Maturity of digital twin and immersive simulation technologies
Your digital twin initiatives, placed on a maturity scale and turned into a roadmap.
10 themes, a 5-level scale. And the action that moves each level to the next.
The framework’s 10 themes, already written from L1 to L5. One company, one business unit, or 300 at once.
Maturity of digital twin and immersive simulation technologies
10 themes, 5-level scale.
Nordhavn Industries
53 / 100
They measure their maturity with Datamensio
An example
This could be your situation.
Take one company as an example: three sites, three spreadsheets, no shared answer.
Nobody can consolidate.
Nordhavn Industries, 2,400 people in Hamburg, Lyon and Porto. A client asks where the group stands. Each site answers in its own spreadsheet, with its own scales.
Three weeks, a single base.
One Digital twin and immersive simulation maturity framework (5-level CMMI scale) assessment launched across all three sites at once, from the managers’ interview notes. The framework was already written, its 10 themes and levels L1 to L5 too.
Two costs avoided before being committed.
A score of 53 out of 100, with the gap concentrated on three themes. The AI companion spotted that two actions duplicated those of another audit. The committee report took one sentence to request.
What it saved them
- 3sites measured on the same base, instead of three questionnaires to reconcile
- 2duplicate actions caught before the spend
- 1committee report, with no manual rework
These figures are an example. They could be yours.
The standard imposes processes. Datamensio says where you stand.
01
The framework is already written
Themes, questions and levels L1 to L5, all written. You do not start from an empty spreadsheet.
02
The score lands the same day
Online, by self-assessment link or in interview. Theme by theme, comparable over time.
03
The gap becomes a costed plan
Every step up carries its action. The AI prioritises on expected effect, not on the order of the standard.
04
Progress can be demonstrated
Campaign after campaign, against your target and against your own past. That is what your board asks for.
The maturity scale
One level, the next, and the action that links the two.
It is this mechanism (a level, a level above, and the action that links the two) that turns an observation into a trajectory.
Is the digital twin resynchronised with the real asset after each physical or software modification?
- N1
No resynchronisation. The model reflects the state of the asset at creation and has not evolved since.
- N2
Updates happen, at the initiative of whoever built the model, with no trigger or defined timeframe.
- N3
Any modification to the asset triggers a model update following a written procedure, with versioning and a designated owner.
- N4
Resynchronisation is built into the change management process, drift between model and reality is measured through indicators and tracked.
- N5
Detected gaps feed into the revision of modelling rules, and the fidelity trajectory is reviewed periodically with operations.
Action to move from L2 to L3
Add a "twin update" step to the equipment change request form, with a named owner and deadline, and check its closure at the monthly change management review.
« With Datamensio, we meet our objectives far more efficiently. The ERDF inspection services and our supervising ministry particularly appreciated an approach that gives them reliable data. »
Director, CCI 94CCI Île-de-France
« We believe this is the most suitable solution to scale our transformation project and measure impact according to our needs. »
Maja SucekChief Operating Officer, Interreg Danube
Rarely on its own
Frameworks combine. Put several together to cover your business, or have the AI write yours.
Take your first measurement
What this framework covers
The digital twin rests on three building blocks: a model of reality (geometric, physical, behavioural or flow based), a data link with the asset or process represented, and a decision use case that justifies the whole thing. Immersive simulation adds a reporting layer in virtual or augmented reality, for design review, operator training or intervention support. This framework assesses the organisation’s maturity across the entire chain: industrial data, models, platforms, business uses, skills and governance. It does not focus on a particular tool but on the ability to generate value with these technologies.
In practice, the difficulty is not technological. It lies in persistence: many organisations accumulate successful mock-ups without ever moving to continuous operation. The questions an industrial management team asks itself are concrete. Is the model resynchronised with the asset after each modification, or does it drift as soon as the line evolves? Who owns the twin once the pilot project ends, engineering or operations? Are decisions taken from the simulation tracked and compared against the observed outcome? Without an answer, the twin remains a showcase.
