Data-Driven Transformation Brings Tech Giant Closer to Its Customers

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Rapid Growth of Big Data Prompts Data Management Innovations

According to Statista, big data – that is, large datasets that can reveal buyer behavior – has grown sevenfold in the past decade.1 This rapid growth is creating an urgency within businesses to identify and adopt innovative approaches to collecting, analyzing, and democratizing customer data across the organization.

One of Dun & Bradstreet’s long-standing clients, a large global technology company, deals with a tremendous influx of data every day. It wanted to harness its big data in order to gain a better understanding of its large, diverse global customer portfolio. To accomplish this goal, the company aggregated data from across the enterprise into a single source of truth that fueled its go-to-market and support teams around the world.

Data Governance Fuels Digital Transformation

The company’s goals were to:

  • Make data broadly available
  • Remove the silos across legacy systems and, as a result, reduce the complexity of the legacy data structures
  • Make it easy for users to find the data they’re looking for

According to the manager of information governance, “Our vision is to collect data from hundreds of sources utilizing cognitive solutions and use it to automate our operational processes.”

However, this wasn’t going to be a case of “build it and (hope) they will come.” Internal engagement with business units was paramount, with regular meetings to discuss the issues facing the use of data, how it’s accessed, and standardization. The company created a consistent, collaborative message around data that infiltrates the business and enables strategy across the business units.

Also, for enterprises embracing cognitive solutions and becoming more AI-enabled, having a solid data foundation and a clear data strategy is a critical foundational step. To support this, our client underwent a cultural shift to drive change and implemented large-scale adoption of data as an asset in its data-driven enterprise.

One of the project leaders commented, “Establishing an enterprisewide, common data strategy is not easy. You’re asking people to give up their silos. You’re asking people to modify their processes so that they treat data consistently, and it’s not just data processes, but it’s also actual functional processes. You’re often talking about changing very fundamental operational processes so that the data is consistent and can be linked up throughout the enterprise.”

Meeting the Demanding Market Expectations of the Digital Economy

Dun & Bradstreet partnered with our client to develop an innovative approach to data-driven transformation and embarked on a journey to build a centralized data management system that would reconcile, match, and improve customer data throughout its life cycle. A vision for a Customer Enterprise Data Platform (CEDP) emerged that would be our client’s data lake for customer data. Data was ingested from over 300 core systems – over a trillion records, with a refresh of more than a billion records a week on a regular schedule.

Through direct access to the Dun & Bradstreet Data Cloud, the company was able to resolve and standardize hundreds of sources and enrich records. It started by identifying customers with a unique key, the Dun & Bradstreet D-U-N-S Number®, which anchors Dun & Bradstreet’s Live Business Identity.

With one key for all customer master records, the company could append a wealth of other information associated with that key. The trusted data would be accessible to downstream systems such as CRM, MAP, and ERP, providing all teams across the enterprise with a common, standard definition of the customer, to empower decision-making throughout the organization.

data workflow diagram

Company records are matched to Dun & Bradstreet reference data. When the records meet Dun & Bradstreet’s high-confidence match criteria, they are approved to enter downstream systems across procurement, finance, sales, and marketing. If a customer matched record changes or is manually manipulated by a team member, the Dun & Bradstreet API validates the change thus ensuring data accuracy and integrity across these matched records throughout their lifetime.


The CEDP supports all business units and is helping build a 360-degree customer view. Users can start at the top of a company to see their overall revenue contribution to the business and drill all the way down to view even minor support cases. Before working with Dun & Bradstreet, it wasn’t uncommon for our client to find 21 records representing the same customer. Now, because of the CEDP, one common key represents one customer. Users can more easily find the data they’re looking for, faster and more easily, because they’ve standardized terms through AI and cognitive technology, embedded data governance into their processes, and worked with stakeholders to migrate data consistently.

Improvement in Data Quality and Efficiency

Increased match performance: In the first 18 months of the project, the client has seen a 20% increase in high-confidence match resolution through the Dun & Bradstreet Data Cloud. As a result, 81% of global customer records have a high confidence D-U-N-S Number assignment, which is enriched dynamically in near real time as compared to the three-to-four-month lag the team previously experienced. We’re working together with this client toward the goal of 100% identity resolution by incorporating new sources of data that will help the client build cognitive solutions to improve business value for its customers.

Access to near-real-time data: With real-time data feeding the CEDP, business units around the world are now able to react faster to changing customer demands. This was critical to meet the demanding market expectations of the digital economy. Productivity savings are estimated by the company to be at least $27 million.

Customer interaction: With the CEDP, business users can find more accurate answers to their questions, faster. This has enabled customer support agents to spend more time with customers on the difficult problems where the company actually needs to have a personal interaction with the customer. As a result, its Net Promoter Score increased 11 points.

Additional data sources: Looking ahead, the company is partnering with Dun & Bradstreet to realize the innovative potential behind its unstructured data, incorporating digital signals such as customer social media and mobile interactions into its data environment, resulting in an even more comprehensive view of its customers. “The next step in our journey is annotating unstructured data about businesses around the globe,” stated the manager of information governance. “Our marketing and sales teams are interested in monitoring digital and social media signals to add more intelligence to how we can better serve our customers. We want to expand what we know about the customer to include what the market knows about the customer.”

Summing up the project, he continued, “With Dun & Bradstreet’s strength in B2B data and our innovative technology, we have a huge opportunity to bring a well-rounded and fruitful solution to better understand our customers.” 

data workflow diagram

Best Practices

  • Treat your data as a corporate asset.
  • Focus on eradicating silos and driving change management.
  • Embed governance across all your functions and business decisions.
  • Results don’t happen overnight. Remember that this is a marathon, not a sprint.


1. Statista, Forecast Revenue Big Data Market Worldwide 2011-2027

We like to share our customers’ successes and inspire other teams that face similar challenges. Due to the sensitive nature of some customers’ businesses and their data strategies, we respect their privacy and do not identify them by name.


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