Master Data Management (MDM)

Definition:

Master Data Management (MDM) denotes the central administration, maintenance and quality assurance of master data in companies.
The aim is to ensure that all systems — e.g. ERP, TMS, CRM or purchasing systems — run on uniform, up-to-date and reliable data access.

MDM typically concerns data about:

• ‍Customers(e.g. name, address, contact person)‍
• Suppliers and service providers
• Products and materials (e.g. article numbers, dimensions, dangerous goods labels)‍
• Sites and plants (e.g. GPS, accesses, opening hours, requirements)

A working MDM ensures that consistent information, redundancy-free and can be used across processes are — the basis for digital collaboration, automation, and compliance.

MDM challenges:

Data silos and system inconsistencies
Companies often store master data in separate systems or departments. This results in different versions of the same information (“multiple truths”) and increases manual effort.
_{Sources/further links:
Deloitte Insights — Data Management Challenges 2023: https://www.deloitte.com}

Lack of data quality and maintenance processes
Incomplete, outdated, or contradictory data sets lead to errors in logistics, purchasing and reporting.
_{Sources/further links:
Gartner — Data Quality Market Guide 2024: https://www.gartner.com}

Complex coordination and approval processes
Especially for multi-site companies, it is unclear who is allowed to change data when approvals are made and which source is binding.
_{Sources/further links:
PwC — Master Data Governance Framework: https://www.pwc.com}

Loady's solution:

Central, neutral platform for operational master data
Loady acts as uniform, verified data source for loading and unloading requirements, location and product information.
All parties involved — shipper, consignee, freight forwarder — are taking action a common, maintained database too.

Structured data sets and versioning
Information such as safety requirements, documents, opening hours or charging conditions is standardised, versioned and maintained in multiple languages.
This prevents inconsistencies between ERP, TMS, and other business systems.

API-based integration with existing systems
Loady data can be automatically synchronized with ERP, TMS or MDM systems via standardized interfaces (API, flat file).
As a result, data remains always up to date and consistent across the company.