the US and China imposing tariffs on hundreds of billions of dollars worth of one another’s goods<\/a>. But with global demand for cheap manufacturing goods still thriving, China remains the supplier of choice.<\/p>\nHowever, to maintain a competitive edge, manufacturing businesses need to explore new ways to move towards \u2018Supply Chain 4.0\u2019 \u2013 in order to become faster, more flexible, accurate, and efficient. Doing this relies on having the right data from the right sources.<\/p>\n
But when there\u2019s so much of it, and with so many parties within a single supply chain using it in different ways, getting a straightforward picture of the data \u2018status quo\u2019 can be very difficult.<\/p>\n
Optimizing Data To See The Bigger Picture<\/h2>\n
In order for manufacturers to get an accurate view of their potential issues impacting their production lines, data analysts and test engineers often spend hours rigorously number-crunching data sources.<\/p>\n
Using tools such as Microsoft Excel, they often build algorithms and formulas exploring different situations across the supply chain \u2013 accuracy is wholly dependent on finding the right data and metrics.<\/p>\n
When it comes to quality assurance, there’s also no guarantee data is 100% accurate as the metrics can quickly become blinkered \u2013 as they\u2019re entirely dependent on one person\u2019s analysis of the datasets. This can send a business in a completely different direction. Plus cumbersome processes can result in analysts having to make assumptions to save time.<\/p>\n
Accurate Data Rather Than A \u2018Best Guess\u2019<\/h2>\n
Manufacturers should be able to take a democratic approach to reviewing data across the whole organisational supply chain \u2013 from product design, development, and R&D to customer service and maintenance. They need a pragmatic view of the entire company.<\/p>\n
Rather than having statistical models provide a \u2018best guess\u2019, what manufacturers need is raw data \u2013 from across the entire supply chain. This will not only help them address \u2018real\u2019 problems when they arise, it\u2019ll also help them make more accurate predictions \u2013 to stop future issues using trusted, unfiltered data from each stage in the manufacturing process.<\/p>\n
Data Helps Redistribute Costs<\/h2>\n
This is where a solution like WATS can really add value. WATS contains detailed information on any failure that occurs during the entire manufacturing process. This gives manufacturers what they need to better understand opportunities, issues, and failures across the whole line \u2013 allowing them to get to the heart of the issues instead of focusing on one specific area.<\/p>\n
WATS\u2019 data is all symptom-based. And because all related datasets are linked together, manufacturers can see the whole picture instead of one specific insight. This allows them to monitor a range of different stages.<\/p>\n
Right now, many manufacturers still rely on single production facilities or contract manufacturers, so while a return to regional supply chains presents an incredibly complex challenge, it might be seen as an easier option.<\/p>\n
Regardless of the options at hand, structured and standardized data formats and visual data interfaces offer companies maximum flexibility. It also reduces structural dependencies on single operational partners, and increases the ability to react to unanticipated events.<\/p>\n
Overall, given the uncertainty of travel, shipping, and other issues facing supply chains in a post-COVID world, using the right data will help manufacturers make fully-formed, more accurate decisions \u2013 data-supported decisions that have the potential to radically improve the profitability of your company<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"As COVID-19 causes economic chaos across the globe, modern supply chains face unprecedented challenges. Even before the crisis hit, trade tensions were rising with the US and China imposing tariffs…<\/p>\n","protected":false},"author":17,"featured_media":4612,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"content-type":"","footnotes":""},"categories":[6],"tags":[],"class_list":{"0":"post-4609","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-blog"},"yoast_head":"\n
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