Benefits and Best Practices of Reference Data Management

Reference data (or valid value lists) is a special type of data and is an important part of data quality and data governance (or as we call it data intelligence). Reference data lists can be used in a variety of areas including business glossary, data definitions, data quality, data integration (mapping between data systems), reporting, and analytics.   Reference data lists make sure that data is consistent. In a previous blog post we covered what is reference data. And in another blog post we cover the additional resources (blog posts, recorded webinars, and videos) we have on reference data. We will discuss in this blog the benefits of reference data management as well as some best practices.

Think of all the various applications or data systems you have and every reference data list in each. For example, say you have 30 applications (ERP, SIS, HRIS, CRM, etc.) or data systems with 20 reference data lists, many of which are similar (gender, customer status, country code, etc.). How do you manage these 600 reference data lists? Think what would happen if someone added a new item (or even worst delated an item from a list). How would that affect integrations, reports, and analytics? What would be the cost in manpower to resolve any issues with unexpected reference data changes? If you aggregate the cost of reference data issues throughout the enterprise, it could be quite costly.

In almost every organization, reporting and analytics are hampered by misunderstandings about reference data that lead to poor data results that cannot be used for decision making. With reference data management you are trying to eliminate the surprise attack where issues are reported only after the reference data change has unplanned impact. The impact of changing reference data when unmanaged tends to break things such as: application processing, reporting and analytics, data integrations, and business processes. The benefits are the following: better quality of data, better trust in data, better reporting of data, staff time savings, cost savings and a better understanding of the data.

In a single application or data system, the implementation, maintenance and use of reference data is not difficult. But in the enterprise, with multiple data systems and multiple reference data lists with similar meaning, the implementation, maintenance and use of reference data is complex. Often, the necessary tasks of reference data management are simply not done. A solution, like the Data Cookbook, needs to be in place so that reference data information is stored and managed.

Here are some best practices in reference data management:

1. Build a better understanding of your reference data by getting a list of approved values, clarify their meaning, understand the mapping of them between data systems, and where they live (technical details).
2. Create a centralized data governance knowledgebase where the critical reference data is known and accessible. This knowledgebase will improve standardization, quality, and operational efficiency.
3. Have a data steward program where someone (a subject matter expert) is assigned to review a reference data change for impact before the change is implemented. The data steward should not be IT or operations alone as the person needs departmental data knowledge as well.  Data stewards must have specific domain knowledge and knowledge about the related reference data in other data systems. There should be workflows in place that involve data stewards for adding new reference data lists and for changing existing lists. The data steward reviews the impact of any reference data list change.  Check out our additional resources regarding data stewardship in this blog post.
4. Form a standardized process for people to request a reference data list change (such as a new employee status code like “Employed – Furloughed”). Additional resources on data requests can be found here.
5. Put into place a sound data governance framework coupled with a data governance solution (like the Data Cookbook) that includes reference data management. The framework should be able to adapt to new demands. And make sure that data governance is part of the organization’s culture (concern for data). More information on data governance framework can be found here.

Hope that this blog post conveyed the importance of reference data management, its benefits and some of the best practices that need to be in place. Valid data lists and reference data are an important part of data governance and an important part of an organization’s trust in data and reporting.

IData has a solution, the Data Cookbook, that can aid the employees and the organization in its data governance, data stewardship and data quality initiatives. IData also has experts that can assist with data governance, reporting, integration and other technology services on an as needed basis. Feel free to contact us and let us know how we can assist.

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