Are Your Data Models Ready for ESG Reporting?
Most Probably They Are Not...
When all is said and done, ESG topics are Data Topics. Companies face a very challenging task with the new EU regulations for ESG Reporting (Environmental, Social, and Governance). This is especially true since the regulations focus not only on the companies' own ESG factors but also on the whole value chain.
For example, if a company sells a T-shirt, all ESG factors from the cotton field to the customers’ wardrobe shall be considered. This is not an easy task, and the basis for the reports is, as mentioned, data. A LOT of data. For correct and complete ESG reporting, companies must gather large volumes of data from various sources, including internal systems, suppliers, and external databases, and ensure it is accurate, reliable, and consistent. This becomes even more challenging with different data formats and uncertainty about the quality of the data delivered by suppliers and other actors. Several players on the market provide fancy dashboards for companies to use for reporting. Still, a dashboard without data is not useful at all. Even if you have the data, you must structure and analyze it correctly, which is very time-consuming without the correct tooling.
As a senior business consultant with experience in leading operations and IT departments in large international companies, Claes Larsson is an expert in data management, data modeling and operational excellence. He strongly believes that data and data management processes are key to successful and smooth operational and reporting processes and has a keen interest in ESG issues, including diversity and inclusion.
ESG Challenges in the Fashion Industry
Fashion is one of the worst business areas regarding ESG, both in terms of human rights, work conditions, and pollution. Fashion stands for more CO2 emissions than all air and sea freight combined. So, let’s look at the process of creating a cotton T-shirt until it reaches the customer.
1. Planting:
- Cotton is planted with the help of tractors and other tools.
- Water and pesticides are used.
2. Harvesting:
- Mechanical harvesters collect cotton bolls from the fields.
- Transport: Tractor or specialized cotton harvesters.
3. Ginning:
- Cotton fibers are separated from seeds.
- Transport: Trucks or containers to move cotton to the gin.
4. Fiber Bales:
- Compressed cotton fibers are bundled into bales.
- Transport: Large trucks or freight trains.
5. Spinning and Weaving/Knitting:
- Cotton yarn is spun into fabric.
- Transport: Cotton yarn is transported to textile mills.
6. Dyeing and Wet Processing:
- Fabric is dyed and treated.
- Transport: Fabric rolls moved within the textile factory.
7. Cutting and Sewing:
- Fabric pieces are cut and stitched into T-shirts.
- Transport: T-shirt blanks moved within the garment factory.
8. Screen Printing and Customization:
- T-shirts are customized with designs.
- Transport: T-shirts transported to screen-printing facilities.
9. Distribution to Retailers:
- Finished T-shirts are packaged and shipped to retailers.
- Transport: Trucks, cargo ships, or air freight.
10. Retail Stores and Online Shops:
- Customers purchase T-shirts from stores or online platforms.
- Transport: Customers take T-shirts home!
All these steps in the process come under the ESG regulations, and different parties are involved. This means even the ESG aspects of the work on the farm, water consummation, emissions, labor situations, etc., shall be considered when companies are obliged to report on ESG.
The amount of collected data and different standards quickly become impossible to overview manually.
Take a Closer Look at How ESG Reporting Works With MDM
With modern and efficient MDM platforms, a lot of the work can be facilitated and even automated, and three essential factors can help here:
- A Data Catalogue that keeps track of where the data originates from.
- Data lineage tracks how data changes over time and by what action and actor.
- AI and Machine Learning to automate as much of the data handling as possible.
The problem of collecting the data and determining its accuracy is still present. Still, blockchain technology can facilitate parts of this tedious work. For example, companies can track the origin of raw materials, labor practices, and environmental impact, and with Immutable records on the blockchain, auditors and stakeholders can verify claims made in ESG reports.
