The Role Data Quality Plays in Master Data Management
Enterprises are dealing with more data than ever before, which means that proper information architecture and storage is crucial. What’s more, the quality of the data you store affects your business more than ever nowadays. This goes double for your contact data records, because you need the most accurate and up-to-date lead and customer data to ensure that marketing, sales, and fulfillment all run smoothly.
Master Data Management, or MDM, involves creating one single master reference source for critical business information such as contact data. The goal of MDM is to reduce redundancies and errors by centrally storing records, as well as increasing access. No matter how well organized your database might be, the quality of its data will ultimately determine the effectiveness of your MDM efforts.
Why is master data management important?
Organizations look to MDM to improve the quality of their key data, and ensure that it is uniform and current. By bringing all data together in a hub, a company can create consistency in record formatting and ensure that updates are available company-wide.
MDM sounds simple in theory, but think of how (and how much) information is created and collected within an entire organization. Let’s take a single customer contact as an example. Over the course of a month, John Smith provides information to your company in three different instances:
- First, he is an existing customer of your services division, and his data exists in their customer records.
- Second, he visits your website and downloads a whitepaper, getting added to your marketing department’s database of leads.
- Third, he calls the sales team for one of your specialty products, and gets added to their database of contacts.
In a typical organization with departmental “silos,” John Smith is now part of as many as three separate databases in your company, none of which have a longitudinal view of his relationship with you as both a customer and a lead. Worse, slight differences in contact records could even turn John into three separate people in a master database. If each of these touch points get assigned to different automation drips and your sales reps are calling and emailing, you have a real disconnect in your efforts and a high likelihood of spamming your contact.
Having good data collection and storage practices is the first step to a good MDM program, but that alone may not solve John Smith’s problem. Ensuring the data he provides is correct, current and most importantly consistent at the point of entry is what guarantees that the best quality contact information is stored as master data. Implementing a lead validation service could help solve this issue at the point of entry by cross-validating each contact record with multiple databases in real time, facilitating accurate merge/purge operations later.
Lead validation not only corrects and appends contact data, it can also feed into your CRM and automation tools to help you further qualify your leads, so your sales team is only dealing with the highest quality information and pursuing genuine prospects. Once your prospects become customers, their contact data records will be passed on to other departments to complete any transactions – and through your MDM they will also have the most up to date and accurate information to conduct their business.
The costs of poor data quality
In a 2018 study conducted by Vanson Bourne, 74% of respondents agreed that while their organizations have more data than ever, they are struggling to generate useful insights. Some say this is because they are not effectively sharing data between departments, but only 29% of respondents say they have complete trust in the data their organization keeps.
Every aspect of your organization can be impacted by poor data quality, especially if your contact data is lacking. If 71% of your sales team feel that their lead information is bad, how effectively can they do their jobs?
Here are just a few of the ways that bad data can hurt your business:
- Marketing – sending marketing materials to existing customers for discounts for new subscribers, spending extra money creating mailers for addresses that don’t exist
- Sales – Multiple sales reps calling the same lead, the same sales rep calling the same lead multiple times, wasting time on bogus leads
- Order fulfillment – bad or incomplete address data causing failed deliveries and chargebacks
- Accounts receivable – sending invoices to incorrect addresses or old business contacts, billing addresses not matching credit card records
- Business development – making bad decisions for growth in a particular market based on inaccurate data
Each of these issues could be solved by creating a master data management system and making sure it is only fed validated contact data from the point of entry. Further, frequently updating the MDM system by validating name, address, phone, email, IP, and other key pieces of information ensures that each data record is as current as possible.
Finally, one major cost of poor data quality – and a key reason for the growth of MDM – is the compliance risk as new data privacy and security regulations have emerged in recent years. For example, the European Union’s recent General Data Protection Regulation (GDPR) and the US Telephone Consumer Protection Act (TCPA) both have severe penalties for unwanted marketing contacts, even when such contact is inadvertently due to data quality issues like bad contact data or changed phone numbers. Accurate, centralized data is now an important part of compliance strategies for any organization.
Trends in master data management and data quality
The competitive advantages of consistent centralized data – together with the advent of cloud-based tools for data quality – have made MDM a growing trend for organizations of all sizes. Moreover, David Jones of the Forbes Technology Council predicts that increasing regulation and the rise of cybersecurity risks are converging to change the way data is managed at the business level. We now live in a world where things like validating contact data, rating lead quality, verifying accurate and current phone or email data, and other data quality tools have now become a new standard for customer-facing businesses.
Today, adding a contact data validation service to your processes before storing master data will improve overall data quality and increase efficiencies among all of your teams. Service Objects offers 24 contact data validation APIs that can stop bad data from undermining your master data management system. Want to learn more? Contact our team to see which API is best for your business type.