Data Governance for Sustainability in the Manufacturing Industry

In this article, we explore a responsible and environmentally conscious approach to data governance in the manufacturing industry. Learn how to implement sustainability in your data governance strategy.

In a world of analytics where industrial information is considered an asset, manufacturers are beginning to take data seriously. Furthermore, faced with increasing costs in energy and materials, compliance requirements and ever-changing demands from customers, investors and local communities, organizations are seeking to manage operations in a way that is both environmentally and socially responsible.

According to a study carried out by AspenTech in 2020, 78% of the companies surveyed see CO2 reduction as a competitive advantage. This approach, known as “sustainable manufacturing,” relies on huge amounts of data which needs to be managed under a solid data governance strategy.

Data governance and Data Management

The term “data governance” refers to the policies, roles and procedures required when handling data. Its aim is to ensure companies understand the value of data, comply with regulations, and get the most from their data. “Data management” on the other hand relates to the implementation of this governance and covers collecting, storing, organizing, and maintaining data. Getting both governance and management right enables you to have accurate, compliant, and trustworthy data.

Environmental, Social and Governance goals

Data for sustainability in manufacturing concerns the entire supply chain and can include for example data on raw materials such as wood from replanted forests, fair pay for workers on coffee farms, proof that you are not employing children in the fashion industry or data covering gender diversity on management boards. Such information not only contributes to a manufacturer’s brand image but also has major financial implications as many investors consider Environmental, Social and Governance (ESG) goals as key to their investments.

The Circular Economy

While many companies claim to be sustainable, others are working in a more “circular” way. The circular economy is an economic model based on the three Rs: Reduce, Reuse and Recycle. It’s all about retaining a product’s lifespan and aims to maintain value as opposed to creating waste. This requires you to list all the materials contained in a product which then gives you a circularity score.

For example, a pack of printing paper could be awarded a score together with the paper used for its packaging, giving you an overall circularity score for the product. The fact that the paper is recycled or not, or whether the packaging contains cardboard would affect the overall result. Other products could be assessed based on their level of plastic or pesticides. All these metrics help manufacturers assess projects on their circularity and enable them to decide whether a product can go back into the supply chain instead of ending up on a landfill site.

A more Responsible World

The younger generation and their fight against climate change, together with the rise of the “WOKE” movement, seeking racial and social justice, is starting to have an impact on how manufacturers approach their business.

Furthermore, Corporate Social Responsibility (CSR) policies now mean manufacturers are facing regulations such as FSC certification that ensures manufacturers are using products that comes from responsibly managed forests, or the UTZ label, for sustainable farming, that applies to coffee, tea and chocolate manufacturers.

The Role of Tech in Data for Sustainability 

Technology has a support role to play in data governance. This means it is important to choose the right solutions to manage how processes and policies around data are set up.

In addition to Product Information Management (PIM) or Master Data Management (MDM) solutions, that can store your information, there are data governance applications available on the market such as:

  • Alation - that positions itself as being able to provide organizations with data that is trusted, compliant, secure and fit for analysis.
  • Informatica – with their Intelligent Data Management CloudTM, they can manage data of any type across any location on a single platform.
  • Ataccama - a Gartner Magic Quadrant Leader for data quality solutions.
  • Collibra – that offers a single system of engagement for data with their Data Intelligence Cloud solution.

The Business Benefits of Data Governance

When thinking about data governance it is important to remember that it’s much bigger than just complying to legislation such as the General Data Protection Regulation (GDPR). It should be seen as part of your day-to-day business operations as it can bring your organization the following benefits:


Data governance allows your organization to ensure the right processes, roles and policies are in place and helps you get the most of your data. It also clarifies what you mean by “data”. For example, if you ask your Sales department what a “customer” is, they will most likely say that it is someone you sell a product to. However, the Marketing team may say a customer is someone who visits the company website. A data governance strategy enables you to avoid such confusion and ensures everyone is on the same page. This means when data reports are made, all parties know what is being reported.


Handling data the right way enables you to bring structure to your organization, and this leads to efficiency, allowing your employees to work better and faster, and to become more data focused. Once you have all your data in order, the different departments within your company can benefit from this. For example, Procurement can purchase from suppliers that score high on sustainability. Marketing can be more transparent towards customers and potential customers. Research and Development can make more circular choices. And at the end of the day all of this will contribute to boosting your sales.


Data governance gives manufacturers the tools to make data handling, management, and storage risk-free and to create an organizational culture that places a high priority on security. It also means your organization can avoid mistakes, leaks, or non-compliance with legal obligations. Furthermore, a comprehensive data governance strategy will allow you to decide who should handle your data internally and create safe methods for managing all of your sensitive data.

Best Practices for building a Data Governance Strategy

A data governance strategy will enable you to understand where you are going with your data, how you should manage it and what the value of that data represents to your organization. It will enable you to determine where you want to be in five years’ time and to establish whether you need more data, better data or better data reports. Basically, it will enable you to decide to what extend you wish your company to become data-driven.

Before putting your data governance strategy into place, it is important to remember that this is not an IT project. It is a company-wide initiative. Therefore it is critical to get people from all the different parts of your organization involved. It is particularly important to have C-level buy-in to ensure things will get done and employees are engaged.

Start small, because if you dive in headfirst you may get lost very quickly. Begin with for example sustainability data on products and focus on things such as the materials used to make them and any certifications. Then move on to suppliers and the data related to the sustainability of their value chain. Afterwards concentrate on customer and the employee data. Working on one set of data at a time will enable you to build and structure the information and develop governance around that category.

Finally, make sure you get the right advice when it comes to choosing data governance software and learn how to assign councils, sponsors and stewards to drive the project throughout your organization.

If you would like your manufacturing business to stay ahead of the competition, then it makes sense to build a solid data governance strategy. When done well, data governance for sustainability in manufacturing helps you increase time to market, boost productivity and enhance customer satisfaction, opening up  opportunities across your entire supply chain.

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