A confusion often recurs: the digital twin is not the 3D mock-up, nor the offline simulation model. The mock-up describes a geometry, the simulation model answers a question asked once. The twin is distinguished by synchronisation with the real asset and by its own life cycle, with versions, validation and retirement. The rise of interoperability standards and open exchange formats is also changing the game: a twin locked into a vendor’s format becomes an asset that is hard to sustain beyond the current contract.
The maturity assessment does not ask whether you are compliant or not. It places each practice on a progressive scale and indicates what moves it to the next level. A score per theme, a target set with the teams, and the gap between the two that directly feeds the action plan. In Pilot, AI groups these actions into a prioritised roadmap, and the benchmark allows sites to be compared with each other and progress to be measured against a site’s own past performance.
The framework is ready to use and you can adapt it. AI adjusts the themes, rephrases the questions to fit your sector, refines the maturity levels, or builds a variant from your own engineering documents and internal standards. In Maps, you remain the owner of the grid and its evolutions.
Reference standard: Digital twin and immersive simulation maturity framework (5-level CMMI scale)
The themes assessed
Strategy and use cases
Existence of an explicit trajectory, selection of use cases on value criteria, arbitration between initiatives, identified sponsor, alignment with the overall industrial programme.
Industrial data and instrumentation
Sensor coverage, quality and frequency of flows, historisation, asset register, consistency of identifiers between engineering and operations systems.
Modelling and fidelity
Nature of models (geometric, physical, behavioural, flow based), fidelity level chosen relative to the use case, validation by comparison with reality, documentation of assumptions.
Synchronisation and twin life cycle
Update mechanism after asset modification, version management, detection of model to reality drift, retirement or archiving procedure.
Platforms and interoperability
Chosen architecture, exchange formats and standards, connection to MES, CMMS, PLM and ERP systems, vendor dependency, model portability.
Immersive simulation and field uses
Design review in a virtual environment, operator training and certification, augmented reality support for interventions, ergonomics and team acceptance.
Operations and decision support
Scenarios simulated before a decision, integration into operations and maintenance rituals, traceability of decisions taken, comparison between simulated and observed results.
Data security and governance
IT/OT segmentation, access control to models, protection of industrial know-how, ownership clauses on models produced by third parties, hosting.
Skills and organisation
Defined roles for operating the twin after the project, modelling and data science skills, training of field teams, dependency on service providers.
Value measurement and scaling up
Benefit indicators defined before launch, tracking of total cost, criteria for rollout to other sites, capitalisation of reusable models.
A short version of the framework is available for the online self-assessment.
Frequently asked questions
Does this framework lead to certification?
No, and no body certifies digital twins. This is a maturity framework: it places your practices on a progressive scale and produces a progression trajectory. The purpose is to steer the industrial transformation, not to award a label.
How is this different from a technical audit of our simulation tools?
A technical audit examines software, architectures and computing performance. The maturity assessment focuses on practices: how models are produced, maintained, used for decisions, and by whom. A perfectly equipped site can be poorly mature, and the reverse also happens.
How long does the assessment take?
The short version can be completed in a single working session. The full version, run collaboratively with engineering, operations, maintenance and industrial IT, typically spans one to two weeks, most of the time being spent gathering contributors.
Can the framework be adapted to our sector?
Yes. The themes, questions and levels can be changed in Maps, and the AI proposes a variant based on your engineering standards or project documents. A process plant and a discrete assembly workshop do not expect the same wording.
How can we compare several sites with each other?
Each site is assessed on the same framework, which makes scores comparable by theme. The benchmark places a business unit against others and against its own earlier assessments. A cross-site roadmap then consolidates the action plans of several sites.
What does the assessment actually produce?
A score per theme, a target, and the gap between the two converted into an action plan. Each action can be linked to an offering from the Services catalogue, with cost, timeframe and expected impact on the score. Reporting to site management is done in Horizon, under your own branding.
Do respondents need modelling expertise?
No for most questions, which concern organisation, uses and governance. Some questions on model fidelity and interoperability require an engineer’s input: the collaborative mode allows these questions to be assigned directly to them.
Where is the data hosted?
In France, with OVH, backed up with Scaleway. No transfer outside the European Union. The AI models used can be selected, including from European solutions, which matters when answers touch on industrial know-how.