Shippers are “cautiously” optimistic that the industry is stabilizing, as experts recommend flexible inventory strategies. A new report compiled by The BlueGrace Logistics Confidence Index has shown a blend of optimism and constrained revenue growth expectations ahead.
Researchers suggest a “cautious approach to inventory decisions” while stressing the importance of “agility.” It recommends closely monitoring market trends.
“Businesses may benefit from developing flexible inventory strategies that can adapt to both potential surpluses and shortages, ensuring operational resilience in the face of fluctuating market conditions,” reads the report.
Inventory forecast is one of the critical pillars of strategic decision-making.
What is inventory forecast?
Stocking up warehouses with supplies and products can be seen as a shot in the dark.
However, inventory forecasting is there to help businesses estimate how much they might need based on data analysis. Using historical sales data, trends, seasonality, and discount events can make the guessing game more certain.
Many small businesses can attest that inventory forecasting can dramatically change a company’s outcome. It helps avoid overstocking or understocking products, and accurately estimating the inventory could save the company thousands of dollars.
Supply chain expert Nikhiel Varghesse warns that an inventory forecast model needs to be reviewed regularly to stay updated. “To stay ahead of demand, review and refine your forecasting methods regularly.”
Why is inventory forecast important? Chief strategist officer at Fulfillment IQ, Harshida Acharya says it helps with supply chain coordination and planning. “By predicting demand more precisely, you can improve procurement strategies, reduce lead times, and enhance production scheduling.”
Inventory forecast techniques
Several inventory forecasting techniques exist, including time series analysis, demand sensing, machine learning models, and collaborative forecasting. One can review previously recorded data trends to identify patterns or trends. Or, one can use real-time data to determine if there is a sudden spike in demand.
However, for the busy owner, the algorithm can predict future demand. The last option is to include other stakeholders to assess the data, which could lead to a more precise analysis.
Efrata Denny, the author of ‘The Supply Chain Management Guide,’ says that when choosing the right forecasting technique, factors such as the nature of the product, data quality, and desired level of accuracy must be considered.
“Consider the complexity of the supply chain and the availability of historical data. Collaborate with data scientists, analysts, and supply chain experts to select a technique that aligns with the organization’s unique characteristics and goals,” says Denny.
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Mia is a multi-award-winning journalist. She has more than 14 years of experience in mainstream media. She's covered many historic moments that happened in Africa and internationally. She has a strong focus on human interest stories, to bring her readers and viewers closer to the topics at hand.
