Bad data costs companies a huge amount of money. How do you boost the quality of your business data, in other words the data you hold on your business relations such as customers, suppliers and prospects? In this article we set out a 4-step plan to help your organization cleanse and enrich its business data.
In 2016, 3,100,000,000 dollars was lost in the US as a result of bad data. That’s hardly surprising: bad data causes companies to take the wrong decisions, lose out on revenue opportunities, waste time and incur reputational damage. But once you’ve cleansed and enriched your data, you can begin to explore new revenue opportunities. You’ll also take faster and better decisions, work more efficiently and benefit from more effective prospecting.
Factors that can harm data quality
The root causes of the problems so many companies have with inaccurate, incomplete and irrelevant data lie in the countless factors that can harm data quality. The main factors are:
- Data is kept isolated in different silos;
- There are multiple users of the data within the organization;
- Data sets get merged following mergers and acquisitions;
- And by far the biggest contaminating factor: human error when entering, editing or maintaining data.
So it’s high time for high quality data. By following our 4-step plan, as set out below, you can boost the quality of your business data.
Step 1: cleanse your data
Have you realized that your data is contaminated? In that case, it’s time for the first step: a big clean-up. For organizations of a certain size, or companies that process high volumes of data on account of the nature of their services, going through every company record manually and correcting any mistakes would simply be impossible. However, there are specialist companies with powerful automated tools that will do this for you.
We offer two important tools for cleansing data sets:
- The Dun & Bradstreet database, which contains data on 300 million companies worldwide.
- The D-U-N-S number, a unique 9-digit identifier for every business entity.
When a company submits a data set to us, the records in question are assigned the corresponding D-U-N-S numbers, then matched with the Dun & Bradstreet database. So for instance any duplicate records, companies that have gone out of business and companies belonging to a single group can be identified. Where the records deviate from the D&B database, suggestions will be made for replacements based on the accurate D&B data.
The company then receives the clean data set in the form of a spreadsheet, or the data is fed back directly into its CRM or ERP system. We also provide a total overview of, for instance, the number of records of companies that have gone out of business, the percentage of duplicates and any deviations in the information.
Step 2: keep your data clean
Once your data is clean, you have to keep it that way. Nine out of ten cases of data contamination are caused by mistakes made during manual entry. The best method for quality assurance is therefore to ensure that new data is entered correctly in the first place.
You can do this by using an API to link your CRM or ERP systems to the Dun & Bradstreet database. Both newly entered and existing business data will then be verified immediately, and where necessary corrected or supplemented. As a result, you’ll have less manual entry work to do and your data will always be up-to-date, accurate and consistent in all your applications. And as you know, consistency is one of the key ingredients of data quality.
Step 3: add external business data
Once data is clean, the logical next step is to enrich it. Enrichment means adding value to existing data. A few of the possible enrichment methods are record linkage, statistical matching or adding data elements to a data set.
Altares – Dun & Bradstreet can supply you with verified data elements in the field of business data. This means that you can, for instance, add industry and geographic codes, corporate structures, name and address data and the D-U-N-S numbers of your customers, suppliers and prospects to your own databases. By doing so you can build up a comprehensive, verified picture of all your business relations.
Step 4: use real-time data and insights
The finishing touch is to make use of real-time, extra high-quality data and insights about your business relations, drawn from the Dun & Bradstreet database. This is a form of Data-as-a-Service (DaaS): real-time, on-demand access to business data in the cloud, whenever and wherever you want.
This data includes:
- Credit and performance rankings
- Predictive indicators and models
- Court judgments
- Sanctions lists
- Information on ultimate beneficial owners
- What about those expensive data management tools?
Many companies, realizing the importance of data quality, make substantial investments in these tools. That may seem like a smart move. But it’s important that you investigate whether you actually need these tools before you buy them.
Simply by following this 4-step plan, you can put your master data management on a much sounder footing. Thanks to automated correction and supplementation, the link with the Dun & Bradstreet database ensures that master data on your business relations will be the same in all your systems and applications.
To take good decisions, you need good data.
Bad data can stand in the way of achieving your company objectives. Even if you have an expensive CRM or ERP system, poor quality data will cause you to take poor decisions. Or, in the words of Dun & Bradstreet’s data guru Scott Taylor: ‘Good decisions made on bad data are just bad decisions you don’t know about yet.’
If your data is contaminated, then the decision-making process can be summed up as: garbage in, garbage out. By following this 4-step plan, you can ensure that your data is gold-standard. As a result, your decisions are sure to be: gold in, gold out.
