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Data related Challenges

The scarcity of clean data has emerged as a prominent challenge in Climate Reporting, but it should not prevent a company from starting with its Climate Reporting. We recommend companies must take action and enhance their Climate Reporting by investing in digital technologies, establishing clear data collection processes, and collaborating with stakeholders.  

Data related Challenges  

  • Lack of data and data fragmentation: Unavailable or scattered data pose significant challenges in Climate Reporting, as necessary data may not be tracked or readily available in a central system, making it difficult to obtain, especially for scope 3 emissions. Gathering the required data from various sources and coordinating with different departments and stakeholders can be time-consuming and resource intensive.  


  • Low data quality and persistent data inaccuracy: There needs to be more consistency regarding data tracking across various sources. This inconsistency can be attributed to several factors, such as the absence of data quality controls and, in general, the existence of weak data governance practices. This makes it challenging to maintain a high standard of data quality, and there is a risk of errors and inconsistencies creeping into the data collection process. Furthermore, although applying expert knowledge and adopting data proxies in the form of estimated values is encouraged at the initial stages of Climate Reporting to fill the gaps in data collection, it can further exacerbate the data quality issues if not replaced in the mid to-long term. 


  • Missing data traceability: As data is collected and aggregated across an organisation, it is subject to passing through various teams, data platforms and repositories and undergoes required transformations. For audit and reporting purposes, solid data lineage is in place to guarantee transparency in the end-to-end tracking of data sources and appropriate visibility over any modification that is applied to the source data before it makes its way into external disclosures. Insufficient data documentation: The entire data collection process should be documented, including assumptions, calculations, and modifications to the data. Accurate documentation takes not only time but also expertise and knowledge.  


  • Growing demands due to mandatory external data validation: The collected data and its documentation will be subject to an external validation as part of the soon mandatory Sustainability Reporting audit. As a result, there is increasing pressure to present a well-orchestrated complete picture which should guarantee the highest standards of accuracy.  


  • Increasing data requests: Another significant challenge facing companies is the increasing demand for data disclosures related to Scope 3 emissions. As more organisations recognise the importance of measuring and reducing their carbon footprint, they seek more extensive and detailed data from their suppliers, customers, and partners. This trend has increased the number of questionnaires sent across companies in their respective value chains. This growing demand for data disclosure can strain the resources of reporting companies, leading to difficulties in managing the workload effectively. Moreover, the need for standardisation in data request formats and data quality requirements can create further challenges for companies.  


  • Requests for revealing sensitive data: As companies are asked to report data, they also face the challenge of how much and what kind of data they can disclose without revealing information that should not be disclosed without it causing a disadvantage from, for example, revealing highly sensitive competitive information. 


  • Increasing complexity with a move from historic to forward-looking data: With the implementation of the regulatory requirements as outlined in the Swiss ordinance on Climate Reporting ordinance on mandatory climate disclosures for large companies and per TCFD, companies will also have to start working with forward looking data, for example concerning the disclosure of exposures to transition risks or to evolving physical risk conditions. Handling such data comes with more complexities than simpler, backwards-looking historical data.  


  • Inadequate data management tools: Many organisations approached sustainability data management and reporting with basic tools such as Excel or similar technologies, posing a significant risk of errors and other consequences. 

Collecting and managing sustainability data poses significant challenges for companies. The required data is often not readily available because of inadequate digital infrastructure, and as a result, the data quality is rarely sufficient to pass an external validation.  

  • Lack of data and data fragmentation: Unavailable or scattered data pose significant challenges in Climate Reporting, as necessary data may not be tracked or readily available in a central system, making it difficult to obtain, especially for scope 3 emissions. Gathering the required data from various sources and coordinating with different departments and stakeholders can be time-consuming and resource intensive.  


  • Low data quality and persistent data inaccuracy: There needs to be more consistency regarding data tracking across various sources. This inconsistency can be attributed to several factors, such as the absence of data quality controls and, in general, the existence of weak data governance practices. This makes it challenging to maintain a high standard of data quality, and there is a risk of errors and inconsistencies creeping into the data collection process. Furthermore, although applying expert knowledge and adopting data proxies in the form of estimated values is encouraged at the initial stages of Climate Reporting to fill the gaps in data collection, it can further exacerbate the data quality issues if not replaced in the mid to-long term. 


  • Missing data traceability: As data is collected and aggregated across an organisation, it is subject to passing through various teams, data platforms and repositories and undergoes required transformations. For audit and reporting purposes, solid data lineage is in place to guarantee transparency in the end-to-end tracking of data sources and appropriate visibility over any modification that is applied to the source data before it makes its way into external disclosures. Insufficient data documentation: The entire data collection process should be documented, including assumptions, calculations, and modifications to the data. Accurate documentation takes not only time but also expertise and knowledge.  


  • Growing demands due to mandatory external data validation: The collected data and its documentation will be subject to an external validation as part of the soon mandatory Sustainability Reporting audit. As a result, there is increasing pressure to present a well-orchestrated complete picture which should guarantee the highest standards of accuracy.  


  • Increasing data requests: Another significant challenge facing companies is the increasing demand for data disclosures related to Scope 3 emissions. As more organisations recognise the importance of measuring and reducing their carbon footprint, they seek more extensive and detailed data from their suppliers, customers, and partners. This trend has increased the number of questionnaires sent across companies in their respective value chains. This growing demand for data disclosure can strain the resources of reporting companies, leading to difficulties in managing the workload effectively. Moreover, the need for standardisation in data request formats and data quality requirements can create further challenges for companies.  


  • Requests for revealing sensitive data: As companies are asked to report data, they also face the challenge of how much and what kind of data they can disclose without revealing information that should not be disclosed without it causing a disadvantage from, for example, revealing highly sensitive competitive information. 


