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Master Data, its quality and completeness, and the processes that create, update, and synchronize across different systems have an outsized impact on sales, commerce, supply chain readiness, and operational excellence. At the same time, many organizations struggle to achieve Master Data Management Excellence.
Before you embark on a Master Data Management Excellence initiative, it is a good idea to understand where your organization stands in terms of Master Data Management.
To evaluate Master Data Excellence, it is essential to consider:
- The quality of the Master Data itself
- The processes involved in creating and updating Master Data
Assessment of Master Data
Master data quality can be assessed using the following dimensions. The first five can be evaluated quantitatively, and the last two are qualitative measures.
- Accuracy
- Definition: Ensuring data is correct and reliable.
- Example: A customer’s address is recorded as “123 Elm Circle” instead of “123 Elm Street,” leading to failed deliveries.
- Completeness
- Definition: Verifying all required data points are available.
- Example: A supplier record is missing critical fields like tax ID, Account Group, or contact information, delaying vendor onboarding.
- Consistency
- Definition: Maintaining uniformity across data sets.
- Example: Material number “123456” in the ERP system is called “RES-123456” in the supply chain planning system, creating confusion and a need for transformation
- Uniqueness
- Definition: Avoiding duplication within data.
- Example: A customer has two profiles in the CRM system due to variations in their name (e.g., “Steph Curry” and “Stephen Wardell Curry”)
- Validity
- Definition: Adhering to defined standards and formats.
- Example: A phone number is entered as “123-456” instead of the required format “(123) 456-7890.”
- Accessibility
- Definition: Ensuring data is readily available to authorized users.
- Example: The corporate Supply chain team should have ready access to Supplier Master data. They shouldn’t have to ask a Master Data analyst for that information.
- Traceability
- Definition: Tracking the origin and changes to data.
- Example: Sales analyst updates a pricing record, but the system lacks an audit log to identify who made the change or why.
Since all Master Data is not the same, Master Data assessments must also be explicitly conducted for different Master Data Objects, including
-
- Part/Item Master Data
- SAP Material Master Data
- SKU Master Data
- Supplier/Vendor Master Data
- Customer Master Data
- Manufacturing Master Data
- Logistics Master Data
- Equipment and Plant Maintenance Master Data
Data Profiling of Existing Master Data
You can use data profiling techniques to assess the current state of Master Data.
Assessment of Master Data Processes
- Cycle Time
- Definition: The cycle time it takes to orchestrate master data processes (New Material, Vendor Onboarding…)
- Example: It takes two weeks for a new material request (with reviews, approvals, and validation…) to be processed before a new material is created in an ERP system
- Scope of Process Support
- Definition: Evaluating the breadth of Master Data handled as part of the master data process
- Example: An end-to-end Material creation process can include Core Material Data, Sales, Pricing/Costing, Bill of Material, Routing, Production Planning, Production Version, etc. We often see traditional Master Data solutions handle core Material Data and call it a day.
- Process Cost
- Definition: Analyzing the expense of maintaining Master Data processes.
- Example: Sometimes, a New Material creation process can cost upwards of $500 per material. Much of it is people’s time following, filling, reviewing, checking…
- Non-Value-Added Activities
- Definition: Amount of non-value-added activity in the master data process
- Example: Employees repeatedly verify data accuracy manually instead of using automated validation tools, consuming unnecessary time.
Master Data Process Analysis Example
Master Data business processes are generally cross-functional and comprise activities that take time and cost. Process mapping and analysis can estimate the cost and cycle time of the AS-IS process.
Process improvement strategies (proactive coordination, automation, workflow management, and automated governance) can be used to assess reduction in cycle time and process cost and data quality improvement.
Impact of Poor Master Data and Master Data Processes
The impact of poor master data and master data processes is wide-ranging. The most severe are related to poor master data and its impact on operations. Some examples include
- Duplicate material records led to $250,000 worth of excess inventory
- Incorrect lead time data resulted in expedited shipping costs
- Missing safety data information led to $100,000 in fines
- Incorrect price conditions led to a $1,000,000 revenue loss
Poor master data processes are a source of cost, too. Many organizations have tens of thousands of master data processes that need systematic support. Without any systematic support, process costs tend to be high, and these costs are directly measurable.
Can I use ZMDM for Master Data Assessment?
Yes, you can. ZMDM has several features that make it a convenient and easy-to-use (also do-it-yourself (DIY)) solution for Master Data Assessment. ZMDM is also much cheaper than an expensive consulting company for your Master Data Assessment.
Email us if you are interested in Master Data Assessment.