How Forward-Thinking Sustainability Management Software Vendors Onboard Customer Data More Efficiently

 Michael Zittermann
Michael Zittermann
Co-Founder & CEO
Published:
July 12, 2024
Updated:
December 2, 2024
How to Streamline Data Onboarding in Sustainability Management

Sustainability management software vendors are likely to become extremely busy. With new regulations coming up in the European Union (EU), four times more companies are now required to report on sustainability.

The Corporate Sustainability Reporting Directive (CSRD) offers great opportunities for sustainability software vendors to acquire new clients. However, this surge in demand also comes with a new set of challenges.

Signing on more new clients typically means managing a larger workload of onboarding client data. New clients often introduce data in various formats and structures, so teams are steadily challenged to restructure, validate, and clean the data before importing it into their systems.

The good news is that with the right data onboarding technology, ESG companies can effectively meet the increasing demand and become reliable partners in promoting sustainable practices across a growing market. Find out how in this guide.

Challenges in data onboarding

Accurate tracking and reporting are crucial for successful sustainability management. To support companies in this effort, software vendors must stay alert to potential challenges with onboarding client data.

From diverse data types and inconsistency to limited scalability and security concerns, these issues become even more critical with the new CSRD rules requiring more detailed and transparent environmental reporting.

Let's delve deeper into why data onboarding can be complex for sustainability software vendors.

Data diversity

Sustainability software providers must deal with different types of data, ranging from energy consumption and supply chain data to business travel information. The fact that every company has its own way of presenting this information adds another layer of complexity.

These datasets are often large and come in formats that aren't always compatible with ESG software. They can range from simple CSV and XLSX spreadsheets to more complex XML and JSON files. The wide variety and intricate structures of data, especially when exported from ERP systems, might mean that users need to either format their data to fit a specific template or deal with errors during the data import process.

Data inconsistency

Data errors can cause a company's emissions calculations to be incorrect, negatively impacting its sustainability record. Dealing with different number formats often causes headaches for companies that need to consolidate data from multiple sources. This includes challenges with date formats (for example, dd-mm-yyyy versus mm-dd-yyyy) and detecting thousand and decimal separators (such as 1.234,56 in the EU format versus 1,234.56 in the US format).

Moreover, inconsistencies in CSV column delimiters or separators for mapping multiple options add extra complexity for ESG companies trying to understand the data they receive.  Even a seemingly minor error, such as misspelling in a category name, can lead to significant issues if not identified and corrected right away.

If data isn't validated and cleaned before being entered into the system, it can be challenging for teams to make data-driven decisions.

Integration challenges

Integrating seamlessly with existing client systems for automated data collection can be both time-consuming and costly.

The vast variety of data sources (e.g. different ERP, travel management, logistics, procurement systems) often exceeds a company's capacity to develop native integrations for each system. Moreover, it's not uncommon that data is initially managed in spreadsheets before moving to a more sophisticated solution.

All these factors highlight the importance of a product's ability to effortlessly ingest diverse data and ensure smooth data flows.

Limited scalability

Manually managing large volumes of data across multiple departments is hardly sustainable. The need to manually reformat or restructure data, or develop custom scripts for data import requires significant human power, making it slow and expensive to scale.

Security and compliance concerns

In today’s global business landscape, ensuring data security and regulatory compliance plays a key role. When importing sensitive data, it's essential to prioritize security within your data onboarding process. Failure to safeguard this data can lead to violations of data privacy regulations, such as GDPR, and harm your reputation. 

AI-powered data importer: A game-changer in sustainability management

The issues outlined above highlight the potential for companies to efficiently onboard client data. By integrating innovative, AI-powered technology into your digital ecosystem, you can seamlessly import messy client data into your software—whether managed by the internal customer onboarding team or directly by your clients themselves.

German-based nuvo brings innovation with its AI-powered data importer designed to simplify the data import process from the ground up. Let’s explore how nuvo can support ESG companies in enabling their customers to excel in sustainability management with AI-powered data onboarding.

nuvo's Data Importer SDK can automatically validate and clean data against your own database and third-party services like Google Maps

Handle diverse data files and structures

Advanced data importers utilize AI algorithms to deal with various data structures. These can accurately handle varying data sets, regardless of whether the data is arranged in matrices or spread over multiple sheets.

These capabilities allow sustainability software providers to significantly reduce manual labor and not worry about new clients introducing unfamiliar data formats and structures. An advanced, AI-powered importer can cater to all use cases. 

Greater scalability

Automating the reformatting, restructuring, and validation of data—either against your database or third-party services—saves considerable human hours. This approach enables companies to onboard data in a scalable way.

Improved data quality 

nuvo can improve data quality through automated validation, cleaning, and enrichment processes. By identifying inconsistencies, missing information, and outliers in the data, it ensures that the inputs into sustainability management systems are accurate and reliable.

Empowering customer self-service

Relying on internal teams for data imports can create bottlenecks and keep the customer waiting. Instead, you can rely on a SaaS tool that can easily fit within your tech stack, equipped with advanced mapping, validation, and cleansing capabilities.

nuvo has an intuitive, self-service interface that allows even non-technical customers to easily import data at their convenience—reducing the need for internal support and putting the power of handling data in the hands of the users themselves. This not only boosts efficiency but also allows your team to allocate resources to more impactful tasks.

Gain a competitive advantage with nuvo 

With the wide variety and increasing volume of data, alongside a growing client base, it's clear that manual data import methods lack scalability and can hardly meet the increased demand for data importing in sustainability management.

By leveraging nuvo’s Data Importer SDK, you can harness the power of AI to automate the onboarding process for diverse datasets, ensuring seamless integration and improved data quality. Get in touch with our team and challenge us with the messiest data you’ve ever received from your clients.

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