5.10 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).

5.10.1 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, or potential for in future situations/ unsure.

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 are assigned, namely (1) immaterial (collective financial effects less than 1 million euros in one year) and (5) material (collective financial effects more than 1 million euros 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 regards 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 euros.

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

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

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

   • High (5): more than 10 million euros.

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)'.

5.10.3 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) the 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. While we do not have direct control over the gas meter, we still consume the heat it generates.
All Scope 2 GHG emissions are calculated by multiplying the activity data with the appropriate EF. 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. 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 both are not 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 simplify Nedap's supply chain, we have distinguished between GHG emissions from product-related and non-product-related activities. Product-related GHG emissions derive from activities involving our sold products, while everything else is categorized as non-product-related GHG emissions. Within our Scope 3 GHG emissions, product-related activities are a significant contributor, with the use phase of our products being the most material category in terms of total GHG emissions. The use phase is calculated on an individual product basis, as well as the downstream transportation GHG emissions, while other product-related categories (the manufacturing process that leads to the product purchases, as well as upstream transportation) are assessed through a portfolio life cycle assessment (LCA). Non-product-related GHG emissions are calculated either based on activity data (GHG calculation tool) or using a spend-based method, with adjustments made for inflation where applicable.

The process of calculating the GHG emissions from product-related activities, which are calculated using a portfolio LCA approach, begins with selecting representative products within each business unit, based on their GHG emissions characteristics, to estimate the total GHG emissions associated with all items sold during the reporting year. By clustering products according to attributes such as material composition, weight and manufacturing processes, we ensure that the selected representative products accurately reflect the overall portfolio. The calculation then proceeds with a detailed LCA for each representative product. GHG emissions data is aggregated at the portfolio level by combining the GHG emissions of both representative and derivative products, multiplied by the total number of items sold, considering the weight ratio of the derivative product with respect to the representative product. This method provides a comprehensive view of the GHG emissions associated with our sold products. As we refine our portfolio analysis over time, particularly by increasing the number of representative products, this approach allows for continuous improvement in the accuracy of our GHG emissions reporting. To ensure accuracy and relevance, the LCAs are conducted using the most up-to-date version of the Ecoinvent database and the IPCC 2021 Life Cycle Impact Assessment Method (LCIAM).

The table below offers an overview of the Scope 3 categories, indicating whether they are applicable to Nedap, product-related or not product-related, and the method used for calculating GHG emissions.

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 all GHG emissions from purchased components and materials used in the production of our sold products. This part is covered by the LCA calculations.
This paragraph of the portfolio LCA includes all GHG emissions from the production phase of the components used in our sold products. The analysis also accounts for GHG emissions from transportation services beyond Tier 1 (e.g., Tier 2, Tier 3) within market activities. Transportation from Tier 1 to Nedap is excluded from this paragraph and will be disclosed in Category 4. The GHG emissions data derived from these representative products are scaled according to the weight ratio between the representative products and their derivative counterparts.

For externally procured products, we applied the portfolio LCA approach as described above, using the product's weights relative to the reference product to determine the Category 1 emissions. For the products we produce ourselves, we determined the most valuable component in the product’s Bill of Material (BOM) and used the purchases of that item in the reporting year to represent the full end-product. Like other purchased products, this was then offset against the reference product. Assumptions and limitations specific to individual representative products are detailed in the corresponding LCA document. 

Purchased services and non-production-related products

This category includes all purchased services not included in other categories and all products purchased that are not categorized as fixed assets (Category 2: Capital goods) and are not related to the sold products. All GHG emissions are calculated using the spend-based method.

The activity data used is the total amount spent on purchased good and services, by product type, as derived from our financial ledger. This amount is multiplied by the EFs, which are cradle-to-gate EFs of the purchased goods or services, expressed in kg CO₂e per EUR, derived from Exciobase. These EFs are corrected for inflation, as the EFs were published in 2019.

