A transparent path from raw data to operating decision.
No mystery boxes, no quarter-long discoveries. Every engagement follows the same five-phase blueprint, walking the four levels of analytics maturity in the order your operation can actually absorb.
Five phases. One transparent path.
Click a phase to see what happens inside it — the activities, the artefacts you walk away with, and the exit criterion that lets us move to the next step.
- Phase 01 · Discover
Map the operation before touching a model.
We sit with operators, plant managers, and your data team to surface the decisions that actually move EBITDA — then score them against data readiness and time-to-value.
DurationWeek 0 · 3–5 daysOwnershipBNC-led, joint workshopsExit CriterionOne use case selected, signed off by sponsor and operations lead.
Key activities- Stakeholder interviews on the shop floor
- Data landscape & source-system inventory
- Use-case scoring (value × feasibility)
Deliverables- Prioritized use-case backlog
- Data readiness heatmap
- Target architecture sketch
Four questions. Each one harder to answer.
Every analytics product lives somewhere on this ladder. We climb it in order — you cannot ask a model what to do next if you can't yet answer what just happened.
- Level 1 · Descriptive
What happened?
Reliable, governed, near-real-time visibility on the metrics that already drive your shift meetings — but with the noise and silos taken out.
In practiceA plant manager opens one dashboard and sees OEE, scrap rate, and on-time-in-full for every line, harmonised across SAP, the MES, and the WMS.
Techniques- KPI modeling
- Data warehousing
- PowerBI / Databricks SQL
ArtefactGoverned dashboards · single source of truth
Where it shows upSurfaces during Discover & Build
What happened?
Reliable, governed, near-real-time visibility on the metrics that already drive your shift meetings — but with the noise and silos taken out.
A plant manager opens one dashboard and sees OEE, scrap rate, and on-time-in-full for every line, harmonised across SAP, the MES, and the WMS.
- KPI modeling
- Data warehousing
- PowerBI / Databricks SQL
Governed dashboards · single source of truth
Surfaces during Discover & Build
Built to outlast the engagement.
Pipeline, not project
Every engagement leaves a versioned, monitored pipeline behind — not a slide deck and a goodbye email.
Your data stays protected
Sensitive operational data is handled in isolated, customer-owned environments — encrypted at rest and in transit, with strict IAM, MFA, and full audit trails on every access.
Dedicated project leads
Every engagement is owned end-to-end by a named senior lead who scopes, builds, and stays accountable for outcomes — no handovers, no shifting cast.
Try the methodology in 14 days.
Our Data Sprint compresses the Discover and Sprint phases into a fixed-scope, fixed-price engagement. You leave with a proof of concept and clear recommendations for next steps.