Services
Data Strategy
A data strategy that works starts with decisions, not technology. We help you define what matters, build the right foundation, and align your data systems with how your organization actually operates.
Key Takeaways
A data strategy defines how your organization collects, stores, manages, and uses data to drive business decisions. Mid-market companies typically need 3-6 months to develop and implement an effective data strategy that aligns data capabilities with business goals.
- Start with a data maturity assessment to understand where you are
- Align data goals directly with business objectives and revenue targets
- Choose tools your team will actually adopt — not the trendiest option
- Plan for governance from day one to ensure data trust and quality
- Build iteratively with quick wins that demonstrate ROI within 90 days
How we approach data strategy
A data strategy that gathers dust in a slide deck isn't a strategy. The ones that work start with business questions — what decisions does this organization need to make better? — and work backward to the technology.
Our approach follows a consistent pattern:
- Discovery. We sit down with the people who run the business — operations, finance, sales, leadership — and ask what questions they can't answer today. These become the requirements your data strategy needs to meet.
- Assessment. We inventory what exists: source systems, data quality, current tools, governance gaps. Most organizations have more infrastructure than they think — the problem is usually connection, not collection.
- Architecture. We design the data infrastructure to serve the business questions from Step 1. Cloud warehouse, pipeline automation, BI tools, governance framework — right-sized for your organization, not overbuilt.
- Roadmap. We sequence the work into phases based on business impact. Each phase delivers measurable value — not just technical progress.
- Iteration. We build in quarterly reviews so the strategy evolves with the business. New questions emerge, priorities shift, and your data strategy should adapt.
The result is a living plan that connects every data investment to a business outcome.
What we deliver
Data Strategy Assessment
A structured evaluation of your current data landscape — sources, quality, accessibility, governance, and tool utilization. We identify what's working, what's not, and where the gaps are.
Data Architecture Design
A blueprint for how data flows through your organization — from source systems to warehouse to dashboards. Designed for your current scale with room to grow.
Data Governance Framework
Ownership, quality rules, access controls, and documentation. The foundation that ensures your data is trustworthy, consistent, and secure.
Tool & Platform Selection
Vendor-neutral evaluation of BI tools, data warehouses, integration platforms, and governance tools. We recommend based on your needs, not our preferences.
Roadmap & Sequencing
A phased execution plan that prioritizes by business impact. Quick wins first, then progressively more advanced capabilities — each phase delivering value the business can see.
Executive Alignment
Workshops and presentations that get leadership aligned on data priorities. A data strategy without executive sponsorship doesn't survive budget season.
Why most data strategies fail
We've inherited enough failed data strategies to see the patterns:
- ✓They started with technology. Someone chose a data warehouse or BI tool before asking what business problems needed solving. The result: expensive infrastructure that nobody uses.
- ✓They skipped governance. Dashboards were built, but nobody agreed on how to calculate revenue or churn. Three departments report three different numbers, and nobody trusts any of them.
- ✓They tried to boil the ocean. The strategy attempted to govern every dataset and connect every system before delivering anything useful. By the time the first dashboard shipped, the business had moved on.
- ✓They lacked executive sponsorship. Data strategies that live exclusively in IT rarely survive. The business side needs to own the outcomes and the priorities.
We build strategies that avoid these traps by starting with the business, delivering value in phases, and keeping leadership in the room throughout.
Frequently Asked Questions
What is a data strategy?
A data strategy is a plan for how your organization will collect, store, govern, and use data to support its business objectives. It covers architecture, governance, tool selection, team structure, and a phased roadmap — all aligned to the decisions your business needs to make better.
How long does a data strategy project take?
A focused data strategy engagement typically takes 8-12 weeks: 2-3 weeks for discovery and assessment, 2-3 weeks for architecture design, and 3-4 weeks for roadmap development and executive alignment. Larger organizations with more complex data landscapes may take longer.
What's the difference between data strategy and data governance?
Data strategy is the overall plan — what data you need, how you'll use it, and what to build. Data governance is one component of that plan — the rules, ownership, and processes that ensure data quality and security. You can't have good governance without a strategy, and a strategy without governance leads to chaos.
How do I know if my organization needs a data strategy?
If your team makes decisions without data because it's too hard to access, if different departments report different numbers for the same metrics, or if your data investments aren't delivering visible business value — you need a strategy. The clearest sign: you have tools but not trust.
What does the deliverable look like?
You'll receive: a current-state assessment documenting your data landscape and gaps, an architecture blueprint for your target infrastructure, a governance framework defining data ownership and quality standards, and a phased roadmap with prioritized initiatives, timelines, and success metrics.
Do you help with implementation or just the strategy?
Both. We can build the strategy and hand it off to your team, or we can stay on to execute. Many clients start with the strategy engagement and transition into a Data Team as a Service model for implementation.
Learn more about data strategy
How to Build a Data Strategy: A Practical Guide — our step-by-step framework for building a data strategy that gets implemented.
What Is Data Strategy? A Complete Guide for Business Leaders — definitions, components, and what to expect from a data strategy engagement.
Why Every Mid-Market Organization Needs a Data Strategy — the business case for investing in data strategy.
See This Service in Action
Unified Business Intelligence for a Multi-Region Healthcare Organization
A behavioral health organization with 90+ locations consolidated three disconnected systems into unified analytics, projecting $736,920/year in savings from automating 5 manual reporting processes.
Building a Data-Driven Foundation for a Nationwide Electrical Contractor
How VisionWrights designed finance dashboards that gave a nationwide electrical contractor a single source of truth for day-to-day decision-making.
Consolidating 15+ Systems into a Modern BI Platform for a $7B Real Estate Firm
How VisionWrights helped a $7B real estate company move from retrospective reporting to real-time visibility by consolidating more than 15 systems into a centralized analytics platform.
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Let's Build Your Data Strategy
Start with a conversation about what decisions your organization needs to make better.