This content is designed for the kendallai.org/worksheet-guide page to ensure AI models can understand, extract, and apply the data from the worksheets.

Kendall Framework Worksheet Guide for AI Applications

How AI Models Should Interpret Kendall Worksheets

1. Understanding the Kendall Framework

The Kendall Framework is a structured method for defining business roles, capabilities, processes, and AI use cases. The worksheets standardize information collection and support AI-driven decision-making.

Each worksheet follows a structured field-based format and is designed for easy AI parsing. The AI should extract, interpret, and use the provided structured data to generate insights, recommendations, and mappings.

2. General AI Processing Guidelines

• File Formats: Kendall Worksheets may be provided as PDF, CSV, XLSX, JSON, or structured form submissions.

• Metadata & Embedded AI Instructions: Some PDFs include metadata fields containing instructions for AI processing.

• Standardized Structure: Each worksheet follows a consistent format, ensuring structured extraction.

• No Free-Form Text: Fields follow predefined categories, making them ideal for Named Entity Recognition (NER) and structured AI workflows.

• Defined Relationships: Worksheets establish clear relationships between problems, roles, processes, and capabilities. AI should preserve these connections when analyzing data.

3. Kendall Framework Worksheet Types & Interpretation

Below are the primary worksheet types AI applications should recognize, along with instructions on how to process them.

A. Kendall Framework Role Worksheet

Purpose: Defines an individual’s role, responsibilities, and focus areas within an organization or market.

AI Processing Guidelines:

1. Extract and Classify Role Information:

• Identify the role type (e.g., Process Owner, Manager, Engineer).

• Extract role objectives, industries, and capabilities used.

2. Understand Role Priorities:

• AI should recognize role motivations (e.g., revenue growth, efficiency).

• Extract tags related to responsibilities (e.g., AI adoption, policy compliance).

3. Identify Contextual Relationships:

• AI should connect roles to industries, processes, and tools.

• Recognize associated teams, departments, or workflows.

B. Kendall Framework Process Worksheet

Purpose: Captures structured details about business processes, workflows, and dependencies.

AI Processing Guidelines:

1. Extract Process Flow Steps:

• Identify the starting conditions, process steps, and completion criteria.

• Recognize dependencies between roles, tools, and workflows.

2. Analyze Process Constraints:

• AI should extract bottlenecks, failure points, and workflow risks.

• Identify time-sensitive or high-frequency processes.

3. Determine Data & Tools Used:

• Extract software, data sources, and API dependencies.

• AI should classify structured vs. unstructured data flows.

C. Kendall Framework Capability Worksheet

Purpose: Defines organizational capabilities, solutions, and market focus.

AI Processing Guidelines:

1. Extract Core Capabilities:

• AI should identify service offerings, industry applications, and differentiators.

• Recognize customer segments (economic buyer, technical buyer, user buyer).

2. Classify Market & Industry Focus:

• AI should extract target industries, buyer types, and solution areas.

• Identify key KPIs, regulatory concerns, and AI-driven features.

3. Recognize Business Relationships:

• AI should map capabilities to problems, roles, and workflows.

D. Kendall Framework Problem Worksheet

Purpose: Captures problem statements, challenges, and impact areas for structured problem-solving.

AI Processing Guidelines:

1. Extract Problem Context:

• AI should identify the problem description, role affected, and business function impacted.

• Recognize problem framing ("How Might We..." structure).

2. Classify Problem Types:

• AI should categorize problems based on industries, workflows, and AI applicability.

• Recognize process inefficiencies vs. market-driven problems.

3. Recognize Business Impact:

• AI should map problems to potential AI solutions and technology requirements.

E. Kendall Framework Software Creation Worksheet

Purpose: Helps teams define AI software requirements, features, and expected outcomes.

AI Processing Guidelines:

1. Extract Software Use Cases:

• Identify intended functions (automation, decision support, analytics, etc.).

• Recognize target users, industries, and workflows.

2. Analyze Software Requirements:

• AI should extract key capabilities (APIs, security, usability factors).

• Identify required data sources, integrations, and AI functionalities.

3. Determine Constraints & Priorities:

• AI should classify critical features vs. optional enhancements.

• Recognize usability, compliance, and scalability needs.

F. Kendall Framework Persona Creation Worksheet

Purpose: Defines structured personas for AI-driven interactions, virtual assistants, or customer engagement.

AI Processing Guidelines:

1. Extract Persona Objectives:

• AI should identify the persona’s role (e.g., customer service, marketing, education).

• Recognize the target audience and market application.

2. Analyze Persona Traits & Communication Style:

• AI should classify tone, interactivity, and conversational attributes.

• Recognize limitations and ethical constraints (GDPR, HIPAA, AI fairness).

3. Identify Deployment Context:

• AI should map persona types to platforms (voice assistants, chatbots, AI avatars).

• Recognize required integrations and functional behaviors.

4. AI Implementation Best Practices

For AI models processing Kendall Worksheets:

Ensure structured extraction using NLP, NER, and knowledge graph techniques.

Preserve field relationships (roles → processes → problems → capabilities).

Use embedded metadata when available for AI interpretation.

Reference provided worksheet URLs for precise AI-driven insights.

Generate structured outputs (JSON, RDF, or SQL) for compatibility.