The Importance of Data Quality:

Data is the life-blood of technology systems. Data drives system functionality, management reporting and decision-making, and if used effectively, data is a major source of competitive advantage. Data can also be an Achilles' heal for organizations in that data is often the basis of legal, political, or public image problems. Ensuring that data is of the highest quality is a major challenge, yet one that organizations cannot afford to overlook.

Data must be of high quality to be of value. That is, the data must be accurate, reliable, complete, and timely. Individuals must trust that the data is useful and relevant to the task at hand if they are to utilize the data and the system. Poor quality data is of little use to an organization (garbage in = garbage out) and is a legitimate reason not to use a system.

The Huge Cost of Data Quality Problems:

The costs of data quality problems are huge and often overlooked. Data quality costs are both direct and indirect.

Direct Costs of Poor Data Quality:
Direct data quality costs are those that have are easily quantifiable and measurable. It is important to remember that these costs are incurred each time the data is used! Examples include:

• Financial costs resulting from to delays in invoicing and receiving payments. This is often due to incorrect product, transaction, or customer contact data;
• Hours wasted tracking down correct information due to incomplete or inaccurate system data. Multiply hours wasted by the employees salary to get a direct financial impact.
• Publication, postage and handling costs for sending marketing materials to inappropriately targeted recipients or recipients with inaccurate contact information.
• The costs of litigation, lost business, or reputation damage due to release of inaccurate or confidential data.

Indirect Costs of Poor Quality Data:
Indirect costs are those that negatively impact the organization but are not easily quantified. Indirect costs include:

•  Low user adoption of the system
•  Unreliable management reporting
•  Customer services and satisfaction problems
•  The opportunity cost of time spent resolving issues caused by data quality problems
•  User frustration with the system

While there costs of data quality are high , the benefits of improving data quality are numerous. High quality data reduces wasted time and resources, increased reliability and usability of the system, and enable more accurate reporting and analysis that improves decision-making.

Solving the Data Quality Problem:
So why do so many organizations struggle to cultivate and maintain high quality data? Often this is due to misconceptions about the nature, cause and solution for data quality problems. Misconceptions include:

• Underestimating the cost and impact of data quality on the organization
• Treating data quality as a technical problem with a technical solution
• Embarking on a one-time data cleanup project, often conducted during the initial system deployment

At TriTuns Innovation we recognize that poor data quality is a behavioral problem, not a technology problem. Data is entered, reviewed, used, and updated by individuals. It is up to individuals to ensure that it is accurate and of the highest quality. Thus, individuals must adjust their behavior to cultivate and maintain high quality data.

TriTuns Innovation helps clients develop a comprehensive program based on ensuring accountability for the prevention, detection, and correction of data problems. We use our expertise in identifying the needs, structural elements, skills, processes, management practices, tools and reward systems required to introduce a successful data quality program in your organization. TriTuns Innovation then guides clients through the difficult transition from program design to implementation.

Please contact TriTuns Innovation to learn more learn more about how we can help you achieve higher quality data and realize all the benefits it provides.