8.9 Sustainability notes

The following notes provide additional context and clarification regarding the data and information presented in the sustainability statement. They include definitions, methodologies, scoring criteria, and references to ensure transparency and alignment with the European Sustainability Reporting Standards (ESRS).

8.9.1 Scoring criteria for IROs

Negative impact assessment

Negative impact is defined as the impairment of, damage to, or the ability to cause impairment of or damage to the economy, environment, and people through business activities. Negative impacts cannot be offset by positive impacts.

The negative impact is scored based on five variables:

1. Actual or potential:
   Whether the impact is already present or could potentially happen in future situations.

2. Severity – Scale:
   How grave the negative impact is for people or the environment. Ranging from minimal (1) to absolute (5).

3. Severity – Scope:
   How widespread the impact is. The number of individuals affected or geographical distribution. Ranging from limited (1) to total (5).

4. Severity – Remediability:
   Whether and to what extent the negative impacts could be remediated (restoring the environment or affected people to their prior state). Ranging from very easy to remedy (1), to non-remediable / irreversible (5).

5. Likelihood:
   How likely it is that this impact will occur. Ranging from rare (1) to (almost) certain (5). Actual impact is set to score ‘(almost) certain (5)’.

Positive impact assessment

Positive impact is defined as Nedap’s contribution to sustainable development through its activities (i.e., products and services) with a positive effect on economy, environment, and people.

The positive impact is scored based on four variables:

1. Actual/potential:
   Whether the impact is already present, may occur in future situations, or is uncertain.

2. Severity – Scale:
   How beneficial the positive impact is for people or the environment. Ranging from minimal (1) to absolute (5).

3. Severity – Scope:
   How widespread the impact is, e.g., the number individuals affected or geographical distribution. Ranging from limited (1) to total (5).

4. Likelihood of impact:
   How likely it is that this positive impact will occur. Ranging from rare (1) to (almost) certain (5). Actual impact is set to score ‘(almost) certain (5)’.

Financial risk assessment

Financial risk is defined as the sustainability-related financial risks arising from environmental, social, or governance matters that may negatively affect Nedap’s financial position, financial performance, cash flows, access to finance, or cost of capital in the short, medium, or long term.

Financial risk is scored based on four variables:

1. Financial risk:
   Effects from risks that influence Nedap’s cash flow, financial position, and financial performance over the short, medium, or long term. One of two scores is assigned: (1) immaterial (collective financial effects less than €1 million in one year) and (5) material (collective financial effects more than €1 million in one year).

2. Reputational risk:
   The sense that an event can cause reputational damage. Ranging from low (1) to high (5).

3. Regulatory risk:
   The sense that an event can cause regulatory consequences. Ranging from low (1) to high (5).

4. Likelihood:
   How likely it is that this risk will occur. Ranging from rare (1) to (almost) certain (5). Actual impact is set to score ‘(almost) certain (5)’.

Financial opportunities assessment

Financial opportunities are defined as uncertain environmental, social, or governance events or conditions that, if they occur, could cause a potential, material positive effect on Nedap’s business model, strategy, its capability to achieve its goals and targets, and to create value, and therefore may influence Nedap’s decisions and those of its business relationship partners with regard to sustainability matters. Like any other opportunity, sustainability-related opportunities are measured as a combination of an impact’s magnitude and the probability of occurrence.

Financial opportunity is scored based on two variables:

1. Financial opportunity:
   The magnitude of the perceived effect on Nedap’s cash flow, financial position, and financial performance over the short, medium, or long term.

2. • Low (1): less than €0.1 million.

   • Medium low (2): between €0.1 and €1 million.

   • Medium (3): between €1 and €2.5 million.

   • Medium high (4): between €2.5 and €10 million.

   • High (5): more than €10 million.

3. Likelihood:
   How likely it is that this opportunity will occur. Ranging from rare (1) to (almost) certain (5). Actual impact is set to score ‘(almost) certain (5)’.

8.9.3 GHG emissions metrics

Scope 1

The scope and company boundaries for scope 1 are all direct GHG emissions from sources that are owned and controlled by Nedap. All GHG emissions from scope 1 are calculated using our GHG calculation tool, where the activity data is multiplied by the appropriate GHG emission factor (EF). For scope 1 combustion, EFs are used that only include the GHG emissions that occur from the combustion of the fuel (tank-to-wheel; TTW). We prioritize the use of market-based EFs or EFs published by the countries in which Nedap operates. If a country does not provide specific EFs, we turn to alternative sources to obtain suitable factors. EFs for refrigerants are based on the published GHG emissions for the (mixture of) leaked gas.

