Following on our previous blog’s introduction to the complexities of the Corporate Sustainability Reporting Directive (CSRD) and the challenges and opportunities it presents, we will now turn to exploring the practical implications of getting “CSRD ready” and some of the critical steps towards future compliance.
Setting up a framework for the discussion that follows, in general there are two paths organizations can take:
- Dive headfirst into the use of a reporting tool.
- Build the approach from scratch either independently or with a partner. This second path leans on data scientists and a platform such as Dataiku.
Whichever path is taken, there is a shared foundational requirement: data preparedness.
This blog post will ultimately share how the end-to-end Dataiku platform can help you and your teams streamline the building process without compromising explainability, quality, or auditability. I’ll explain why and how Dataiku can help your analytics and IT teams better collaborate with lines of business to access, prepare, and aggregate in addition to model, analyze, and monitor results.
How — and Why — Is Dataiku Positioning Itself in the Reporting Space?
To Be Useful, Data Needs to Be Prepared & Complete
Whether organizations are just starting their CSRD compliance journey or are well on their way, data preparedness, aggregation, completeness, and pipelines are foundational. Fundamentally, the CSDR exercise hinges on the transparent, explainable achievement of the aforementioned data activities at scale. This is not straightforward: In practice, CSRD compliance often involves disparate data strewn across organizational silos, where stakeholders have limited experience collaborating and different levels of data skill sets.
What’s more, today it is often the case that stakeholders rely on spreadsheets with different data structures, maintenance schedules, and ownership, which introduces additional challenges to meeting goals around foundational data preparedness.
The Challenge of Going Straight to SaaS Reporting Tools
Sustainability teams often turn to Software-as-a-Service (SaaS) reporting platforms to help them with CSRD compliance. These are designed to provide valuable prepackaged resources to support reporting journeys such as ready-made reporting blueprints, emission factor libraries, and benchmarks like rates of decarbonization by subsector, for example.
However, without clean data pipelines, their efficacy will be limited. Indeed, these are most useful when an organization already has access to a pool of comprehensive, ready-to-use data (whether it is internal, external, or some combination).
CSRD Is a Deliberate and Collaborative Effort
Plugging previously siloed data directly into a reporting SaaS platform might also side-step an opportunity implied by the CSRD’s scope: Namely, to infuse sustainability data into a line of business’s operational data in such a way that it be considered on par with their conventional data. Practically, CSRD leads may eventually access data without meaningfully engaging with its source’s owners who might therefore retain his business-as-usual perspective.
Fundamentally, this dynamic challenges the CSRD’s aim of integrating sustainability across lines of businesses’ remits by disincentivizing conversations about data access, decarbonization objective-setting, and execution between sustainability teams, analytics teams, and subject matter experts. Arguably, this collaboration is critical to identifying and implementing meaningful opportunities to address socio-environmental impacts and meeting identified targets.
Setting CSRD Data Foundations With Dataiku
Whatever path is taken — whether a SaaS tool is used or an organization builds out its own approach — Dataiku can help to set data foundations given our expertise across the entire end-to-end analytics and AI lifecycle, from data connectivity to model monitoring.
The Journey to Data-Driven Reporting
Where and how does one broach the task of building European Sustainability Reporting Standards (ESRS) data points? We understand the journey to data-driven reporting as being composed of six steps represented in the above arborescence.
In forthcoming blogs, we will introduce steps 3 to 6 of our approach while today, we’ll focus on data preparation considerations relevant to CSRD compliance efforts — whether you’re using a SaaS tool or building out your own approach.
1. Centralize Your Data in an ESG Foundation
We assume a compliance or sustainability lead is tasked with ensuring that CSRD data points defined by the ESRS are built adequately and promptly. This usually implies working alongside analytics teams to access necessary data strewn across the organization’s information systems — before working on its transformation. Relevant data could be distributed in spreadsheets that extract from a company’s data warehouse, its Enterprise Resource Plan (i.e., supply chain data), the Warehouse or Transport Management System (i.e., raw materials or distribution/logistics data), be it alternative or external data (i.e,. climate risk data, suppliers’ sustainability reports). Problematically, accessing this data can be a headache for IT in terms of ad hoc permissioning, connection building, and legacy system maintenance.
Instead, we recommend overcoming this by turning the pain into an opportunity to consolidate a sustainability data lake: an ESG data foundation. Relieve IT’s team burden by centralizing your data with Dataiku’s architectural extensibility to a wide range of cloud, lake, and proprietary storage infrastructure systems. Next, leverage the Dataiku data catalog and data tags to organize assembled data via the lens of your choice — from sustainability thematics to ESRS subcategories for facilitated eXtensible Business Reporting Language (XBRL) tagging.
2. Streamline Data Preparation, Aggregation, & Consolidation
By centralizing company-wide data in a single, accessible, and easily maintained source, raw data can be collected, parsed, and prepared to output a disaggregated pool of golden-copy data available for replication and reuse by permitted profiles. Here, Dataiku’s ability to industrialize data standardization, ETL, and EDA with explainable, visual pipelines and pre-built statistical cards can optimize analytics teams’ efficiency. To learn more about Dataiku’s ability to support data centralization, organization, and analytics, refer to Novartis’ experience streamlining their corporate analytics with Dataiku to prime data-driven decision-making.
Another key challenge when building ESRS data points involves transforming data to expected output, or building reliable, relevant proxies from available data when pre-existing data is insufficient. Be it a full- or low-code user working with structured or unstructured data, Dataiku’s GenAI-powered assistant AI Prepare is sure to boost performance by empowering users with greater autonomy and freeing them from more mundane tasks to focus on more technical procedures.
Let’s Recap
This article explained that regardless of one’s approach to CSRD compliance, the data preparation step is paramount be it as an end in itself — by amounting to reliable results, and a means to end — by enabling meaningful collaboration between sustainability and lines of businesses. To these ends, we shared Dataiku’s recommended ESG data foundation approach that primes for explainability, scalability, and time efficiency.
Next time, we will walk through how Dataiku can help organizations leverage their ESG data foundation to forecast the evolution of doubly material impacts, perform scenario analysis to test their transition plan’s validity, facilitate data quality monitoring throughout their processes, and generate narrative responses to certain ESRS data points.