Master data management preserves the integrity of critical master data at the foundation of your automated business system, whether it is a WMS or any other transaction-centric application. Would you build a house without pouring a good, solid, reliable foundation? Of course not. The house relies on the foundation to support its structure and purpose. Even though master data is established once and centrally maintained, it is constantly used to validate many of the elements of a given transaction. Master data can be as fundamental as lists of customers, addresses, items and their physical characteristics, carrier services, and warehouse location capacities. These lists and their corresponding data elements are used in the forms, reports, and displays of execution systems, but they are also used to validate if a combination of factors is acceptable or not in a process flow, and/or they are used to take different branches of logic in a transaction-driven logic design.
If one or more elements of master data are missing or incorrect, the business process that relies on that data might fail or produce unintended results. Either of these endings will slow your operation down and cause frustration, ultimately costing you money. The worst result would be for a process that ends poorly because of bad master data to become known to your customer, probably due to a quality of service failure. Can your business risk inefficiencies rooted in bad master data, or is it worth a proactive investment in better master data management?
Master data and its integrity is the foundation of your automated business system, whether it is a WMS or any other transaction-centric application. Can your business risk inefficiencies rooted in bad master data, or is it worth a proactive investment in better master data management?
In complex business models, it is common to find master data maintained on one application and introduced to a downstream application. That integration mechanism between applications must be robust, failure-proof and timely in its execution. It is also common to witness an execution system such as a WMS be asked to transact product movements before the product master data has propagated. You can imagine the results.
Master data maintenance by its nature is very granular and detail-specific. All it takes is one element to be missing or incorrect for one or more business processes to fail. Many times though, master data management is shunted within an organization to roles that have very little visibility and/or accountability, viewing that role as somewhat clerical in nature. With oversight diminished, quality suffers. But your business running at peak efficiency relies on the timely accuracy of this information always.
Let’s take an example of what I am talking about. A new customer is being established, and elements of master data might include their payment terms and whether they pay freight charges or not. You can probably guess that it is easy to incorrectly set these elements in the master data, because those elements do not receive much attention. However, after the first wrong invoice for product or freight – because your process did what the master data told it to do – your customer could be quite upset and your effort to retain and please that customer in the future will become more difficult.
That example above is straightforward but often master data drives very complex internal processes in how you handle and pick your inventory for customer orders. Concerns about shelf life, lot traceability, dimensions, and weight can all be combined in many different and reasonable ways because of the way you and your customer have agreed to work together. Compliance with labeling and packaging requirements might drive you to organize your efforts in a certain predefined manner. These considerations are set into motion by combinations of master data about your operation, your customers, your products and your automation. As the complexity arises, the combination of master data elements drives very specific, repeatable outcomes. And if you change something in your physical operation, you must ensure that the master data that models your operation is changed in concert with the physical change. You take a big risk as you may not know what will happen if you forget to change the master data when physical changes happen.
Let’s take a few more concrete examples from distribution:
- If your SKU’s at every level do not carry correct and valid values of physical properties such as weight and the length, width and height in each of the units of measure that you store and pick that SKU, the system cannot be expected to reliably find valid warehouse storage locations for putaway and replenishments, nor can any cartonization routines be expected to properly fill any repackaging cartons for compact yet efficient shipping. Remember that freight carriers might penalize you for shipping too much “air” in a carton, or you could find that the goods intended for one carton do not really all fit! Both situations lead to rework and loss of efficiency and will drive up your cost of operations.
- If your addresses of your customers are not correct, your carriers will either penalize you or they will take longer than their service level agreement to deliver your packages, all because they could not interpret data you supplied that did not meet their standards.
- If you use EDI – especially ASN’s either inbound or outbound – the degree in which transactions can successfully process relies heavily on master data integrity and consistency across multiple organizations. Severe financial penalties fall on organizations where data quality problems are exacerbated by poor master data quality, causing electronic transactions to be rejected and the subsequent movement of materials is delayed. Everyone loses if elements of master data are not thoroughly vetted and maintained.
The complexity of master data has evolved to the point now where WMS applications rely on hundreds of elements to be set up correctly before any transaction can be driven through the system – or integrated with other applications both internally and externally. If you don’t know the meaning of any data element, if you can’t understand the relationship between data elements, and/or if you want to ensure that your model performs exactly as you have physically designed it, you should consider an expert review of your master data. After an assessment of the current state of your master data, the Accelogix supply chain solutions team can also help you setup, validate, and bring improved master data to production. Your business will become more efficient through effective master data attention and curation, and that efficiency will flow directly to your bottom line.
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