{"id":10103,"date":"2022-02-03T07:50:44","date_gmt":"2022-02-03T05:50:44","guid":{"rendered":"https:\/\/sg.syspro.com\/blog\/?p=10103"},"modified":"2022-02-21T11:26:26","modified_gmt":"2022-02-21T09:26:26","slug":"how-ai-is-transforming-manufacturing-part-2-inventory-management","status":"publish","type":"post","link":"https:\/\/sg.syspro.com\/blog\/erp-for-inventory\/how-ai-is-transforming-manufacturing-part-2-inventory-management\/","title":{"rendered":"How AI is transforming manufacturing Part 2: Inventory management"},"content":{"rendered":"

Manufacturers have incurred significant financial losses due to supply chain<\/a> disruptions and the subsequent inventory management<\/a> challenges. With companies producing more and more products worldwide, the issue of keeping track of enormous amounts of parts and materials used in the manufacturing process has grown increasingly complex. In addition, these parts frequently use several departments or plants within a company. As a result, when ordering a component, it may have to be shipped from one end to the other. Companies struggling to manage their supply chains often lack data for decision making, have siloed systems and inefficient inventory management practices.<\/p>\n

Effective inventory control centers on the balance of holding enough inventory to ensure the business operates effectively while avoiding the overstocking that ties up valuable cashflow and leads to waste. Inventory control can benefit from Artificial Intelligence (AI)<\/a> because AI provides powerful insights for companies, highlighting interesting trends from large volumes of data that help procurement and warehouse teams to better manage the daily tasks of inventory management.<\/p>\n

Inventory management in the supply chain <\/strong><\/h2>\n

To better understand the possible applications of AI for inventory management, let’s focus our sights on the most common problems that companies face while managing the inventory and establishing efficient supply chains.<\/p>\n

Effective data management<\/u><\/p>\n

While carefully built and supported inventory management software can track and store data, it would still require tremendous efforts to process all of it.\u00a0Furthermore, data handling may necessitate collaboration amongst many departments to maintain performance and quality. Raw materials, work in progress, and completed items are the three primary forms of inventories. To track and report the data, each form of inventory necessitates database management software and specialized methods.<\/p>\n

Tracking issues<\/u><\/p>\n

It is getting harder to track every item in the inventory and to get relevant analysis out of it. Failure to follow every incoming and outgoing item can have devastating effects on turnover. Manufacturers need an adequate response to increasing or decreasing demand to make timely delivery decisions. While the Internet of Things (IoT) allows the sharing of data within devices, AI acquires the power to unlock responses, offering both creativity and context to drive smart actions. The data delivered from the sensor can be analyzed with AI, enabling businesses to make informed decisions.<\/p>\n

Difficulties with business planning<\/u><\/p>\n

Inventory management is a big part of successful planning for manufacturing businesses in any industry. Successful growth methodologies require real-time collection and processing of all data.<\/p>\n

AI in inventory management<\/strong><\/h2>\n

In the field of inventory management, AI can be used to get a better understanding of inventory levels. It can dynamically manage stock replenishment and preferred stock levels based on many variables \u2013 internal ones such as current stock levels, lead times, historical and seasonal sales, days of supply, and external ones like market data, weather trends, and social media data. This enables organizations to plan and avoid stock-outs.<\/p>\n

Here are ways AI inventory management can offer massive support to manufacturers:<\/p>\n

Demand management<\/u><\/h3>\n

Using AI in demand planning allows an organization to optimize product availability by decreasing stock-outs and spoilage. It can also help with getting a better understanding of sales patterns. AI algorithms can handle many variables and analyze complex relationships to develop demand plans. Predictions that usually exceed human-based forecasts in quality and quantity. Several reports, including McKinsey Smartening up with Artificial Intelligence<\/a> have shown that AI improved demand forecasting by reducing forecasting errors by 50% and reduced lost sales by 65% with better product availability.<\/p>\n

Order fulfillment <\/u><\/h3>\n

When AI is integrated with a company\u2019s order management system, the analytical capabilities of the technology can process the large volume of real-time information coming from internal and external sources to make critical decisions about order fulfilment.<\/p>\n

Supplier management<\/u><\/h3>\n

A significant challenge for many manufacturers is tracking supplier quality and performance. Using AI, manufacturers can discover quickly who their best and worst suppliers are, and which inventory reception areas are most accurate in catching errors.<\/p>\n

AI in inventory management can help companies eliminate time-consuming and tedious inventory tasks. It can also provide companies with better data to make decisions about inventory, which will result in higher profits and lower losses. AI has a great deal of potential to revolutionize how inventory management is working.<\/p>\n

Explore our Inventor Management suite<\/a> to provide you with superior inventory control, traceability and recall management to be able to optimize stocking levels, free-up working capital, provide more effective customer servicing and benefit from improved profits.<\/p>\n","protected":false},"excerpt":{"rendered":"

Reading Time: <\/span> 4<\/span> minutes<\/span><\/span>Manufacturers have incurred significant financial losses due to supply chain disruptions and the subsequent inventory management challenges. With companies producing more and more products worldwide, the issue of keeping track of enormous amounts of parts and materials used in the manufacturing process has grown increasingly complex. In addition, these parts frequently use several departments or … Read more<\/a><\/p>\n","protected":false},"author":142,"featured_media":10105,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[148],"tags":[281,90],"class_list":["post-10103","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-erp-for-inventory","tag-erp-and-digitization","tag-managing-inventory-with-erp"],"acf":[],"yoast_head":"\nHow AI is transforming manufacturing Part 2: Inventory | SYSPRO Blog<\/title>\n<meta name=\"description\" content=\"SYSPRO ERP Blog - AI is transforming manufacturing Part 2: Inventory management. 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