Unfortunately, despite their good intentions and stated strategic objectives, organizations often struggle with the implementation of initiatives that lead to improved ESG-impact (Mazur-Wierzbicka 2021; Sheehan et al. 2023). One of the reasons why organizations face such difficulties is the belief that these goals can be achieved by creating an ‘add-on’ to the existing organization, such as a separate ESG department, or assigning specific responsibilities to staff members (Jebe 2019; López-Cabarcos et al. 2025). Examples of such efforts include appointing a sustainable officer, requiring suppliers to hold some ‘sustainability certificates’ or extending the yearly financial reports with sustainability statistics (Müller et al. 2025).

While any such actions can have strong positive effects, in practice these frequently turn out to be more focused on achieving compliance and/or improved risk management rather than fundamentally changing the organization’s sustainability performance as such (Li et al. 2024). Clearly, the objectives of compliance and risk management on the one hand and improvement on the other hand are rather reinforcing each other than contradictory. Nevertheless, it can be observed that making concrete steps towards improvement is not always given priority (Jiang and Han 2025). The starting point of this research therefore was that, to establish a true sustainability impact of value chains, an extra effort or approach would be needed. This approach can be summarized by the slogan “Sustainability is not a department; it is a mindset”.

To bring such a mindset to life, this paper proposes to connect the objectives of achieving a more sustainable organization directly to the work floor by providing the management and the value adding (primary) processes with a ‘common language’ (King and Cohen 2023). This paper introduces a practical method that can be used by operations, and process- or value chain managers to measure and improve the impact of sustainability efforts. This method has been coined ‘Sustainability Impact Value Added Accounting’ or sivaa.

Within sivaa the word ‘accounting’ relates to ‘to account for’; to measure and improve and to hold people ‘accountable’ for their behavior (Holmes et al. 2012). The sivaa-method is designed as a managerial tool to steer sustainability impact across the entire value chain. While it builds on established carbon accounting standards – most notably the Greenhouse Gas Protocol and its Scope 1, 2, and 3 structure – it departs from their compliance-oriented logic.

Rather than organizing emissions into reporting silos based on organizational boundaries, sivaa adopts a chain-oriented perspective. The central question is not which emissions fall under direct control, but where interventions in the value chain can generate the greatest and fastest impact. Although it uses existing emission factors and conversion methodologies, it does not seek disclosure-grade precision. Instead, it prioritizes decision relevance: identifying impact hotspots, directing improvement efforts, and strategically enhancing data quality where the largest reductions can be achieved, see Figure 1.

Compliance with CSRD, CSDDD and other directives is important and can be a major step for any firm towards ESG-related efforts. However, a practical instrument for continuous improvement seems to be lacking. Although the sivaa-method can fill this gap, it is important to understand that it primarily functions as a managerial steering instrument, not as an external reporting framework. It complements regulatory requirements such as the CSRD and the CSDDD, but its core purpose is to enable systemic improvement rather than compliance-driven disclosure.

In terms of ESG, sivaa can be considered as a governance tool. Under sivaa, data are collected to facilitate better decision making, i.e., it provides the necessary steering information for the organization and in fact the entire value chain to enhance the (ecological and social) sustainability performance. The tool has been presented as a means of support for improving the performance of the entire value chain with limited data. This supports the organization’s prioritization of focusing on issues that are within its sphere of influence and on issues that are most important. Although reports can be used to supplement sivaa and inform the selection of appropriate CO₂ reduction actions, obtaining assurance is not the main goal of sivaa. Rather, sivaa can be seen as the starting point for collaboration in the value chain. It can expose the state of any chosen ESG-related datapoint in the value chain. Imperfect data is as relevant as perfect data, as it can shift the focus to action.

In designing the sivaa-method, several principles were leading:

1. following the flow of products through the end-to-end value chain and using a value-add approach for calculating sustainability performance;
2. allowing professionals to focus on their own value-adding steps so to jointly get insights in, and steering information for, managing the entire value chain;
3. finding improvement as a focus point next to, or in addition to, compliance and risk management; and
4. allowing for incomplete data as to ensure practical usability rather than exact reporting.

These principles will be further discussed in Section 3.

