In today’s data-driven business environment, managing reference data has become a critical component of many organizations. Reference data are static information we use as the basis for transactions and analytics, such as currencies, geographic locations, and legal entities.

Reference data management (RDM) is the systematic process of organizing, storing, and maintaining reference data. which is the set of data used to define or categorize other data.

In this article, we will look at reference data management, its importance, and how it can help you achieve your data management goals.

What Is Reference Data?

Reference data, also known as static data, is data that rarely change. For example, currencies, countries, time zones, exchange rates, securities identifiers, legal entities, and product codes.

Reference data is unavoidable; almost every department in every organization uses it. Managing reference data is an important part of data management for organizations of all sizes and industries. 

It allows you to be more efficient, reduces losses, and ensures compliance with regulatory requirements. This includes stock trading, risk management, compliance, accounting, and reporting.

For example, in the financial industry, reference data is used for trade processing, settlement, and regulatory reporting. You can use reference data to identify patients, medical codes, and drug classifications.

Reference data also helps avoid errors, reduce operational risk, and improve data quality. It ensures accuracy and consistency across all your organization’s systems and applications.

What Are Examples of Reference Data?

The majority of reference data assets are managed by standards organizations such as ISO. Here are some common examples:

• Currencies: ISO currency codes, exchange rates, and currency symbols.
• Countries: country codes, names, regions, time zones, and currencies used
• Legal entities: company names, addresses, registration numbers, and tax identification numbers.
• Products: product codes, descriptions, pricing, and availability.
• Securities: security identifiers, ticker symbols, security names, and issuer information.
• Time zones: UTC offsets, daylight saving time rules, and geographic location
• Units of measurement: length, weight, volume, temperature, etc.

What Is Reference Data Management?

Reference data management (RDM) is the process of collecting, managing, maintaining, and distributing reference data across an organization. 

It typically involves establishing reference data standards and governance policies to ensure uniformity, accuracy, and completeness. For example, defining data elements, creating hierarchies, and assigning metadata to ensure proper data classification and usage.

RDM allows organizations to create a centralized and standardized reference data repository. The repository can be accessed by different systems and applications within the organization.

Effective reference data management requires establishing processes for data collection, data quality control, data mapping, and data distribution. This reduces data redundancy, improves data quality, and increases operational efficiency.

It also involves establishing ownership and responsibility for reference data, developing data usage policies, and ensuring compliance with relevant regulations and standards.

Importance of Reference Data Management

Here are some of the main benefits of implementing an effective reference data management system:

• Accurate Decision-Making

Reference data management minimizes the likelihood of data errors. This improves the accuracy of your data analytics, allowing you to make better data-driven decisions.

For example, it helps you make better risk management decisions. You could also use it as a guide to help you identify and understand transaction patterns in your organization.

• Improves Operational Efficiency

Reference data management helps you reduce data redundancy and ensure data reliability across all systems and applications. This simplifies your data management processes and provides employees with the information they need to be more effective.

• Regulatory Compliance

In most countries, your organization must comply with various data management regulations and standards, such as GDPR, Basel III, and Solvency II.  RDM helps you ensure that your reference data is regulatory compliant, avoiding potential fines, penalties, and negative publicity.

• Reduces Operational Risk

Inaccurate or unreliable reference data can cause transaction errors, misreporting, and other operational risks. Effective reference data management practices enable you to reduce these risks by ensuring your data’s accuracy and reliability.

• Better Customer Experience 

Accurate and consistent reference data can improve the customer experience by reducing errors in transactions and improving the speed of service delivery. It also helps you discover data inconsistencies, and resolve complaints faster.

What Are Some Common Reference Data Problems?

• Incomplete or Missing Data

One of the most common negative consequences of reference data problems is incomplete or missing data. Missing data makes it difficult to make data-driven decisions.

Recovering missing data means extra cost, which would reduce your organization’s profit. 

For example, some contact information is missing from your database. This can make it difficult to reach out to them for marketing or sales purposes. You may miss out on opportunities to engage with those customers and earn their loyalty.

Read Also – What is Records Management: Process & Best Practices

• Inaccurate or Inconsistent Data

Although reference data is supposed to be consistent and static across all systems and applications, it can become unreliable due to factors such as human error, different data collection standards, or data source change.

Inaccurate or inconsistent data can be problematic, and in some cases, fatal. For example, if healthcare professionals mix up medical codes, it can lead to incorrect diagnoses and treatment plans.

Inaccurate data can also result in complex financial issues. For example, if you discover errors in your financial database, you will have to audit and modify a huge percentage of your financial records.

Also, if you don’t discover the inaccuracies, it could lead to accounting errors and result in financial misstatements. This could significantly damage your company’s reputation and financial health.

• Standardization Problems

Without effective reference data management systems, there would be no measurement standards. This makes it difficult to draw conclusions and make recommendations with information collected from multiple sources.

For example, if one source measures weight in kg and another in lbs, you can’t compare the data or draw conclusions unless the units are converted. If a measurement standard is specified, the unit conversion process can be avoided entirely, saving you time and resources.

The standardization problem also extends to legal issues such as names.

For example, most legal entities for product registration allow you to trademark your company name so that no one impersonates you. A common way for legal entities to do this is to check new names for similarity in appearance and sound, and if the product is distinct enough, it is registered.

This prevents two distinct entities from being confused with one another. It also prevents your company records from being mixed up.

• Poor Quality Data

Poor data quality is a common side effect of ineffective reference data management. It can result in incorrect insights and decisions. This can have a significant impact on your company’s operational efficiency, sales, and even reputation.

For example, a marketing campaign targeting a specific audience may fail if the data used is inaccurate or out-of-date. Customers may become dissatisfied with your products if you do not tailor them to their needs.

Combining dissatisfied customers with marketing to people who do not need your product is a recipe for financial disaster. It could result in, low sales, negative brand perception, and reputation.

Here’s another example, if you have a poor-quality medical database, patients may receive the wrong medication, dosage, or treatment, causing adverse outcomes.

• Security and Privacy Concerns

There are significant security and privacy concerns without an effective and secure reference data management system. For example, customers’ personally identifiable information (PII) stored in a company database, could be vulnerable to data breaches or cyberattacks, potentially leading to identity theft or fraud.

Similarly, sensitive data stored in a company database, such as trade secrets or intellectual property, could be vulnerable to insider threats, resulting in financial loss.

It could also damage your company’s reputation. People are less likely to trust you with their data or money if they know your security can be breached.

Security breaches are also a leading cause of company shutdowns; customers don’t trust you with their money, and neither do investors.

Conclusion

Reference data management enables you to make smart data-driven decisions by ensuring you have accurate, consistent, and reliable reference data for various business functions.

Using a simple and customizable reference data management solution like Formplus enables your organization collect and manage data effectively. It also increases customer loyalty and sales.