Published on Alvarez & Marsal | Management Consulting | Professional Services(https://www.alvarezandmarsal.com)

January 17, 2013

While there are many challenges faced when creating the enterprise view of a customer, the pervasive useof relational database technology has been one of the key enablers assisting organizations with thedevelopment of a flexible data model. Although creating this model is by no means a mission impossible— it is possible, portable and reusable, once all business components and rules are logically defined.

The goal of this article is to provide an appreciation of moving toward the creation of an enterprise viewand the value that can be exploited from achieving such a goal.

For more than 20 years, both businesses and information technology sought after the perceived benefits ofthe enterprise view and quickly realized the challenges set upon them. Those challenges varied across awide spectrum — from political aversion, mainly driven by a silo effect (see diagram below) and the needby certain industries to keep customer information proprietary across specified lines of business. The otherconstraint was due to high estimated costs relative to the development, maintenance and lack oftechnology and expertise — compounded by the ability to think through a flexible database design tohandle changes such as mergers and acquisitions to integrate a newly procured business into existing dataframeworks. Instead, most industries decided to allow for multiple customer databases driven by thespecific businesses that owned the customer. Keep in mind that many organizations can still have multipleancillary customer databases within each silo, fragmenting the view even more.

Siloed Customer View By Business

Mission Impossible? Creating a Single Enterprise View of the Customer

During the late 1980s and 1990s Information Engineering was touted as the most innovative methodologyto shepherd in such a concept, since its focus was on exploiting the use of relational database designthrough the use of CASE Technology and active (or passive) data dictionaries. That approach focused ondeveloping conceptual designs through the use of data and process diagrams with a key ingredient:building a strong partnership with the business user community for requirements, approval and ongoingdevelopment to meet evolving needs over time. The overall goal was to have the business drive thetechnology solutions, not the other way around.

By the late 1990s, Customer Relationship Management (CRM) questioned the need to put such a model inplace to accommodate marketing needs, using a one-size fits all approach. By late 2001, with theexpansion of compliance requirements, such as the USA PATRIOT Act, the need for an enterprise view wasbeing echoed again at conferences, by regulators, business users and technologists.

In 2013, the business need is still alive and well, with few positive results. It is still perceived to be adaunting task that has now found a stewardship in the Financial Services’ Compliance Department andRisk Management — an interesting place that does not have customer ownership, but has a reliance onvarious data elements to meet their “know your customer” regulatory obligations combined with theproducts and services used. Regardles of their responsibility for risk rating and monitoring transactionsagainst a comprehensive view of the customer, they do not create the customer, but maintain attributeswithin the profile for review. Based on the compliance business mandate and regulatory obligations, it iscritical that a comprehensive customer profile, through an Enterprise View, is maintained and reviewed sothat accurate (or close to accurate) information is maintained and accessible by both owners and specifiedbusiness areas.

Developing a Model

So how does an organization achieve its goal in implementing the enterprise view of the customer? Thefirst step is to develop a conceptual customer data model representing relationships to core entities,defining business rules (also referred to as relationships) and capturing the salient attributes; thecombination represents high-level requirements easily understood by both users and technologists. Oncecompleted, the model must be reviewed by the business owners to ensure accuracy of the rules and

attribute definitions, while providing the foundation for database design.

Once a consensus is reached by the business owners, two key steps must take place: (1) creation of anormalized logical data model and (2) inventory and assessment of the current customer data. Thecreation of a normalized (3rd Normal Form or 3NF) data model assists in defining all attributes,dependencies and to ensure that a comprehensive list of business rules are in place before creating thephysical database design. By taking an inventory and assessment of the current customer data,determinations will be made as to the extent of the cleansing effort. Some examples of common customercleansing techniques used are street address standardization against the U.S. Post Office database and thestandardization of common name prefixes, suffixes, and honorifics (i.e., Esq., Col.). Data cleansing andtransformation will require extensive efforts, but can be expedited by using third-party software andengaging individuals that have spent years fine-tuning the process, coupled with the use of an Extraction,Transformation and Load (ETL) application for mapping, edits and validation. Data augmentation mayrequire an organization to use external data sources (e.g., Dun & Bradstreet) to provide additional data likeorganizational structures and names of senior management. A&M recommends using an ETL tool, insteadof building your own load process. These tools are proven while providing the integration effort with aconsistent, reusable and auditable process.

The Next Step

The next step is the creation of the physical data structures (tables, columns and rows). The normalizedmodel does not typically result in a one-to-one match to the physical data structures. There is a series ofcalculations and reviews executed based on data load approaches and complexities associated to variousaccess methods (e.g., views). Typically, this work is performed by the Data Administrator (representing thebusiness) and the Database Administrator. Also keep in mind that the Data Administrator role is a rare, butbadly needed, position in many organizations. Therefore, it is important that all customer-centric areasparticipate and communicate their access and specific requirements to the Data Administrator, since mostof their information needs will be met through various levels of reporting and access paths to the customerinformation. Moreover, a thorough review of ancillary processes supporting a specific department’s policiesand procedures requires scrutiny to ensure that the data captured in the customer profile reflects thestated information needs.

As an example, a bank’s Legal or Compliance department, specifically BSA / AML, uses tools to assist inmeeting regulatory obligations, such as transaction monitoring and interdiction applications for watch-listreviews. Because there are various levels of reviews needed to truly know the customer, the departmentwill require update and read access. By granting this access, it allows the Compliance Department toupdate specific attributes, such as risk ranking (or ratings), based on the customers’ behavior over time.This information can occur in one of two ways: manually, as mentioned where the Compliance Departmentupdates the customer risk rating through the user interface, or from an automated feedback that providesan updated score on a monthly basis, using the information gathered from alert generation whentransaction activity exceeds (or undervalues) the anticipated (or assigned) score. In some cases,Compliance may require override capabilities, timestamping the rating differences, while maintaining anaudit trail of the updates. If overriding existing risk ratings from an automated feed is not desired,providing reporting capabilities with potential changes, with a subsequent manual review, could be used asan alternative. The overall goal is to provide an aquifer of meaningful information to enhance Compliance’sreview process, along with other customer-centric departments in terms of knowing their customers, whileminimizing risk.

Reaping the Benefits

It should be clear to see how the benefits provided by the enterprise view of a customer can easilyoutweigh the costs over time. The summarized list below shows the positive results that A&M has seenorganizations capitalize on over the years, while both minimizing risks internally and increasing customersatisfaction across the brand.

The diagram that follows is a simplified illustration depicting the Enterprise View at the center of allcustomer related functions (directly and indirectly) within a global banking organization and could apply toany industry sector.

Enterprise View By Business and Function Areas

Here are some inherent benefits from implementing an Enterprise View of your Customer:

Consolidates all products and services at the customer / party level, while contributing to theelimination of data duplicationProvides better customer intelligence across the board to manage risk, profitability and productdevelopment (e.g., cross-selling)Defines other meaningful relationships, directly and indirectly (e.g., householding)Timely and frequent updates to critical business attributes (i.e., risk ranking / scoring, credit scores,demographics) to better understand the clients’ customersProvides the capabilities to meet regulatory obligations for financial institutions, as well asobligations for other industries (FATCA, FCPA, AML)Better controls over managing customer and business expectations

Mission impossible? Moving to an Enterprise View is not a business option for the 21st century, but a longoverdue strategy that every business needs to have put in place, providing the competitive advantage onall fronts.

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Authors:Peter Kwan, http://pkwan@alvarezandmarsal.com, +1 212 763 9674