The remainder of this paper is organized as follows. The next section outlines the key drivers that motivate organizations to map their sustainability performance. Section 3 explains the sivaa-method, while section 4 discusses its validation based on discussions with several groups of potential users. The conclusions are presented in section 5.

The European Union is actively engaged in building an expansive and interconnected regulatory framework aimed at advancing sustainability, transparency, and accountability throughout value chains. This regulatory framework comprises multiple legislative pillars, spanning reporting (Corportate Sustainability Reporting Directive, CSRD), due diligence (Corporate Sustainability Due Diligence Directive, CSDDD), market instruments (EU Emission Trade System, ETS), Carbon Border Adjustment Mechanism, CBAM), and product policy (Circular Economy Act, Eco-design requirements for sustainable products in the Ecodesign for Sustainable Products Regulation, ESPR, requirements for timber in the European Union Timber Regulation, EUTR) (Koning et al. 2023). Together, these instruments serve as major catalysts for increasing the availability of data within value chains.

While the CSRD imposes these requirements through reporting standards, their implications extend to governance structures and strategic planning, requiring a deep operationalization of ESG across the entire value chain (Vâlcu and Spătaru-Negură 2025). The CSDDD (European Parliament & Council of the European Union 2024) and the CSRD partially overlap, as both instruments address broadly the same ESG components. However, the CSDDD focuses more specifically on identifying certain ESG-related risks, ensuring that these risks are mitigated, and that adverse impacts are effectively addressed. The CSDDD is strongly inspired by the OECD Guidelines for Multinational Enterprises (OECD 2023), although it differs in certain aspects of design and scope (Enneking 2022).

While ongoing geopolitical turbulence has exerted considerable pressure on the EU’s sustainability policy and legislative initiatives, as demonstrated by the EU Omnibus proposal (European Commission 2024), which seeks to moderate both the scope and the implementation timeline of these regulations, the underlying rationale for data visibility in value chains remains fundamentally unchanged. Firstly, a number of companies remain subject to reporting requirements or will be in the near future, underscoring the urgency of preparing internal systems and value chain interfaces for compliance. In the wake of mitigating the consequences for small and medium sized companies (SME), the European Commission proposed Voluntary Sustainability Standards for SMEs, the VSME (EFRAG 2024).

Secondly, the climate crisis and broader sustainability concerns remain pressing, regardless of shifting political sentiment – a sentiment that could easily reverse. The EU Omnibus package, moreover, was not received without criticism (Bertram 2025; Business & Human Rights Resource Centre 2025) Thirdly, reputation, brand value, and the increasing scrutiny of investors and consumers have driven companies to incorporate contractual sustainability commitments (ESG clauses) into their operations (Olmos Giupponi and Figueroa 2024). In other words, many companies already operate within value chains governed by such contractual sustainability obligations, which remain binding regardless of temporary legislative delays.

Typically, any organization has a strategy to achieve its mission or purpose where the strategy is needed to get a clear focus (what value do I want to bring to which type of customers), differentiation (how can I achieve a competitive advantage), alignment (creating a consistent pattern of decisions throughout the organization) and priority setting (what inevitable choices are needed), cf., Whittington et al. (2023). Within organizations, the business strategy is translated into functional strategies such as financial strategy, marketing strategy, and value chain strategy (Van der Veen and Van Buren 2021).

One of the reasons to enhance sustainability in value chain processes is that consumers appreciate products and services that are produced in an ‘honest’ way without leaving a substantial footprint (Camilleri et al. 2023). As companies aim to create customer value, offering sustainable products may be one way of competing in the marketplace (Oduro and Haylemariam 2025). Clearly, upon their purchasing decisions, consumers are not only looking for sustainability; many other factors are considered both in terms of the product-features such as quality, usability, availability, and brand as well as in terms of consumer characteristics including income, demographics, and social norms. To describe the added value of sustainable products compared to their traditional counterparts, the term willingness-to-pay (WTP) is frequently used. Although consumers typically have at least some WTP for sustainable products, the percentage varies largely between customer groups and between products/services, i.e., the WTP per product-market combination fluctuates heavily (Li and Kallas 2021; Sanghvi et al. 2025; Sindhu et al. 2025).

