M01
Digitalisation, digitisation, and digital
People use “digital” to mean everything and therefore it means nothing.
Course summary
Digitalisation
Use this page to revisit what each stage gives you and return to the exact weak point that needs another pass.
Stage 1 of 3
Digitalisation Foundations
Start with what digitalisation actually means, how data, people, processes and systems fit together, and how to read basic diagrams and operating models.
M02
Why digitalisation matters
Digitalisation matters because expectations are higher, services are more complex, and regulation is tighter.
M03
Components of a digitalised system
Digitalisation is not one technology.
M04
Data, standards, and interoperability
A dataset is only useful when people trust it.
M05
Platforms, journeys, and dashboards
A platform keeps digital work consistent.
M06
Risks, governance, and people
Digitalisation creates new risks.
Stage 2 of 3
Digitalisation Intermediate
Move into platforms, integration, data sharing, capabilities, and how organisations design digital journeys and services in practice.
M01
Data pipelines and flows
A pipeline is only valuable when each step is owned and tested.
M02
Analytics, AI, and control loops
Collecting data is the easy part.
M03
APIs and system integration
APIs are the contracts that keep systems aligned.
M04
Data models and mapping
A shared data model keeps systems aligned.
M05
Operations, monitoring, and observability
telemetry is essential for safe operations.
Stage 3 of 3
Digitalisation Advanced
Look at digital roadmaps, operating models, governance, regulation and how to align data, architecture and people at sector or enterprise scale.
M01
Strategy and target state architecture
A target state keeps strategy concrete.
M02
Data sharing, models, and standards
At scale, digitalisation depends on shared meaning.
M03
Platforms, ecosystems, and governance
A platform only works when governance is clear.
M04
Measurement, risk, and roadmaps
Digitalisation is never complete, so you need a way to steer.