Reframing Organizational Insight Using Voting Behavior Models and the AMPLIO JTBD Framework

Product Overview

Design for Motivation, Deliver with Intelligence

Understand what people truly need—and build systems that actually deliver.

This all-in-one guide brings together behavioral science, systems thinking, Agile coaching, and value stream management to help product teams, enterprise leaders, and transformation coaches make better, more human-centered decisions.

Whether you're designing software, improving services, or building public trust, this resource shows you how to:

• Decode motivation using the Michigan, Columbia, and Rational Choice behavior models
• Discover Jobs-To-Be-Done (JTBD) with clarity and empathy
• Write measurable, value-first requirements using Requirements by Objectives (RBO)
• Allocate effort wisely with Lean Allocation and Cost of Delay tools
• Deliver incrementally with EVO (Evolutionary Project Management)
• Apply Theory of Constraints (ToC) and feedback loops to spot bottlenecks
• Use Planguage and Impact Estimation Tables (IETs) to track progress and make better design choices
• Leverage Generative AI to augment—never replace—human insight
• Coach teams toward value through Toyota KATA routines and systems-based journaling

🧭 What’s Inside

SECTION 1: Behavioral Foundations for Organizational Insight

• 1.1 Overview of the Michigan, Columbia, and Rational Choice Models
• 1.2 How Motivation Models Apply to Stakeholders and Teams
• 1.3 Reframing Behavior Using AMPLIO’s JTBD Framework
• 1.4 Case Study Applications Across Tech, Nonprofit, and Education
• 1.5 Segmenting Stakeholders by Model and Designing for Each

SECTION 2: From Motivation to Measurable Value

• 2.1 Introduction to JTBD in Systems Context
• 2.2 Writing Requirements by Objectives (RBO) from JTBD
• 2.3 Systems Thinking for Coaches: From Parts to Purpose
• 2.4 RBO Templates, Examples, and Common Pitfalls
• 2.5 Workshop Kit: Motivation Beyond Metrics

SECTION 3: Value Stream Thinking and Lean Allocation

• 3.1 What Is a Value Stream? How to Think in Flow
• 3.2 Lean Allocation: Scoring by Value/Effort & Cost of Delay
• 3.3 Prioritizing by JTBD Impact and Flow Contribution
• 3.4 Avoiding False Tradeoffs: Suboptimization and System Failure
• 3.5 Tools: Lean Score Matrix, Flow Diagnostic Logs, Delay Risk Grid

SECTION 4: EVO Strategy and Planguage for Iterative Value

• 4.1 EVO: Delivering Value in Small, Measurable Steps
• 4.2 EVO Planning: Outcome First, Effort Second
• 4.3 Gilb’s Planguage: Tags, Meters, Scales, Past, Goal, Tolerance
• 4.4 Impact Estimation Tables (IET): Comparing Design Options
• 4.5 EVO Logs and RBO-Linked Progress Tracking

SECTION 5: Theory of Constraints and Systems Design

• 5.1 Introduction to Theory of Constraints (ToC)
• 5.2 Identifying Constraints in Flow
• 5.3 Exploiting, Subordinating, and Elevating Bottlenecks
• 5.4 Using Feedback Loops and Delay Awareness in Coaching
• 5.5 Mapping Constraint-Driven Systems with Templates

SECTION 6: KATA Coaching and Behavior-Driven Improvement

• 6.1 Aligning Toyota KATA with RBO, JTBD, and Systems Awareness
• 6.2 Coach's Weekly Routine Using EVO + RBO
• 6.3 KATA Coaching Prompts by Step
• 6.4 Reflection Journal for Coaches and System Influencers
• 6.5 Workshop Script: Coaching for Value, Not Activity

SECTION 7: Generative AI for Value Design and Delivery

• 7.1 Strategic Use Cases for GenAI in JTBD and RBO
• 7.2 Impact Estimation Tables for AI Use Cases
• 7.3 Guardrails: How to Use GenAI Without Substituting for Thinking
• 7.4 Co-Creating EVO Steps and Constraints Analysis with AI
• 7.5 Metrics for GenAI in Planning, Flow, and Feedback Systems

SECTION 8: Appendices and Resources

• 8.1 Lean Tools Decision Grid (When to Use or Avoid)
• 8.2 Impact Estimation Table Templates (Editable + Scored)
• 8.3 Case Studies: Three Sector Simulations + Outcome Data
• 8.4 KATA + EVO Flow Alignment Cards
• 8.5 Coach’s Planner, System Journal, and Stakeholder Mapping Guide
• 8.6 Glossary of Terms: JTBD, RBO, Planguage, ToC, EVO, KATA