  • Increasing complexity with a move from historic to forward-looking data: With the implementation of the regulatory requirements as outlined in the Swiss ordinance on Climate Reporting ordinance on mandatory climate disclosures for large companies and per TCFD, companies will also have to start working with forward looking data, for example concerning the disclosure of exposures to transition risks or to evolving physical risk conditions. Handling such data comes with more complexities than simpler, backwards-looking historical data.  


  • Inadequate data management tools: Many organisations approached sustainability data management and reporting with basic tools such as Excel or similar technologies, posing a significant risk of errors and other consequences. 

Collecting and managing sustainability data poses significant challenges for companies. The required data is often not readily available because of inadequate digital infrastructure, and as a result, the data quality is rarely sufficient to pass an external validation.  

  • Lack of data and data fragmentation: Unavailable or scattered data pose significant challenges in Climate Reporting, as necessary data may not be tracked or readily available in a central system, making it difficult to obtain, especially for scope 3 emissions. Gathering the required data from various sources and coordinating with different departments and stakeholders can be time-consuming and resource intensive.  


  • Low data quality and persistent data inaccuracy: There needs to be more consistency regarding data tracking across various sources. This inconsistency can be attributed to several factors, such as the absence of data quality controls and, in general, the existence of weak data governance practices. This makes it challenging to maintain a high standard of data quality, and there is a risk of errors and inconsistencies creeping into the data collection process. Furthermore, although applying expert knowledge and adopting data proxies in the form of estimated values is encouraged at the initial stages of Climate Reporting to fill the gaps in data collection, it can further exacerbate the data quality issues if not replaced in the mid to-long term. 


  • Missing data traceability: As data is collected and aggregated across an organisation, it is subject to passing through various teams, data platforms and repositories and undergoes required transformations. For audit and reporting purposes, solid data lineage is in place to guarantee transparency in the end-to-end tracking of data sources and appropriate visibility over any modification that is applied to the source data before it makes its way into external disclosures. Insufficient data documentation: The entire data collection process should be documented, including assumptions, calculations, and modifications to the data. Accurate documentation takes not only time but also expertise and knowledge.  


  • Growing demands due to mandatory external data validation: The collected data and its documentation will be subject to an external validation as part of the soon mandatory Sustainability Reporting audit. As a result, there is increasing pressure to present a well-orchestrated complete picture which should guarantee the highest standards of accuracy.  


  • Increasing data requests: Another significant challenge facing companies is the increasing demand for data disclosures related to Scope 3 emissions. As more organisations recognise the importance of measuring and reducing their carbon footprint, they seek more extensive and detailed data from their suppliers, customers, and partners. This trend has increased the number of questionnaires sent across companies in their respective value chains. This growing demand for data disclosure can strain the resources of reporting companies, leading to difficulties in managing the workload effectively. Moreover, the need for standardisation in data request formats and data quality requirements can create further challenges for companies.  


  • Requests for revealing sensitive data: As companies are asked to report data, they also face the challenge of how much and what kind of data they can disclose without revealing information that should not be disclosed without it causing a disadvantage from, for example, revealing highly sensitive competitive information. 


  • Increasing complexity with a move from historic to forward-looking data: With the implementation of the regulatory requirements as outlined in the Swiss ordinance on Climate Reporting ordinance on mandatory climate disclosures for large companies and per TCFD, companies will also have to start working with forward looking data, for example concerning the disclosure of exposures to transition risks or to evolving physical risk conditions. Handling such data comes with more complexities than simpler, backwards-looking historical data.  


  • Inadequate data management tools: Many organisations approached sustainability data management and reporting with basic tools such as Excel or similar technologies, posing a significant risk of errors and other consequences. 

Deep Dive - Consequences of using Excel and other simple data management tools for sustainability reporting:  

As data required for Climate Reporting often involves complex and diverse datasets with multiple variables, manual maintenance of Excel can lead to errors in data input, processing, and analysis. These errors can undermine the accuracy and reliability of sustainability reports, potentially leading to reputational damage for companies (e.g. “unintentional” greenwashing resulting from inaccurate disclosures).  

Another typical challenge of using inadequate technologies is managing, maintaining, and analysing large datasets. As the volume and complexity of sustainability data increase, it becomes challenging to process and analyse data efficiently. Lengthy processing times and errors are often a consequence, which makes it challenging to generate timely and accurate reports. Moreover, using tools like Excel to manage sustainability data can create a lack of transparency and accountability. With multiple users accessing and updating worksheets, it becomes challenging – if not impossible - to track changes, implement appropriate controls, monitor data quality, and ensure consistency. 

Climate Reporting Data – worthwhile actions & opportunities   

New sustainability and climate regulations allow companies to enhance transparency, bolster their reputation, and attract investors by showcasing their dedication to sustainability. Effective data management enables companies to identify areas for improvement, demonstrate sustainability performance to stakeholders, achieve cost savings, and drive innovation.  

Invest in digital data collection and management technologies:

Companies should adopt digital solutions to automate and streamline collecting, managing, and analysing sustainability data.  

Opportunity: Improve the accuracy and efficiency of data collection, reducing the potential for errors and saving time and resources. Digital technologies can automate data collection from various sources, including suppliers, customers, and stakeholders, which can help companies obtain more comprehensive and reliable data for Sustainability Reporting. Furthermore, it helps companies manage and analyse large volumes of sustainability data, enabling them to identify trends and patterns, gain valuable insights into their sustainability performance, and track their progress. 