The first principle stems from the aim to place the process of value creation at the core of sivaa’s analytical framework. It seeks to identify which activities contribute to value generation and to assess the sustainability effects associated with these activities. These effects – referred to as ‘impact’ – may encompass both social and ecological dimensions.

It can be noted that this principle implies that the method enables greater transparency regarding the sustainability performance of any given product or service. Ideally, any end-user considering the purchase of a product or service would not only see its price but also the extent to which social and/or ecological standards are met. For example, this could include information on how much water was used in producing the product, the CO₂ emissions generated throughout the value chain, and the degree of assurance that no forced labor participated in its creation. The term ‘(digital) product passport’ is frequently associated with this line of thinking (Zhang and Seuring 2024).

The second principle aims to prioritize the process of determining which activities contribute to value generation and to assess the sustainability effects associated with these activities. In this, sivaa resembles the idea of VAT (Value Added Tax), where each entity in the value chain pays tax only on the value added. Similarly, sivaa determines the sustainability effects for their added value. To improve sustainability performance, ideally all entities across the end-to-end value chain should jointly monitor their key performance measures. However, in practice, such an approach is often not feasible. There are simply too many organizations involved, dispersed across the globe, and participating in a multitude of different value chains.

To counter this challenge, a value-adding approach is taken. The entire value chain is split up into ‘product + transport units’ (PTUs). Within each of these PTU-building blocks, the manager responsible can first obtain the information per product unit about the sustainability impact of the purchased materials (e.g., CO₂ emissions or water usage) obtained from the supplier and add to this the entity’s own sustainability impact from the transformation process. Added to this is the transportation of the products between the units. This information can be shared with the PTU’s customers so that these can do the same for their own PTU. By combining the information gathered in all PTUs, the sustainability impact of the final product can be distilled easily.

Figure 4 presents an example of a value chain for dairy desserts such as fruit yogurt. Next to energy, a manufacturer of such products relies primarily on three key inputs/ingredients: milk (supplied by dairy farmers), fruit (by growers), and packaging materials (by a packaging producer). The manufacturers supply the finished products to a retailer, who subsequently sells them to consumers. In the figure, the yellow rectangles represent value-adding activities, while the red arrows indicate transport flows. The dashed boxes denote the PTUs. The blue arrows represent hand-offs, illustrating the flow of products throughout the value chain.

It is important to note that sivaa does not have the immediate goal of reporting to external bodies, i.e., it is not per se a financial accounting instrument. Rather, it is a tool that can be used on the work floor in the primary processes following the Plan-Do-Check-Act improvement cycle. Especially, the instrument provides the necessary data for ‘Check’ and can be instrumental in finding ways to ‘Act’, i.e., through sivaa the organization and in fact all value chain entities can get the necessary steering information to make informed decisions on where to focus the sustainability improvement efforts.

One of the more pressing issues in sustainability impact improvement is the lack of reliable data. Recognizing that impact data can vary significantly in reliability and completeness, a unique feature of sivaa is that it not only reports on the sustainability level achieved but, also provides an indicator of the quality of the data on which this outcome is based. Sivaa thereto, distinguishes between four different data quality labels:

• Bronze: based on estimates or assumptions (e.g., averages);
• Silver: combines verified data with assumptions;
• Gold: based primarily on empirical data, with limited uncertainty;
• Diamond: derived from robust, verifiable, preferably real-time data sources.

The richer the label, the more accurate and precise the sustainability data are. The underlying logic is that, on the one hand, using ‘poor’ data is better than not having any data at all, while on the other hand, before making radical improvement decisions, the sensitivity of the data should be considered. At the same time, this stratification in data quality labels brings transparency to the value chain regarding the robustness of information. It enables organizations to target improvements in data quality over time. The fact that any company in the value chain, regardless of its position, can begin to develop insight is essential.

Note that according to this principle, the data do not necessarily have to be measured directly. When drawing a comparison with the data categorization used in the Greenhouse Gas Protocol (GHG), it becomes clear that within sivaa, not all data are required to be ‘primary’ (data provided by suppliers or others that directly relate to specific activities in the reporting company’s value chain). The method is designed to allow organizations to start with secondary data (industry-average-data, e.g., from published databases, government statistics, literature studies, and industry associations, financial data, proxy data, and other generic data), (Greenhouse Gas Protocol 2013). In cases where the need is greatest, or when a company’s strategy calls for intervention, it can then be assessed whether a transition from secondary to primary data is feasible. In Figure 5 the process of applying sivaa will be explained in six steps.

