Accelerated Innovation

Defining Your LLM Evaluation Scope

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Defining Your LLM Evaluation Scope

Description

This capability focuses on how organizations define the goals, constraints, and intended use cases for their Large Language Model (LLM) evaluations. It includes establishing clear objectives, aligning on performance metrics, and scoping evaluation criteria to ensure selected models meet business and technical needs.

Why it's Important

Selecting the right LLM is foundational to GenAI success, but that selection is only as good as the clarity of the evaluation scope. Without clearly defined objectives and constraints, teams risk misaligned evaluations, wasted resources, or poor model fit. A well-scoped evaluation helps organizations compare models more effectively, accelerate procurement or build decisions, and ensure alignment with user needs and enterprise priorities. It also enables repeatable evaluation practices that can scale across teams, use cases, and model types.

Why it's Challenging @ Scale

  • Lack of shared evaluation goals across teams: Different groups may approach LLM selection with varying priorities, leading to fragmented or conflicting objectives.
  • Overreliance on generic metrics: Teams often default to widely available benchmarks that may not reflect their real-world use cases or requirements.
  • Difficulty balancing flexibility and standardization: It can be challenging to allow for custom evaluation criteria while still maintaining consistency across efforts.
  • Limited visibility into constraints: Key technical, regulatory, or resource constraints are often overlooked when defining scope.
  • Slow or unclear feedback loops: Without clear measurement criteria and review processes, teams struggle to improve evaluation scope over time.

Complexity

High: Maturing this capability requires aligning stakeholders on evaluation priorities, translating those into structured criteria, and embedding them into repeatable evaluation workflows.

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Taking Action

Though most organizations begin their GenAI journey with significant knowledge gaps, there are targeted actions that can be taken to accelerate the process. Select your group’s current maturity, based on your assessment results, and act today.