Implement a clear data collection process:

Companies should implement transparent data collection processes, which involve establishing a systematic and consistent approach to collecting, managing, and reporting sustainability data. The process should be designed to ensure that the data collected is accurate, complete, and reliable. Being able to achieve 100% data coverage even to the most distant corners of the supply chain is unlikely. Companies can prioritise data collection efforts in the spots where impacts are higher or more important. 

Opportunity: With more solid data collection practices and effective controls in place, resulting in improved data quality, comes the chance to reduce internal and external audit efforts and costs and overall exposure to risks of greenwashing allegations. 

Collaborate with stakeholders:

Collaborating with suppliers, customers, and other stakeholders to improve data collection is an excellent way for companies to demonstrate their commitment to sustainability and manage their risks better. However, companies must be transparent about the data they are willing to share. If companies fear sharing sensitive, they can provide aggregated data or redirect stakeholders to publicly available data in the form of common reporting standards that were already published. This approach can help companies balance data privacy concerns and the need to guarantee transparency in Climate Reporting.  

Opportunity: Collaborating with stakeholders on Climate Reporting can help build trust and establish a shared sense of purpose, leading to increased stakeholder engagement and support.

Hire specialised personnel:

Especially larger companies should hire personnel with technical data science skills and expertise to implement a generally more datacentric strategy.  

Opportunity: By leveraging advanced data analytics and modelling techniques, companies can not only go beyond a yearly Climate Reporting exercise and gain deeper insights into their sustainability performance, identify areas for improvement, and ultimately steer the way they conduct business towards achievement of sustainability targets they set themselves once-a-year Climate Reporting. Finally, developing the necessary skills to comprehend the implications of forward-looking analytics and scenario analysis regarding climate change is crucial for enhancing a company's resilience.

Défis liés à l’obtention de données

Le manque de données vérifiables se pose comme un défi majeur dans le reporting climatique, mais cela ne devrait pas empêcher une entreprise de commencer. Nous recommandons aux entreprises de prendre des mesures et d'améliorer leur reporting en investissant dans les technologies numériques, en établissant des processus de collecte de données clairs et en collaborant avec leurs parties prenantes. 

Défis liés à l’obtention de données 

  • Manque et fragmentation des données : Les données requises ne sont souvent pas immédiatement disponibles en raison d'une infrastructure numérique insuffisante, et par conséquent, la qualité des données est rarement suffisante pour passer un audit externe. 


  • Faible qualité des données et inexactitudes persistantes : Il doit y avoir plus de cohérence en ce qui concerne la traçabilité des données. Cette incohérence peut être attribuée à plusieurs facteurs, tels que l'absence de contrôles de qualité des données et, en général, des pratiques de gouvernance sur le reporting climatique encore balbutiantes.  


  • Traçabilité des données manquantes : À mesure que les données sont collectées et agrégées dans une organisation, elles passent par diverses équipes, plates-formes, approbations, et subissant des transformations requises. À des fins d'audit et de reporting, une traçabilité des données doit être mise en place pour garantir la transparence dans le suivi de bout en bout des sources de données et une visibilité appropriée sur toute modification apportée aux données sources avant leur inclusion dans le rapport final. Cela généralement se résume à un journal d’audit sur les données. 


  • Documentation insuffisante des données : L'ensemble du processus de collecte de données doit être documenté, y compris les hypothèses, les calculs, les facteurs d’émissions et les modifications apportées aux données.  


  • Demandes croissantes en raison de la validation externe des données obligatoires : Les données collectées et leur documentation seront soumises à des audits externes dans le cadre des réglementations Suisse et Européenne (CSRD). Par conséquent, il y a une pression croissante pour présenter une image complète et bien orchestrée, qui devrait garantir les normes les plus élevées de précision. 


  • Demandes croissantes de données liées aux émissions de Scope 3 : À mesure que plus en plus d'organisations reconnaissent l'importance de mesurer et de réduire leur empreinte carbone, elles recherchent des données plus étendues et détaillées auprès de leurs fournisseurs, clients et partenaires. Cette tendance a augmenté le nombre de questionnaires envoyés aux entreprises dans leurs chaînes de provisionnement respectives. Cette demande croissante de reporting de données peut mettre à rude épreuve les ressources des entreprises, ce qui rend difficile la gestion efficace de la charge de travail. De plus, le manque d’harmonisation des formats de questionnaires et des exigences en matière de qualité des données peut créer d'autres défis pour les entreprises. 


  • Demandes de divulgation de données sensibles : Au fur et à mesure que les entreprises sont invitées à communiquer des données, elles sont également confrontées au défi de savoir quelle quantité et quel type de données elles peuvent divulguer sans révéler des informations qui ne devraient pas être divulguées sans que cela n'entraîne un désavantage, par exemple, la révélation d'informations concurrentielles très sensibles. 


  • Une complexité croissante avec le passage de données historiques à des données prospectives : Avec la mise en œuvre des exigences réglementaires décrites dans l'ordonnance suisse sur le reporting climatique, l'ordonnance sur les informations climatiques obligatoires pour les grandes entreprises et la TCFD, les entreprises devront également commencer à travailler avec des données prospectives, par exemple en ce qui concerne la divulgation des expositions aux risques de transition ou à l'évolution des conditions de risques physiques. Le traitement de ces données est plus complexe que celui de données historiques.


  • Outils de gestion des données inadéquats : De nombreuses organisations ont abordé la gestion et la communication des données relatives au développement durable avec des outils de base tels qu'Excel ou des technologies similaires, ce qui présente un risque important d'erreurs et d'autres conséquences. 

Collecting and managing sustainability data poses significant challenges for companies. The required data is often not readily available because of inadequate digital infrastructure, and as a result, the data quality is rarely sufficient to pass an external validation.  

