Managing Inventory Costs by Improved Forecasting

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Working out the right inventory volumes that will both ensure the sufficient availability of working capital as well as maintain order fullfilment rates at a level that is expected by the customers has always been a crucial issue for manufacturers.
Managing Inventory Costs by Improved Forecasting_Powering_Intelligent_Manufacturing

Due to this being such an important business challenge, manufacturers have continuously strived to reimagine their supply chains and set them up in ways that will alleviate some of the pressures of this challenge.

However, a new set of circumstances introduced additional challenges that need solving and added additional complexity to this issue. Manufacturers are now forced to expand their product lines as well as adjust their R&D times to deal with the shortening of the life-cycle of each product. Meanwhile, profit margins are threatened by the rising cost of raw materials and distribution as direct-to-consumer shipping is becoming increasingly expected of manufacturers.

So what innovations can be incorporated in the supply chain to enable manufacturers to keep inventory costs in check even with all these challenges before them?

This time the answer is not so much a matter of inventory management optimization but rather in the organization’s ability to accurately and reliably predict future demand levels. This means incorporating new information into the forecasting models and having high supply chain visibility to effectively manage the flow of materials based on the forecasting numbers. For most manufacturers continuing to use conventional techniques to reduce costs – it is becoming increasingly urgent to reconsider the way they go about forecasting demand.

Old Challenges and Additional Market Demands

A conventional Sales and Operations Planning (SOP) model relies on forecasting data to dictate the production activities of all units along the supply chain. The disparity between this forecast and the actual demand is the single most impactful factor on excess inventory across the entirety of the supply chain. Having these forecasts miss the mark is not all that rare of an occurrence since the estimation models used to produce them are not based on current information and have been exposed to employee biases multiple times along the process.

Traditional models have recently been tested even further. The market is now requiring manufacturers to ship directly to customers and bring new products to market faster and more often. Direct-to-consumer shipping is only going to see further increases since improved delivery performance and a larger variety of products remain the main avenues traditional retailers are choosing to try and hamper Amazon’s growing market share. One of the effects of this is that this shifts inventory risk from the retailer/distributor to the manufacturer – and with many products being associated with short-lived fads, the risk of getting large quantities of inventory stranded in the warehouse only compounds.

Using Big Data to Transform Old Forecasting Models

Still it’s not all grim, as manufacturers now have powerful solutions that can enable them to retain the flexibility to quickly respond to the current market shifts. Combining current and dynamic big data collection technology and advanced analytics tools, manufacturers can enter a new era of demand forecasting. With improved accuracy and an ability to quickly adapt to new information, manufacturers can significantly reduce inventory risks while improving customer relations.

By implementing a solution that can enable your organization to pinpoint future demand, detect disruption, improve overall visibility and automate management processes – you will be able to keep your business competitive for years to come.

Merit Solutions has deep expertise in business transformation, manufacturing digitalization, industrial IoT. If you’re looking to make improvements to your operational efficiency by leveraging digital technologies contact us today!

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