What is Master Data Management?

Master Data Management (MDM) is the art of ensuring high quality enterprise data.

Master data are those entities, relationships, and attributes that are critical for a company – they are the spine of your corporation.

A fully implemented Master Data Management strategy is the prerequisite of implementing your Industry 4.0 strategy.

It consists of three major parts:
Data Strategy – Implement the MDM strategy including a Master Data Management Governance body.
Change Management – Enable the organization to produce consistent high quality Master Data.
Data Management – Polishing the existing data to achieve compliance to the data strategy. This is achieved using data profiling, data cleansing and data enrichment techniques.

MDM projects are holistic change management projects, not only IT projects.

Yes, there is a need to adjust IT infrastructure, profile, cleanse and even migrate data, but success is with the people. Master Data Governance will not work without a mind shift towards responsibility, quality and end-to-end understanding of business impact caused by inappropriate data quality.

Optimization of master data management that only focuses on information technology is insufficient. A crisp Master Data strategy as well as building a solid organization and governance and continuous monitoring of data quality is essential.


The Master Data Wheel (Source: Holistic Analytics)

Our Contribution

Data Strategy

Holistic Analytics works closely along the eight data quality dimensions defined by the CMMI Data Management Maturity Model:

Accuracy – related to exactness of the data
Completeness – related to availability of full attributes (i.e. contact record without email address)
Coverage – related to availability (i.e. unavailable language translation)
Conformity – related to alignment to required standards (i.e. telephone number format for autodial)
Consistency – related to data consistency (i.e. Zip code does not match city)
Duplication – related to redundancy (i.e. many records of same contact)
Integrity – related to data relationship (i.e. contact record does not match client details)
Actuality – related to up-to-date information (i.e. out of date customer details)

Change Management

Simply honing the data and implementing nice software solutions is not going to do the job if the staff does not understand the impacts of data quality. Key to success is to make people want to go for high quality data. However, this requires time and effort. To remain cost neutral there is the need to change your business processes to free bandwidth for quality.

Master Data Management projects have to touch many parts of your business to ensure success.

Given that for more than 30 years we applied holistic change methods in previous permanent and interim positions it allows Holistic Analytics to balance technology, processes, organizational structures, people and corporate culture to achieve the desired outcome.

Data Management

Once your organization is ready for producing – and more important – sustaining high quality data Holistic Analytics can assist in profiling, cleansing and enriching your data. It does not matter what kind of ERP system you use. Be it SAP, Microsoft Navision, Sage, JD Edwards or any other system on the market.