  • Lack of data and data fragmentation: Unavailable or scattered data pose significant challenges in Climate Reporting, as necessary data may not be tracked or readily available in a central system, making it difficult to obtain, especially for scope 3 emissions. Gathering the required data from various sources and coordinating with different departments and stakeholders can be time-consuming and resource intensive.  


  • Low data quality and persistent data inaccuracy: There needs to be more consistency regarding data tracking across various sources. This inconsistency can be attributed to several factors, such as the absence of data quality controls and, in general, the existence of weak data governance practices. This makes it challenging to maintain a high standard of data quality, and there is a risk of errors and inconsistencies creeping into the data collection process. Furthermore, although applying expert knowledge and adopting data proxies in the form of estimated values is encouraged at the initial stages of Climate Reporting to fill the gaps in data collection, it can further exacerbate the data quality issues if not replaced in the mid to-long term. 


  • Missing data traceability: As data is collected and aggregated across an organisation, it is subject to passing through various teams, data platforms and repositories and undergoes required transformations. For audit and reporting purposes, solid data lineage is in place to guarantee transparency in the end-to-end tracking of data sources and appropriate visibility over any modification that is applied to the source data before it makes its way into external disclosures. Insufficient data documentation: The entire data collection process should be documented, including assumptions, calculations, and modifications to the data. Accurate documentation takes not only time but also expertise and knowledge.  


  • Growing demands due to mandatory external data validation: The collected data and its documentation will be subject to an external validation as part of the soon mandatory Sustainability Reporting audit. As a result, there is increasing pressure to present a well-orchestrated complete picture which should guarantee the highest standards of accuracy.  


  • Increasing data requests: Another significant challenge facing companies is the increasing demand for data disclosures related to Scope 3 emissions. As more organisations recognise the importance of measuring and reducing their carbon footprint, they seek more extensive and detailed data from their suppliers, customers, and partners. This trend has increased the number of questionnaires sent across companies in their respective value chains. This growing demand for data disclosure can strain the resources of reporting companies, leading to difficulties in managing the workload effectively. Moreover, the need for standardisation in data request formats and data quality requirements can create further challenges for companies.  


  • Requests for revealing sensitive data: As companies are asked to report data, they also face the challenge of how much and what kind of data they can disclose without revealing information that should not be disclosed without it causing a disadvantage from, for example, revealing highly sensitive competitive information. 


  • Increasing complexity with a move from historic to forward-looking data: With the implementation of the regulatory requirements as outlined in the Swiss ordinance on Climate Reporting ordinance on mandatory climate disclosures for large companies and per TCFD, companies will also have to start working with forward looking data, for example concerning the disclosure of exposures to transition risks or to evolving physical risk conditions. Handling such data comes with more complexities than simpler, backwards-looking historical data.  


  • Inadequate data management tools: Many organisations approached sustainability data management and reporting with basic tools such as Excel or similar technologies, posing a significant risk of errors and other consequences. 

Collecting and managing sustainability data poses significant challenges for companies. The required data is often not readily available because of inadequate digital infrastructure, and as a result, the data quality is rarely sufficient to pass an external validation.  

  • Lack of data and data fragmentation: Unavailable or scattered data pose significant challenges in Climate Reporting, as necessary data may not be tracked or readily available in a central system, making it difficult to obtain, especially for scope 3 emissions. Gathering the required data from various sources and coordinating with different departments and stakeholders can be time-consuming and resource intensive.  


  • Low data quality and persistent data inaccuracy: There needs to be more consistency regarding data tracking across various sources. This inconsistency can be attributed to several factors, such as the absence of data quality controls and, in general, the existence of weak data governance practices. This makes it challenging to maintain a high standard of data quality, and there is a risk of errors and inconsistencies creeping into the data collection process. Furthermore, although applying expert knowledge and adopting data proxies in the form of estimated values is encouraged at the initial stages of Climate Reporting to fill the gaps in data collection, it can further exacerbate the data quality issues if not replaced in the mid to-long term. 


  • Missing data traceability: As data is collected and aggregated across an organisation, it is subject to passing through various teams, data platforms and repositories and undergoes required transformations. For audit and reporting purposes, solid data lineage is in place to guarantee transparency in the end-to-end tracking of data sources and appropriate visibility over any modification that is applied to the source data before it makes its way into external disclosures. Insufficient data documentation: The entire data collection process should be documented, including assumptions, calculations, and modifications to the data. Accurate documentation takes not only time but also expertise and knowledge.  


  • Growing demands due to mandatory external data validation: The collected data and its documentation will be subject to an external validation as part of the soon mandatory Sustainability Reporting audit. As a result, there is increasing pressure to present a well-orchestrated complete picture which should guarantee the highest standards of accuracy.  


  • Increasing data requests: Another significant challenge facing companies is the increasing demand for data disclosures related to Scope 3 emissions. As more organisations recognise the importance of measuring and reducing their carbon footprint, they seek more extensive and detailed data from their suppliers, customers, and partners. This trend has increased the number of questionnaires sent across companies in their respective value chains. This growing demand for data disclosure can strain the resources of reporting companies, leading to difficulties in managing the workload effectively. Moreover, the need for standardisation in data request formats and data quality requirements can create further challenges for companies.  


  • Requests for revealing sensitive data: As companies are asked to report data, they also face the challenge of how much and what kind of data they can disclose without revealing information that should not be disclosed without it causing a disadvantage from, for example, revealing highly sensitive competitive information. 


  • Increasing complexity with a move from historic to forward-looking data: With the implementation of the regulatory requirements as outlined in the Swiss ordinance on Climate Reporting ordinance on mandatory climate disclosures for large companies and per TCFD, companies will also have to start working with forward looking data, for example concerning the disclosure of exposures to transition risks or to evolving physical risk conditions. Handling such data comes with more complexities than simpler, backwards-looking historical data.  


