The Flawed Vision of Customer Data Integration – How to Get It Right the First Time?


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The early pioneers of Customer Data Integration (CDI) had a primary goal – to create the most reliable customer data for the company by bringing together and resolving inconsistent, and oftentimes incomplete, customer data which was at the time siloed in disparate applications across the enterprise. The CDI promise was to have reliable customer data available to benefit a myriad of customer-facing operations in marketing, merchandising, contracting, account management and invoicing, to name a few. Focusing on these priorities, many organizations selected a CDI technology that enabled them to solely optimize customer data. Other enterprise data such as products, locations, and accounts, for example, were considered out of scope and not necessary for the initial CDI project.

While incremental benefits were gained with this approach, many companies that were caught up in this early CDI gold rush soon realized in hindsight that their CDI projects missed the big picture. Take the example of Bank X, a major financial services firm providing a range of banking, investment, and trust services to small and mid-sized businesses, entrepreneurs, professionals, and affluent individuals. Their CDI system did provide the answer to “who is my customer?” by solving the mystery of exactly who they were interacting with – whether it was an individual or an organization. However they were unable to realize that Fred Jones, who has a 401k account through his employer, is also a high net worth client due to his lucrative individual accounts. As a result, they were not able to answer the critical question of “how do my customer interactions across all of the banking services affect my business?” This lack of insight led to unrealized revenue potential as a result of unexplored opportunities to cross-sell new banking products to this individual.

The Traits of a Visionary CDI

The true golden opportunity for CDI lies in its ability to uncover the depth of interactions and to understand the relationships companies have with their customers. This level of insight is a significant business value and one that organizations can’t afford to overlook. Enter Bank Y, a competitor to Bank X with the same lines of business. Bank Y realized early on in their CDI planning that their business solution should extend beyond mere identification and correction of their individual and business customers. Their key objective was to gain a 360-degree view into the multiple relationships each had among themselves, their accounts and their locations. While the resolution and accuracy of their customer details were important, it was only a precursor to the critical relationships that needed to be unearthed across customer and other types of related data such as accounts and locations.

With this as a core requirement, Bank Y needed a CDI technology that could handle entity types beyond just customer. The technology also needed to deliver rich relationship management and visualization capabilities such as client-to-account, account-to-organization, and organization-to-organization. This led them in search of a flexible CDI technology that could solve not just their current, but future challenges as well. In essence, Bank Y needed a CDI platform which would allow them to have:

· A single view of each of their individual and business customers and the relationship among them, their accounts, and locations.

· Highly accurate, real-time visibility into their customers’ assets, liabilities, profitability, and risk profiles.

· Greater knowledge of customer information and account/organization relationships in order to accommodate and comply with industry and government regulations.

CDI Evolves into MDM

Bank Y certainly wasn’t thinking about adopting a multi-domain Master Data Management (MDM) when they first started out. Ironically today, they are positioned to perform MDM processes on other data beyond customer using the same CDI platform with which they began their journey. The same fundamental concepts for identifying and resolving customer data are equally applicable to other data such as product, funds, and accounts. Although their vision began with CDI, the Bank is now well-positioned for the next phase in their vision.

CDI to MDM: A Vision Repeated Across Industries

There are many instances of visionary CDI success in other industries as well. One example involves a pharmaceutical giant with a Gartner award-winning deployment. They extended their CDI vision beyond customer data to include contracts, organizations, delivery channels and pricing. Ultimately, they created a highly efficient system that utilizes relationships across these different data types to:

· More accurately process payments, rebates and disputes.

· Produce reliable reports and performance metrics.

· Better comply with regulations requiring controls over data such as SOX.

· Increase customer service levels through error prevention, perfect orders, timely payments and end-to-end experiences.

· Adapt more quickly to changing market conditions.

· Introduce new products into the sales channel faster.

· Improve the sourcing of new customers and negotiation of new contracts.

· Resolve potential problems faster.

· Manage data and fix errors in contracting, finance and supply chain using fewer resources.

· Drive down the rate of write-offs, unresolved disputes and deductions.

This expansion to a broader use case enabled them to increase their return in their multi-domain MDM technology investment, which would not have been possible if had they stayed with simply mastering customer data.

CDI Done Right

Three or four years ago, many vendors were happy to portray CDI as a small problem. You just needed a CDI tool to get it done quickly, then your CRM and other customer-facing systems would be harmoniously integrated with accurate, real-time customer information and the business benefits would naturally flow from there. It was a flawed vision that did not take into account that larger business benefits can be realized by tying the customer data to other enterprise data to enable a true 360-degree view.

Multi-domain MDM is certainly the logical progression that enables data integration beyond the single class of customer data for larger benefit realization.

These five simple steps start the journey from CDI to MDM:

1. Identify the complete business problem – Don’t narrowly conclude that a CDI tool is the only solution to inconsistent and duplicate customer data. Instead, identify the complete range of business problems that stem from poor customer data quality. In many cases, it might be poor customer service, an inability to cross-sell and up-sell, or non-compliance with regulations. In all these cases, fixing just the customer data might not solve the business problem.

2. Validate it with the business users – Although IT might implement the MDM technology to create reliable master data, it is the line of business people who benefit from such clean data. Include them in the discovery process to determine which types of data, and the relationships among them, will need to be addressed to solve the complete business problem.

3. Select a flexible multi-domain MDM technology – Ensure that the technology you select can handle multi-domain MDM – customer, product, account, location, and so forth – and the complex relationships among them. Beware of vendors who claim MDM and relationship management capabilities, but offer a product that cannot handle anything beyond mere identification and correction of customer data. Most importantly, ask for customer references.

4. Start with customer data – Centrally create reliable customer data and supply it back to the business process that will benefit from such data.

5. Expand to other data and their relationship with customer data – Remember, the business problem is not solved in its entirety until other enterprise data and their relationships with customer data are mastered. Note that the same MDM technology is leveraged for higher return on investment.

Following in Visionary Footsteps

The common thread among firms with the most successful CDI implementations is that they understood CDI as a starting point in a larger business progression. Those firms deriving the greatest value from their CDI investments are the ones that started by integrating customer data and then progressed to integrate that unified, real-time view of customers with other classes of enterprise data sourced from operational systems including: product, account, organization, and location. These visionaries understood that a customer-only CDI platform in and of itself has limited value, and that broader value can be realized by integrating it with other data in a true multi-domain MDM form. By following these visionaries’ footsteps, you will be well on your way to reaping the benefits from not only your initial CDI efforts but also from the larger multi-domain MDM initiative as well.

Ravi Shankar
Ravi Shankar is Senior Director, MDM Product Marketing, Informatica. Shankar is responsible for product and technical marketing activities for master data management (MDM) as part of the Data Quality business unit at Informatica. Shankar joined Informatica following the Siperian acquisition, where he ran product marketing. He helped position the company as a proven leader in multidomain MDM.


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