Reference data: Definition, benefits, and potential pitfalls

Knowing how to easily identify, list, and access reference data has become a must-have skill for any company that seeks to be data-driven.

So, what is reference data, and what implications does it hold for your operation's performance?

Reference data definition & examples

Gartner defines reference data as "a consistent and uniform set of identifiers and attributes that accurately describe the strategic information required for an organization to function properly." For a company, reference data is thus used to structure information that changes little over time.

While reference data is used to define and classify other data, master data is directly linked to business entities and provides customer and product data.

Master data is necessary for business transactions. This is information that you don't want to lose and that you want to be able to access quickly and easily.

• For example, imagine an e-commerce site that sells sporting goods. Its reference data consists of its product catalog data as well as the names and addresses of its customers.
  
  This data is critical to the company because it is permanent and is used to power the primary applications and operational processes such as billing, shipping, digital marketing, and so on.
  
  
• Now, consider the billing process for this e-commerce site. The billing system makes use of several types of data: A customer's purchase history, including the quantity of each item. For example, two T-shirts and five tennis rackets. This is variable data, which means that it varies with each order based on the needs of the customer.
  
  This is referred to as operational data. Next is information such as the customer's name and billing address, as well as the identification code for each item.
  
  This data varies a little over time and is not transactional. The customer's name is always the same, and it is required for the billing process. (That is, you cannot send an invoice without a first and last name.) This type of data is referred to as reference data.

Cross-functionality is also an important concept in understanding reference data, whose use is distributed throughout the company. After all, the inventory management application and the ordering application both use reference data related to the company's products.

Similarly, applications use customer data for handling disputes as part of after-sales service, deliveries, and more.

Common master data management issues

Most companies regard data as a gold mine, but often, it can be difficult to extract usable, reliable information from datasets. But why is this?

Data is typically replicated in multiple silos (databases, Excel spreadsheets, etc.) spread across the enterprise with little or no governance to manage or update information. This affects the quality, speed, and availability of data. Data quality issues lead to failures in business processes and transactions. Decision makers then make poor decisions based on incorrect data.

This is why data classification is essential. Master data management addresses these issues by providing a unified view of reference data for better decision-making and business processes.

The business value of effective data management

The goal of using reference data management is to select and create a single version of the data that will serve as a reference for all departments within the organization. Therefore, reference data management refers to the IT tools used to classify reference data and the philosophy surrounding this approach.

Thinking and decision-making are greatly facilitated when all entities in your IT system or data stack use the same clean, consolidated, centralized, and current data. The process of data management helps companies develop a common language around data.

The benefits of successful data management for an organization include:

Conclusion

Without question, data is your company's most valuable asset, and reference data management lets you maximize its potential.

Reference data management stands as a crucial pillar in the foundation of effective and efficient data governance. Through its meticulous organization, maintenance, and dissemination of reference data, reference data management empowers organizations to make informed decisions, enhance data quality, and streamline operations.

The benefits of implementing a robust reference data management framework are far-reaching, ranging from improved data accuracy and consistency to increased regulatory compliance and agility in adapting to evolving business needs.

As businesses navigate an increasingly data-centric landscape, understanding the significance of reference data management becomes paramount. Embracing reference data management not only fosters a culture of data integrity but also positions organizations to harness the full potential of their data assets in a rapidly changing digital environment.