Overall, participants expressed a positive view of applicability of the sivaa-method. However, they also noted that an underlying question is why companies would want to apply the method (is it financially motivated, driven by regulation, or intrinsically motivated?). It was observed that applying sivaa in practice can be a significant challenge, particularly for organizations that are not already actively engaged in sustainability. The method was described as ‘quick & dirty’: it does not need to be perfect, but it helps to get started, learn where the focus areas are, and initiate the conversation.

One participant remarked that the sivaa approach can be compared to more classical risk analysis, where it is often more effective to start efforts in high-risk areas. By doing so, a significant part of the impact can be mapped with relatively little effort, and this principle applies to the sivaa instrument as well.

Several participants noted that it can be difficult to determine where to begin with sivaa. Questions raised include: which party in the value chain should initiate this? How many FTEs will be required to map everything? Is this suitable for small and medium-sized enterprises (SMEs) that have limited capacity and knowledge? Regarding the latter question, it was suggested that support from industry organizations could be helpful.

The general impression was that the sivaa-method provides organizations with the ability to better compare suppliers and identify where the greatest emissions occur. This can provide insight into potential improvement areas and serve as a basis for targeted actions. At the same time, some participants expressed concern that there is a risk the sivaa-method could be used as a checklist, emphasizing data collection over achieving actual improvements. It was stated that the strength of sivaa does not lie in data-precision but in the insights that lead to reduced environmental impact.

Participants noted that a key aspect of the method is collaboration with value chain partners. In their experience, some companies are pressured by their customers to become more sustainable, which in turn requires their suppliers to follow suit. This requires intensive coordination, especially since organizations often work with a large number of suppliers. It was noted that not all suppliers are ready to participate. A suggested solution to this issue was to not involve everyone immediately, but to start with the most important suppliers or the largest emitters.

Participants also found it challenging to be transparent. Some noted that there can be an unequal power dynamic, particularly upstream in the chain (where many smaller companies operate), which can create a sense of being pressured. It was further noted that the data provided by suppliers does not always reflect the underlying data. For that, one would need to look ‘under the hood’. It was also mentioned that companies must be willing to make choices and be ‘open’ for feedback (possibly on ‘poor’ performance) themselves. Participants stated that it is often ‘difficult’ to substantiate the data because there is a fear of being held accountable for these. Therefore, it must be clear what the method is used for: not for accountability, but rather for improvement purposes.

Several participants noted that determining the scope within the value chain is often challenging. It is not always clear where the chain begins or ends, for example, in the case of purchases through auctions where products are only registered by type and quantity. This results in a lack of detailed information and raises the question of who in the chain should take the initiative.

A frequently mentioned area for improvement is tooling and user guidance. The method should be combined with existing data insights or systems. Ideally, standards should be made centrally available.

Overall, the participating controllers were fairly positive about the sivaa-method. A noted advantage of the method is that the sivaa-method appears logical and straightforward, making it easy to apply. Participants sometimes experienced a somewhat resistant reaction when dealing with (particularly non-financial) reporting: the tendency to first discuss or define terms in considerable detail. The strength of this method is that such discussions are less necessary.

It was noted that sivaa can be a useful tool for conducting a cost-benefit analysis aimed at improving sustainability and serves to identify areas where data quality can be improved. The method can facilitate discussions both internally within an organization and across the entire value chain.

In the group of controllers, it emerged that participants currently involved in collecting ESG data referred to the application of sivaa in obtaining internal commitment and setting up internal processes and systems. Various data sources depend on off-balance sheet accounting registration, and the sivaa-method provides a place to connect such data with more robust data that does exist in systems. In addition to the supporting role of sivaa in registering non-financial data, the participant referred to the internal support for collecting these data and the still limited guidance on this within the organization. It is precisely in building this support, facilitating discussion, and working together to achieve improvement that the sivaa-method can be easily accessible. Small improvements can be made visible, and successes can be reported.

For companies that are already advanced in sustainability reporting, some participants noted that the method may be ‘too simple’. However, for companies just beginning to map ESG components in their value chain, the sivaa could be a suitable instrument.