  • Inadequate data management tools: Many organisations approached sustainability data management and reporting with basic tools such as Excel or similar technologies, posing a significant risk of errors and other consequences. 

Deep Dive - Conséquences de l'utilisation d'Excel et d'autres outils simples de gestion des données pour les rapports sur le développement durable : 

Étant donné que les données requises pour les rapports sur le climat impliquent souvent des ensembles de données complexes et diversifiés avec de multiples variables, la maintenance manuelle d'Excel peut entraîner des erreurs dans la saisie, le traitement et l'analyse des données. Ces erreurs peuvent nuire à l'exactitude et à la fiabilité des rapports sur le développement durable, ce qui peut nuire à la réputation des entreprises (par exemple, le greenwashing "involontaire" résultant d'informations inexactes).  

Un autre défi typique de l'utilisation de technologies inadéquates est la gestion, la maintenance et l'analyse de vastes ensembles de données. À mesure que le volume et la complexité des données sur le développement durable augmentent, il devient difficile de les traiter et de les analyser efficacement. Il en résulte souvent des temps de traitement longs et des erreurs, ce qui rend difficile la production de rapports précis en temps voulu. En outre, l'utilisation d'outils tels qu'Excel pour gérer les données relatives au développement durable peut entraîner un manque de transparence et de responsabilité. Lorsque plusieurs utilisateurs accèdent aux fichiers Excel et les mettent à jour, il devient difficile, voire impossible, de suivre les changements, de mettre en œuvre des contrôles appropriés, de surveiller la qualité des données et de garantir la cohérence. 

Données du rapport sur le climat - actions et opportunités intéressantes 

Les nouvelles réglementations en matière de durabilité et de climat permettent aux entreprises d'améliorer leur transparence, de renforcer leur réputation et d'attirer les investisseurs en montrant leur engagement envers la durabilité. Une gestion efficace des données permet aux entreprises d'identifier les domaines à améliorer, de démontrer leur performance en matière de durabilité aux parties prenantes, de réaliser des économies de coûts et de stimuler l'innovation. 

Investissez dans les technologies de collecte et de gestion de données:

Les entreprises devraient adopter des solutions numériques pour automatiser et rationaliser la collecte, la gestion et l'analyse des données de durabilité. 

Opportunité : Améliorez la précision et l'efficacité de la collecte de données, réduisez le risque d'erreurs et économisez du temps et des ressources. Les technologies numériques peuvent automatiser la collecte de données auprès de diverses sources, notamment les fournisseurs, les clients et les parties prenantes, ce qui peut aider les entreprises à obtenir des données plus complètes et fiables pour la communication sur la durabilité. De plus, elles aident les entreprises à gérer et à analyser de grandes quantités de données de durabilité, ce qui leur permet d'identifier des tendances, d'obtenir des informations sur leur impact en matière de durabilité et de suivre leurs progrès. 

Mettez en place un processus clair de collecte de données :

Les entreprises devraient mettre en place des processus de collecte de données transparents, qui consistent à établir une approche systématique et cohérente de la collecte, de la gestion et de la communication des données de durabilité.

Opportunité : Avec des pratiques de collecte de données plus solides et des contrôles efficaces en place, ce qui se traduit par une amélioration de la qualité des données, les entreprises ont la possibilité de réduire les efforts et les coûts d'audit internes et externes, ainsi que l'exposition globale aux risques de greenwashing accidentel. 

Collaborez avec les parties prenantes :

Collaborer avec les fournisseurs, les clients et d'autres parties prenantes pour améliorer la collecte de données est un excellent moyen pour les entreprises de montrer leur engagement envers la durabilité et de mieux gérer leurs risques. Cependant, les entreprises doivent être transparentes concernant les données qu'elles sont prêtes à partager. Si les entreprises craignent de partager des données sensibles, elles peuvent fournir des données agrégées ou orienter les parties prenantes vers des données disponibles publiquement sous forme de normes de communication courantes déjà publiées. Cette approche peut aider les entreprises à équilibrer les préoccupations liées à la protection des données et la nécessité de garantir la transparence dans la communication sur le climat.

Opportunité : Collaborer avec les parties prenantes sur la communication sur le climat peut contribuer à renforcer la confiance et à établir un sentiment partagé de mission, ce qui peut entraîner une plus grande implication et un plus grand soutien des parties prenantes.

Embauchez du personnel spécialisé :

Surtout les grandes entreprises devraient embaucher du personnel ayant des compétences techniques en science des données et de l'expertise pour mettre en œuvre une stratégie généralement plus axée sur les données. 

Opportunité : En tirant parti de techniques avancées d'analyse et de modélisation des données, les entreprises peuvent non seulement aller au-delà de l'exercice annuel de communication sur le climat et obtenir des informations plus approfondies sur leur performance en matière de durabilité, identifier des domaines à améliorer et finalement orienter la manière dont elles mènent leurs activités vers l'atteinte des objectifs de durabilité qu'elles se sont fixés grâce à la communication sur le climat. Enfin, développer les compétences nécessaires pour comprendre les implications de l'analyse prospective et de l'analyse de scénarios en matière de changement climatique est crucial pour renforcer la résilience d'une entreprise.

Datenherausforderungen

Der Mangel an sauberen Daten hat sich als eine Herausforderung in der Klimaberichterstattung herauskristallisiert, sollte Unternehmen jedoch nicht davon abhalten, mit ihrer Klimaberichterstattung zu beginnen. Wir empfehlen Unternehmen, Maßnahmen zu ergreifen und ihre Klimaberichterstattung zu verbessern, indem sie in digitale Technologien investieren, klare Datensammlungsprozesse etablieren und mit Stakeholdern zusammenarbeiten. 