MDM also offers other advantages in the process, such as:
- Centralized Data Governance: MDM creates a centralized repository for all master data elements related to ESG reporting. This ensures data consistency, accuracy, and integrity. By implementing robust data governance policies and procedures, organizations can maintain control over their data assets and mitigate the risk of errors and inconsistencies.
- Data Quality Management: MDM enables companies to implement rigorous data quality controls to identify and manage inaccuracies, duplicates, and discrepancies in their ESG data. By standardizing data formats, validating data inputs, and cleansing data records, organizations can enhance the reliability and trustworthiness of their ESG disclosures.
- Data Integration and Aggregation: MDM facilitates seamless integration and aggregation of ESG data from various sources, including internal systems, third-party databases, and regulatory filings. By consolidating data across the organization, companies can gain a holistic view of their ESG performance and generate comprehensive reports that comply with regulatory requirements.
- Stakeholder Engagement: MDM empowers organizations to engage stakeholders proactively by providing timely and accurate ESG information. By leveraging MDM capabilities such as data visualization and reporting tools, companies can effectively communicate their sustainability initiatives, track progress against targets, and respond to stakeholder inquiries.
- Scalability and Flexibility: MDM solutions are highly scalable and adaptable, allowing companies to accommodate ever-changing regulatory requirements and business needs. Whether expanding ESG reporting scope, incorporating new data sources, or supporting international compliance standards, MDM provides the flexibility to scale operations seamlessly.
Since we are examining many aspects of the processes when manufacturing, transporting, and delivering products, we cannot be satisfied with just looking at the product data itself, primarily since ESG comprises much more than “just” emissions of CO2 and other greenhouse gases.
This means we cannot use an ordinary PIM system for this, and we need to include more data domains such as...
- Suppliers
- Sub Suppliers
- Means of Transport
- Production Facilities
- Storage Locations
- Machinery
- Service Providers
- Consumables
- Service Cycles
- Customers
- Customer Locations
- Stores
- Store Locations
- Energy Consumption
- Etc., etc., etc.
Hence, we need a Multi-domain Master Data Management Platform to solve this gigantic puzzle of Data Points. Multi-domain MDM manages all the different types of master data in one place, bringing the multiple data domains and processes associated with each into a centralized platform.
How Parsionate Can Support Your ESG Reporting Needs
Unfortunately, we often see that ESG topics are assigned to companies' financial departments, and this is frankly not the best idea. This is because ESG reporting handles data for various data points and has very little to do with pure financial data. Instead, the people responsible for Master Data Management in the company should be involved with the resources accountable for Compliance, Sustainability, and Business Ethics.
Most companies already have PIM systems capable of handling most parts of the product-related ESG topics. If your company has been foresighted enough to use a good Multi-Domain MDM Platform, you would be able to also handle all other aspects, such as suppliers, blacklisted companies, transport options, machinery, factories, warehousing, etc., etc.
We at Parsionate are experts in data management, data modeling, and processes surrounding data flows, integrations, data strategy, and data governance, among other things.
We know that the current Data Models for Products and Suppliers often lack the capabilities to handle ESG topics, and we also know how these capabilities need to be implemented.
As Gartner describes in the image below, several other parts of correct and efficient ESG reporting must be in place. We can assist you with almost all of them.
To a large degree, the correct implementation of any Multi Domain Data Model comes down to a certain mindset, where you holistically look at all the different domains and how they relate to each other. Usually, the product or the offering is seen as a centerpiece of the Data Model, and one example could, from a high-level viewpoint, look like this, where all domains would need various attributes for correct and complete ESG Reporting. In the image below, the domains where we see a clear need for ESG-related data to be stored are marked with bold text.
As you can see, many different data domains come into play if you want to do complete and correct ESG reporting. Parsionate’s knowledge in data modeling, our holistic viewpoint regarding data, and how different data domains relate to each other give a good foundation for setting up your new data models, integrations, and even the MDM solution itself.
So, what are you waiting for? Contact us and let us help you become ESG compliant!
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