Companies have been facing challenges with reference data for as long as I can remember. Isn’t it time we review some of our long-lasting assumptions?
Reference data is dead: Long live reference data!
To start, let’s think about how we talk about reference data. It has been part of the enterprise landscape for long enough now that it’s become commonplace in our vocabulary. But your company’s reference data from 5 years ago can’t be the same as today’s: your business has evolved. Your customer base and the markets have developed and matured. Your company has been involved in mergers or acquisitions. And your organization as well as its IT infrastructure have been transformed.
Since “the only thing that is constant is change,” the context for – and your reference data itself – will only continue to change. As a result, chances are that various stakeholders around the company may have different pictures in mind when it comes to reference data. This is important to remember and to take into account when you make decisions about the supporting systems and processes.
An MDM approach may help you manage reference data, but…
The similarities with master data make it possible to leverage master data management for reference data management. However, it is a misconception to think that all your reference data needs are met as a result of such a choice. To trust your reference data – and your master data, in fact – you may have realized by now that managing it only takes you so far. Identifying the root causes of data quality issues remains challenging with no or limited traceability. Also, as analytics software grows smarter and extends its reach into exponentially growing datasets, understanding and controlling the source is no longer optional.
If you want to achieve greatness, governance is really your best ally, and as it is now widely recognized as a game changer, there has never been a better time to leverage synergies between management and governance of reference data.
Don’t wait for regulations to take action
Another important realization is that not all data is equal. And reference data is not benefiting from the same innovative and aggressive approach as, let’s say, big data.
Reference data may not so obviously prove valuable at first sight, but it, nonetheless, deserves attention as the risk and associated cost of neglecting it can be very high, possibly leading to transactional errors, impacting your company’s revenue and reputation. And while regulatory compliance, for example, can be a strong driver for change, being proactive and strategic will save you from the consequences of rampant, pervasive data quality issues.
Forget about ownership (for a moment)
We have been struggling with the ownership of reference data, repeatedly asking the question: Is it technology or is it the business owning it? More important than any answer to that question, which emphasizes silos and often leads us to finger pointing, lies a realization that “what unites us is far greater than what divides us” and what we see as a growing need for a collaborative culture of governance.
Engaging all stakeholders through a data governance platform and processes will empower owners and stewards alike and allow them to grow as true champions of fit-for-purpose, reliable data inside your organization.
Collibra: A data governance platform for your reference data
Beyond supporting the core needs as a system of record for your code sets, hierarchies and code mappings across domains and applications, Collibra Data Governance Center enables you to control and extract as much value from reference data as possible by leveraging governance at all levels:
- Articulation of your data assets’ definitions in business terms
- Assignment of associated roles and responsibilities
- Organizational structure for the storage of the data
In combination with such context, traceability empowers users across the organization to fully understand and trust the data they rely on for their own purpose. This is essential to guarantee meaningful (re)usability of reference data enterprise-wise as well as data quality.
Customizable workflows foster active collaboration between users around common reference data and maximize operational efficiency of review and approval processes, including the reporting and resolution of issues.
Now that you have the opportunity to shift perspective, ask not what your reference data can do for you, ask what you can do for your reference data. Will you be a good data citizen?