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Our Approach
Our Approach
Decision performance is the beginning and the end. No visibility is too expensive.
Our Frameworks
Our Frameworks
Every capable agent operates under a set of rights and responsibilities. Stable and effective systems require these to remain appropriately balanced. Persistent imbalance creates adaptive pressure that is resolved through structural change, cultural adaptation, or system degradation.
Decision Opportunity Representation (DOOR) is a framework for formally representing decision opportunities—the situations in which an agent can deliberately impact the environment.
The Decision Organization Map (DOM) is a framework for mapping how an organization organizes its recurring decision opportunities. Rather than evaluating business performance, DOM describes how decision opportunities are coordinated throughout the organization and identifies opportunities to improve decision organization.
DOM is built on three independent dimensions: Objective Orientation, Decision Opportunity Portfolio, Decision Opportunity Representation.
ICE stands for Impact, Confidence, and Ease — three factors used to score and rank experiment ideas on a scale of 1 to 10.
Impact — How much will this move your target metric?
Confidence — How sure are you it will work?
Ease — How quickly can you ship it?
David Parmenter argues that meaningful performance measures should be closely aligned with organizational objectives, clearly understood by users, measured frequently enough to support timely action, and assigned to individuals who can influence the results. In his framework, effective KPIs are not merely metrics to monitor performance—they are measures that drive appropriate behaviors and improve decision-making throughout the organization.
Joe Reis and Matt Housley define data ingestion as more than simply moving data between systems, emphasizing that effective ingestion pipelines should be designed for reliability, scalability, durability, schema evolution, error handling, and operational maintainability. Their data engineering lifecycle provides a practical framework for evaluating whether ingestion architectures can consistently deliver high-quality data to downstream analytics and decision-making systems.
Cole Nussbaumer Knaflic argues that effective data visualizations should communicate a clear message by reducing unnecessary visual complexity and directing the audience's attention to the most important insights. Her framework emphasizes audience-centered design, thoughtful visual encoding, and purposeful use of color and annotation to transform charts into compelling, decision-supporting narratives.
Apollo Root Cause Analysis (ARCA), developed by Dean Gano, provides a structured, evidence-based framework for identifying the underlying causes of organizational problems by mapping cause-and-effect relationships rather than relying on linear assumptions. The methodology emphasizes that effective problem-solving requires addressing multiple contributing causes through corrective actions that eliminate or control the conditions responsible for recurring failures.
The Decision Alert Design (DAD) Framework is a structured methodology for designing effective organizational alerting systems. Rather than relying solely on thresholds, DAD determines whether an alert should exist, how important it is, and the most appropriate communication mechanism based on decision value, urgency, and organizational impact.
A/B testing is a controlled experimentation framework that compares two or more alternatives by randomly assigning subjects to different variants and measuring differences in outcomes. It provides statistically grounded evidence for selecting the option that performs best, making it a widely used approach for optimizing products, marketing, user experiences, and business decisions.
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