When a chief data officer achieves excellence in master data governance, they’re transformed from someone who spends their time reactively fixing things when data gets messy or breaks a system, to a proactive, all-seeing business enabler. This series explores why master data governance is vital for: data modelling, data quality, rich content, industry standards and data enrichment.
As the saying goes, “If you’re not sure of the source, don’t drink the water.”
It’s a similar principle for the governance of data enrichment.
Because if you choose to drink that dodgy water, it’s not just you you’re potentially infecting.
That water will flow through your organization, getting into many systems and exposing itself to people who might assume they’re fine to use it, and that it’s reliable and accurate.
But we’re here to help you stop that from happening. Continue reading this guide to see how you can drive business transformation by improving your data enrichment process with master data governance.
In a nutshell, data enrichment is the process of enhancing raw data with additional information to make it more valuable and useful for analysis or decision-making.
It involves adding context, insights or attributes to existing data, which can include demographic details, geographic locations, social media activity or other relevant data points.
Essentially, it's like adding extra layers of information to basic data to make it more meaningful and informative.
Third-party sources are often the best way to enrich your data set when a user looks into an individual record, or a set of records, but finds information missing from certain fields.
For example, they might want to enrich a customer data set with addresses, company information, financials, credit scores, or risk data.
When it comes to data enrichment, good data governance—where you have the right controls and approval processes in place—will ensure that people are careful about where they get the data from and what they use it for.
Otherwise, instead of benefitting from data enrichment, your business might unwittingly be suffering from data impoverishment, and the commercial risks that go with it.
When data gets personal: personally identifiable information (PII)
You only have to spend approximately 0.241 seconds on an online store these days before getting a popup offering a 10% discount on your first order—in exchange for you subscribing to their marketing emails.
They’re pretty much all at it, due to the planned deprecation of third-party cookies.
Put simply, there’ll be less third-party information available about the interests and behaviors of consumers. Or rather, there’ll be less widespread trade and re-trade of this information. Instead, you’ll be buying it directly from the businesses who collected it and got permission to sell it on to you.
This cookie data is used extensively in digital experience personalization.
Say you’re someone who watches videos of snowboarder Shaun White for three hours every week, as he throws “hella” crazy Triple Cork 1440s.
Then it’s a safe bet that you’re more likely to be in the market to buy a new snowboard than your average Joe—and so you’ll be more likely to see targeted ads from snowboard brands.
Likewise, if 3ft of fresh snow is forecast to fall next week at the ski resort that’s just two hours from your known address, then there’s probably another targeted ad coming your way.
It’s a good time to look back at previous rounds of data enrichment—will the rules you used still be good going forward? Or do they need modifying or scrapping? It’s essential that your data enrichment process has checks and balances to safeguard personally identifiable information (PII).
It also makes sense to look at what’s going on with the data once it’s in your systems.
Is it easy to find data when it needs to be disclosed, modified or deleted? Or can you guarantee it was matched to the right person in each system? You don’t want to be sending Jerry Maguire snowboard promos when it’s Geri Maguire who truly loves to carve up the mountain.
When you don’t know who you’re dealing with: prospect and customer management
If you’re a chief data officer working in a B2B organization, you and your team are uniquely positioned to understand the pains of poorly managed data enrichment.
It can cause all sorts of issues when it comes to targeting the right prospects and customers, including:
When you need to scope out your carbon emissions: regulations and sustainability
Third-party data plays a key role in reporting the carbon emissions your business is responsible for, across both your own operations and the suppliers you work with.
So, to be confident in how sustainable your product is, and that your suppliers are sticking to all standards and regulations, the data needs to be accurate, reliable and coming from a trustworthy source.
If your data isn’t enriched to a certain standard, it’ll be useless for downstream processing, because either:
So, why mightn’t your data enrichment have proper governance? It’s most likely because you don’t have the correct MDM software and resulting workflows, or you haven’t yet made sure the enriched data fits your data model. We also have a guide on data modelling—surprise, surprise—which you can read here.
That means field-level validation is essential for enrichment. Every field of data needs to be:
So, anyone can enrich a record, but without strong data governance, you’ll get data quality problems—turning data enrichment into data impoverishment.
>>Start building your foundation for better data enrichment, with this checklist.<<
If you’re still not convinced about just how important data governance is when it comes to data enrichment, here are some real-life examples of how businesses can suffer.
We’re warning you though, things are about to get scary.
Instagram and TikTok failed to protect children’s data
In September 2022, Instagram was fined a whopping $403m for mishandling data (email addresses and phone numbers) belonging to children. The data in question was made more visible to others when users upgraded their profiles to business accounts to access Instagram’s analytics tools.
Exactly a year later, in September 2023, TikTok was fined $370m—for similar reasons to Instagram. It was ruled that TikTok had failed to comply with multiple articles under GDPR, relating to how it processed the data of minors, as well as data security and data protection by design.
IKEA and H&M accidentally committed greenwashing
While Ikea was ahead of the game on sustainability initiatives, the furniture company inadvertently found itself involved in a scandal. In 2021, it was found to be selling wood that its supplier had illegally sourced from Russia. However, the blame was eventually placed on the Forest Stewardship Council (FSC), which had wrongly certified the wood for sustainability.
In 2022, the fashion retailer H&M was accused of false advertising, when it was found that customers were given misleading sustainability information based on the Higg Sustainability Profile—a metric gauging how much carbon a material’s manufacturing releases into the atmosphere compared to traditional materials. In one instance, it was claimed that an item of clothing required 20% less water to create, when it was actually 20% more. H&M blamed it on a technical error.
Getting it right with master data governance
What you just read above might have left you in a bit of a cold sweat. So, now it’s time to make sure the same doesn’t happen to your own organization.
As the chief data officer, it’s your responsibility to make sure everyone in the business feels empowered to:
When chief data officers get this right, they enable teams and departments to fill their knowledge gaps by mapping valuable attributes to known entities. They can then create more interesting data relationships that they can use to drive business performance and enhance the customer experiences.
In other words, you'll become a source of guidance for your business.
One of the most satisfying parts of working on your data governance, is that it’s easy to tell when you’ve got it right. Here are some of the things you’ll notice:
Without the right governance in place, you could quickly lose control of third-party data, especially with the high volume that can be ingested into your systems, and the speed at which it can progress through them.
But put these basic steps in place, and your domain leads will be free to take advantage of valuable third-party data while being selective with trust and credibility.
It’ll give them the confidence to start hunting for data to fill knowledge gaps, which helps the business run better.
Here’s what you need to do as a chief data officer:
When you have the right master data management platform, that supports proper data enrichment practices, these are just some of the things you’ll be able to achieve:
Get a head start on with your data enrichment, by downloading our handy checklist here.