Frameworks

Frameworks

Core Frameworks

These frameworks form the foundation of Leading with Data. They reflect how I build analytics teams, design operating models, and structure decision‑making systems.

Each framework includes a clear thesis, practical guidance, and examples you can apply directly to your team.

Process‑First Data Strategy

A practical approach to stabilizing data by fixing the underlying business processes first.
This framework explains why most “data problems” are actually process problems — and how to diagnose and correct them.

Key ideas:

  • Process drives data quality
  • Fix upstream friction before modeling
  • Data strategy must follow business process strategy

Explore → /frameworks/process-first-data-strategy/

System‑First vs. Process‑First

A comparison of two competing approaches to analytics and system design — and why Process‑First consistently produces more stable, scalable outcomes.

Key ideas:

  • System‑First creates brittle, tool‑driven solutions
  • Process‑First creates durable, business‑aligned systems
  • How to shift your team from System‑First to Process‑First

Explore → (link to your future page)

Operating‑Model Clarity

A framework for defining how analytics teams actually operate: decision rights, intake, prioritization, communication loops, and value measurement.

Key ideas:

  • Clear ownership reduces churn
  • Predictable intake increases trust
  • Prioritization rules prevent chaos
  • Communication loops create alignment

Explore → (link to your future page)

Decision Intelligence for Analytics Teams

A practical model for aligning analytics work to the decisions it supports — not the dashboards it produces.

Key ideas:

  • Decisions are the unit of value
  • Every model/report should map to a decision
  • Decision pathways reveal gaps in data, process, or systems

Explore → (link to your future page)

Systems Thinking for Analytics

A way to understand data problems as symptoms of larger system dynamics — and how to design analytics workflows that account for upstream and downstream effects.

Key ideas:

  • Data issues are rarely isolated
  • Feedback loops matter
  • Systems thinking improves reliability and scale

Explore → (link to your future page)

How to Use These Frameworks

These frameworks are meant to be:

  • practical
  • adaptable
  • actionable
  • team‑friendly

Use them to:

  • clarify your team’s operating model
  • diagnose recurring data issues
  • improve decision‑making workflows
  • guide system design and governance
  • align analytics work to business outcomes

More frameworks will be added over time as I continue refining and documenting the models I use in practice.

Coming Soon

  • Process‑First Data Strategy (full guide)
  • Operating‑Model Clarity (full guide)
  • Decision Intelligence for Analytics Teams
  • Systems Thinking for Analytics
  • Intake & Prioritization Models
  • Governance & Enablement Frameworks

Stay tuned — this section will grow into a complete library of strategic models for analytics leadership.