Importance of Data and Analytics in Inventory Management.

[Etini]

Inventory management has to do with the quantity and amount of productive stock ideal for a business to hold per time. There are two extremes to this. Hold too little inventory, you have a shortfall that can't meet up with the demands of customers. Hold too much inventory per time, and you incur costs of warehousing for nothing and may experience possible wastage. How does a business then know the optimal amount of inventory it should hold per time?

Data and analytics offer businesses the option of making informed decisions on the levels of inventory that are they can hold per time. What data and analytics does is that it studies demand patterns based on historical data to predict to a minimal error percentage the Ideal amount of inventory to hold at a particular point of the business cycle.

Imagine having to stock 30 pieces of products following analytics results and being able to sell 27. Your money of not tied in unsold inventory and you reduce cost of warehousing while reducing the risks of wastage.

Data analytics approach to inventory management is smart approach to inventory management.

 

[Phantasm]

Data and analytics are essential in inventory management, giving businesses insights to optimize their supply chain processes. They enable accurate demand planning, optimize stock levels, reduce holding costs, and improve ordering and replenishment processes. In addition, they provide supply chain visibility that enables tracking of movement, monitoring of supplier performance and identifying potential bottle necks. Data analytics also support seasonal inventory planning to ensure products are available during demand peaks and not overstocked during slow times. Analytics aid in risk management too helping identify and mitigate risks inherent in inventory management as well as evaluating supplier performance and understanding customer behavior. Moreover, data analysis helps in waste reduction, compliance with industry regulations and continuous improvement. In conclusion, integrating data and analytics in inventory management results in better decisions making process, higher operational efficiency and improved adaptability to market dynamics.