Is Poor Data Quality Affecting Your Revenue Potential?
Is your organization spending too much time or not enough time analyzing the quality of your data? Is it becoming difficult to identify the business unit responsible for managing your data quality. Most organization will rely solely on IT to fix data quality issues but each business unit (manufacturing, product development, marketing and sales) has a responsibility to assure that data is of quality in reference to how the data is entered, stored and managed. Poor data quality can negatively impact an organization in several ways, especially as it continues to increase and expands its data within a complex, multi-tier ecosystem. The provocation to enhancing data quality derives from two main factors: reducing overall IT cost and the need to improve risk management associated to data quality.
Data Quality is the multi-tier measurement of the competence of a particular data set. Organizations leverage data quality for business intelligence and organizational decisions.
Features of Data Quality include:
- Update status
- Consistency across Data Sources
- Appropriate presentation
What can be done to Boost Data Quality?
Implementation of accessing data quality should rely on the business area responsible for the data, this will make it possible to detect the quality issues upfront. To assure a successful data quality process, a data management plan should be put in place to identify the root of the data problem, validating the values of data and change business processes to improve the future data sets.
If your business does not have a handle on data quality, then related costs and risk will prove to be difficult to manage. The following data quality attributes are the most desirable because they offer business value:
Reliability of Data is paramount in assuring that data quality is held at a particular standard. Is your organization capable of performing efficiently in your current data quality process? What is the likelihood that your reduction in revenue is directly resulting from the quality of your data? Is your organization not properly monitoring data quality? If not, then the chances of data failures, security breaches, and compliance issue become much higher.
Data Quality Analysis Improves Implementation Results
“Following Data Quality Best Practices generates a 66% increase in revenue *
* “The Impact of Bad Data on Demand Creation” Sirius Decisions, 2012
Poor or inefficient data can decrease revenue potential and cause system wide critical errors. The ability to quickly alleviate complexity or risk directly associated with data, results in a more cost efficient organization. Being able to access the reliability of the business data for sales can directly impact sales revenue for better or worst. Accessing the reliability of customer data can reduce the cost of shipping issues or cross-selling/up-selling opportunities in relationship to the quality of data provided or inputted on new and existing customers. Data quality control provides specific benefits including:
- Speed Up Organizational Decisions
- Insightful Business Intelligence
- Improved Data Health
- Elimination of Hidden Data Risks
- Regained Control of Legacy Data Sets
- Exclude, Accept and Correct Data
Early data problem identification provides the opportunity to boost performance, reliability, and productivity within an organization. Improved data quality also allows an organization to decrease technical debt and associated risks. ASTRA offers a solution for analyzing data quality and regaining control. If inconsistent data is taking away from organization performance or increasing costs, it may be time to consider a data quality process to better identify these data problems long before they cause extensive internal and external damage.
Learn how to improve your bottom line with ASTRA which provides better accuracy, accessibility and reliability of Data. Click here for a free demo.