Build vs. Buy Dilemma in Contract Lifecycle Management (CLM) A Strategic Perspective

by | Mar 10, 2025 | CLM, Digital Transformation & Strategy

Navigating the Build vs. Buy Dilemma in Contract Lifecycle Management (CLM): A Strategic Perspective

 

In the rapidly evolving landscape of enterprise technology, organizations are often caught between competing priorities: Best of Breed vs. Best of Suite, and Build vs. Buy. These debates, rooted in traditional decision-making for ERP, CRM, S2P, CLM, BI, and beyond, now face a new layer of complexity—Artificial Intelligence (AI).

 Today’s businesses must not only evaluate immediate operational needs but also position themselves to capitalize on emerging technologies like Machine Learning (ML) and Large Language Models (LLMs). This article unpacks the nuances of these decisions, focusing on their implications for CLM and broader enterprise ecosystems.

Why the Build vs. Buy Debate Persists

The decision to build a custom solution or buy an off-the-shelf product has been foundational in enterprise technology strategy. Each path offers distinct advantages and risks:

 When to Build

Organizations may lean toward building when:

  1. Unique Requirements: Specialized workflows or niche industry needs demand tailored solutions.
  2. Full Control: Ownership of code, data, and updates aligns with governance priorities.
  3. Scalability: Flexible architecture to adapt over time.
  4. Internal Expertise: Strong development teams can support ongoing innovation.

However, building comes with significant risks:

  • Higher Costs: Upfront investments in talent, infrastructure, and maintenance.
  • Longer Timelines: Slow to deploy, risking missed opportunities.
  • Obsolescence: Failure to keep pace with evolving technology trends.

 When to Buy

Buying a solution is ideal when:

  1. Speed to Market: Rapid deployment meets urgent needs.
  2. Cost Efficiency: Subscription pricing avoids large upfront investments.
  3. Proven Capabilities: Vendors bring pre-built AI features and domain expertise.
  4. Scalability: Enterprise-grade platforms scale globally with minimal disruption.

Yet, off-the-shelf solutions can have drawbacks:

  • Limited Customization: May not address all unique needs.
  • Vendor Dependency: Roadmaps and updates controlled externally.
  • Generic AI Models: Lack specificity for industry or enterprise nuances.

Best of Breed vs. Best of Suite: A Layered Decision

Closely tied to the Build vs. Buy debate, the choice between Best of Breed (BoB) and Best of Suite (BoS) strategies reflects how enterprises prioritize specialization versus integration.

Best of Breed

Focused, specialized tools—like Icertis for CLM or Zendesk for customer service—deliver deep functionality in specific areas.

  • Pros: Faster innovation, niche expertise, greater flexibility.
  • Cons: Complex integrations, potential silos, higher total costs.

Best of Suite

Unified platforms like SAP, Oracle, or Salesforce integrate diverse functions into a cohesive ecosystem.

  • Pros: Seamless data flow, simplified governance, single-vendor management.
  • Cons: Diluted functionality, slower innovation cycles, limited customization.

AI’s Long-Term Impact on Build vs. Buy

The evolution of AI, particularly agentic AI, is reshaping the traditional Build vs. Buy decision. With AI-driven contract drafting, intelligent negotiation support, and real-time risk assessment, organizations may find that the need for heavy customization diminishes. AI-enabled automation enhances the adaptability of off-the-shelf solutions, reducing development burdens while still allowing for specialized enhancements through AI-driven configurability.

The Changing Vendor Landscape

ERP Consolidation As ERP providers continue acquiring CLM vendors, the Build vs. Buy and BoB vs. BoS debates are shifting. This consolidation means fewer standalone CLM options, pushing enterprises toward deeper native integrations within ERP ecosystems. While this may simplify data flow and governance, it also raises concerns about innovation cycles and dependency on a single vendor’s roadmap. Enterprises must assess whether a fully integrated solution aligns with their agility and innovation needs.

A Hybrid Approach: The Best of Both Worlds

For many enterprises, a hybrid strategy combining the stability of Best of Suite with the agility of Best of Breed is ideal.  

Key Components of a Hybrid Approach

  1. Core Platform Selection:
      • Opt for scalable, feature-rich platforms with strong API support.
      • Prioritize vendors with robust AI capabilities and modular architectures.
  2. Custom Enhancement Layers:
      • Develop microservices to address specific needs.
      • Create bespoke AI agents for tasks like predictive analytics, contract validation, or compliance monitoring.
      • Integrate advanced tools with low-code/no-code platforms to accelerate deployment.
  3. Emerging Trends to Leverage:
      • Composable Enterprise: API-first and mobile-first solutions enable agility.
      • Exponential Innovation: AI fosters iterative, continuous improvement.
      • Human-Machine Collaboration: Automation enhances productivity without sidelining human expertise.

Future-Proofing Strategies for AI-Ready Enterprises:

To remain competitive in an AI-driven landscape, organizations should focus on:

  • Modular Architectures: Ensuring technology investments can evolve with emerging innovations.
  • Low-Code/No-Code Extensibility: Empowering business users to adapt workflows without deep technical expertise.
  • API-First Strategies: Facilitating seamless integrations between AI-driven CLM solutions and broader enterprise ecosystems.
  • AI Governance Frameworks: Establishing policies for responsible AI adoption and ongoing model refinement.

Why CLM Matters Across Ecosystems

Contract Lifecycle Management sits at the crossroads of multiple systems—ERP, S2P, CRM, and O2C—making the Build vs. Buy and BoB vs. BoS debates particularly significant. 

AI in CLM

AI transforms CLM capabilities:

  • Predictive Analytics: Assess contract risks and opportunities.
  • Contract Drafting: Use LLMs to auto-generate precise clauses.
  • Autonomous Agents: Proactively monitor compliance and suggest updates. 

Emerging AI-Driven Innovations

  • Advanced Analytics Agents: Provide actionable insights into contract performance.
  • Custom AI Models: Tailor solutions for industry-specific requirements.
  • Unified Data Layers: Bridge silos between procurement, legal, and sales.

Framework for Strategic Decision-Making

 To navigate these decisions effectively:

  1. Assess Business Objectives: Prioritize outcomes like agility, scalability, and cost efficiency.
  2. Evaluate AI Readiness: Ensure data infrastructure supports emerging technologies.
  3. Balance Costs and Value: Consider long-term ROI over initial expenses.
  4. Align Stakeholders: Foster collaboration between IT, legal, and business units.
  5. Plan for Scalability: Choose platforms with robust APIs and modularity for future growth.

Conclusion: Crafting the Right Strategy for Transformation

The Build vs. Buy and Best of Breed vs. Best of Suite debates remain pivotal, but AI is redefining their parameters. By embracing hybrid approaches, leveraging AI’s transformative power, and aligning decisions with business outcomes, enterprises can position themselves for sustained success.

About

Mahin Chugh is a seasoned digital transformation and contract lifecycle management (CLM) expert, with extensive experience in solution architecture and strategic account management. Over his career, he has held leadership roles at Oracle, Hewlett Packard, Tata Consultancy Services, and Icertis, driving impactful digital initiatives and managing large-scale ERP, SaaS, and outsourcing projects. Mahin specializes in optimizing business processes, enhancing compliance, and delivering tailored CLM solutions across industries.

With global experience spanning Australia, the Nordics, the UK, India, and the EU, Mahin has a proven track record in leading high-value deals, managing multi-vendor ecosystems, and aligning technology with business goals. Certified in TOGAF, Prince2, and ITIL, he combines strategic insights with cutting-edge tools to help organizations navigate complex technology landscapes and achieve transformative growth.

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