Toimitusketjun kestävyys tarkoittaa yrityksen toimitusketjun vaikutusta ihmisoikeuksien edistämiseen, reiluihin työoloihin, ympäristöystävällisiin käytäntöihin ja korruption vastaiseen toimintaan. Tarve kestävien valintojen integroimiseksi toimitusketjun hallintaan kasvaa jatkuvasti.
Vuonna 2024 voimaan tuleva Corporate Sustainability Reporting Directive (CSRD) laajentaa nykyisiä ei-taloudellista raportointia koskevia sääntöjä ja edellyttää standardoidun kestävyysraportin julkaisemista. Vuosikertomusten tulee jatkossa sisältää myös tietoa yrityksen toiminnan vaikutuksista kestävyyteen.
Raportointivaatimusten täyttämiseksi yritysten on hankittava kattavia kestävyyttä koskevia tietoja toimitusketjustaan. Tämä korostaa kokonaisvaltaisen toimitusketjun kestävyyden arvioinnin merkitystä – ei vain raportoinnin vuoksi, vaan myös yrityksen pitkän aikavälin vastuullisuuden ja maineen vahvistamiseksi.
End-to-end supply chain sustainability is a concept that involves the entire supply chain, from raw material to own production or service. It focuses on the environmental, social, and economic aspects of sustainability in order to create a holistic approach to green business practices.
Organizations that rely on multiple suppliers and lengthy supply chains as a part of their core business face some of the biggest barriers to achieving true sustainability. This is because of uncertainty how to accurately measure a supplier’s sustainability, and because it’s challenging to look all the way down the supply chain to assess the sustainability of even second- and even third-tier suppliers.
The new standards and requirements emphasize the construction of a sustainable supply and value chain, and it is a priority for many responsible companies. Responsible companies realize that managing and improving environmental, social and financial performance throughout their supply chain helps save resources, optimize processes and potentially discover new product innovations. Increased productivity promotes the profitability of companies and responds to the growing number of stakeholders who demand more responsible supply chains.
As operations evolve towards more sustainable processes and values throughout the supply chain, companies struggle with the implementation of new processes and requirements. There are several practical steps to creating and maintaining a sustainable supply chain. It is increasingly clear that supply chains play a crucial role in our efforts to create more responsible and sustainable value chains for companies, but how do we do this in practice and create a responsible supply chain management system?
Value Creation Model (VCM) is a system model, technically a causal loop diagram, which shows how value is created. To avoid vanity metrics, you need to identify your goals first and relate your metrics to them. Model to help its clients to recognize the abstract and too often non-visible Value Paths, which effect their business’ ability to create value and impact sustainability.
The Value Creation Model shows how each phase in the process creates value or imposes a risk for losing value. All nodes in the model are candidates for metrics.
The causality chains can be used for identifying the leading indicators that have a positive or negative impact on your goals. Value Creation Model makes visible the interdependencies of different Value Paths within an organization. For instance, it shows how customer experience Value Path has effects to sales, brand image, churn and the amount of orders. Value Paths make abstract measurable and thus make it possible for organizations to improve their sustainability metrics.
The actual metrics are defined for the nodes Value Creation Model. A normalized index value (0 – 100 – 200) is calculated for each metric. 100 represents the intended target level, zero the bottom value and 200 the maximum. This allows aggregation and averaging different kinds of metrics.
The value of a parent metric can be represented by its index value which in turn can be calculated by averaging the calculated index values of its child metrics such as test pass rate or the number of critical defects.
It is possible to leverage Machine Learning for predictions and e.g. for trend analysis and anomaly detection on a Value Path of the Value Creation Model.
Value Paths are an invaluable visual tool for all members across the organization in recognising their position as part of the whole and their personal effects within the organisation and to the entire business.
Blue arrows in the picture denote positive (assumed) causality, so for instance when Velocity increases, so does the Flow of value. Respectively, a red arrow means that the variables move to the opposite direction.
Value Paths provide leading indicators for proactive corrective actions.
The concept of Value Path allows focusing on the most important causality chains in the model to address specific business issues.
It is easy to see from the two value paths what the leading indicators and assumed causalities are.
The picture above shows a simple, early draft example exploring the benefits and the overall value creation logic of a Customer Relationship Management (CRM) system. This text book example reflects the real-world experience well: often the benefits – value – is created ‘outside’ the actual IT system as a positive impact to business processes. A portfolio level Value Creation Model™ may have some hundreds of nodes. Each node in the model is a potential metric and a leading indicator for the key goals of the organization. Thus, Value Creation Model™ also gives us the metrics we need to measure and lead the realization of the expected benefits.
As organizations navigate the complexities of ESG reporting, one of the key challenges lies in the seamless collection and integration of relevant data. In this chapter, we will delve into the three principles that can significantly ease the process: strongly automated collection of data, simple and efficient data collection workflows, and API integrations into existing software systems.
In the quest for comprehensive ESG reporting, the first principle to embrace is the strongly automated collection of data. Automation plays a pivotal role in ensuring accuracy, timeliness, and completeness of the information gathered. By implementing sophisticated data collection tools and technologies, companies can reduce the burden on manual efforts, minimize errors, and enhance the reliability of their ESG data.
Key Strategies:
The second principle focuses on creating simple and efficient data collection workflows. Complex and convoluted processes can hinder the willingness of stakeholders to actively participate in data submission. Therefore, it is crucial to design streamlined workflows that are user-friendly and aligned with the unique requirements of ESG reporting.
Best Practices:
The third principle centers around the seamless integration of ESG data into existing software systems through Application Programming Interfaces (APIs). This integration not only enhances the overall efficiency of data management but also facilitates the incorporation of ESG metrics into broader business strategies.
By applying these principles, organizations can simplify the ESG reporting process, improve data accuracy, and align sustainability efforts with broader business strategies
Integration Strategies:
