By Joe DeSiena, President Consulting Services
Many organizations can achieve data quality by applying the most effective methodology for accelerating the data cleansing and control processes.
The ten major steps that must be taken to achieve Data Quality are:
- Acknowledge the problem
- Identify the root causes
- Determine the scope of the problem by prioritizing data importance and performing the necessary data assessments
- Estimate the anticipated ROI, focusing on the difference between the cost of improving Data Quality vs. the cost of doing nothing
- Establish a single owner of Data Quality with accountability (e.g., make it a senior management role, such as a Data Officer/DQ COE)
- Create a Data Quality vision and strategy
- Identify the key change drivers
- Develop a formal Data Quality improvement program based on specific tools wherever possible
- Use a value-driven approach for large projects
- Make it a priority to move your organization up through the levels of the Data Maturity model
Need help with achieving data quality. Bardess Group provides Data Quality solutions for Fortune 500 and middle-market corporations that are targeted at:
- Increasing Customer Satisfaction
- Increasing Revenue and Margins
- Increasing Collaboration between Functional Departments
- Improving Operational Efficiency
Contact us today for more information.
About the Author
Joe DeSiena is President of Consulting Services at Bardess Group, Ltd., a Management Consulting firm specializing in data revitalization, business process design, and information technology for services-related businesses. He is currently a board member of the Society for Information Management in New Jersey.
He is an experienced management consultant with over 20 years of professional experience assisting Fortune 500 clients in resolving business issues related to the Triangle Relationship between business data, processes and systems functions for services and sales organizations. More specifically, he has directed engagements in services marketing and delivery, business planning, data revitalization, data migration, process design and reengineering among others. He has shared his experience and insights in presentations before numerous senior client and association groups.
Joe DeSiena’s industry exposure includes data networking, telecommunications, manufacturing, pharmaceuticals, financial services, utilities, travel and entertainment among others. He has corporate management experience in major companies such as American Express, Chase, Bristol Meyers-Squibb, Coopers & Lybrand (PWC), Deloitte Touche, and Pan Am. Joe DeSiena is a graduate of the Stern School of Business at NYU with an MBA in Finance. He received his B.A. in Mathematics and Economics from the State University of New York at Stony Brook graduating Magna Cum Laude with Phi Beta Kappa honors.