The most important part of any journey is starting… To move from “Exploring” to “Experimenting”, focus on the following key actions:
  • Explore Key Concepts & Best Practices: Complete the Evaluating and Selecting the Best Model(s) for Your GenAI Solution workshop (2 hrs.) to understand foundational key concepts and explore applied best practices
  • Outlining the Model Evaluation Lifecycle
  • Understanding Model Types and Capabilities
  • Aligning Evaluation to Solution Objectives
  • Comparing Commercial vs. Open Source Options
  • Establishing a Reusable Evaluation Framework
  • Define Your Action Plan: Outline concrete, prioritized steps your organization will take to implement GenAI Strategy
  • Align on your Current State and define your Target State
  • Create an actionable enablement plan
  • Define target timeline and measures of success
  • Deliver Quick Wins: Small, high-impact GenAI projects that can demonstrate tangible value in a short time frame
  • Draft LLM Evaluation Objectives: Define initial goals and priorities for one or more evaluation efforts.
  • Align on Must-Have Constraints: Identify technical, regulatory, or operational boundaries early in the process.
  • Pilot a Use-Case-Aligned Scoring Rubric: Test a lightweight scoring method aligned to a specific business problem.
To move from Experimentation to “Lifting-Off”, prioritize the following actions:
  • Complete one or more of our Deep Dive Courses: Begin exploring key concepts and best practices, including:
  • Defining Your Model Objectives & Requirements
  • Model Evaluation Data Assessment and Prep
  • Selecting In-Scope Models
  • LLM Evaluation
  • Nail It Before You Scale It: Assess and optimize your solution or process before adopting it at scale
  • Assess Your Proposed Solution or Process: Review whether evaluation scope documents are clearly defined, relevant, and aligned to use case needs.
  • Define in-scope Processes and Guardrails: Identify how evaluation scope is developed, reviewed, and enforced across teams.
  • Close any Data or Measurement Gaps: Ensure business goals and evaluation metrics are well-linked and that feedback loops are in place.
  • Define Your Adoption & Scaling Plan: Create a structured roadmap for how GenAI solutions will be rolled out across teams, workflows, or business units
  • Define Your Phased Implementation Plan: Sequence rollout of scope definition practices starting with high-priority GenAI use cases.
  • Build Awareness and Finalize Enablers: Provide scoping templates, examples, and training to teams participating in evaluations.
  • Operationalize Your Comms Plan: Share success stories and reinforce the value of strong scope practices across the organization.
To move from Lifting-Off to “Accelerating”, prioritize the following actions:
  • Formalize Your Best Practices: Document and standardize what’s working to ensure consistent, scalable success across teams and use cases
  • Standardize Scope Templates: Publish reusable scope templates that include evaluation goals, constraints, and use-case alignment.
  • Create Evaluation Scope Playbooks: Provide teams with step-by-step instructions for scoping LLM evaluations effectively.
  • Integrate Scope Reviews into Development Workflows: Embed scope checkpoints into GenAI solution planning and delivery cycles.
  • Accelerate Your Adoption: Intensify efforts to embed GenAI across your organization by expanding use cases, increasing user engagement, and removing adoption barriers
  • Broaden Scope Alignment Across Teams: Extend evaluation scope practices to new domains, teams, or business units.
  • Equip Teams with Training and Examples: Offer curated examples and training sessions to help teams apply scope best practices.
  • Conduct Evaluation Retrospectives: Use completed evaluations to improve future scoping accuracy and team confidence.
  • Celebrate Your Wins: Publicly acknowledge team accomplishments to build and sustain adoption momentum
  • Showcase Effective Scope Use Cases: Highlight evaluations that achieved strong results through well-defined scope.
  • Share Before-and-After Comparisons: Illustrate how scope clarity improved evaluation efficiency or model fit.
  • Recognize Scope Champions: Acknowledge teams or individuals who contributed to refining scope practices.
The “Accelerating” stage represents “Target State” for many capabilities. “Breaking Away”, on the other hand, suggests that the specific Capability represents a clear competitive advantage for your business
  • Streamline & Embed: Integrate GenAI into core workflows while eliminating friction points to make usage seamless and routine
  • Embed Scope Templates in Planning Tools: Make scope definitions a required artifact in solution planning tools and workflows.
  • Require Scope in Model Registrations: Ensure all LLM registrations include standardized scope documentation.
  • Harmonize Scoping Practices Across Use Cases: Align scoping processes across internal, external, and cross-functional GenAI efforts.
  • Leverage Automation: Using GenAI-powered tools and workflows to streamline repetitive tasks, enhance operational efficiency, and reduce manual effort
  • Automate Scope Review Workflows: Use AI to check for completeness and consistency in submitted evaluation scopes.
  • Generate Draft Scopes Automatically: Leverage prompts and past examples to pre-fill scope templates for new evaluations.
  • Track Scope Coverage and Gaps: Implement dashboards to monitor where evaluations are missing key scoping elements.
  • Evolve & Further Accelerate: Continuously refining GenAI strategies based on insights and outcomes, while expanding into more complex or high-impact use cases
  • Update Scope Guidelines Based on Results: Refine scope practices based on evaluation outcomes and team feedback.
  • Expand to Multimodal Evaluation: Extend scope practices to audio, visual, or multimodal GenAI models.
  • Benchmark Scoping Quality Over Time: Measure scoping maturity across teams and use cases to guide future investments.

Key "Watchouts"

As you take action you’ll want to avoid:

  • Rushing scope definition: Skipping this step or doing it poorly results in wasted evaluation cycles and poor model fit.
  • Using one-size-fits-all templates: Generic scope documents may miss domain-specific constraints or priorities.
  • Overlooking stakeholder alignment: Misalignment between technical and business teams leads to unclear evaluation goals.
  • Focusing only on short-term needs: Scopes that ignore future use cases or scaling requirements create rework later.
  • Failing to revisit and refine scope: Scope needs to evolve based on new insights, outcomes, and business changes.

Targeted Benefits

While Defining Your LLM Evaluation Scope can be challenging, its benefits are clear and compelling, including:

  • Improved model fit: Clear scope enables more targeted evaluations and better-aligned model selections.
  • Faster decision-making: Well-scoped evaluations accelerate shortlisting, comparisons, and approvals.
  • Reduced wasted effort: Avoids evaluating models that don’t meet must-have constraints or needs.
  • Stronger cross-team alignment: Brings business, technical, and data stakeholders into early agreement.
  • More scalable practices: Enables consistent and repeatable evaluation methods across teams and use cases.

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Eddie
Accelerated Innovation

Hi, I'm Eddie 👋

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