Reference Data Management: Some best practices and common pitfalls

The effective management of reference data has emerged as a pivotal element in sustaining operational efficiency, optimising spend and fostering a transparent, repeatable, and informed decision-making process. Reference Data Management (RDM) entails the organisation, categorization, and oversight of reference data – the foundational data used for classifying and contextualising other datasets. However, distinguishing what strategies yield success and what pitfalls to avoid is integral to building a solid RDM strategy.

What is Reference Data Management?

Reference Data Management (RDM) is a set of processes, people and technologies that allows the organisation, maintenance, and optimisation of reference data within a financial institution. At a high level, RDM can be divided into three functional areas:

– Managing Reference Data usage and spend
– Managing Reference Data quality, availability and distribution
– Managing Reference Data governance and policies

Managing Usage and Spend management, as well as Managing Data Governance are cross-business functions and generally benefit from being managed by central teams within organisations. Managing data quality, availability and distribution are entity specific and therefore their functions should typically be siloed within organisations, as different business units will have differing requirements for data and how it is sourced and distributed.

At Xpansion we provide solutions for all three functions above and we believe it is important to distinguish these, as each will bring its own challenges and requirements. In this article we provide some best practices and common pitfalls when dealing with Reference Data Usage and Spend.

Reference Data Management, best practices, and common pitfalls


Best practices

Monitoring usage 

Gaining insights into data consumption behaviour is a cornerstone of a robust RDM strategy. Metering data usage allows you to ascertain data consumption patterns, understand data flows, and paves the way for better decision making through precise actions and predictable outcomes. Data usage metering should focus both on inbound and outbound data for a more comprehensive view and deeper analytics.

Actively Controlling Non-production data usage

By limiting access to data without genuine business value, you curtail wasteful expenditure on irrelevant datasets and avoid unnecessary spend and mitigate cost spikes. Actively creating data access control rules in the organisation also avoids compliance pitfalls and licensing issues, so that it is not just applicable to non-production data.

Checking and reconciling invoices

Reconciling invoices maintains accountability and reduces spend leakage. It is imperative to have mechanisms to check that your organisation is being charged correctly, in line with current agreements in place. Mistakes happen, however having tools in place to validate invoices removes doubt and maintains accountability and transparency.

Know what data you have and what data you have access to

Cataloguing data isn’t limited to merely identifying what data your organisation possesses. It extends to understanding the spectrum of available data, including both external vendor sources and internal sources, as well as using metadata attributes to enhance the meaning of the data. By assessing the data landscape comprehensively, you minimise redundancy, understand user requirements and curb inefficient expenditure.

Establishing cross-organisational team units for RDM

To be most effective, Reference data management usage and spend function should be incorporated within a cross-business team. Optimal results arise from globalising RDM operations within expansive organisations, facilitating insights-driven decisions that benefit the entire enterprise in an efficiently orchestrated manner. This is especially true for usage and cost optimisation, as well as data governance.

Leveraging External Expertise

Recognising the intricacies of RDM and how complex reference data commercials can be, seeking guidance from experts augments your data management strategy. Collaborating with knowledgeable professionals lends insights into best practices, innovative tools, and strategic methodologies. Seek experts that continuously add value to your team rather than performing one-off exercises.

Common pitfalls

Introducing complexity through data caching 

Data caching, when not offered as part of a more complete Enterprise Data Management (EDM) or Master Data Management (MDM) solution, adds both technical and operational complexity which, in most cases, yields disappointing returns, masks data quality issues and creates confusion with data consumers.

When properly implemented, a solid EDM/MDM solution will provide the ability to remove duplicated requests for data, store bulk file information and provide a golden data copy to users within the organisation, as well as the possibility to benefit from multiple data vendors at the same time.

A solid data strategy in an organisation should include one or more EDM systems which are properly configured, and which will also negate the need for a separate and complex data caching and distribution system.

Using multiple vendor accounts

Relying on multiple accounts for cost allocation and usage reporting fragments the organisation and leads to inefficient processes, duplicated usage and increased spend. Streamlining cost allocation through a unified reference data hierarchy enhances financial tracking and reporting accuracy and is in the spirit of keeping things simple. Rather than duplicating accounts, it would be more advisable to reduce the number of accounts and apply usage monitoring to allocate spend internally, in a fair way and combined with a full usage report.

Using a One-off approach

RDM is a continuous process, not a sporadic effort. Treating RDM as an isolated task might deliver some value in the short term, however it is a false economy as over time, inefficiencies will arise again and will be more costly to address. A more effective strategy would be to introduce continuous controls and monitoring to enable a proactive management strategy that is able to respond in real-time to business requirements and changes.



We hope this article has helped shed some light on some best practices and common pitfalls in the area of reference data management. RDM can be a daunting task with clients not quite sure where to start and how to deliver value quickly with little impact to the business. At Xpansion we advocate a bottom up approach: start with small projects that deliver and gradually expand best practices throughout. We have been helping organisations of all sizes for more than 10 years and are here to help. Get in touch with us for a demo of our products or to discuss your needs further!