Why these books exist

Across years of working with leaders, teams, data, and decisions, one pattern appeared consistently:

most decision failures were not caused by lack of intelligence, data, or effort—but by lack of decision-ready clarity.

People are routinely asked to decide under unclear conditions: noisy or misleading evidence, unstable interpretation, invisible constraints, or diffused responsibility. Data may exist without being interpretable. Accountability may be assigned without being meaningful. And human judgment—variable and state-dependent—is often treated as if it were constant.

These books were written to close that gap.

Each addresses decision quality from a different layer of the same system: data judgment, human judgment, and organizational decision design.

They can be read independently. Together, they form a coherent body of work on deciding clearly under real-world constraints.

Six Word Lessons for Data-Based Decision-Making

Focus: Data judgment → decision-ready awareness.

This book helps people move from having data to interpreting evidence more responsibly when decisions are on the line.

It presents 100 concise lessons drawn from analytics, BI, metrics, and statistical thinking—each capturing a recurring decision trap, misinterpretation, or judgment error that shows up in real organizations.

Rather than teaching step-by-step methods, the lessons function as cognitive guardrails—principles to recognize before acting on data.

The book sharpens judgment by helping readers:

• notice when data is misleading rather than informative,
• recognize signal vs noise errors before committing to action,
• avoid false precision, metric worship, and overconfidence,
• ask better questions of analysis, dashboards, and reports.

Its value is not procedural instruction, but decision awareness—making it harder to make confident mistakes with data.

Truths That Govern Life

Focus: Human judgment → adult decision clarity.

This book steps outside business and addresses decision-making at its human core.

It explores liberating, corrective, and regulatory truths about identity, desire, limitation, responsibility, and action—drawing from psychology, philosophy, and lived experience. It does not promise happiness, optimization, or inspiration.

Instead, it offers something more demanding: clarity where guarantees don’t exist.

Readers develop:

• greater tolerance for uncertainty and limits,
• clearer responsibility boundaries,
• reduced self-deception in decision narratives,
• more grounded, coherent choices under real constraints.

Its value lies in refining personal judgment so decisions—inside and outside work—become more conscious, adult, and livable.

HDE: Human Decision Engineering

(Upcoming Q2 2026)

Focus: Human variability → decision reliability.

This book introduces Human Decision Engineering (HDE) as a foundational discipline within the Decision Capability Framework.

Rather than treating people as the problem to fix, HDE treats human judgment variability as a system constraint to design for.

The book formalizes:

• Decision Readiness as a validity condition,
• Cognitive variability as a source of decision noise,
• Rules for when not to decide,
• Integration with Lean, Six Sigma, and SPC,
• Separation between process variation, data noise, bias, and human state effects.

Its core insight is simple and rigorous:

SPC stabilizes the process;
HDE stabilizes the interpreter of the process.

The value is more reliable decisions—not by trying harder, but by engineering better conditions for judgment.

Choosing Clarity When Decisions Matter Most

(Upcoming 2027)

Focus: The canonical articulation of end-to-end Decision Capability.

This book is the complete, integrated articulation of the Decision Capability Framework.

It is not a training manual or a collection of techniques. Those live in the engines, modules, and applied programs that operationalize the framework.

Instead, this book provides the full system view:

• Why the framework is structured as it is,
• How its parts work together,
• and What must be true for decision reliability to exist at scale.

It integrates, in one place:

• Decision and process modeling,
• Decision ownership and accountability,
• Metrics, BI, and decision-ready evidence,
• Statistical discipline,
• Judgment limits and interpretation,
• Cadence, governance, and decision gating,
• Learning loops that compound over time.

At its core is a simple premise:

Many decision failures are not analytical failures, but decisions made under invalid conditions.

Choosing Clarity defines those conditions, shows how to design for them end-to-end, and establishes Decision Capability as an organizational discipline—on par with finance, operations, or quality.

Its value is integration and legitimacy:

a shared mental model leaders can use to understand, align, and govern how decisions are made across the organization.