Datenherausforderungen

  • Fehlende Daten und Datenfragmentierung: Fehlende oder verstreute Daten stellen in der Klimaberichterstattung erhebliche Herausforderungen dar, da notwendige Daten möglicherweise nicht erfasst oder nicht in einem zentralen System verfügbar sind, was die Beschaffung, insbesondere für Scope 3-Emissionen, erschwert. Das Sammeln der erforderlichen Daten aus verschiedenen Quellen und die Abstimmung mit verschiedenen Abteilungen und Stakeholdern kann zeitaufwändig und ressourcenintensiv sein. 


  • Niedrige Datenqualität und fortwährende Dateninkonsistenz: Es muss eine größere Konsistenz bei der Datenerfassung in verschiedenen Quellen herrschen. Diese Inkonsistenz kann auf mehrere Faktoren zurückgeführt werden, wie das Fehlen von Datenqualitätskontrollen und im Allgemeinen schwache Datenverwaltungspraktiken. Dies macht es schwierig, hohe Datenqualitätsstandards aufrechtzuerhalten, und es besteht das Risiko von Fehlern und Inkonsistenzen im Datensammlungsprozess. 


  • Fehlende Datenrückverfolgbarkeit: Da Daten in einer Organisation gesammelt und aggregiert werden, durchlaufen sie verschiedene Teams, Datenplattformen und -speicher und unterliegen diverser Transformationen. Für Audit- und Berichtszwecke muss eine solide Datenherkunft implementiert werden, um Transparenz bei der lückenlosen Verfolgung der Datenquellen und angemessene Sichtbarkeit über Änderungen sicherzustellen. 


  • Unzureichende Dokumentation der Daten: Der gesamte Prozess der Datenerfassung sollte dokumentiert werden, einschließlich Annahmen, Berechnungen und Änderungen an den Daten. Eine genaue Dokumentation erfordert nicht nur Zeit, sondern auch Fachkenntnisse. 

    Wachsender Druck durch die obligatorische externe Datenvalidierung: Die gesammelten Daten und deren Dokumentation unterliegen einer externen Validierung als Teil der bald obligatorischen Nachhaltigkeitsberichterstattung. Daher besteht ein wachsender Druck, ein gut orchestriertes Gesamtbild vorzulegen. 


  • Zunehmende Anfragen nach Daten: Ein weiteres bedeutendes Problem, dem sich Unternehmen stellen, ist die steigende Nachfrage nach Datenoffenlegungen im Zusammenhang mit Scope 3-Emissionen. Da immer mehr Organisationen die Bedeutung der Messung und Reduzierung ihres CO2-Fußabdrucks erkennen, suchen sie umfangreichere und detailliertere Daten von ihren Lieferanten, Kunden und Partnern. Dieser Trend hat die Anzahl der Fragebögen, die zwischen Unternehmen in ihren jeweiligen Wertschöpfungsketten versendet werden, erhöht. Diese steigende Nachfrage nach Datenoffenlegung kann die Ressourcen der berichtenden Unternehmen belasten und die effektive Bewältigung der Arbeitsbelastung erschweren.  


  • Aufforderungen zur Offenlegung sensibler Daten: Da die Unternehmen aufgefordert werden, Daten zu melden, stehen sie auch vor der Herausforderung, wie viele und welche Art von Daten sie offenlegen können, ohne Informationen preiszugeben, die nicht offengelegt werden sollten, ohne dass ihnen dadurch ein Nachteil entsteht, z. B. durch die Preisgabe hochsensibler Wettbewerbsinformationen 


  • Zunehmende Komplexität durch den Übergang von historischen zu zukunftsorientierten Daten: Mit der Umsetzung der regulatorischen Anforderungen, wie sie in der Schweizer Verordnung über die Klimaberichterstattung (Klimareporting-Verordnung) für grosse Unternehmen und gemäss TCFD festgelegt sind, müssen Unternehmen auch mit zukunftsgerichteten Daten arbeiten, zum Beispiel in Bezug auf die Offenlegung von Expositionen gegenüber Übergangsrisiken oder sich entwickelnden physischen Risikobedingungen. Der Umgang mit solchen Daten ist komplexer als mit rückwärtsgerichteten historischen Daten.   


  • Unzureichende Datenmanagement-Tools: Viele Organisationen haben die Verwaltung von Nachhaltigkeitsdaten und die Berichterstattung mit einfachen Werkzeugen wie Excel oder ähnlichen Technologien in Angriff genommen, was ein erhebliches Risiko von Fehlern und anderen Konsequenzen mit sich bringt. 

Collecting and managing sustainability data poses significant challenges for companies. The required data is often not readily available because of inadequate digital infrastructure, and as a result, the data quality is rarely sufficient to pass an external validation.  

  • Lack of data and data fragmentation: Unavailable or scattered data pose significant challenges in Climate Reporting, as necessary data may not be tracked or readily available in a central system, making it difficult to obtain, especially for scope 3 emissions. Gathering the required data from various sources and coordinating with different departments and stakeholders can be time-consuming and resource intensive.  


  • Low data quality and persistent data inaccuracy: There needs to be more consistency regarding data tracking across various sources. This inconsistency can be attributed to several factors, such as the absence of data quality controls and, in general, the existence of weak data governance practices. This makes it challenging to maintain a high standard of data quality, and there is a risk of errors and inconsistencies creeping into the data collection process. Furthermore, although applying expert knowledge and adopting data proxies in the form of estimated values is encouraged at the initial stages of Climate Reporting to fill the gaps in data collection, it can further exacerbate the data quality issues if not replaced in the mid to-long term. 


