Our Approach to Transformation
Pragmatic, risk-aware, outcome-driven transformation for industrial engineering and data platforms — a playbook I use to convert pilots into sustained business value while keeping operations running.
Principles I follow
- Business-first: start with measurable outcomes (cost, throughput, safety, cycle-time) and work backwards to technical scope.
- Incremental delivery: small, safe pilots that deliver value early and de-risk at every step.
- Repeatable patterns: build blueprints and reusable components so success can be scaled across sites/regions.
- Operational ownership: hand over reliable runbooks, dashboards and SRE practices so operations own day-2 support.
- Data confidence: governed datasets, semantic layers and signed-off KPIs to make executive decisions trustable.
Phased Delivery — Discovery → Pilot → Scale → Operate
1. Discover (2–4 weeks)
Rapid fact-finding to map stakeholders, data sources, and constraints. Deliverables:
- Business impact hypotheses and priority KPIs.
- Source-of-truth inventory (systems, sensors, files, people).
- Feasibility & risk map with pragmatic next-step recommendations.
2. Pilot (6–12 weeks)
Build a focused proof-of-value that demonstrates ROI and informs architecture decisions. Deliverables:
- Working data pipeline / ingestion to a serving table or semantic view.
- Operational dashboard with validated KPIs and user acceptance tests.
- Clear migration & scale plan (costs, infra, team roles).
3. Scale (3–9 months)
Apply learnings to a broader rollout with hardened platform components and governance. Deliverables:
- Platform components (governed lakehouse, streaming layer, semantic APIs).
- Multi-tenant boundary & quota model where required (regions / business units).
- Automated CI/CD, infra-as-code and templates for rapid project bootstrapping.
4. Operate (ongoing)
Transfer ownership to operations and product teams with the right tooling and runbooks. Deliverables:
- Runbooks, SLOs, alerting and on-call playbooks for incident response.
- Governance cadence (dataset owners, KPI review board, release window policies).
- Continuous improvement loop: instrumentation + metric-driven backlog prioritisation.
Example: Data Flow (Interactive)
Hover layers to highlight them. Click the diagram to open an expanded, interactive view.
Example: Governance (Interactive)
Hover building blocks to focus them. Click to expand the governance diagram.
Patterns & Technical Choices
Data Platform
- Open table formats (Iceberg/Delta) on object storage for ACID & time-travel.
- Parquet columnar files for cost-efficient analytics and compaction strategies.
- Serving tables / materialized views for executive dashboards to ensure low-latency.
Streaming & Integration
- Event-first ingestion (Kafka or managed pub/sub) for replayability and resiliency.
- Lightweight edge adapters for OT/PLC systems to avoid plant disruption.
- Schema evolution patterns & data contracts to prevent downstream breakages.
Want a customised transformation plan?
I prepare bespoke, phased plans aligned to your priorities — from a short discovery to full delivery. Share your challenge and I’ll propose a concrete next step.