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August 2020 #12253 Page #44
Change Your Supply Chain Management with Analytics and Systems Integration By Owen Eldridge Solution Provider 4Ward Solutions Group
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elying on traditional supply chain execution systems is becoming increasingly more difficult, with a mix of global operating systems, pricing pressures, and ever-increasing customer expectations. There are also recent economic impacts such as COVID-19, supply shortages, the global recession, supplier bases that have shrunk or moved offshore, as well as increased competition from low-cost outsourcers. All of these challenges potentially create waste in your supply chain. All businesses with a supply chain devote a fair amount of time to making sure it adds value, but there are opportunities for companies in our industry to take advantage of other tools and processes to dig deeper into supply chain data in search of savings and efficiencies. Even so, many of our businesses seem to talk about changing the supply chain dynamic but do little to make that happen. The result is a myriad of feelings including “we have no control over the supply chain” to “I just don’t have time other than to make sure I am getting a fair price.” Buying lumber or buying plates for components is one of the areas we tend to focus a lot on, but what tools are we using to evaluate if we are getting a “good deal” from a vendor? As an example, anyone can negotiate a raw material price, but have you evaluated what you are really getting in value, or when you should buy based on the market? Effective supply chain management in manufacturing is essential for collaboration and coordination, as well as efficient business practices. A good best practice for achieving this management is by using analytics and integrating information in your systems.
What is Data Analytics? Data analytics is the science of examining raw data to help draw conclusions about information. It is used in many industries to allow companies and organizations to make better business decisions and in the sciences to verify (or disprove) existing models or theories. In the past few years, we’ve been hearing more and more about the use of data analytics in the supply chain and logistics function, in other words, connecting a company’s information systems (management, accounting, production) and utilizing the data they have.
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