  • Missing data traceability: As data is collected and aggregated across an organisation, it is subject to passing through various teams, data platforms and repositories and undergoes required transformations. For audit and reporting purposes, solid data lineage is in place to guarantee transparency in the end-to-end tracking of data sources and appropriate visibility over any modification that is applied to the source data before it makes its way into external disclosures. Insufficient data documentation: The entire data collection process should be documented, including assumptions, calculations, and modifications to the data. Accurate documentation takes not only time but also expertise and knowledge.  


  • Growing demands due to mandatory external data validation: The collected data and its documentation will be subject to an external validation as part of the soon mandatory Sustainability Reporting audit. As a result, there is increasing pressure to present a well-orchestrated complete picture which should guarantee the highest standards of accuracy.  


  • Increasing data requests: Another significant challenge facing companies is the increasing demand for data disclosures related to Scope 3 emissions. As more organisations recognise the importance of measuring and reducing their carbon footprint, they seek more extensive and detailed data from their suppliers, customers, and partners. This trend has increased the number of questionnaires sent across companies in their respective value chains. This growing demand for data disclosure can strain the resources of reporting companies, leading to difficulties in managing the workload effectively. Moreover, the need for standardisation in data request formats and data quality requirements can create further challenges for companies.  


  • Requests for revealing sensitive data: As companies are asked to report data, they also face the challenge of how much and what kind of data they can disclose without revealing information that should not be disclosed without it causing a disadvantage from, for example, revealing highly sensitive competitive information. 


  • Increasing complexity with a move from historic to forward-looking data: With the implementation of the regulatory requirements as outlined in the Swiss ordinance on Climate Reporting ordinance on mandatory climate disclosures for large companies and per TCFD, companies will also have to start working with forward looking data, for example concerning the disclosure of exposures to transition risks or to evolving physical risk conditions. Handling such data comes with more complexities than simpler, backwards-looking historical data.  


  • Inadequate data management tools: Many organisations approached sustainability data management and reporting with basic tools such as Excel or similar technologies, posing a significant risk of errors and other consequences. 

Collecting and managing sustainability data poses significant challenges for companies. The required data is often not readily available because of inadequate digital infrastructure, and as a result, the data quality is rarely sufficient to pass an external validation.  

  • Lack of data and data fragmentation: Unavailable or scattered data pose significant challenges in Climate Reporting, as necessary data may not be tracked or readily available in a central system, making it difficult to obtain, especially for scope 3 emissions. Gathering the required data from various sources and coordinating with different departments and stakeholders can be time-consuming and resource intensive.  


  • Low data quality and persistent data inaccuracy: There needs to be more consistency regarding data tracking across various sources. This inconsistency can be attributed to several factors, such as the absence of data quality controls and, in general, the existence of weak data governance practices. This makes it challenging to maintain a high standard of data quality, and there is a risk of errors and inconsistencies creeping into the data collection process. Furthermore, although applying expert knowledge and adopting data proxies in the form of estimated values is encouraged at the initial stages of Climate Reporting to fill the gaps in data collection, it can further exacerbate the data quality issues if not replaced in the mid to-long term. 


  • Missing data traceability: As data is collected and aggregated across an organisation, it is subject to passing through various teams, data platforms and repositories and undergoes required transformations. For audit and reporting purposes, solid data lineage is in place to guarantee transparency in the end-to-end tracking of data sources and appropriate visibility over any modification that is applied to the source data before it makes its way into external disclosures. Insufficient data documentation: The entire data collection process should be documented, including assumptions, calculations, and modifications to the data. Accurate documentation takes not only time but also expertise and knowledge.  


  • Growing demands due to mandatory external data validation: The collected data and its documentation will be subject to an external validation as part of the soon mandatory Sustainability Reporting audit. As a result, there is increasing pressure to present a well-orchestrated complete picture which should guarantee the highest standards of accuracy.  


  • Increasing data requests: Another significant challenge facing companies is the increasing demand for data disclosures related to Scope 3 emissions. As more organisations recognise the importance of measuring and reducing their carbon footprint, they seek more extensive and detailed data from their suppliers, customers, and partners. This trend has increased the number of questionnaires sent across companies in their respective value chains. This growing demand for data disclosure can strain the resources of reporting companies, leading to difficulties in managing the workload effectively. Moreover, the need for standardisation in data request formats and data quality requirements can create further challenges for companies.  


  • Requests for revealing sensitive data: As companies are asked to report data, they also face the challenge of how much and what kind of data they can disclose without revealing information that should not be disclosed without it causing a disadvantage from, for example, revealing highly sensitive competitive information. 


  • Increasing complexity with a move from historic to forward-looking data: With the implementation of the regulatory requirements as outlined in the Swiss ordinance on Climate Reporting ordinance on mandatory climate disclosures for large companies and per TCFD, companies will also have to start working with forward looking data, for example concerning the disclosure of exposures to transition risks or to evolving physical risk conditions. Handling such data comes with more complexities than simpler, backwards-looking historical data.  


  • Inadequate data management tools: Many organisations approached sustainability data management and reporting with basic tools such as Excel or similar technologies, posing a significant risk of errors and other consequences. 

Deep Dive - Konsequenzen der Verwendung von Excel und anderen einfachen Datenmanagement-Tools für die Nachhaltigkeitsberichterstattung:  

Da es sich bei den für die Klimaberichterstattung erforderlichen Daten oft um komplexe und vielfältige Datensätze mit mehreren Variablen handelt, kann die manuelle Pflege von Excel zu Fehlern bei der Dateneingabe, -verarbeitung und -analyse führen. Diese Fehler können die Genauigkeit und Verlässlichkeit von Nachhaltigkeitsberichten untermauern und möglicherweise zu Reputationsschäden für Unternehmen führen (z. B. "unbeabsichtigtes" Greenwashing durch ungenaue Angaben).  