Stationary combustion

This scope 1 category includes all fuel combustion in stationary equipment, such as boilers, heaters, and engines. Specifically, it covers the consumption of natural gas for heating our buildings.

Additionally, this category includes electricity generation from our solar panels, provided that the electricity is consumed on site and does not first feed into the grid. All activity data in this subsection is gathered through an overview provided by the supplier or the invoices itself.

The activity data included is:

• Total consumption of natural gas per entity.

• Total electricity generated by own solar panels and consumed on site.

Mobile combustion

This paragraph includes all mobile combustion from vehicles owned and controlled by Nedap. GHG emissions from electric vehicles are accounted for in scope 2. The activity data is based on actual data received on the amount of fuel consumed in the reporting year. If Nedap subsidiaries do not have actual data, GHG emissions will be estimated based on kilometers driven, the type of fuel, and the vehicle’s fuel efficiency. Default values from credible sources such as national databases will be used.

The activity data included is:

• Total fuel consumption from gasoline-fueled cars.

• Total fuel consumption from diesel-fueled cars.

Leakage of refrigerants

This category includes all GHG emissions that arise from leakage of refrigerants in cooling equipment from our air conditioning systems. The activity data is gathered from the external parties responsible for maintaining our air conditioning systems.

The activity data included is:

• Total amount of refrigerant leakage per type of refrigerant.

Scope 2 calculations

Scope 2 GHG emissions are indirect GHG emissions resulting from the generation of purchased electricity, heating, steam, and cooling. For Nedap, this means we account for the electricity used for our buildings, owned hardware in data centers, and owned or leased electric vehicles. Additionally, we account for the gas consumption at Nedap Germany, even though we do not have direct control over the gas meter.

All scope 2 GHG emissions are calculated by multiplying the activity data by the appropriate EF. The EFs used only include GHG emissions from the combustion of fuel TTW. We prioritize the use of market-based EFs or EFs published by the countries in which Nedap operates. If a country does not provide specific EFs, we turn to alternative sources to obtain suitable factors. We distinguish between market-based and location-based GHG emissions calculations.

Market-based approach

Under the market-based approach, EFs are sourced from our suppliers and must meet the scope 2 quality criteria. If supplier-specific factors are unavailable, location-based grid-average EFs are used.

GHG emissions are then calculated by multiplying the consumed electricity by the supplier-specific EF.

Location-based approach

The location-based approach utilizes country-specific EFs, focusing on grid-average GHG emissions that are beyond corporate control. For each of our geographic locations, we collect the appropriate grid GHG emission factor to accurately calculate location-based GHG emissions.

GHG emissions are calculated by multiplying the consumed electricity by the grid-average EF corresponding to each specific geographic location.

The activity data included is:

• Purchased electricity consumption.

• Electricity consumed by data centers.

• Purchased electricity for vehicles outside of the charging stations at Nedap.

• Consumption of natural gas from Nedap Germany.

The activity data used is preferably based on electricity data from our supplier. When direct electricity consumption data is unavailable, we ask the landlords for an estimation of our contribution to the building’s consumption. When neither is available, we will estimate GHG emissions using the following parameters: the size of the office (m²), the number of days employees are present, and standardized energy consumption based on local energy consumption.

Scope 3 calculations

To structure Nedap’s Scope 3 greenhouse gas accounting, a distinction is made between product-related and non-product-related activities. Product-related GHG emissions arise from activities directly associated with Nedap’s sold products, while all other Scope 3 emissions are classified as non-product-related. Within Scope 3, product-related activities represent a significant share of total GHG emissions, with the use phase of sold products being the most material category. Use-phase emissions are calculated at an individual product level, as are emissions related to upstream and downstream transportation and the end-of-life treatment of sold products. Emissions associated with the manufacturing of purchased components and materials are calculated using a scalable, LCA-based portfolio approach. Non-product-related GHG emissions are calculated using either activity-based data or a spend-based approach, depending on data availability. Where spend-based methods are applied, emission factors expressed in kgCO₂e per euro of expenditure are used and adjusted to the reporting year to ensure consistency over time.

