Introduction – Data Quality as a Cost Reduction Technique

There is no arguing that information technology (IT) is typically a cost center, in which many different types of operating costs are incurred, accumulated and offset against organizational revenues and profits. As a core component of IT, the staff, hardware, software and support dedicated to data management is often directly accountable for many of those costs. But although data management contributes to corporate expenses, there remain opportunities to apply best practices in data quality management as techniques that can reduce expenses across the board.

There are different aspects to the meaning of “cost reduction.” To some, it focuses solely on eliminating or reducing operational expenses. But reduced costs are often linked to increased efficiencies in day-to-day operations as well as improved performance for revenue-generating activities. In other words, within the scope of a performance-oriented organization, data quality management can be used to seek out operational efficiencies for cost reduction, leading to increased margins and, consequently, increased profits.

This paper will review aspects of cost reduction by examining some typical financial accounting expense categories. The paper then selects some specific examples and assesses their reliance on high-quality data. In turn, the paper looks at how data quality services can be applied in those examples to reduce expenses. Last, we reiterate the potential for applying data quality management as a way to manage and reduce organizational expenses.

Understanding Expenses

The objective of a program identifying operational efficiency may signify a “slash and burn” approach to reducing expenses. However, eliminating staff or services necessary to keep the business running will increase not only the workload for staff remaining after a layoff, but it also reduces the effectiveness in fulfilling those tasks and ultimately detracts from the employee experience. This leads to increased turnover and an overall reduction in organizational knowledge.

Reducing expenses is more about being smart in understanding where costs have exceeded reasonable levels and determining ways to identify and eliminate excessive costs. And this is where quality data comes in – if the source of waste can be attributed to situations in which successful business operations are negatively impacted by poor data quality, then (logic would suggest) data quality improvement will help in identifying ways to streamline processes and reduce costs. More importantly, the effects of applying these techniques during weaker economic times will train people to work smarter in the future, helping the organization improve competitiveness and agility during economic recovery and expansion.

The challenge for the data professional lies not in the knowledge of good data management techniques, but in understanding the financial lingua franca that describes how money is spent in order to run a business, usually encapsulated within the finance department’s chart of accounts. This chart lists the “channels” through which money flows into and out of the organization.