Although participants described the method as useful, they also found it ‘challenging’. This challenge is threefold:

1. It relates to the transparency that the method provides in the value chain. The data could possibly reveal that the organization performs less well compared to its chain partners.
2. There may be uncertainty about what a request to apply the method means for the company itself (e.g., implications for oneself and colleagues).
3. There was a guidance issue because the data are not precise. If an imprecise outcome indicates a ‘good’ result, there is a risk that the ‘incorrect decision’ could be made to not act upon it.

Financial professionals within organizations reported that there is a challenge to ensure that the sivaa calculation itself is not seen as the ultimate goal; all stakeholders must understand that the purpose is to initiate discussions in the value chain based on the results of the calculation, not the calculation itself. For companies that are more advanced in sustainability reporting on CO₂, a connection to the European Reporting Standards (ESRS) is logical. Additionally, companies would benefit from further standardization of certain data or from tools to facilitate the application of the method.

Participants view sivaa as a good opportunity to map the value chain and build a common language for Scope 3. Obtaining data was identified as the main concern, followed by data quality.

Finding relevant data to support ESG-compliance and improvement is a challenging issue in practice. Financial professionals often want figures to be as precise as possible. Letting go of this need for precision may be the biggest challenge when applying sivaa within Finance; after all, the aim is not precise sustainability reporting, but a method focused on mapping the main trends to collaboratively work on improvements.

Several participants expressed concerns about data reliability. While it is possible to guide sustainability improvements based on broad trends, questions remain about whether the ‘correct’ direction is being pursued. Moreover, participants indicated that the method allows too much room for discussion. While the logic behind sivaa is generally understood, the collection and assessment of data must be harmonized to achieve a credible and widely supported outcome. This also prevents discussions from getting stuck in methodological debates rather than addressing the actual issues at hand. Clarity is required regarding how a specific data quality rating (bronze, silver, gold, diamond) is assigned; for example: when is data considered ‘silver’ versus ‘gold’?

Participants indicated that obtaining data is considered the most challenging aspect, even more so than data quality. It was noted that there can be a certain level of fear or embarrassment within the chain (figures can take on a life of their own, and relative outsiders may quickly form judgments). It remains important to use sivaa as a starting point for discussion, i.e., it serves a quite different function than finding out who can be blamed for what.

From an ESG perspective, participants felt the method is particularly well-suited to the environmental (E) component, and less so to the social (S) components; the latter component often includes ‘softer’ KPIs that require a more precise definition.

It was also noted that the method does not appear equally applicable to all types of value chains. For production chains, sivaa is more straightforward to use than for service-oriented chains.

Participants emphasized that mapping the value chain is not an endpoint. It is necessary to define where the endpoint lies; otherwise, the scope will continue to expand. This relates to defining materiality within sustainability reporting under CSRD and ESRS.

To make the sivaa-method more applicable across the value chain, it is important to keep explanations as simple and accessible as possible. A short guide or one-pager could help organizations and their chain partners quickly form a collective understanding of what is expected, facilitating discussions and coordinated actions.

It was also suggested that sector-specific templates would be useful. This would give organizations a more concrete idea of how to perform the assessment in their own context, simplifying the process and increasing the method’s usability and relevance.

Financial participants indicated that a logical next step is to link the results of CO₂ measurements to the financial performance of an organization. By integrating sivaa into regular financial reporting, sustainable KPIs become part of standard business operations.

Finally, it was noted that it is crucial for the method to align with existing laws and regulations. When sivaa is integrated with applicable legal frameworks, it enhances credibility, applicability, and the likelihood that organizations will embed the method into their processes.

A respondent noted that the current tool primarily focuses on mapping CO₂ emissions. However, according to the respondent, this is not where the greatest challenge lies. In the area of CO₂, many companies are already relatively advanced: there is considerable attention to this topic and a wide range of tools available. At the same time, progress in other risk domains lags behind; precisely in those areas the method could, according to the respondent, prove particularly valuable.

For measuring CO₂ emissions across the value chain, there is already extensive external tooling available, offered by dozens of providers (estimated at around fifty) each covering various aspects of measurement. Other aspects that could be incorporated include water usage, nitrogen and particulate matter emissions, and the use of chemical substances, among others. A key issue here, however, is that differences in definitions quickly arise, which does not benefit the consistent application of the method.