In 2025, sustainability attributes have been further integrated into Nedap’s IT landscape, and manufacturing stages have been embedded into the emissions calculation and reporting process. As a result, product- and portfolio-level CO₂e emissions are now systematically calculated and aggregated through Nedap’s internal reporting environment. In addition, the set of representative products has been expanded, taking into account purchase value, further improving portfolio coverage. To ensure accuracy and relevance, life cycle assessments are conducted using the most recent version of the Ecoinvent database and the IPCC 2021 Life Cycle Impact Assessment Method (LCIAM). All GHG emissions are calculated in accordance with the principles and requirements of ESRS E1 and the GHG Protocol, using methodologies that ensure consistency, transparency, and comparability across reporting periods.

The table below provides an overview of the Scope 3 categories, indicating their applicability to Nedap, whether they are product-related or non-product-related, and the calculation method applied.

Category 1: Purchased goods and services

This category includes GHG emissions from all purchased goods and services not otherwise covered by other upstream scope 3 categories (i.e., categories 2 through 8). To provide a clear breakdown of what is included in this category, we distinguish between product-related purchases and services and non-production-related products.

Product-related purchases

This category includes GHG emissions arising from purchased components and materials used in the production of Nedap’s sold products. Product-related emissions are calculated using a scalable, LCA-based portfolio methodology embedded in Nedap’s IT landscape. This methodology enables the calculation of cradle-to-gate emissions at component level and the consistent aggregation of results at product and portfolio level.

As not all products and components are yet fully enriched with the required sustainability attributes in the Product Lifecycle Management (PLM) system, a clustering approach is applied for part of the product portfolio. Representative products are used to estimate emissions for similar products with comparable material composition and manufacturing characteristics. GHG emissions are aggregated at cluster level by combining the emissions of representative and derivative products, multiplied by the total number of items purchased and adjusted using the weight ratio of derivative products relative to their representative counterparts. This approach provides a comprehensive and scalable view of the greenhouse gas emissions associated with Nedap’s purchased products. As portfolio coverage increases year-on-year, the proportion of products calculated using primary component-level data increases, thereby improving the overall accuracy and completeness of the results.

Where primary product or component data is not yet available, documented assumptions and representative data are applied. These assumptions are reviewed periodically and progressively replaced by primary data as system integration improves and products are updated. In addition, the determination of product and component weights is systematically documented, for example based on supplier specifications, CAD-based mass calculations or standardized reference data. This ensures traceability of key inputs, supports internal validation and external assurance, and enables continuous improvement of data quality.

Purchased services and non-production-related products

For purchased services and other non-product-related goods that fall outside the scope of the product portfolio LCA, GHG emissions are calculated using a spend-based approach. This approach is based on financial general ledger data and applies representative emission factors expressed in kgCO₂e per euro of expenditure, adjusted for inflation to ensure consistency over time.

Category 2: Capital goods

GHG emissions from capital goods are calculated using a spend-based approach. This calculation is based on the balance sheet entries for capitalized assets acquired during the reporting year and applies representative emission factors expressed in kgCO₂e per euro of expenditure, adjusted for inflation. The reported emissions cover upstream (cradle-to-gate) emissions associated with the production of these capital goods and exclude emissions related to their use phase.

Category 3: Fuel- and energy-related activities (not included in scope 1 or 2)

The activity data for this category will be derived from the same data collected for scope 1 and 2 GHG emissions. An EF that excludes combustion-related GHG emissions will be applied. Where possible, well-to-tank (WTT) factors will be sourced from the same dataset as scope 1 and 2 to maintain consistency.

In addition, next to the data center GHG emissions from the energy used, the additional energy required to cool and operate the data centers, calculated based on the power usage effectiveness (PUE) of each data center, is included. GHG emissions data are sourced based on the published EFs of the country where the GHG emissions took place or, if unknown, the WTT factors published by the UK government.

Category 4: Upstream transportation and distribution

This category includes all GHG emissions sociated with upstream logistics activities that are arranged and paid for by Nedap, including intercompany shipments. Because shipment-level payment responsibilities are not consistently available for all transport flows, transportation emissions are calculated at an individual product level and subsequently allocated between category 4 and category 9. For allocation purposes, it is assumed that two-thirds of transportation emissions are reported under category 4 and one-third under category 9 (Downstream transportation and distribution), to ensure consistent reporting and avoid double counting.

Emissions related to upstream warehousing are calculated using a spend-based approach, based on financial general ledger entries mapped to warehousing activities. This spend-based calculation follows the same methodology as applied under category 1.

For determining the transportation modes, the following assumptions are applied:

• For transport distances up to 2,500 kilometers, transportation is assumed to take place exclusively by truck.

