A data strategy your teams will actually run

Most data strategies are slide decks nobody executes. Brainforge produces the working version: a maturity assessment grounded in your real stack, metrics your leadership agrees on, and a governance operating model with clear owners — so the strategy survives contact with Monday.

In plain terms

What Data Strategy means in practice

Data strategy consulting from Brainforge — data maturity assessments, metrics alignment, governance, and a data operating model that turns scattered data into a business asset.

Where teams get stuck

Data maturity assessment, metrics alignment, governance, and an operating model your teams can actually run.

Leadership wants a data strategy, but past efforts became slideware.

Departments run on different numbers and no single metric is trusted.

We don't know who owns our data or who is accountable when it is wrong.

Investments in tools and hires have not produced the expected value.

What we deliver

Core Data Strategy

Data maturity assessment

A grounded audit of your stack, skills, and governance to find where data value leaks.

Metrics and KPI alignment

One agreed set of business metrics, defined once, owned by the right team.

Data governance operating model

Ownership, policies, and decision rights that keep data trustworthy as the business scales.

How deep it goes

Capabilities behind the work

The same delivery primitives (context, controls, and review) show up across every engagement.

Data maturity assessment

A current-state audit covering stack, skills, governance, and value leakage.

Maturity scoringStack assessmentValue-leak analysis

Metrics and KPI alignment

Business metric definition with owners and agreed calculation rules.

Metric definitionKPI alignmentExecutive reporting design

Governance and operating model

Decision rights, ownership, and policies that make data a managed asset.

Data governanceOwnership designPolicy and standards

Roadmap and investment planning

A funded, prioritized plan that ties data work to business outcomes.

Roadmap designROI framingExecutive communication

What changes

Outcomes you can point to

A prioritized data roadmap leadership can fund and approve.
One agreed metric system across the business.
A governance operating model with clear owners and decision rights.
A data investment plan tied to business outcomes.

Proof in production

See where this work shows up.

From Pendo sprawl to a governed activation plan

How a scattered tool stack became a governed, AI-ready data strategy with owners.

Read the governed activation case study →

Clean data for smarter shipping ops

How a governed data foundation turned fragmented logistics data into a decision asset.

Read the shipping data case study →

Common questions

Data Strategy, straight answers

What does data strategy consulting cost?

Engagements start with a scoped data maturity assessment or strategy sprint, so you pay for a bounded outcome. Most teams begin with a four-to-six-week assessment that produces the roadmap and metric system.

How is this different from the big firm data strategy reports?

Big-firm deliverables are often slide decks disconnected from your stack. Our strategy is grounded in a technical audit of what you actually run, and it names owners, decision rights, and a funded roadmap that a team can execute.

Do we need to have a modern data stack first?

No. The assessment works from whatever stack you have, and part of the strategy is deciding what to fix, consolidate, or replace rather than assuming new tools are the answer.

Will you run the strategy or hand us a document?

We hand over an executable plan and the operating model, and we are available to build the first priority items. The point is a strategy your team can run, not a document that sits on a shelf.

Can this support AI readiness?

Yes. Governed data with agreed metrics is the same foundation AI features need, so the strategy we produce includes AI-readiness as a lens on the roadmap.

How we work