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The Business Value of Data Standards

  • June 01 2004, 1:00am EDT
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Data Standards Yield Both Long- and Short-Term Benefits

This month, we will continue the exploration of the definition and use of data standards by looking at the business value.

The most important concept to keep in mind when discussing the definition and use of data standards is predictability. Predictability associated with information exchange allows application developers to design and implement application architectures that can exploit expectations to allow for more efficient processing. These expectations encapsulate business value statements such as:

  1. Enabling effective sharing of information between collaborating partners - improving communication that, in turn, improves collections.
  2. Reducing the amount of manual intervention in information processing and facilitating straight-through processing, which increases productivity and can reduce costs.
  3. Establishing a repository of definitions of common business terms used across your organization's enterprise.
  4. Providing a means for publishing those definitions for the benefit of your information exchange partners.
  5. Streamlining on-demand client access to improve knowledge-worker workflow.
  6. Improving the quality and consistency of enterprise information.
  7. Supporting the ongoing adoption of the use of standard data elements in coordination with any kind of application or system modernization.
  8. Promoting the migration to a services-based architecture, which will simplify the process for improving and extending production systems.
  9. Promoting the evolution of an enterprise architecture.

These value statements all address one or more value propositions related to the way your organization does business. Following are some examples.
Reducing manual intervention increases knowledge-worker productivity, as long as their time is spent (for the most part) on remediation of issues that cannot be captured and reconciled automatically based on the use of standards and automated business rules.

Facilitating automated straight-through processing will result in increased processing volumes and increased throughput, which ultimately reduces the individual operational processing cost per transaction.

Data standards can provide a blueprint for new or modernized application development, which will result in reduced costs to deploy a system. Having data standards for both interchange and information modeling against which the deployed system can be checked may contribute to an overall lowering of the total cost of operations.

Streamlining on-demand access to information can improve interactive workflows that might have been impeded due to limited trust or limited access to information. Improved workflows will increase customer interaction throughput, resulting in improved customer relations.

Clearly defining information exchange requirements will enhance the ability to automate interaction with external partners via a services-based architecture, allowing for unsupervised provision of information-based transactions.

Aggregating and subsequently publishing your organization's business terms, their corresponding definitions and any formatting and exchange standards is a good way to capture corporate knowledge as content, which then can be managed (and perhaps even be made subject to taxonomy analysis). Doing so will enhance your approach to knowledge management as well.

I can't help but interject a short bit about the criticality of the relationship between data standards and an organizational data quality strategy. Any exercise used to resolve differences in perception and understanding of the meaning of data within the business operations context will contribute to the improvement of the quality of information. This is especially true when individuals in separate organizations who are responsible for exchanging data sit down and talk.

In addition, because data standards contribute to a baseline for determining the difference between "valid" and "invalid" exchanges and, consequently, measuring some aspects of information compliance, their existence helps in defining metrics that can contribute to an overall information quality scorecard. Measuring validity and using the results of these metrics to assess the quality of information exchanged and to determine root causes of exposed problems, especially during information exchange, is a large part of any organization's information quality strategy.

Reviewing the business value of defining and using data standards in concert with your set of organizational business requirements shows how tightly coupled effective data standards are to any enterprise architecture effort. While your organization's long-term goals are affected by the definition and use of standards, it does not preclude short-term benefits that can be achieved as well. However, keeping any data standards efforts consistent with these long-term intentions will contribute significantly to the success of any ongoing information architecture and design program.

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