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How to Map Data Governance Policies to Business Processes by Sunil Soares

Business process management and data governance are beginning to converge. Data governance practitioners need to take advantage of this trend for the following reasons:

  • Address data at the source – Data stewards can use data profiling tools and data quality scorecards to uncover issues with the underlying data. However, the intelligent use of BPM tools can help data stewards reach back into upstream processes to fix data quality issues at the point of creation.
  • Focus data stewardship efforts – The data governance program will have a higher probability of success if it focuses on a high impact business process and a handful of critical attributes.
  • Sell the value of data governance to the business – The business may say that IT owns the data, but they will never say that IT owns the business process. So starting from the business process is a good way to engage business users around data governance.

Figure 1: Mapping of corporate banking customer on-boarding process

This article discusses the process that a bank would go through to on-board corporate customers. The process described here is highly simplified, but it serves to demonstrate the core tenets associated with the mapping of data governance policies to business processes.

The process involves two actors:

  1. Sales signs a contract with the customer.
  2. Operations handles all the other aspects of the customer on-boarding process. Customer data stewards reside within Operations. These data stewards establish policies in conjunction with other departments, such as Risk. There will be separate data stewardship departments for local customers (with operations in only one country) and global customers (with operations across more than one country).

We describe each activity below along with a short description and sample data governance policies that need to be established by the data stewards.

1. Sign the Contract with the Customer
Description: The Sales department signs a contract with a customer that may have multiple subsidiaries all over the world.
Sample Data Governance Policy: A business definition for customer: “Customer is anybody to whom we deliver services for payment.”

2. Set Up Identity Information
Description: This includes the legal name, previous legal names and legal form.
Sample Data Governance Policies: Legal name is the registered legal name of the entity as found in its native language on its documentation of incorporation. The legal name has a maximum of 175 characters and may include Unicode characters.
Legal norm depends upon the jurisdiction of the entity and is often appended to the legal name. The list of acceptable legal forms includes, but is not limited to, Limited Liability Company, Limited Partnership, Public Limited Company, Private Limited Company, General Partnership and Sole Proprietor.

3. Set Up Other Attributes
Description: North American Industry Classification System is the standard used by U.S. federal agencies to collect statistical data by industry.
Sample Data Governance Policies:
Reference data – The bank may gather reference data on acceptable NAICS codes.
Conglomerates – In the case of conglomerates with subsidiaries that operate in multiple industries, the bank will use the industry with the most revenues for the entire group.

4. Set Up Address and Contacts
Description: Address should include both the address of incorporation and the mailing address. Contact information may include phone, fax and email for individual contacts within corporations.
Sample Data Governance Policies: The address of incorporation should be based on the document of incorporation. It should not be the address where the headquarters are located, where the company is physically operating, or other alternatives.
Email address – Customer data stewards need to establish consistent data validation rules for contact information. For example, email addresses need to adhere to a specific format from the Internet Engineering Task Force.

5. Set Up Legal Hierarchy
Description: Banks consider two organizations to be part of a legal hierarchy when the overall credit exposure needs to be aggregated for risk purposes. For example, any exposure to GE Japan would potentially need to be included within the overall exposure to GE.
Sample Data Governance Policies:
Definition – A legal hierarchy incorporates situations where a company owns more than 50 percent of another company or controls the operations of another company, even if it owns less than 50 percent of that company.
Timing of changes to hierarchies – When a company announces the acquisition of another company, the legal hierarchy needs to be updated at the time of the announcement as opposed to the effective date of the acquisition.
Sovereign risk – In the case of customers with operations in multiple countries, the bank will take the “worst” country risk across the country of incorporation, the country of the guarantor and the country of primary operations.

6. Set Up Economic Hierarchy
Description: An economic hierarchy incorporates situations where one or more companies are tied together economically.
Sample Data Governance Policies: The customer data stewards will identify the situations where economic hierarchies need to be maintained. An example may include the franchisees of a specific fast food chain.

This is a very simplistic example, but it shows the value of focusing data governance efforts on a single high-value business process and a handful of critical attributes.

Click here to see full post published on www.information-management...

Sunil Soares is the founder and managing partner of Information Asset, LLC, a consulting firm that specializes in helping organizations build out their data governance programs. Prior to this role, Sunil was the Director of Information Governance at IBM, and worked with clients across six continents and multiple industries. Sunil’s first book, "The IBM Data Governance Unified Process," details the 14 steps and almost 100 sub-steps to implement a data governance program. The book has been used by several organizations as the blueprint for their data governance programs, and has also been translated into Chinese. Sunil’s second book, "Selling Information Governance to the Business: Best Practices by Industry and Job Function," reviews the best way to approach data governance by industry and function. Sunil’s third book, "Big Data Governance," reviews the importance of data governance for different types of big data such as social media, machine-to-machine, big transaction data, biometrics, and human generated data. Sunil has also worked at the Financial Services Strategy Consulting Practice of Booz Allen & Hamilton in New York. Sunil lives in New Jersey and holds an MBA in Finance and Marketing from the University of Chicago Booth School of Business.

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