 
Eine weitere typische Herausforderung bei der Verwendung unzureichender digitaler Lösungen ist die Verwaltung, Pflege und Analyse großer Datenmengen. Je größer und komplexer die Nachhaltigkeitsdaten werden, desto schwieriger wird es, die Daten effizient zu verarbeiten und zu analysieren. Lange Verarbeitungszeiten und Fehler sind oft die Folge, was die Erstellung zeitnaher und genauer Berichte erschwert. Außerdem kann die Verwendung von Tools wie Excel zur Verwaltung von Nachhaltigkeitsdaten zu einem Mangel an Transparenz und Verantwortlichkeit führen. Wenn mehrere Benutzer auf Arbeitsblätter zugreifen und diese aktualisieren, wird es schwierig - wenn nicht gar unmöglich -, Änderungen nachzuvollziehen, angemessene Kontrollen durchzuführen, die Datenqualität zu überwachen und Konsistenz zu gewährleisten.

Daten zur Klimaberichterstattung - lohnende Maßnahmen und Chancen 

Die neuen Nachhaltigkeits- und Klimavorschriften ermöglichen es Unternehmen, die Transparenz zu erhöhen, ihren Ruf zu stärken und Investoren anzuziehen, indem sie ihr Engagement für Nachhaltigkeit zeigen. Eine effektive Datenverwaltung ermöglicht es Unternehmen, Bereiche zur Verbesserung zu identifizieren, ihre Leistung in Bezug auf Nachhaltigkeit den Stakeholdern zu demonstrieren, Kosten einzusparen und Innovationen voranzutreiben. 

Investieren Sie in digitale Datensammlungs- und -verwaltungstechnologien:

Unternehmen sollten digitale Lösungen übernehmen, um die Datensammlung, -verwaltung und -analyse in Bezug auf Nachhaltigkeit zu automatisieren und zu optimieren.

Chancen: Verbessern Sie die Genauigkeit und Effizienz der Datensammlung, reduzieren Sie das Potenzial für Fehler und sparen Sie Zeit und Ressourcen. Digitale Technologien können die Datensammlung aus verschiedenen Quellen, einschließlich Lieferanten, Kunden und Stakeholdern, automatisieren, was Unternehmen dabei helfen kann, umfassendere und zuverlässigere Daten für die Nachhaltigkeitsberichterstattung zu erhalten. Darüber hinaus unterstützen sie Unternehmen bei der Verwaltung und Analyse großer Mengen an Nachhaltigkeitsdaten, was es ihnen ermöglicht, Trends und Muster zu identifizieren, wertvolle Einblicke in ihre Nachhaltigkeitsleistung zu gewinnen und ihren Fortschritt zu verfolgen. 

Etablieren Sie einen klaren Prozess zur Datensammlung:

Unternehmen sollten transparente Prozesse zur Datensammlung einführen, die darin bestehen, einen systematischen und konsistenten Ansatz zur Datensammlung, -verwaltung und -berichterstattung in Bezug auf Nachhaltigkeit zu etablieren. 

Chancen: Mit soliden Datensammlungspraktiken und effektiven Kontrollen, die zu einer verbesserten Datenqualität führen, besteht die Möglichkeit, interne und externe Prüfungsbemühungen und -kosten zu reduzieren und die allgemeine Exposition gegenüber Risiken von Greenwashing-Vorwürfen zu verringern. 

Zusammenarbeit mit Stakeholdern:

Die Zusammenarbeit mit Lieferanten, Kunden und anderen Stakeholdern zur Verbesserung der Datensammlung ist eine ausgezeichnete Möglichkeit für Unternehmen, ihr Engagement für Nachhaltigkeit zu zeigen und ihre Risiken besser zu managen. Unternehmen müssen jedoch transparent sein, welche Daten sie bereit sind zu teilen. Wenn Unternehmen Bedenken haben, sensible Daten zu teilen, können sie aggregierte Daten bereitstellen oder Stakeholder auf verfügbare Daten in Form von bereits veröffentlichten Berichtsstandards verweisen. Mit dieser Herangehensweise können Unternehmen Datenschutzbedenken und die Notwendigkeit, Transparenz in der Klimaberichterstattung zu gewährleisten, ausbalancieren. 

Chancen: Die Zusammenarbeit mit Stakeholdern in Bezug auf die Klimaberichterstattung kann dazu beitragen, Vertrauen aufzubauen und ein gemeinsames Verständnis zu etablieren, was zu einer erhöhten Stakeholder-Beteiligung und -Unterstützung führen kann.

Einstellung von spezialisierten Mitarbeitern:

Insbesondere größere Unternehmen sollten Mitarbeiter mit technischen Datenanalysefähigkeiten und Fachwissen einstellen, um eine im Allgemeinen datenzentrierte Strategie umzusetzen. 

Chancen: Durch den Einsatz fortschrittlicher Datenanalyse- und Modellierungstechniken können Unternehmen nicht nur über das jährliche Klimaberichterstattungsverfahren hinausgehen, sondern auch tiefere Einblicke in ihre Nachhaltigkeitsleistung gewinnen, Bereiche zur Verbesserung identifizieren und letztendlich die Art und Weise steuern, wie sie ihr Geschäft im Hinblick auf die von ihnen festgelegten Nachhaltigkeitsziele führen, die sie in der jährlichen Klimaberichterstattung festlegen. Schließlich ist die Entwicklung der erforderlichen Fähigkeiten, um die Auswirkungen der zukunftsorientierten Analyse und Szenarioanalyse in Bezug auf den Klimawandel zu verstehen, entscheidend für die Stärkung der Widerstandsfähigkeit eines Unternehmens.

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