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Set Your Data in Motion with Master Data

Whether or not you’re keeping track of it, all of your departments are collecting and storing data. Like raindrops on the field of your business, your sales teams collect pieces of data with each prospect conversation and closed deal. Your customer service teams are collecting data every time a point of contact changes or provides feedback on a product. Your warehouse is collecting inventory and shipping information to help manage its processes.

To continue the metaphor, like rain, this data can’t serve your company or – if you will – effectively water your crops, if you’re not capturing and distributing it effectively. If all your data is collecting in silos, you’re not taking advantage of the benefits that Master Data can provide to your business.

If you could take that data, structure it, use it to connect the silos in your business, make sure it covers all your business needs, and ensure that it is trustworthy, you would have the ability to tap into the full value of Master Data. Enabling the fluid movement of information, insights, and analytics across your enterprise can help quality data nourish your company’s decision-making processes and analytics-based endeavors. No matter where your company is in its data journey, you can start to create an environment where you can rely on the data you push to your teams’ platforms, and be assured that the data is helping your teams make better informed decisions.

The questions then become: Which data constitutes Master Data? What is good Master Data?

Defining Master Data

Master Data is the strong foundation on which a company should build its data-driven strategy.  Data can be mastered at the application level (e.g., a Customer Relationship Management – CRM - system), between applications or departments, and across a distributed enterprise (with or without a formal Master Data Management – MDM – program). It should contain the central information about the customers you sell to, vendors you buy from, parties you partner with, and prospects you are interested in, as well as the products you make and services you provide. Good Master Data is:

  • Expertly structured
  • Unified and connected
  • Broad and in depth
  • High quality

Let’s take a closer look at each one of these attributes:

Expertly structured.

This means structuring your data around a shared understanding of each business entity with which you engage. To structure data correctly, you’ll need to address four distinct levels: entity, hierarchy, segment, and location. Many companies are seeing value in basing their data structure on the Dun & Bradstreet D-U-N-S® Number. Not only does it provide entity structure, but it also identifies corporate hierarchies and other business linkages, and in the future, if you’re interested in connecting your data with another company (interoperability) or platform, using a global standard—such as the D-U-N-S Number—could help expedite the process.

Unified and connected.

The concept of connecting your data leads to the next feature of good Master Data. Good Master Data is unified and connected across your organization. That means that the source data your sales teams are using is the same as what your marketing teams are using, as well as your development teams. The first step is connecting your data with your defined structure, and the next is to share it across your company’s systems and processes in a way that best supports business goals and is in line with the specific technology you use.

Broad and in-depth.

Your data should give your teams insight into customers, prospects, and partners across geographies, industries, and segments. You can leverage all your teams and third-party systems to achieve breadth, but depth usually comes from a third-party system that can enrich your data with insight and information that your teams don’t or can’t collect.

Well-governed and clean.

The need for well-governed and clean data should be obvious, but it assumes that you and your teams know what low quality and poorly governed data looks like as well.

Low Quality Data – Low quality data is akin to contaminated water: duplicate records, inconsistent spelling and naming conventions, low fill rates of basic firmographics, incomplete hierarchy structures, and spotty category definitions. Quality data can be trusted as complete, current, and accurate.

Poorly Governed Data – Poorly governed data lets valuable information slip away, or go untended, or it allows bad data to slip in. It is the responsibility of multiple stakeholders, each of whom have different objectives, so there is often no firm, standard process in place.

Your Data is Ready. What Now?

Your data is only valuable if it is in motion, integrating silos and being used for critical decisions, according to Dun & Bradstreet Master Data, Market Development, and Innovation Leader Scott Taylor. In addition, as entities and relationships move and change, the data must move and change with them. If your data flows well across your organization, you can make right data, right place, and right-time decisions, every time.

To read more about the value Master Data can bring, download Taylor’s whitepaper, “Setting Your Data in Motion.” This paper is the first in Dun & Bradstreet’s Master Data Knowledge Series, where we’ll cover the many benefits of taking the Master Data approach. Subsequent papers will address the practical aspects of putting a program in place.

Download Whitepaper

 

 

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