100+
Organisations trust Oxand
10%+
Increase in asset availability
10,000+
Ageing and energy models
20 years
Of asset expertise
−29%
GHG emissions cut on 15-year plans
Expertise · Predictive Maintenance ROI
Return-on-investment through predictive maintenance.
Use predictive models and asset analytics to forecast degradation, costs and risks — then feed those insights directly into your investment plans to lower total cost of ownership and stabilise CAPEX.
up to 30% TCO reduction
>95% ageing forecasts right after 10 years
28% energy consumption cut on 15-year plans
Reactive maintenance lets asset condition fall into the failure-risk zone; predictive, planned interventions keep it above the threshold across 30 years.
Four pressures that make reactive maintenance a budget trap.
01
Increasing costs and complexity
Emergency repairs and unplanned downtime are consistently more expensive than scheduled maintenance. As asset portfolios age, the gap between reactive and predictive cost curves widens.
02
Unpredictable asset performance
Without degradation models, teams cannot anticipate which assets will fail next or what the downstream service and financial consequences will be.
03
Compliance with evolving standards
Regulators increasingly require documented maintenance rationale. Reactive decisions leave organisations unable to demonstrate that high-risk assets are proactively managed.
04
Pressure to demonstrate ROI
Boards and finance teams demand evidence that maintenance spend translates into measurable risk reduction and lifecycle savings — not just a cost centre.
Predictive maintenance ROI
is the measurable financial return from shifting maintenance decisions off reactive triggers onto data-driven forecasts of degradation, failure probability and cost. Simeo by Oxand brings 10,000+ ageing and energy performance laws and 30,000+ maintenance actions and cost bases to every scheduling decision — so organisations reach lower total cost of ownership without installing a single new sensor.
Oxand's approach to preventive maintenance and ROI.
Optimise
Lower total cost of ownership
Use predictive insights to schedule maintenance and asset renewal at the optimal time — not too early, not too late. Simeo's 10,000+ ageing models and 30,000+ maintenance cost bases determine the intervention window that minimises lifecycle spend.
Decide
Data-driven investment decisions
Leverage Simeo's models to forecast asset performance and guide CAPEX and OPEX decisions. Every maintenance recommendation links back to a quantified risk reduction and a projected cost saving — making the case for investment transparent and auditable.
Simulate
Scenario simulations and portfolio dashboards
Visualise your portfolio and compare maintenance strategies under budget, service-level, risk and decarbonisation constraints. Tailor dashboards for operations teams, compliance leads and executive sponsors — all from a single model.
Protect
Early risk detection before costs escalate
Identify vulnerabilities and high-cost maintenance issues before they become critical. Simeo flags assets crossing risk thresholds so teams can intervene proactively, protecting budgets while maintaining agreed service levels.
Reactive maintenance vs. predictive investment planning with Oxand Simeo™.
Reactive maintenance
- Emergency repairs only — triggered by failure, not forecasts
- No long-term view of asset lifecycle or cost trajectory
- Unstable budgets and unpredictable annual costs
- No clear evidence linking maintenance spend to risk reduction
With Oxand Simeo™
- Predictive models guiding maintenance and renewal decisions
- Stable investment trajectories with clear CAPEX/OPEX planning
- Transparent ROI with fewer surprises and minimal disruption
- Audit-ready evidence linking every intervention to a risk outcome
Designed for every role responsible for maintenance decisions.
Facility & asset managers
Manage maintenance schedules and budgets proactively, maximising asset uptime and reducing the volume of unplanned interventions.
Compliance & QA
Simplify regulatory compliance through transparent predictive data — every maintenance decision is traceable to a risk assessment and cost justification.
Executives & sponsors
Access clear, traceable evidence trails generated automatically from Simeo to simplify audits, justify CAPEX and demonstrate ROI to boards.
Clients who moved from reactive to predictive.
Département de la Meuse
“We needed a tool that would allow us to consolidate the fragmented data we had and project it in a way that could be clearly presented to our elected officials, who are the decisio…”
Dominique VANON — Chief Executive Officer (General Director of Services)
APRR-AREA
“A solution that connects the technical teams, the finance teams and executive management alike”
Xavier Rigo — Deputy CEO, APRR
In'li
“We turned to Oxand because we needed a tool that would provide us with a predictive—not just corrective—view and help us manage our investments more effectively. Oxand stood out fo…”
Laura Stolz — Head of Budget and Asset Valuation Department
LaGuardia Airport
“As asset leader, I'm aware of the need to challenge our practices and be at the top level of operation and maintenance practices. Within this context, we want as a first step to pe…”
Viparis
“What we do not measure, we can neither steer nor put a value on. An estate is not a fixed inheritance, it is a living asset to be developed with intent. Simeo helps us answer a sim…”
Cyril Touboul — Technical and Works Director
Douarnenez Habitat
Help Douarnenez Habitat move from reactive to predictive management with Oxand Simeo™, optimizing investments and communicating decisions clearly.
Ville du Havre
How did the City of Le Havre leverage Oxand Simeo to optimize its 300-building portfolio, streamline maintenance and deconstruction, and plan sustainable school…
SDIS55
How did the Meuse Departmental Fire and Rescue Service leverage Oxand Simeo to centralize asset knowledge, optimize investments, and improve building conditions…
CD06 Alpes-Maritimes
How did the Alpes-Maritimes Department leverage Oxand Simeo to map energy performance, define consumption trajectories, and plan investments to meet Décret Tert…
Ville de Marseille
Help Marseille digitize school asset data to plan preventive maintenance, optimize energy use, and guide investments across 472 schools.
Ministry of Defense
Support the Ministry of the Armed Forces in assessing budgets and resources to preserve €15 B in assets and reduce its growing infrastructure grey debt.
Conseil Départemental des Yvelines
How did the Yvelines Departmental Council leverage Oxand Simeo to prioritize maintenance, improve energy performance, and prevent the growth of grey debt under …
Frequently asked questions
How does Oxand deliver predictive maintenance without IoT sensors?
We use data modelling and historical performance data instead of costly sensor-based systems, making predictive maintenance accessible to organisations that lack a sensor estate. Simeo's 10,000+ ageing models derive forecasts from the data you already have.
How quickly can we expect to see cost savings?
Clients typically observe significant cost savings within 6 to 12 months of implementation, as optimised maintenance schedules reduce emergency interventions from the first planning cycle.
Do we need to install new hardware or sensors?
No. Oxand's solution relies on existing inspection records, CMMS exports and operational data, eliminating the need for sensor installations or infrastructure changes.
Can Oxand's approach be applied across different sectors?
Yes. The solutions are flexible and have been applied in infrastructure, real estate, energy and transportation, adapting Simeo's ageing and cost models to the specific degradation patterns of each asset class.
How do we connect our existing systems to Simeo?
Simeo supports bulk import of spreadsheets and CMMS exports, BIM models and IoT feeds, as well as direct REST and GraphQL API connections to systems such as SAP and Maximo.
Ready to lower your total cost of ownership?
Bring your maintenance history and asset register. We'll show you where predictive models change the investment calculus — no new sensors required.