ecosystems).
  • Moved from slow "cost-plus" to agile, integrated defense-as-a-service.

Framework Analysis for Anduril

Anduril exemplifies Leslie’s strategic transformation:

• Anticipated maturity in simple surveillance.
• Bold pivot to integrated autonomy and weapon-platform ecosystems.
• Built new capabilities via acquisitions, software-first strategy, and factory-scale manufacturing.
• Achieved scale—financial, contractual, and structural—to challenge traditional defense giants.

Emerson

Emerson illustrates Mark Leslie’s framework of strategic transformation—reinventing its business model to sustain growth before legacy markets plateau:

Core/Legacy Model (Pre-2018)

• Emerson began in 1890 as a maker of electric motors, fans, tools, and HVAC components. Over decades, it evolved into an industrial conglomerate offering hardware such as valves, compressors, and measurement instruments.
• Its business operated on a product centric, cost plus model, emphasizing manufacturing scale, cost efficiencies, and breadth of industrial portfolio.

Strategic Inflection (Around 2019)

• By the late 2010s, industrial markets matured; Emerson’s historically cyclical hardware revenue faced margin compression.
• Customer needs shifted toward software-driven automation, predictive analytics, and digital transformation—creating pressure to re-think the hardware-focused model.

New Growth Organization (2019)

• Emerson launched a dedicated Digital Transformation unit to integrate sensors, analytics, and industrial software—signaling a pivot from hardware to solutions.

Portfolio Streamlining (2021 - 2024)

• Divested lower-growth assets: spun off Colour Technologies (Copeland) HVAC JV to Blackstone (~$14bn stake, and remaining 40% sold in June 2024 for $3.5bn).
• These proceeds were redeployed into automation and debt reduction, sharpening focus.

Select “Build + Buy” for Automation

• Merged its software units with AspenTech in 2021 (now ~55% owned), and in Nov 2024 offered to acquire remaining shares at ~$15bn valuation (wholly owned as of March 2025).
• In April 2023, Emerson acquired National Instruments for $8.2bn, expanding into test & measurement automation.

Software + Services Model (2024–2025)

• Now delivering Plantweb ecosystem, DeltaV, and Ovation software—offering real time monitoring, predictive maintenance, and even automation-as-a-service.
• CEO Lal Karsanbhai calls it the “final phase of its portfolio transformation” into an industrial tech leader.

Mapping to Leslie’s Framework

• Core Model: Hardware-focused, cost efficient industrial manufacturing.
• Inflection Trigger: Maturing industries and rising demand for digitization.
• New Business Model: Transition to automation-as-a-service, software-integrated solutions, with strategic M&A and portfolio reshaping.
• Result: Enhanced financial metrics, more predictable growth, and market leadership in industrial automation.

Emerson demonstrates Leslie’s strategic transformation:

• It proactively recognized declining prospects in its legacy hardware businesses.
• By reinvesting capital into software, automation, and high-growth acquisitions, it shifted from cyclical OEM to a value-rich industrial-tech platform.
• The result: stronger growth trajectory, improved margins, and a refined business model aligned with modern manufacturing trends.

Failure Through the Lens of Leslie's Strategic Transformation Framework

WeWork

Ignition (2010–2015)

WeWork found strong product-market fit by:

• Offering flexible co-working spaces for freelancers, startups, and small businesses
• Capitalizing on post-2008 economic uncertainty and the rise of the gig/freelance economy
• Turning real estate into a “service” with tech-enabled access and community-focused design

Strategic Positioning: Disrupted traditional office leases by selling flexibility and community.

Hypergrowth (2016–2018)

Fueled by massive funding (primarily from SoftBank), WeWork:

• Expanded globally at breakneck speed
• Branded itself as a tech company with lofty claims about reshaping how people work
• Began to position itself as a lifestyle and operating system for work (e.g., WeLive, WeGrow)

Valuation Peak: $47 billion pre-IPO

Narrative: “We are not just a real estate company—we’re a global platform for work.”

Flattening + Failure to Transform (2019–2023)

WeWork hit the stall point—but instead of a clear, focused strategic transformation, it:

• Overextended into unrelated verticals (WeLive, WeGrow) without market fit
• Failed to adopt a true tech layer (despite tech-company valuation)
• Did not transition into higher-margin software or services to complement the core real estate
• Maintained an unsustainable cost structure based on long-term leases and short-term customers
• Faced a failed IPO in 2019, massive valuation crash, and leadership collapse (Adam Neumann ousted)

No S-curve Jump: It failed to pivot to a sustainable platform or business model beyond real estate arbitrage.

Outcome

• Bankruptcy filed in 2023
• Former valuation: $47bn → < $100M
• Asset sell-offs and retrenchment, while competitors like Industrious evolved with more discipline and tech-enabled models

Strategic Takeaways:

• Transformation didn’t happen when growth stalled. Instead, WeWork doubled down on the existing flawed model.
• Identity confusion (real estate vs. tech) masked a lack of genuine innovation or reinvention.
• Missed opportunities to evolve into a hybrid work infrastructure provider, workplace analytics platform, or enterprise space-as-a-service player.

Concluding Thoughts

Key Takeaways for Leaders:

• Don’t rest on early success. Hyper-growth fades.
• Anticipate the stall and proactively reinvent your strategy.
• Leverage your existing strengths (tech, brand, talent) in new markets.
• Transformation is not iteration. It’s a bold leap, not a refinement.