Data and analytics
Numbers that don't match across departments, reports built by hand that arrive late, and data nobody uses to make decisions. We also solve the precondition for any AI project: getting the data in order.
Who it's for
Companies with systems (ERP, CRM, accounting, spreadsheets) that generate information, but whose management still decides with Excel and month-old data.
What we offer
The offerings are bought as a ladder: the assessment opens the door, BI and AI readiness convert, and the platform is for clients with more maturity.
Data assessment
Source inventory, data quality, maturity level, ranked use cases and a 90-day roadmap
- Typical duration
- 3 weeks
BI and dashboards
Metrics with a single definition, automated connections and role-based dashboards; the first phase delivers a working dashboard in 4 weeks
- Typical duration
- 4 to 8 weeks
AI data readiness
Always tied to a specific AI case: extraction, cleanup, classification of sensitive data, loading for the AI, and an evaluation set
- Typical duration
- 4 to 6 weeks
Data platform
Automated ingestion, data layers, monitored quality, a catalog, and migration of existing dashboards
- Typical duration
- 10 to 16 weeks
Monthly operations
Maintenance of pipelines, dashboards and models, plus new metrics
- Typical duration
- Ongoing
Typical deliverables
- Source inventory and quality scorecard.
- A metrics dictionary signed off by each department.
- Published dashboards with role-based access.
- Documented pipelines with monitoring and alerts.
- A roadmap and the proposal for the next phase.
How it connects with the other lines
It's the foundation for AI automation.
The assessment surfaces cases for software, apps and automation.
Every delivery includes training so the team can use and maintain the dashboards.
The assessment's source inventory is the basis for data and AI governance.
Technology
Agnostic. BPD doesn't tie itself to any cloud or tool. The stack choice is a deliverable of the assessment and is decided on five criteria: what the client already pays for, what its team knows how to use, the volume and type of data, the three-year cost, and the security and data residency requirements. Where possible, we prefer portable tools and open formats.
How we measure success
- Days to close the books or build reports, before and after.
- Dashboard usage by management.
- Data quality per source, measured in the assessment and afterward.
What we don't do
- Dashboards without metrics that are defined and validated with the department.
- Data platforms for clients that haven't been through an assessment yet.
- Tool migrations the problem doesn't call for.
Start with an assessment
We start with a fixed-price assessment, and from there each phase comes with its own fixed price.
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