Migrating From Enterprise Data Mountain to Data Eccentricity: The MDM Effect

Master data is the footer of any business, get it wrong and you are out of business very quickly. Master Data is dynamic and without constant attention things can become muddled very quickly. 

However, if MDM is your “project,” the stakes will be high so you will want to hit the right notes as you launch your Process master data management MDM initiative.  

Here are quick takeaways by Graham Smith to effectively make your process master data management initiative a huge success! These ten points will take you through the journey that triumphs! 

• Clearly Understanding the Business Problem
• MDM Objectives are realistic.
• Clear and tight Project Scope
• Early commitment from all stakeholders
• A structured Multidimensional MDM.
• Process Driven approach to MDM
• Responsibilities are clearly defined
• Flexible Technology 
• Organizational Standards and reusable models
• Never overlook the Change Management

After ensuring all these chief roles are managed carefully, finally you reach here… Following is the MDM maturity model.

MDM Maturity Model  

The model is effectually depicting that companies typically move from one area to the next as their ability to manage data effectively – across the organization – increases. To put you at ease, the book by Tony Fisher, former CEO of Data Flux, said that about 85 percent of all companies is into the ‘Undisciplined’ or ‘Reactive’ stages. Data has long been an afterthought of both business and IT processes, and this clearly explains the vast majority of people on the early stages of data governance maturity.   

The Climax: Barriers in Adopting Data Governance

A recent industry report recognized the substantial importance of establishing a data governance organization in order to solve most of master data management issues.  However, as the study indicated, two of the top three barriers to establishing effective governance is the problem of how to organize the ownership across territories and business units. The most prominent barriers to a successful data governance organization were:

• Data ownership and other territorial issues.
• Lack of understanding of governance.
• Lack of cross-business unit coordination
• Poor state of data management infrastructure
• Non sustainable executive sponsorship
• Resistance to accountability
• Lack of business justification

The Solution: Data Stewardship

Data stewardship is the management and oversight of an organization's data assets to help provide business users with high-quality eccentric data that is easily accessible in a consistent manner. Data stewardship maintains a constant, reliable quality.  It is a primary responsibility of people in any business organization. While data governance focuses on high -level policies and procedures, data stewardship focuses on tactical coordination and implementation.

The Bottom Line:  

How are you viewing your data? How are you treating your data? Most importantly…how are you managing your data? Are the most crucial questions that you must take note to. The days of assuming everything is fine are long gone. Data (to be more accurate information) is an asset that you can use to benefit your organization. Or, it can paralyze – and even embarrass- you. The choice is yours.