Data Quality Engineering in Financial Services

Chapter 6. Operational Efficiency Cost Model

This chapter presents a cost-based model that illustrates the cost of incorrect, out-of-tolerance data to a financial firm’s operational efficiency. It is not a theoretical or subjective model, but rather a model that is based on the real costs of the employees’ time that is spent and wasted when their work is affected by poor-quality data.

Demonstrating to your firm the benefits and impact of high-quality data can be challenging. We often hear stories about how data quality directly affects a firm’s operation, and typically, these stories tend to be about negative events. Generally, you do not hear colleagues at the water cooler praising the quality of their data. Yet, you may hear something like, “I just spent half my day trying to figure out why the data was wrong.”

The operational efficiency model we’ll use in this chapter is designed to clearly demonstrate the cost of incorrect data in terms of employees’ time and effort to work with and fix incorrect or misaligned data within a business function. The model also demonstrates the value of accurate data, which allows employees to spend their time efficiently instead of wasting their time triaging and solving data quality issues.

Model Details

This simple model is designed to demonstrate the cost of data, the cost of incorrect data, and the cost savings that can result from using pre-use data validations that employ the DQS framework versus post-use reconciliation ...