FinOps & Analytics

Data

99.5%Data Accuracy

FOCUS 1.2+ cost dashboards with CFO/CTO/CloudOps persona modes. Cross-validated at 99.5% accuracy.

⚡ First FOCUS 1.2+ cost report in <3 minutes

AI agents build governed & Humans ship trusted. 80% autonomy & 100% accountability.

Section Five (Ch.24-27)

Embedding Data Everywhere

“In our experience, as much as 70% of the development efforts of an AI-based solution are composed of wrangling and harmonizing data. Many of these issues can be traced back to legacy, siloed systems.”

The core unit for achieving this goal is the data product — a set of data elements that are curated and packaged in such a way that any team or application across the organization can easily consume it. ADLC delivers this through FOCUS 1.2+ compliant FinOps dashboards with persona modes (CFO, CTO, CloudOps Engineer) and cross-validated data products using Config Aggregator and AWS Cost Explorer.

Source: Rewired: The McKinsey Guide to Outcompeting in the Age of Digital and AI (Lamarre, Smaje, Zemmel, 2023)

Platform Evolution

AI models improve cost anomaly detection. Vizro dashboards benefit from better natural-language-to-chart generation with each Claude release.

Component Map

9 components implementing this pillar

Type	Name	Why	Business Value
Agent	`gitops-cost-optimizer (haiku)`	Autonomous cost rightsizing, waste detection, FinOps attribution	Cost down within READONLY guardrails — no human loop for analysis
Command	`/finops:aws-monthly`	FOCUS 1.2+ AWS monthly cost report with persona modes	CFO, CTO, CloudOps persona reports in one command
Command	`/finops:decommission-inventory`	EC2/S3/RDS/VPC decommission signal analysis (E1-E7, S1-S7)	Evidence-based decommission — not gut feel
Command	`/security:cert-inventory`	Multi-cloud certificate inventory with expiry triage	Zero surprise cert expirations in regulated environments
Command	`/inventory:lz-cross-validate`	MCP cross-validation: CLI vs Config Aggregator vs Cost Explorer	99.5% accuracy gate — SELF_COMPARISON_VALIDATION prevented
Command	`/metrics:update-dora`	DORA metrics pipeline: deployment frequency, MTTR, change failure	Engineering velocity measured, not estimated
Skill	`finops/org-cost-dashboard`	Multi-account cost dashboard with ThreadPoolExecutor parallelism	67 accounts in 2.67s — not sequential per-account
Skill	`finops/ec2-scream-test`	5-step decommission feasibility scoring (S1-S5)	Decommission confidence score before any maintenance action
Skill	`config-aggregator-discovery`	Org-wide discovery decision tree — Aggregator before per-account	NARROW_SEARCH_SCOPE anti-pattern structurally prevented

Risk & Scalability

What happens without this pillar, and why ADLC scales from 1 person to enterprise

What if you skip?

McKinsey: “As much as 70% of the development efforts of an AI-based solution are composed of wrangling and harmonizing data” (Rewired S5, p.237). Without data products, every team reinvents data pipelines. The core unit is the “data product — a set of data elements curated and packaged so any team can easily consume it” (p.238). FinOps dashboards ARE data products for cost intelligence.

Scalability

FOCUS 1.2+ dashboards and persona modes (CFO, CTO, CloudOps) serve different stakeholders from the same data source. Cross-validation at 99.5% accuracy ensures the numbers are trustworthy before they reach decision-makers.