• For distances exceeding 2,500 kilometers, a mixed transport model is applied, assuming 5% of the distance travelled by truck, 5% by sea freight, and 90% by air freight.

Category 5: Waste generated in operations

This category describes the GHG emissions from the treatment of waste generated by Nedap’s operations and includes both waste from our owned buildings and leased offices. As input, we use the total mass of the waste generated and the proportion of waste treated by different methods (e.g., landfill, incineration, recycling). The EFs used are closed-loop waste disposal emission factors published by the UK government.

Where applicable, we utilize data provided by our waste processor. For Nedap N.V., this data is readily available, including detailed information on waste processing methods. For Nedap subsidiaries where this data is unavailable, we estimate waste generation based on factors such as average days spent in the office, number of employees, and national average office waste generation figures.

The GHG emissions that arise from waste generated in our operations are calculated using our GHG calculation tool.

Category 6: Business travel

This category includes GHG emissions from employee transportation for business-related activities in vehicles not owned or operated by Nedap. The GHG emissions are calculated in the GHG calculation tool, using a distance-based approach.

We differentiate between various means of travel, including air, rail, road (bus or car–rental or employee-owned, excluding commuting), and water.

For Nedap, we collect the data based on kilometers traveled through reimbursed travel expenses or travel-related expense records. We typically have data available for the distance and method of travel. When precise data is unavailable, the distances will be calculated.

The total number of kilometers traveled are multiplied by the appropriate EF, which is specific to the type of vehicle and the geographical location where travel took place.

Category 7: Employee commuting

This category includes GHG emissions from employees commuting between their homes and the office, excluding trips with company-owned or leased cars. The activity data is based on the total distance traveled by all employees and the breakdown of the various modes of transportation used, such as car, bus, and train.

In countries where Nedap reimburses commuting expenses, we have accurate data on the total commuting distance for the reporting year. If this data is unavailable, we calculate the activity data based on the distance between employees’ residential addresses and the office, average days spent in the office, and a breakdown of the modes of transportation used. The GHG emissions that arise from employee commuting are calculated using our GHG calculation tool.

Category 8: Upstream leased assets

This category is not applicable to Nedap. Leased office buildings and vehicles are accounted for in scope 2.

Category 9: Downstream transportation and distribution

This category includes GHG emissions associated with transportation for which Nedap does not arrange or pay for the service. Because shipment-level information on payment responsibility is not consistently available for all transport flows, transportation emissions are calculated at an individual product level and subsequently allocated between category 4 and category 9. For allocation purposes, it is assumed that one-third of transportation emissions are reported under this category, with the remaining two-thirds allocated to category 4 (Upstream transportation and distribution), to ensure consistent reporting and avoid double counting.

The same transportation mode assumptions as applied under category 4 are used for downstream transportation calculations.

Category 10: Processing of sold products

Category 10 includes GHG emissions from the processing of sold intermediate products by third parties, which are products that require further processing, transformation, or inclusion in another product before use. This category is not applicable to Nedap, since we do not sell intermediate products.

Category 11: Use of sold products

In this category, we look at the future use phase of the sold products in the reporting year. This means that we look at the GHG emissions from our sold products in the use phase over their entire lifetime.

The calculation of the use phase GHG emissions for products involves a structured approach focused on estimating GHG emissions during the product’s operation over its entire lifetime. GHG emissions are calculated for each individual product, based on its sales quantity, to ensure accurate GHG emissions calculations.

One of the primary challenges in this calculation is determining the exact location where the product will be used. To address this, we use the EFs for the geographic region of the country to which the product is shipped. The geographic region is in most cases the continent on which the country is situated. Only in the case of Oceania, we specifically use the respective EFs for Australia and New Zealand due to the significant difference between them.

The GHG emissions calculation is based on the estimated total use of electricity during the product’s lifetime, formulated as:
Total use of electricity during lifetime [kWh] (= power consumption [W] / 1,000 x duty cycle [%] x product lifetime [h]) x geography-specific EF [kgCO₂e / kWh] x sales quantity

The total use of electricity during the product’s lifetime is calculated by first determining the product’s power consumption, measured in watts (W). Most of the time, this information is included on the data sheets of the product and provided by the product experts of the business units. This power consumption is then multiplied by the duty cycle, which represents the number of hours the product is in use per day as a fraction of 24 hours, effectively expressed as a percentage. The result is then multiplied by the product’s estimated lifetime, measured in years, to determine the total electricity consumption over its entire lifetime. As the EF is given in kgCO₂e per kWh, we convert watts to kilowatts by dividing the result by 1,000, and we convert years to hours by multiplying the result by 24 hours and 365 days.

