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When a chemical manufacturer acquired a multimillion-dollar product line from a competitor, it discovered something about the data associated with the product they were acquiring: The competitor's data was neither mature nor complete. Neither was the chemical manufacturer's data. Nearly a year and $40 million later, the company had integrated production of the acquired product into its own portfolio, and the acquisition was a success. But the transition didn't happen as quickly as it could have if both companies had controlled and managed their product data better.
Scenarios such as this highlight the value of master data management (MDM) software for manufacturers. MDM software includes process, governance, policy, standards and tools to manage an organization's critical data -- for example, the management of data used in ERP systems and cross-enterprise data. Master data management software manages multiple silos of information encompassing everything from accounting and engineering specifications, to weather, supply chain, safety and regulatory compliance. MDM software can capture and preserve any data associated with a manufacturing cycle, from its earliest design and development stages to arrival on a customer's docks.
At its recent Master Data Management Summit in Europe, Gartner recommended a structural approach to implementing master data management, beginning with strategy for development and planning, then setting up a process to govern data. Subsequently, this will aid change management of all types and smartly utilize data targeted at strategic business goals. Once set, data management can be measured, monitored and altered to stay on course.
This approach is akin to what Monsanto, the billion-dollar agricultural company, is doing as it has begun capitalizing on predictive analytics in assimilating big data and information that captures everything from weather to supply chain details and biological factoids about its underlying agricultural products. Monsanto touts its approach as "turning data into food."
David Parrish, SAP's director of industrial machinery and components, said that MDM gives manufacturers a way to streamline data for efficiency and to build a strategic advantage. He described MDM as a vehicle for creating, distributing and maintaining complete and accurate master data for everyone in your organization, "with a single version of the truth -- for better-informed business decisions, improved process efficiency and faster responsiveness to change."
According to Parrish, MDM's benefits include consolidation of data, scrubbing it to be meaningful, synchronizing it with other available data attributes and integrating it with other software to create consummate business efficiency. Such benefits create added value for today's globally competitive manufacturer.
And manufacturers welcome MDM once they realize its value. Chad Dotzenrod, principal consultant with SWC Technology Partners, said his conversations with manufacturing clients go well when he discusses master data management software. "I wish every software solution was as easy to demonstrate value and provide immediate impact," he said. "You just don't see that with other software products. Many times you hear horror stories about how long it takes to implement a new ERP solution, whereas MDM can be done very tactically. There are instances where we went in and in less than a month we put it in place to do something tactically and provide immediate ROI."
Using technology to manage master data is a key ingredient in manufacturing ROI -- particularly for strategy development. According to Mohan Ponnudurai, industry solutions director at Sparta Systems, MDM is even more important when, like the chemical manufacturer, a company expands its business through a merger and acquisition.
"Many companies inherit disparate systems, creating a mix of incoherent data leading to inefficiencies and ineffectiveness," Ponnudaurai said. "When it comes to regulated industries that require submissions and reporting, using old or wrong data can lead to non-compliance and other legal problems. Operationally, it becomes a nightmare to manage systems and processes when the source data are coming from disparate and incompatible systems."
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