I'm Charmaine Gray, Founder of Data Done Right Advisory. I’ve spent my career across three kinds of environments: internal data leadership, formal consulting engagements, and client-facing analytics delivery at scale. That includes enterprise consulting environments such as Citi and Wendy’s International, executive roles inside complex organizations, and teams whose reporting and analytics supported external clients ranging from thousands of direct-to-consumer brands at Daasity to global, major financial institutions at Fiserv.
I’ve also done this work at every level, from writing code and shaping data models to leading functions, setting direction, and designing the operating structure around the work. That range matters. It means the advice is grounded in delivery, informed by leadership, and shaped by what holds up when expectations are high.
At Fiserv, I worked in an environment where reporting, process discipline, and delivery quality had to hold up under executive review. Much of the reporting and analytics my team delivered supported external clients, including global, major financial institutions. Earlier in my career, I also worked through consulting engagements in enterprise environments such as Citi and Wendy’s International.
At Daasity, where I joined as employee eight and was promoted from Director to Vice President within approximately six months, I built and scaled a revenue-generating analytics delivery organization from 3 to 25 people across data architecture, ETL, BI, implementation, QA, and client delivery. I designed the organization, delivery standards, repeatable processes, staffing model, and commercial controls needed to support revenue, quality, and growth together. The organization exceeded its first-year booked-revenue target by 48 percent, and Professional Services merchants showed more than 50 percent lower observed churn than base-platform merchants over a one-year comparison.
At a high-growth mobile commerce SaaS platform, I inherited a low-trust reporting environment and led the work to establish a governed reporting foundation leadership could rely on. Data accuracy moved from roughly 40 percent to near-complete confidence, reconciliation effort dropped by more than 90 percent, and the business gained a CFO-safe source of truth for revenue and product usage. I also led the work that turned a long-stalled incrementality question into commercial evidence the business could use in GTM, product, and executive decision-making.
Clients hire me for an outside executive’s perspective, shaped by internal leadership, consulting environments, and externally accountable delivery. Here's what you can expect and how Data Done Right is different:
I’ve led both internal data organizations and client-facing analytics services at scale. That is the bridge this kind of work requires.
My work tends to center on a few recurring themes: trustworthy reporting, metric clarity, operating discipline, and teams that can carry the work forward without constant rework. I care about the technical details, but I care just as much about the conditions around them: who owns what, how work enters the function, how priorities are set, how releases are reviewed, and how trust is maintained once immediate pressure passes.
The work often lands across definitions, signoff paths, release discipline, intake models, and cross-functional expectations, not just dashboards or pipeline logic. The outputs are advisory by design: diagnostics, strategic roadmaps, KPI frameworks, operating model designs, templates, AI-readiness assessments, and prioritized recommendations.
The workflows, playbooks, and operating models behind Data Done Right were built through years of hands-on delivery and executive leadership, before generative AI became part of the toolkit. I now use AI to productionize those proven methods, adapt them faster, and apply them more consistently without outsourcing the judgment, standards, or accountability behind the work.
If the issue extends beyond a dashboard and into definitions, ownership, reporting discipline, or the way the function runs, I can help define what needs to change, what comes first, and what the business needs to support. That is exactly what Data Done Right Advisory is built to do.
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