Clear data ownership paves the way for data-driven manufacturing

Businesses across industries generate and use large amounts of data to make strategic insights-led decisions and improve their operations. Within manufacturing, data is produced at every stage of the production process—from design and prototyping to production and quality control. However, the question of who owns this data can be complex, and it's becoming increasingly important for businesses to understand their rights and responsibilities of data ownership.

The million-dollar question: Who owns the data?

Within a manufacturing organization, multiple people across various departments have access to data and can interpret, use, edit and source it. When embarking on a journey of better data management, including designing a data strategy, one of the first questions manufacturers need a clear answer to is: "Who owns the data?" This question will form the foundation for starting the actual data “work,” including determining who is responsible for maintaining the data and for correcting and improving its quality.

For instance: who owns the sales data, and who should have or would benefit from its access? Do product designers understand why customers are buying what they buy? Do supply chain managers have access to demand levels? Who is responsible for tracking waste? Can the operations team access the data needed to tweak processes to make them more efficient? Are those on the shop floor entering the data that is needed to make these adjustments?

The many interwoven layers must be designed with data-led insights from across the company.

Data is not just an "IT issue"

There is a pervasive notion that data is an "IT issue" and that responsibility for every data stream and for all data collection falls under the IT department. This is not the case, and such a mindset can result in taking the wrong path when seeking to become data driven. An organization’s IT department and systems enable data to be created, processed, developed and analyzed efficiently. But data also exists outside of IT systems, for example, as physical documents and folders that may be created and saved in disparate ways.

In many cases, data ownership depends on a variety of factors, including the type of data, how it was generated and whether any contracts or agreements are in place. Additionally, data ownership laws and regulations vary by country and region, further complicating the issue.

Assigning data ownership

Addressing the question of data ownership begins with a clear understanding of the different definitions, roles and accountabilities.

Across the manufacturing value chain, activities are organized, segmented and managed by business processes or units, and each one usually has a separately defined owner. Data concept (the data associated with a particular domain) and data content ownership should follow the structure of business processes, with data grouped into different categories specific to that business unit or process and the teams using it. Business processes, data standards and operation guidelines can be developed around each category to guide how the data is created and maintained. These data categories and teams are referred to as “data domains.” For instance, in the human resources domain, there would be owners for data concepts such as job roles, career levels and training.

The data domain is where the ultimate responsibility and ownership of the data concept should rest. For each unit or process, it is important to have an elected data concept owner who is close to the day-to-day business operations. In practice, the data concept owner will be assisted by other process, data and application experts in the data domain. Data content owners are responsible for creating and maintaining the data based on the defined data concepts.

In data-driven manufacturing, process owners are also data concept and data content owners, as they receive a lot of data from other business processes and their data domains. For example, product data comes from R&D, product portfolio and product management processes, supplier data comes from procurement processes, and logistics data comes from logistics processes. Typically, the supply chain process comprises procurement, manufacturing and logistics processes and is organized under the operations unit.

Depending on the data content, data content owner roles are held by R&D engineers as well as product, customer, category, production, logistics and project managers. Each individual must be trained and engaged to act as required by the business process and the data concepts. The data concept owner defines how the unit works (collaboratively), what information is needed and generated within the unit and the necessary access rights.

Data ownership and third-party suppliers

For processes involving third-party suppliers or other supply chain participants, the issue of data ownership becomes more complex. In some cases, the ownership of third-party data may be governed by contractual agreements between the manufacturer and the supplier. Typically, a major part of the data for “buy items” are owned by the supplier, and the data for “make items” are managed fully by the manufacturers.

In other cases, ownership of third-party data may also be governed by laws or regulations. For example, in the European Union, the General Data Protection Regulation (GDPR) specifies that individuals have the right to access and control their personal data, regardless of who generates or stores that data. In such instances, the data concept and data content owners must be equipped with the knowledge and training to understand regulations that may affect their data.

Key roles for data ownership and governance

In addition to the data concept owner and data content owner, there are other key data governance roles to fill. The people chosen for each role must have the training and know-how to complete their tasks.

• Process owner - Creates guidelines and policies for the business process they own, including a vision for the data concepts and applications that are part of the process.
• Data domain lead - Ensures all business representatives and teams are familiar with the data concepts of the data domain and know how to make use of data management experts, services and support functions for data maintenance.
• Application owner - Owns the information system and is responsible for its proper functioning and integrations.
• Data specialist - Creates and maintains data in the information system

Paving the way forward

Ultimately, the question of who owns the data produced and used by the business can be complex, especially if business processes are not clarified. Growing your organization’s data capabilities is a long and demanding process that requires clear data governance, data development, data maintenance, change management, careful communication and collaboration between the business, process, data and IT organizations.

Equally important is for manufacturers to understand their rights and responsibilities when it comes to data governance and to take steps to ensure data practices are compliant with relevant laws and regulations. Doing so can help ensure that decisions are based on accurate and reliable data, while also protecting the organization’s legal and ethical responsibilities with respect to data ownership.

At CGI, we offer a systematic approach to designing and executing data governance models based on business processes to support our clients’ profitable growth. Get in touch with us to learn how we can help you.