by Angela Guess
A recent article discusses how master data management can support supply chain planning. The article begins, “Most companies with large scale, complex supply chains have installed specialized software to manage those supply chains. In complex business environments, specialized software is required to plan and execute supply chain activities while optimizing inventory levels, controlling freight costs, and providing target levels of customer service. These are critical business objectives and companies typically spend tens of millions of dollars to install either supply chain planning modules within their ERP systems or separate supply chain planning applications to operate in conjunction with their ERP systems.”
“However,” it continues, “many companies are disappointed in the return on their investments in these systems. The supply chain planning module or planning application does not deliver the desired benefits of optimizing inventory, freight, and customer service levels. In extreme cases, business users may even reach a point where they don’t trust the planning system’s guidance and simply execute transactions according to their own ideas of what will work.”
The article goes on, “These kinds of failures are usually not due to inherent problems or lack of capability in the planning systems themselves. Rather, a likely cause of a supply chain planning system’s underperformance is a widespread problem in providing accurate inputs to make the system work well. The old concern about ‘garbage in / garbage out’ applies to an extreme degree to the operation of supply chain planning systems. Of particular importance is the master data – the master data controls the execution of transactions and provides the structure for the planning system.”
photo credit: kevindooley
