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How to Reach Optimum Inventory with an AI-powered Demand Sensing Approach

AI-enabled demand sensing solutions provide many benefits when it comes to supply chain forecasting, including improved accuracy, increased efficiency and enhanced reliability. By using AI-based algorithms in conjunction with Big Data analytics, a vast number of inputs can be taken into consideration and analyzed simultaneously. This helps to create more accurate forecasts that are better able to anticipate events or shifts in the marketplace.

The webinar “How to Reach Optimum Inventory with an AI-powered Demand Sensing Approach” held by Sheetal Yadav, COO at Anamind along with Lu Shi, Partner Success Manager at GMDH Streamline uncovered the capabilities of Demand Sensing and its impact on the supply chain.

Potential Losses & Excess Stock

In supply chain management, potential losses and excess stock can result from various factors, including being out of stock. Common reasons for being out of stock include demand fluctuations, sales forecasting errors, poor supplier performance, logistics incidents, quality incidents, and issues with operations reliability. By identifying the root cause of these issues and implementing proactive measures to address them, businesses can minimize the risk of lost sales, excess inventory, and other negative impacts on their bottom line. It is crucial to prioritize supply chain optimization, data-driven decision-making, and communication with suppliers to ensure that inventory levels are always maintained at optimal levels.

Disadvantages Of Keeping High Safety Stock

While safety stock can help businesses mitigate the risk of stockouts and ensure continuity of operations, there are also disadvantages to keeping high levels of safety stock. One major disadvantage is the increased holding cost associated with excess inventory. This can include expenses related to storage, handling, and insurance, which can add up over time and negatively impact a business’s bottom line. Additionally, for products that have a limited shelf life or are susceptible to damage or quality deterioration, keeping excessive safety stock can lead to waste and additional costs associated with disposing of expired or damaged goods. As such, it is important to carefully balance safety stock levels with other factors such as demand forecasting accuracy and supplier performance to optimize inventory management and minimize overall costs.

Safety Stock: factors to consider

Safety stock is a critical component of inventory management that helps businesses mitigate the risk of stockouts and ensure continuity of operations. The key of safety stock include demand and supply variability, as well as the following factors:

    1) Forecast Accuracy: The accuracy of demand forecasting is crucial in determining the appropriate levels of safety stock. Inaccurate forecasts can lead to excess inventory or stockouts, both of which can negatively impact a business’s bottom line.
    2) Lead Time: The amount of time it takes for suppliers to deliver products can impact safety stock levels. Longer lead times may require higher levels of safety stock to ensure continuity of operations during periods of high demand or supplier delays.
    3) Service Level: The desired level of service can also impact safety stock levels. Businesses that prioritize high service levels may need to maintain higher levels of safety stock to ensure that they can meet customer demand even during periods of high demand or supply disruptions.

By carefully evaluating these factors and optimizing safety stock levels accordingly, businesses can ensure that they are able to meet demand while minimizing excess inventory and associated costs.

Demand Sensing Capabilities

Demand Sensing eliminates supply chain lag by reducing the time between events and the response to those events.The goal is to reduce the total time elapsed from the emergence of a statistically meaningful mix of demand signals to the planner’s ability to respond intelligently to those signals.

Streamline’s demand sensing feature, when enabled, leverages existing sales data for incomplete periods to refine and adjust our forecasts. Specifically, it considers the current state of sales for a period and calculates how much of a product is likely to be sold in the remaining days based on various factors, such as the current date and the number of days left in the period.

For instance, in the event of unexpectedly high sales during the middle of a month, the demand sensing feature will make intelligent predictions for the remaining days of the month, accounting for the current sales trend and how much time is left in the period. This ensures the sales forecast is always up-to-date, accurate, and reliable.

Impact of Demand Sensing on a Company’s supply chain

  • Better Forecast Accuracy than Demand Forecasting
  • Improved inventory requirements and reduced transportation costs
  • Increased service levels
  • Provides a more responsive framework to fulfill demand in short-term with precision
  • On a final note

    “Demand Sensing is a powerful tool that can improve the accuracy of inventory requirements, minimize transportation costs, and increase service levels. By utilizing Streamline, businesses can easily access this feature with just one click, allowing the system to begin optimizing inventory immediately,” – said Sheetal Yadav. “Streamline is a user-friendly platform that offers intuitive navigation and seamless integration with other systems, making it an ideal solution for businesses looking to streamline their supply chain operations and improve overall efficiency.”

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    • 99+% inventory availability.
    • Up to 99% forecast accuracy.
    • Up to 98% reduction in stockouts.
    • Up to 50% reduction in excess inventory.
    • 1-5 percentage points margin improvement.
    • Up to 56X ROI in one year. 100% ROI in the first 3 months.
    • Up to 90% reduction in time spent on forecasting, planning, and ordering.