SAP APM: Sensor technology with a system

Sensors in the vehicle, digital twins in the SAP system, and sound decisions on leasing, CO₂, and maintenance – that’s exactly what you get when you combine SAP APM with connected assets. Instead of spreadsheets, rough estimates, and scattered data, fleet managers and maintenance leaders gain a clear view of how vehicles actually perform – and which actions truly make economic sense.

In the day-to-day work of a fleet or pool manager, three core questions revolve around usage, cost, and CO₂ footprint. Modern vehicles – in the webinar example, a BMW iX3 – already provide this information via telematics, but initially only in the manufacturer backend or an app. For decision-making in the SAP landscape, this data is missing in the right place.

This is where SAP APM comes in. Via SAP Integration Suite on SAP BTP, telemetry data is retrieved from the manufacturer backend, transformed, and brought into the SAP world. Vehicles are represented in SAP S/4HANA as functional locations or equipment; SAP Asset Performance Management builds the digital twin on top of this.

In practice, this means values such as mileage, tire pressure, service due dates, battery charge levels, or energy consumption appear as indicators in SAP APM. They can be visualized, stored and trended over time, and embedded into rules. The physical vehicle becomes a structured, analyzable digital representation – linked to SAP master data, sensor values, and predictions.

This enables more than just condition monitoring. The digital twin becomes the basis for concrete decisions: leasing development, maintenance needs, resource deployment, and fleet strategy.

A well-defined master data model is the foundation of usable digital twins. In the example shown, the BMW iX3 was created as equipment in S/4HANA – including serial number, technical characteristics, and leasing data. Additional information is maintained in a structured way using classifications, for example:

• Leasing start, leasing end, mileage limit

• Battery properties such as capacity and number of charging cycles

In SAP APM, this master data is combined with measurement points and indicators. Typical indicators include:

• Current mileage

• Weekly mileage

• Tire pressure

• Battery charge level

• Energy charged per charging session

The model is flexible enough to represent different vehicle or machine types, yet standardized enough for an entire fleet. Diverging data models from different manufacturers are harmonized via integration and classification. All information flows into a consistent APM model – regardless of whether it relates to vehicles, machines, or plants.

Especially with leased vehicles, unnecessary costs arise when mileage is only checked at the end of the contract. Many companies still manage this in Excel – error-prone, non-transparent, and often dependent on individual employees.

With SAP Asset Performance Management, this process can be set up in a structured way:

1. Capture actual data
Telematics continuously delivers the current mileage. SAP APM stores and tracks these values automatically over time.

2. Calculate weekly mileage
An APM rule aggregates the past weeks into an average weekly mileage – robust and without outliers.

3. Project values until the end of the contract
The contract duration from the master data is combined with the projected development to calculate the expected mileage at contract end.

4. Alerts for potential exceedance
If a defined threshold is exceeded, SAP APM creates an alert. All relevant indicators are directly linked.

In practice, this means you can identify early on which vehicles are likely to exceed their mileage limit – and can rebalance, renegotiate, or adjust the fleet strategy in time.

This approach can be rolled out from an initial pilot to entire fleets – regardless of size or manufacturer.

Once sustainability goals become relevant, rough, average-based CO₂ calculations are no longer sufficient. Data sources and calculation methods differ significantly between combustion engines and electric vehicles.

Combustion engines: relatively simple calculation
For conventional vehicles, consumption, distance, and a CO₂ equivalent per liter of fuel are sufficient. These values can be held and analyzed as indicators in SAP APM.

Electric vehicles: same consumption, different CO₂ balance
For EVs, it’s not just the energy consumed that matters, but also the electricity mix at the time of charging. This factor fluctuates depending on region, grid operator, and time – in the webinar, it was shown that Mannheim and Ludwigshafen can already differ significantly.

Technically, this can be mapped as follows:

• The vehicle provides energy charged, timestamp, and GPS location for each charging session.

• An external service such as Electricity Maps supplies the regional CO₂ factor.

• SAP Integration Suite combines these values and passes them on to SAP APM.

This creates an exact CO₂ balance across all charging processes – not based on averages, but on real data. Combined with SAP Analytics Cloud, scenarios can be simulated, for example: what happens if specific locations switch to certified green power?

The architecture is deliberately modular and works beyond fleets:

• SAP S/4HANA provides technical objects and classifications.

• SAP APM processes indicators, rules, and alerts.

• SAP PLM can enrich the setup with product and 3D information.

• SSAM (SAP Service and Asset Manager) links APM alerts to mobile execution.

This creates an end-to-end chain:
Sensor value → indicator in APM → rule → alert → work order → mobile execution in SSAM.

For companies using SAP EAM, this provides a natural path toward predictive maintenance. Evora often starts with an 8-week proof of concept in which APM is hosted, a first asset is connected, and data model, integration, and alerts are tested jointly.

If you’d like to see practical project examples and a live demonstration of the digital twin in SAP APM, we recommend our on-demand webinar. We show how sensor technology, integration, and APM rules interact – and which steps are most effective for a successful start.

👉 On-demand webinar “Sensor data, but with a system – from data to value”:
https://www.evorait.com/de/events/sensorik-aber-mit-system-von-daten-zum-nutzen/