Wednesday, July 25, 2018

Master data management and your business

This is a sponsored conversation written by Wrapped Up N U on behalf of Diamond Links.

photo courtesy of pexels

Master data management is also known as MDM can be full of detours and dead ends and very stressful for any business owner. You may be asking yourself what exactly is Master data management and how exactly does it apply to my business? So let's break it down into terms we all can understand. According to Wikipedia; In business, master data management (MDM) is a method used to define and manage the critical data of an organization to provide, with data integration, a single point of reference. The data that is mastered may include reference data- the set of permissible values, and the analytical data that supports decision making.

In computing, a master data management tool can be used to support master data management by removing duplicates, standardizing data (mass maintaining), and incorporating rules to eliminate incorrect data from entering the system in order to create an authoritative source of master data. Master data are the products, accounts and parties for which the business transactions[disambiguation needed] are completed. The root cause problem stems from business unit and product line segmentation, in which the same customer will be serviced by different product lines, with redundant data being entered about the customer (a.k.a. party in the role of a customer) and account in order to process the transaction. The redundancy of party and account data is compounded in the front to back office life cycle, where the authoritative single source for the party, account and product data is needed but is often once again redundantly entered or augmented.

Master, data management has the objective of providing processes for collecting, aggregating, matching, consolidating, quality-assuring, persisting and distributing such data throughout an organization to ensure consistency and control in the ongoing maintenance and application use of this information.

The term recalls the concept of a master file from an earlier computing era.

photo courtesy of pexels



1. Establish a business case
It is easy to get executive buy-in if key corporate goals are linked to the MDM project through a business case. You need to define a strong business case to get sponsorship and funding from senior management.

2. Get executive sponsorship
Most MDM projects are part of enterprise-level data management initiatives that are driven with critical business priorities. MDM should be positioned as an enabler of the key business activities, and it should be explained to potential sponsors as to how MDM can help them, and they should be brought on board as supporters.

A strong executive sponsor will help get the right funding and support. An executive backup can help you to deal with internal politics and conflicts. Typically, a high-ranking executive needs to communicate the MDM business case, and the ongoing matrix of success as the program rolls out.

3. Get business Involved
MDM is all about solving business issues by effective management of master data that is critical to business operations. MDM should be driven by business needs for otherwise it will be turn out to be another isolated master data mart.

Active involvement of business groups improves the overall success and usability of the MDM Program. Various organizational groups and business lines should be brought into the loop right at the beginning of the MDM program. MDM project should, therefore, be jointly owned by business units and the IT department.

4. Invest sufficient time in planning and evaluation
MDM implementation is more complex than people realize. Investing sufficient time in planning and evaluation is vital as this helps to get the bigger picture of the master data landscape.

Start with the MDM Blue Print definition, a thorough understanding of the commonality and divergence of the master information is a critical success factor for the MDM program. A feasibility and options analysis for MDM solution should be performed. A “Build Vs Buy” analysis is recommended.

It is also recommended you perform a detail tool evaluation and proof-of-concept (POC). It is good to talk to reference customers and learn from their mistakes.

5. Institute MDM governance and stewardship
Do not underestimate the complexities and politics involved in executing the MDM project. There may be strong resistance from some of the groups in releasing data ownership. It may be hard to motivate individual groups to support the centralized MDM initiative.

It is advisable to define and establish the MDM governance committee and stewardship well in advance before the start of the MDM project. The governance committee helps increase the acceptance of the MDM program with business groups, and MDM stewards help in the efficient execution of the day-to-day MDM activities.

6. Adopt the right topology and architecture
MDM is unique to every organization, as it is a collection of processes, technology and governance practices specific to the enterprise. Organizations should adopt the right architecture for the MDM environment to support the long-term functional and non-functional requirements.

The architecture should define to accommodate the data coming from big data Sources. Parameters like “Integration point between MDM and other sources”, “Management of Master Data from different external & internal sources”, “Definition and classification of Master data”, “Process of unstructured and semi-structured Master Data”, “system performance”, “data growth”, “concurrence usages”, etc should be considered to define the topology of the MDM environment.

It is good to be cautious as real-time data integration strategy may add complexities to the architecture. It is, therefore, best to adopt real-time architecture only if necessary. It is recommended that you define a flexible data model and process architecture to adopt the future changes without much of re-work. It is suggested that SOA architecture is adopted with the re-usable components strategy.

7. Define the data quality strategy
A quality data is a prerequisite for the success of MDM. One of the key expectations from the MDM program is to improve data transparency and provide a single version of truth of master information. Organizations should define the data quality strategy to correct and enhance the quality of master data before it gets incorporated into the MDM Hub. It is suggested that detail analysis and assessment of the enterprise data be performed before embarking on an MDM program.

8. Get the right staffing and SI partner - Carefully chose the team
MDM is a relatively new technology with a shortage of experienced resources in the market. Carefully select the SI partner and create a team mix of SI consultant and internal staff. The team should constitute the mix of business and technical experts. Tools and technology training should be organized for the team as and when needed.

Sub-contracting key staff from vendors during the initial phase of implementation may be needed. However, it is recommended that you build a Master Data Competency Center (MDCC) to support the long-term multi-generation MDM program.

MDM being a niche technology, it commands premium rates for MDM consultant so the budget has to be planned accordingly. The team should have the complete attention of the HR department, to avoid any staff attrition and poaching. To keep the team motivated, special allowances, bonuses and recognition schemes should be taken into account.

9. Adopt phased implementation approach-Think big, build step-by-step
Organizations should define the blueprint of enterprise-wide MDM, but limit the scope of initial implementation. An iterative or spiral implementation approach is suggested over the waterfall model.

MDM implementation should be grouped into small and logical projects and this grouping can be done based on subject area, business unit, geography etc.

It is important to define the long-term master data management vision and outline the activities in tune to achieving the long-term goal. Define each implementation piece of puzzle rightly and avoid building a stovepipe MDM application.

10. Start with a quick win project first- Show a quick ROI realization
It is important to start by first identifying the common and critical business problems, and knowing which one is to be tackled first. Executive sponsors and business owners will be eager to see the ROI from the MDM implementation and may get impatient.

A quick win project with tangible ROI should be identified and implemented first. The first MDM implementation should be quick and easy be completed within a six-month time frame and provide tangible ROI and significant business value.
By adopting this strategy it is possible to ensure the success of the initial MDM implementation, and pave the way for further expansion.


Master data management best practices can be achieved using software from a company that best understands your business and customer base. As always keep it southern Y'all!

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