Digital Transformation
Digital Transformation Roadmap for Factories
A practical roadmap for industrial digitalization projects, from data foundations to dashboards, AI, and adoption.
In this guideExecutive summaryStep 1: Identify business problemsStep 2: Map data sourcesStep 3: Build trusted data foundationsStep 4: Build operational dashboardsStep 5: Automate workflowsStep 6: Add AI where it creates valueSummary
Executive summary
Digital transformation in factories should not start with software.
It should start with operational problems.
The roadmap should connect data, systems, people, and decisions.
Step 1: Identify business problems
Examples include:
- Excessive downtime
- Slow reporting
- Poor quality visibility
- Manual inspections
- Weak maintenance planning
- Energy waste
- Lack of production transparency
- PLCs
- SCADA
- Historians
- ERP
- CMMS
- Lab systems
- Spreadsheets
- Manual forms
- Google Sheets or Microsoft Lists
- Tag definitions
- Equipment hierarchy
- Timestamp standards
- Data validation
- Ownership
- Access control
- Production
- Downtime
- Reliability
- Quality
- Energy
- Inspection apps
- Shift reports
- Stoppage classification
- Maintenance notifications
- Backup reminders
- Approval workflows
- Anomaly detection
- Quality prediction
- Predictive maintenance
- Report summarization
- Recommendation support
Step 2: Map data sources
Typical sources include:
Step 3: Build trusted data foundations
Before AI, the plant needs reliable data.
This includes:
Step 4: Build operational dashboards
Dashboards should be built around users and decisions.
Start with high-value areas:
Step 5: Automate workflows
Good digitalization reduces manual follow-up.
Examples:
Step 6: Add AI where it creates value
AI should come after data and workflows are mature enough.
Good early AI use cases include:
Summary
Digital transformation is not a dashboard project.
It is a long-term improvement system that connects data to action.