The Challenge
Why data strategies fail.
A strategy without execution is just an expensive presentation. Most data strategies lack the pragmatic prioritization needed to survive CFO scrutiny.
The Vision Deck Nobody Opens
You have a slide deck titled "Data Strategy" on SharePoint. It describes a "data-driven culture" and lists "key initiatives." But when a new Power BI project starts, nobody references it. When someone proposes a Fabric implementation, the deck stays closed. The strategy exists. Execution doesn't.os;t.
Competing Priorities, No Framework
Finance wants faster monthly close. Marketing wants customer analytics. Operations wants real-time Power BI dashboards. IT wants to modernize the data warehouse to Fabric. Everyone has legitimate needs and executive sponsors. Nobody has a framework for deciding "this first, that later, this never."
No Business Case That Survives CFO Scrutiny
You know you need to invest in Microsoft Fabric. But the CFO wants numbers. What's the ROI on a Lakehouse? What's the cost of inaction? What's the total investment over 18 months? Without a business case that answers these questions with credible numbers, data initiatives compete for budget against projects with clearer returns — and lose.
Deliverables
What a real strategy looks like.
Current State Assessment
A clear-eyed view of your existing data landscape: Azure resources, data flows, Power BI reports, capabilities, gaps, and technical debt.
Prioritized Roadmap
A phased implementation plan with 90-day milestones, dependencies, and decision points. Each phase delivers measurable business value.
Business Case
Financial analysis quantifying investment and expected return. Includes cost of current state, Fabric capacity costs, implementation investment, and expected benefits.
Governance Model
A governance framework using Microsoft Purview: data ownership, quality standards, sensitivity labels, and lineage tracking.
Methodology
How we build a strategy
Interviews, architectural design, and financial modeling — typically 6–8 weeks from kickoff to final presentation.
Discovery
We interview stakeholders, review Azure consumption, audit existing Power BI content, and assess current state. We map business objectives to data requirements.
Strategy Development
We design the target state architecture on Fabric, prioritize initiatives, and build the roadmap via working sessions with your team — not in isolation.
Business Case Development
We quantify Fabric capacity costs, implementation services, internal effort, and expected returns. We document assumptions so the business case is deeply credible.
Validation & Alignment
We present the strategy to leadership, incorporate feedback, and finalize deliverables. Our goal is organizational buy-in, not just documentation.
How we built a data strategy for a multi-company construction group.
The Situation
A PE-backed fire protection contractor had grown through acquisition. Five regional business units, each with their own ERP (mix of QuickBooks, Sage, and ServiceTitan for field ops), different job costing practices, and no consolidated financial view. The CFO needed unified reporting for board meetings but couldn't get consistent numbers. Manual report compilation took two weeks — and nobody trusted the final numbers.
What We Built
- Current State Map: 7 source systems, 14 different definitions of "revenue," zero shared data infrastructure.
- Target State Architecture: Microsoft Fabric with OneLake as unified storage. Lakehouse for consolidated data. Power BI semantic model for consistent metrics.
- Business Case: $340K annual savings from eliminated reconciliation. $180K implementation. 18-month payback.
2 Hours
Board deck generation time (down from 2 weeks)
16 Weeks
Phase 1 completed
Frequently Asked Questions
How long does a strategy engagement take?
Do we need a maturity assessment first?
What makes a strategy actually get implemented?
Continue Your Journey
Explore related services to help you define and execute your data strategy.
Maturity Assessment
Evaluate your current data capabilities and identify gaps before building your strategy.
Platform Evaluation
Objective analysis to select the right tools and architecture for your specific needs.
Foundation Build
Implement a robust, scalable data architecture that serves as the bedrock for analytics.