A further remark was that for CO₂ the CSRD and CSDDD are driving changes in the scope of reporting obligations. Companies that were previously intrinsically motivated to initiate sustainability reporting have, as a result of the so-called Omnibus effect (on EU Omnibus Package, see section 2 above), partially come to a standstill. This group, however, is particularly interesting to further support: they have already initiated the process, but the external pressure to comply with legislation has temporarily diminished. These are often companies that aim to manage their impact rather than focus solely on compliance. Typically, these are SMEs with 150 to 1,000 employees. The instrument aligns well with their needs.

With respect to the obligations under the CSDDD, companies are required to conduct a due diligence process – meaning, to exercise appropriate diligence. This aligns with the OECD Guiding Principles, which similarly emphasize that outcomes should be measurable and that so-called priority risks must be identified.

The vast majority of companies approaches sustainability primarily through the lens of compliance (meeting legal requirements) and risk management, often within the framework of double materiality; for example, assessing both how biodiversity loss affects the company and how the company’s activities impact biodiversity. A crucial point of attention in this regard is prioritization: determining what is truly material or relevant for the company. The respondent sees potential for the method precisely in this area. It can be particularly relevant for companies that have already started measuring and reporting their impact but are not yet subject to current European regulatory requirements. In such cases, the emphasis lies more on managing within the value chain rather than on compliance with legal requirements. However, by linking the method to the CSRD (VSME), companies can achieve both compliance and value creation.

For softer KPIs (such as those addressed under the CSDDD or OECD Guidelines), a respondent expects that the emphasis will increasingly shift towards transparency and data visibility. This is important, as it would be undesirable for companies to refrain from reporting altogether out of concern that the available information is insufficiently dependable.

A respondent addressed the topic of compliance. It was discussed to what extent organizations risk becoming constrained by rigid definitions. The respondent notes that there is considerable debate focused on defining concepts, particularly among accountants and controllers, who tend to emphasize measurability and verifiability. Within ESG departments, however, the focus is different: it is centered on generating insights, acting, and fostering continuous improvement. This orientation aligns closely with the principles of the OECD Guidelines, which is focused on continuously improving the cycle of due diligence, which aligns well with the four principles of the sivaa-method.

A major challenge for implementing sivaa is that companies often lack a clear understanding of the structure of their value chains. The question arises as to how much effort and cost they are willing to invest in fully mapping them. One advantage of sivaa is that it is not always necessary to work exclusively with fully factual data; estimated data can also be valuable for generating insight.

According to a respondent, transparency within the value chain remains crucial. Ultimately, consumers should also be able to see the impact of a product. The sivaa-method enables such impact to be determined per product unit.

A respondent observed that retailers or companies that sell directly to consumers more frequently provide insight into impact than industrial enterprises. A digital product passport can support this effort. Currently, there is considerable attention for the digital product passport, though primarily for consumer products rather than industrial goods. For companies with their own production lines (such as some major brands) it is relatively easy to trace their value chains. For SMEs with dozens of tiers and multiple actors, however, this is nearly impossible. This is particularly true for raw material procurement, where inputs are often purchased in bulk on open markets, resulting in a wide variety of low-incentive supplier-buyer relationships and, consequently, highly opaque value chains.

A respondent noted that the topic is gaining broader attention, for example in the context of circular products such as batteries. In practice, estimations are still frequently used instead of measured data, though expectations are that this will become more professionalized in the coming years. The respondent considers it an advantage that the instrument incorporates different data quality levels. Although there is also a clear push from a compliance perspective to ensure the highest possible level of data certainty, the advantage of this instrument is that it allows for a rapid estimation of the most significant risks. This approach is fully consistent with the OECD framework (particularly its emphasis on ‘risks that matter’) and aligns well with what organizations are seeking.

Transparency is crucial in the value chain, both internally and externally. Therefore, working towards a product passport that indicates the impact of a product for the end user is a valuable goal. This method could support this objective if it links to such a goal or tool.

