Develop automated services for validating data records against the quality rules you have defined. A strategic implementation enables the rules and validation mechanisms to be shared across applications and deployed at various locations in an organization's information flow for continuous data inspection and quality measurement.
The results can be fed into a variety of reporting schemes -- for example, direct notifications and alerts sent to data stewards to address anomalies and high-priority data flaws, and data quality dashboards and scorecards with aggregated metrics for a wider audience.
- Understanding and managing customer requirements.
- Aligning key business processes to achieve those requirements.
- Utilizing rigorous data analysis to minimize variation in those processes.
- Driving rapid and sustainable improvement to business processes.
Improvement initiative should focus on the essential processes necessary to meet customer expectations.
These are the main processes that enable the organization to add value to goods and services and supply them to customers. Implicit within this is an understanding of what the customers - internal and external - actually want and need.
- Identifying and understanding these processes in detail.
- Understanding the levels of quality (especially tolerance of variation) that customers (internal and external) expect.
- Measuring the effectiveness and efficiency of each process performance.
Identification of the key processes relating to hard copy/print within the organization that determine effectively meeting customer expectations; then measuring the effectiveness and efficiency of the processes (notably measuring variation in quality and analyzing the causes), and then initiating improvements in the weakest processes.
Data quality assessment: to identify data errors and erroneous data elements and to measure the impact of various data-driven business processes. Both components - to identify errors and to understand their implications - are critical. Data quality assessment can be accomplished in different ways, from simple qualitative assessment to detailed quantitative measurement. Assessments can be made based on general knowledge, guiding principles or specific standards.
The purpose of data quality assessment is to understand the condition of data in relation to expectations or particular purposes or both and to draw a conclusion about whether it meets expectations or satisfies the requirements of particular purposes. This process always implies the need also to understand how effectively data represents the objects, events and concepts it is designed to represent. It is critical to understand vendor support capabilities and systems data collection methodology to insure that you are reviewing data significant to performance of in place SLA.
That is where partnering with an experienced Copier and Printer Management Consultant, to benefit from their collective knowledge, brings results that can maximize process improvements and cost savings.