For products powered by batteries, we distinguish between primary and rechargeable batteries. Rechargeable batteries, whether replaceable or not, are treated as if the product is directly connected to the grid. For primary non-replaceable batteries, GHG emissions are accounted for during production, as they are charged once. For primary replaceable batteries, GHG emissions from additional battery purchases during the product’s lifetime are considered indirect use phase GHG emissions, and these will be included if they exceed 5% of the product’s production phase GHG emissions. 

Once the total electricity consumption is calculated, it is multiplied by the region-specific EF in kgCO₂e / kWh, and the total number of items sold in the reporting period is applied to determine the overall GHG emissions during the use phase of the sold products in a given year. Grid factors are used for the following global regions: Africa, Asia, Australia, Europe, Latin America and the Caribbean (South America), New Zealand, and North America.

Category 12: End-of-life treatment of sold products

GHG emissions from the end-of-life treatment of sold products are calculated using a globally weighted average emission factor. The weighting of end-of-life treatment routes is based on global electronic waste collection and treatment shares as reported in The Global E-Waste Monitor 2024. No product- or region-specific end-of-life data is currently available; therefore, a global average approach is applied.

The following end-of-life treatment routes are included in the weighted average: formal recycling, informal recycling, open burning and disposal to landfill. For each of these treatment routes, corresponding emission factors from the Ecoinvent database are applied. The overall end-of-life emission factor is calculated by combining the treatment shares with the respective Ecoinvent emission factors.

This globally weighted emission factor is applied consistently to all products sold by Nedap, reflecting an average global end-of-life scenario and ensuring methodological consistency across the product portfolio.

Category 13: Downstream leased assets

This category is not applicable, as Nedap does not lease out assets to other entities.

Category 14: Franchises

This category is not applicable, as Nedap does not have any franchises.

Category 15: Investments

This category is not applicable, as Nedap is not an investor, nor a financial company.

8.9.4 Senior management

Nedap’s senior management (which is referred to as ‘top management’ in the ESRS) consists of the following roles as of 31 December 2025:

• Managing Director Healthcare

• Managing Director Livestock

• Managing Director Retail

• Managing Director Security

• Managing Director UV

• HR Director

• General Counsel

• Team lead Communications

• Team Lead IT

• Team Lead Smart

• Concern Controller

• Investor Relations Manager

• Internal Auditor

• Director Brand & Design

• Managing Director Nedap FZE

• Managing Director Nedap Inc.

As of 31 December 2024, the senior management within Nedap consisted of 15 people, including 2 females and 13 males.

During 2025, Nedap updated its senior management structure to better reflect its strategic priorities and way of working. This included the addition of the strategic role of Director Brand & Design and aligning the definition of senior management with the Nedap Leadership Team (NLT). As a result, senior management as of 31 December 2025 consisted of 16 people, including 1 female and 15 males.

8.9.5 Incident classification

It is logical that an incident that affects two customers in one key market requires different measures and involvement of Nedap employees than an incident that affects all key markets and customers of Nedap. We have therefore determined escalation levels that allow us to scale up based on the nature of the incident, with specific follow-up measures assigned to each level. To align with Nedap’s risk management approach, we use the following escalation levels:

• Vital: the impact of the incident is so big that the continuation of the company can be seriously affected.

• Critical: the impact of the incident is of such a magnitude that significant damage can be caused to the company.

• Regular: the impact of the incident remains limited and within manageable proportions.

The escalation level is determined based on the incident’s size and exposure. Where the term “parties” is used below, it may refer to customers, suppliers, service providers, sub-processors, linking parties, or data subjects, depending on the nature of the incident.

Size

Within the criterion of size, the following gradations can be distinguished:

• Small: no or a few parties/applications are affected number < 5%.

• Medium: multiple parties/applications are affected number < 25%.

• Large: many parties/applications are affected number > 25%.

• Completely: all parties/applications are affected number = 100%.

Exposure

Within the criterion of exposure, the following gradations can be distinguished:

• Limited: one business unit or legal entity is affected.

• Wide: multiple business units or legal entities are affected.

• Completely: all business units or legal entities are affected.

Classification matrix

The following matrix has been drawn up to determine the escalation level: