…True Wisdom Is Knowing What You Don’t Know
What Is External Referential Data?
Traditionally, referential data is defined as a superset from which information is derived to complete a study, task, or goal. Think back to school and writing a research paper. Your teacher or professor expected a bibliography or works cited section at the end of your paper.
This helps substantiate any claims or points you made in your work. It could be a list of books, publications, interviews, or websites that helped you cohesively bring together your research work. External referential data for master data is very similar to this. It is a collection of data curated by an authority external to your organization or enterprise.
You Don’t Know What You Don’t Know
The value proposition of using external referential data boils down to the age-old lessons of teachers ranging from Confucius to contemporary speakers like Jim Rohn.
According to Confucius, “True wisdom is knowing what you don’t know.” Rohn adds urgency to this sentiment when he notes, “What you don’t know will hurt you.” Not knowing or not being able to fact-check your internally generated data could provide you incomplete – or worse, incorrect – data for decision-making.
Gartner noted that, on average, companies take, a $15 million annual hit attributable to poor dataExternal Website. Opens New Window. To add urgency to the matter, Gartner also found that 60% of companies do not measure the financial impact of poor data.
Being able to enrich your organization’s data with timely, trusted, and relevant referential data from an external authority will increase ROI and add credibility to your master data. Below are the reasons why.
Having trusted sources of external referential data makes data upkeep predictable and sustainable.
The 3 R’s of Referential Data
Relevance – Your organization’s master data gains significance when updated, validated, or enriched by well-curated external referential data. Take customer name and address data, for instance. Many questions could arise upon the provision of this valuable pair of data attributes: Is the postal code provided correctly for tax purposes?
Are we working with a branch or a headquarters? Is this customer still in business? Under what other names do they do business? External referential data providers like Dun & Bradstreet can provide answers to these questions (and more) and deliver a competitive advantage to your data users.
Attributes like the “Out of Business” indicator and the various “Doing Business As” fields available can provide answers to, if not guidance on, these questions. Using referential data, not only will you be able to add more intelligence to the customer record through the enrichment of firmographic attributes and hierarchy, but you will also be able to validate the completeness of internally generated data.
Reduces burden in maintaining data – Imagine if your customer master file relied completely on internally generated data. Your customer analytics would be short-sighted and quickly become outdated. Why? It’s not enough to get the data right upon entry – it also needs to be sustainably maintained. Chances are that data maintenance would be quite reactive and dependent on manual updates.
Having trusted sources of external referential data makes data upkeep predictable and sustainable. These are the initial benefits of consuming relevant and curated data from an external source. Not only will your data have a wider scope of coverage (depending on your need), but you can also reduce manual errors, aged data, and misinformation by bringing in external referential data either via a batch process or API technology.
Either way, it significantly reduces the hardship of manual data stewardship. As a result, you will realize the benefits of automation, speed, and predictability through economies of scale. Be it via matching, periodic data refresh, or data recertification, Dun & Bradstreet will be able to reduce the burden of managing your master data assets.
Reliability – In problem-solving, it is said that two heads are better than one. With data management, it’s no different. The more qualified sources you get for your data, the better validation gets. This is a key role of external referential data. Being able to infuse your customer master file with data from reputable vendors and sources should increase your users’ confidence in the data. Referential data removes the guesswork. Authoritative sources provide strength for the data, so it can be used contextually to prove theories and settle arguments.
For example, segmentation exercises use firmographic data such as employee total, annual sales, and industry. These are typical data attributes that can be ingested from an external vendor or partner on a defined schedule. If you source this data from regarded experts, the due diligence already performed by its curators increases the data’s reliability.
The benefit of the increased dependability of your data is passed to the segmentation practitioners who need the data. This is one of the biggest reasons why long-term clients trust Dun & Bradstreet’s Data Cloud. On top of removing the guesswork in business processes by making them data-driven, their curated data is a cornerstone in building data reliability within the enterprise.
Putting It Together
External referential data should be a crucial part of your master data strategy. When you put it all together (relevance, reduction of burden, and reliability), it removes the internal biases of your data. Essentially, an independent and consistent source of referential data provides a factual and demonstrated control to mitigate risks that make business decisions vulnerable.