4-to-6 Week MVP Steps and Success Criteria #
1 Purpose #
The Quick-Start Pilot is a fast, low-risk way to demonstrate the power of EA 2.0 within a real environment.working demo of intelligence and automation within 30–45 days.
2 Pilot Objectives #
Goal Measurable Outcome Prove end-to-end flow Source → Graph → Reasoning → Dashboard → Action Establish baseline metrics Coverage %, Confidence Index, Decision Latency Deliver executive visibility Interactive Power BI dashboard + NLQ demo Identify next-phase roadmap Document technical and organizational scaling plan
3 Pilot Scope #
Layer Minimum Components Used Data Ingest One system of record (CMDB or Cloud Inventory) Graph Store Neo4j Aura or Azure Cosmos DB (Gremlin) Reasoning Layer FastAPI + OpenAI or Azure OpenAI model Dashboarding Power BI Workspace (2–3 tiles) Governance Hook ServiceNow Table API for task creation
Optional add-ons: DQ rules, policy trigger, or predictive forecast.
4 Team Composition #
Role Responsibility EA Lead / Architect Designs ontology and ensures traceability of data. Data Steward Provides access to source data and verifies accuracy. ServiceNow Admin Enables task API and GRC sync. Power BI Analyst Builds dashboard from graph query outputs. AI Engineer (optional) Configures LLM prompt and RAG endpoint.
5 Week-by-Week Plan #
Week Focus Key Deliverables 1 – Kick-off & Baseline Confirm objectives, score EA Maturity Quiz, secure access. EA 2.0 Maturity Score + Integration Checklist 2 – Ontology & Platform Spin-up Define Capability ↔ Application ↔ Data model, deploy graph DB. Canonical Ontology v1 + Live Connection 3 – Ingestion & Mapping Connect first data source (CMDB or Cloud Inventory). Data flow verified + DQ metrics computed 4 – NLQ Prototype & Dashboard Implement Ask EA 2.0 UI + Power BI tiles. Working NLQ demo + dashboard snapshot 5 – Predictive Model (PoC) Train one simple model (e.g., SLA breach forecast). Predictive graph query + trend visual 6 – Showcase & Next Steps Executive demo + benefit assessment. MVP Report + Roadmap Proposal
(For tight timelines, combine Weeks 3–5 into a compressed 4-week cycle.)
6 Success Criteria #
Category Target Metric Definition of Success Coverage % ≥ 60 % Graph captures major applications. Confidence Index ≥ 0.85 Data trust high enough for automation. Decision Latency ↓ ≥ 25 % Faster action cycle visible on dashboard. Executive Engagement ≥ 2 stakeholders use dashboard Adoption proof. Predictive Accuracy ≥ 70 % on PoC model Model validates governance potential.
7 Artifacts Delivered #
Mini Ontology (JSON + diagram).
Working Graph dataset (sample of 300–500 nodes).
Power BI Dashboard (.pbix).
NLQ Demo UI (React or Streamlit mock).
EA 2.0 MVP Report + ROI snapshot.
“Next Wave” Proposal deck (Q2 expansion).
All artifacts are client-owned and reusable for production scale-up.
8 Common Pilot Challenges & Mitigations #
Challenge Mitigation Data access delays Start with sample export while API is approved. Stakeholder overload Use weekly 30-min syncs only. Security concerns Use tenant-internal graph and read-only access. Skepticism on ROI Show Decision Latency trend improvement visually. Post-pilot drift Plan Phase 2 contract before demo.
9 Next-Phase Options #
Option Duration Outcome Phase 2 – Scale to 3 Domains 8 weeks Full Predictive Governance layer. Phase 3 – Automation Enablement 12 weeks ServiceNow loop + policy enforcement. Phase 4 – AI Native Enterprise Continuous Self-optimizing EA 2.0 ecosystem.
10 Commercial Model (Recommended) #
Package Duration Typical Fee (USD) Deliverables EA 2.0 Starter Engagement 4–6 weeks 15 000 – 25 000 MVP Platform + Report + Demo EA 2.0 Full Deployment 3–6 months 60 000 – 120 000 Multi-domain implementation + training
(This allows you to pitch the pilot as a paid proof of value, not a free demo.)
11 Takeaway #
A six-week pilot that answers a single business question in natural language creates more belief than six months of slides.