Category 2: Capital goods

This category includes all upstream (i.e., cradle-to-gate) GHG emissions from the production of capital goods purchased or acquired by Nedap in the reporting year. GHG emissions from the use of capital goods by the reporting company are accounted for in either Scope 1 or 2. The total spend on capital goods by category is then multiplied by representative cradle-to-gate EFs derived from Exciobase. These EFs are corrected for inflation, as the EFs were published in 2019.

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 emissions took place or, if unknown, the WTT factors published by the UK government.

Category 4: Upstream transportation and distribution

Upstream transportation and distribution are product-related activities; therefore, the GHG emissions are calculated through the portfolio LCA. GHG emissions from upstream transportation and distribution are calculated by focusing on the transport of goods between Tier 1 suppliers and the warehouses from where the products are shipped downstream. The transport modes considered include aggregated values of varying GHG emission class and size class trucks, as well as sea and air freight. These GHG emissions are categorized separately from other upstream transportation activities, which are included in market activities of purchased services (Scope 3, Category 1 - Purchased goods and services). The GHG emissions data for transportation between Tier 1 suppliers and our warehouse, derived from these representative products, is then extrapolated based on the weight ratio to estimate the GHG emissions for the derivative products.
As previously stated, due to the complexity and time-consuming nature of tracking GHG emissions for all purchased items, our focus is on calculating GHG emissions based on the components of products that have been sold. Assumptions and limitations specific to individual representative products are detailed in the corresponding LCA document.

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 employee 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

For Nedap, downstream transportation and distribution GHG emissions are calculated based on the distance traveled by sold products from our warehouse to the customer during the reporting year. Although this category is product related, it is not integrated into our LCA, as we have precise data on the transportation of our sold products. As a result, we have opted for a more accurate calculation method tailored to this specific activity.
We calculate the distance between our warehouse and the destination where the products are shipped, which is then multiplied by the appropriate EF based on the means of transport.
For determining distance, we assume an average distance to the destination country based on the location of our customers, who may be multinationals that further transport and use the products in various countries. 

For transportation modes, we assume the following:

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

• For distances exceeding 2,500 kilometers, we use a mixed model, assuming 5% of the distance travelled by truck, 5% by boat and 90% by plane. 

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 for the entire lifetime of the sold products.

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 [kg CO₂e / 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 kg CO₂e 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 kg CO₂e / 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

This category covers GHG emissions from the disposal and treatment of products sold by Nedap during the reporting year, at their future end of life. GHG emissions are calculated by multiplying the amount of waste by the appropriate EF, which is based on the type of material and the specific waste handling process used.

GHG emissions from the end-of-life treatment of our products are included in our Category 1 product related emissions, as the software we use to calculate emissions does include this in the LCA, but does not separately report this value. Based on previous versions of our LCA for most items in the portfolio, we were able to estimate the GHG emissions related to this category for all products.

Assumptions and limitations specific to individual representative products are detailed in the corresponding LCA document.

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. 

5.10.4 Senior management

Nedap's senior management (which is referred to as 'top management' in the ESRS) consists of the following roles:

• Business unit leaders Healthcare (2x)

• Business unit leader Identification Systems

• Business unit leader Light Controls

• Business unit leader Livestock

• Business unit leader Retail

• Business unit leader Security

• Team lead Human Resources

• General Counsel

• Team lead Communications

• Team lead IT

• Team lead Smart

• Concern controller

• Investor Relations manager

• Internal auditor

• Managing Director Nedap FZE

• Managing Director Nedap Inc.

At the end of 2023, the senior leadership within Nedap consisted of 17 people, including 3 females and 14 males.

During 2024, the position of business unit leader Identification Systems was discontinued, and at the end of 2024, the position of business unit leader Security was vacant. Hence, at the end of 2024, the senior leadership within Nedap consisted of 15 people, including 2 females and 13 males.

5.10.5 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 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: