Why you need to engage your entire organisation when introducing Master Data Management
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Introducing Master Data Management (MDM) into an organization is a cross-functional endeavor that centers on creating a single source of truth for an organization relating to specific areas, including, for example, supplier data.
The task of introducing MDM is frequently an IT project and considered primarily from a technical perspective. However, for success to be achieved, in addition to data management itself, equal weight should also be placed on considerations relating to people and governance.
The pooling and sharing of data across functions is relatively simply to achieve. However, maintaining the usefulness, applicability or relevance of the information is much more difficult, which is why you need to engage the entire organization when introducing Master Data Management.
What is Master Data Management?
Gartner describes MDM as a “technology-enabled discipline in which business and IT work together to ensure the uniformity, accuracy, stewardship, semantic consistency and accountability of the enterprise’s official shared master data assets.”
Master Data Management is a comprehensive way in which organizations can link all their data from important sources into a single location. It can then be used as a common point of reference by various stakeholders within the business and facilitates the sharing of data between departments and key figures.
It provides businesses with a way in which they can streamline the sharing of the data acquired from different platforms, systems and applications, and make this information useful to other stakeholders across the business.
Master Data Management from a Supplier Data and Supply Chain Perspective
Master data relating to suppliers can include such information as locations, bank accounts, audits, products or contacts. From a supply chain perspective, MDM creates a single view of all vital data related to the supply chain.
Supplier Master Data Management is crucial in the context of Procurement and supply chains because data is divided between an especially large numbers of systems and databases, due to the complex nature of the relationships and activities involved.
For supply chain master data, consistent identifiers need to be used throughout to describe key aspects, including products, materials, customers, locations, and vendors; it also means that the relationship between each entity is easily distinguishable.
When implemented, Master Data Management leads to more accurate and consistent data that is up to date across various systems and processes throughout the organization. It leads to enhanced decision-making, better forecasting, and improved operational efficiency across the business, resulting in a more agile and robust supply chain.
Introducing Supply Chain and Supplier Master Data Management into your Organization
In many organizations, numerous departments interact with suppliers and keep their records of data that are not easily accessible to key personnel in other departments.
This leads to issues that severely impact data quality. Awareness of these issues should be the starting point for understanding the problems that occur when MDM is not implemented or, indeed, that will be uncovered during the implementation of MDM.
How do Issues with Supplier Data Occur?
Two important occurrences matter in the lifespan of a piece of data: the moment it is created and the moment it is used. The data’s quality is fixed at the point of creation, yet the quality of the data is not judged until the moment it is used.
There are various reasons why problems with supplier data can occur but they can be eradicated by implementing a Supplier Master Data Management strategy.
Manual entry
Organizations relying on data being inputted into a system manually leave themselves open to human error, resulting in data that is inaccurate, incomplete, or both. This could include omissions of parts of the data essential to other departments, typos, erroneous data entered into the wrong fields, missed entries and out-of-date information.
Lack of consistency
A lack of consistency and standardization occurs when there is no common standard or process for recording and maintaining data. This quickly leads to discrepancies in the data that cause confusion and provide inaccurate results. Examples of these can include recording variations of a vendor’s name, using incorrect date formatting and using shorthand for inputting details and information.
Neglecting validation
The lack of consistency is made worse when no systems are in place to validate supplier data when it is entered or updated. These errors are not identified and continue to propagate throughout the organization. If these changes are not made and validated, it can lead to incorrect data en masse.
Lack of accessibility
Due to the nature of supply chains, a lack of accessibility to supplier data essentially renders it useless. This stifles the organization’s processes and ability to make decisions based on accurate data, which impacts the business’s overall performance and profitability. Even if the data held within the departments is wholly accurate, without the ability to access it, it serves no purpose to the organization.
Changing the Mindset for Data Creation
When it comes to moving towards a single source of truth for data and bridging gaps between silos, the key to doing so effectively is to make it clear to each department that supplier master data is much more than just an IT concern.
Introducing new data governance measures should be treated as a business-wide transformation project. An important aspect of successfully implementing business transformation is to help people understand how data will be used further down the line.
Whenever someone creates data, they are creating it to meet their needs at that moment. This means that basic data might not be a problem for them in that instant. However, it when others come to use it in the future for different purposes, shortcomings of the data render it unfit for purpose. Therefore, to reduce the risk of this occurring on an ongoing basis, as part of the transformation project, you need to make it clear to people at the point of creation how that supplier data will be used by others in the future, while also introducing processes that make it easier to create better data records.
Enhancing Business Communication for Effective Supplier Master Data Management Implementation
As introducing Supplier Master Data Management will be a business-wide transformation project, rather than impacting just one department, there must be unwavering commitment and buy-in from the organization’s leaders to enact change.
Therefore, there needs to be clear and compelling communication with the wider organization in terms they will understand and that will help drive the business case for adoption of MDM. This means talking to them in broader, more understandable terms, rather than highly technical language or jargon. The business processes they will be interested in, and therefore the ones you need to address, are:
- Supplier onboarding
- Reporting analysis
- Supplier management
- Supplier phase-out
However, while speaking to them in broader business terms is essential, this does not mean talking in abstract terms. In other words, there needs to be a clear link highlighted between data processes and business processes that they are familiar with to showcase the value of Master Data Governance fully.
Empowering Departments: Master Data Governance as an Enabler, not a Controller
While the main aim of Master Data Governance is to make data more accessible in a centralized point, a degree of localized flexibility is also required. Those working within the silos must be aware of MDM’s benefits, but these individuals should not feel like they are being “policed”.
Ensure they clearly understand how it will empower them and their role in transforming the organization’s data to improve overall performance; essentially, they should feel enabled. It should also be communicated that the central data repository is not there to replace existing systems but to allow greater efficiency.
Essential Features for an Effective Supplier Master Data Governance Solution
When implementing Master Data Governance transformation within an organization, several essential requirements should be considered before and throughout the implementation. It should not be viewed as a technical project but as something that will evolve the organization in its entirety.
Therefore, careful planning, strategy development and refinement are required, including understanding how the transformation will impact workflows and ensuring that disruption is minimized.
Data model
An effective Master Data Management solution requires an adaptable data model that users and suppliers can easily navigate and use.
Therefore, the model should be flexible, intuitive and agile enough to handle various types of data shifts in the business environment.
Data consolidation
Given the number of systems your organization will likely use, the solution must support consolidation. It should be designed to integrate and harmonize data from all required sources to ensure a consistent record for each supplier. This will remove confusion and conflicts arising from inconsistencies in data.
Data flow
In the context of Supplier Information Management, the data flow should start from a centralized location. This ensures that all systems can access the same, fully updated information, ensuring that duplication instances are avoided and data quality is promoted.
Data governance workflow
When data is centralized, the need for robust data governance increases. Therefore, the MDM solution should facilitate automated and manual checks when changes to the data are carried out. This provides the possibility to check for error detection and correct any discrepancies in the data before it is disseminated, ensuring that the accuracy and reliability of the data are maintained.
Data staging
Data staging provides a buffer stage where changes made by suppliers or users are not applied immediately but will only be visible once approved. This additional layer of verification prevents incorrect data and duplicates from being added and enhances the overall quality of the supplier data.
Organizations that implement a Supplier Master Data Management solution that addresses these five key areas are empowered to overcome data silos and differing systems challenges, facilitating transformational change across the organization.
Article updated June 24