From multiple discussions with potential users with different backgrounds, it became clear that the sivaa instrument not only services its purpose (identifying possible sustainability improvements in a value chain setting) but is also very intuitive, and easy to use because it fundamentally follows the value adding activities throughout the organization internally and through the external value chain. The potential users were also especially charmed by two sivaa-features, namely (1) the VAT-like approach of using the value-added activities for determining the sustainability impact, and (2) including several data quality levels, and the possibility to use this in calculations. The first feature helped users in providing the required steering information while the second feature resonated with their aims of approaching sustainability from a risk management perspective. As such, sivaa was seen as a method that could contribute to getting reliable sustainability information for improvement purposes which enables companies to make better choices towards their sustainability objectives.

Next to this highly positive reception on the instrument and its underlying features, there also remain some concerns and points for further research and development. First, although sivaa is found to be very usable for measurable and relative ‘objective’ data such as greenhouse gas and other emissions or water usage and more in general for the ‘E’ variables, it is far less obvious how to apply this the same method for the ‘S’ dimension. The key issue is that in these areas the definitions, measurements, and ‘addibility’ of data are far less clear. Although some ideas have been discussed above (see section 3), further research and additional experiments might be needed to get a better grip on how to apply sivaa for all aspects of ESG.

Second, from the various discussions with potential users it became clear that many organizations dominantly use a so-called ‘compliancy and risk-management approach’ towards sustainability, and that the urge to fulfill the legal and other reporting requirements has a dominant priority over actual sustainability improvement efforts within the primary processes. Obviously, nobody would claim that sustainability reporting is a goal in itself yet especially considering the recent National and European laws such as CSRD and CSDDD, it is only natural that companies want to ensure that the necessary steps towards sustainability reporting are taken, before engaging in further efforts. From this perspective, potential users of sivaa are looking for the integration of their sustainability efforts towards both reporting and improvement. Also, there is a demand for standardized data to use within the sivaa-method. Further research would be needed to see how sivaa can be integrated with reporting methods and standards. One recent example of this in the Netherlands is the “Uniforme kernset CO₂-e data”, see Topsector Logistiek (2025).

As a side-remark, it might be observed that the sivaa-method may be particularly relevant for SMEs (100–1,000 employees) that, due to the mitigation and postponement of European reporting requirements under the EU Omnibus Package, no longer face immediate legal CO₂-emission reporting obligations. Nevertheless, these companies remain motivated to strategically enhance the sustainability performance of their value chains.

Third, as mentioned, when it comes to their sustainability efforts, many organizations focus not only on reporting but also on sustainability risk management. An important feature of sivaa is that it can be easily determined which value chain activities will have the greatest impact on sustainability. This aligns well with the effort to identify and inventory the most significant sources of potential risk. However, at the same time sivaa allows working with sources that have a different data-quality; some of the data are highly dependable, as they are based on actual measurements, whereas other data may be little more than guesstimate. Some potential users have expressed their concern about this data quality differentiation. As there is broad acceptance that data quality is frequently imperfect, many improvements efforts are targeted in getting more accurate data as these are needed for both reporting and risk management purposes. In other words, companies, especially at the staff level, feel a strong natural need to decrease their uncertainty. However, despite that this is an understandable objective, the sivaa-method is designed for decision making under data-uncertainty, hence uses a different approach. Further research is needed to see how companies and value chains can deal with this. With this, it is also interesting to further research into how many different data-labels are needed. In the presented sivaa-instrument there are four levels (bronze, silver, gold, diamond). Although it seems logical to at least distinguish two levels (estimated vs. measured data), it might be that maybe three levels are needed.

Fourth, one of the appreciated features of sivaa is that it focusses on the sustainability aspects of the product rather than on the performance of a firm. This appeared to be particularly interesting for organizations that participate in value chains creating consumer products. In such value chains, increasingly the concept of a product passport is introduced and used, and the data gathered through sivaa corresponds well with such efforts. However, it can also be remarked that organizations that work predominately with industrial products and/or more upstream in the value chain might have less interest in this feature. For example, such organizations might purchase raw materials and commodities from ‘spot markets’ so that these do not even have clear relations with their suppliers. Conceptually speaking, each value chain would end at the consumer (unless of course, circular chains are considered), but this might not be the everyday reality of firms making industrial products. Therefore, a final interesting research direction listed here might be how to scope the value chain in which sivaa is used.