In the current business climate, a well-organised management of inventory is crucial to cut costs while meeting the needs of customers. Although many enterprises are taking advantage of modern technology, it is easy to implement the application for predictive management of inventories with no AI using proven methods, strategies and carefully planned scheduling.
Understanding Predictive Inventory Management
The term “predictive” refers to the practice of anticipating future demand and adjusting the levels of inventory to be able to meet it. Traditionally, businesses relied on historical sales data and seasonal demand, as well as market trends, to determine the need to stock.
Even without artificial intelligence, these strategies can still be useful to small and mid-sized businesses seeking to lower costs and enhance the efficiency of their supply chains.
Methods for Prediction Without AI
The most widely used method is called time-series analysis, in which companies study patterns in sales in order to anticipate demand for the future. For instance, retailers can identify seasons with peak times that are repeated and prepare their inventory before the deadline.
Another option is to utilise low orders (EOQ), which will help in determining the best size for an order, which balances the expense of carrying and the expense of placing an order. Safety stock calculations also aid in preventing shortages when demand spikes suddenly.
Excel spreadsheets, as well as spreadsheets that are part of an ERP system, can be used to implement this kind of strategy.
With the aid of built-in analytics tools, businesses can create precise forecasts and evaluate the efficiency of their businesses without relying on the power of AI to drive their systems.
Benefits of a Non-AI Approach
The ability to predict inventory that uses no AI is cost-effective, especially for businesses that don’t have the funds to invest in the most advanced technological advancements. It lets companies streamline processes, cut down on inefficiency and increase the satisfaction of clients.
Furthermore, using proven and old models can make forecasting more transparent since managers can clearly observe the processes of making decisions.
The Future of Inventory Planning
While AI can provide greater automation and more sophisticated analysis, companies can still achieve success with conventional forecasting methods.
By combining data analysis and an ERP system and methodical plan, companies can devise efficient inventory strategies that meet the needs of customers without straying too far.
For smaller companies, they could offer the option of using prescriptive management until more sophisticated tools are needed.