How To Use AI For Inventory Forecasting

Inventory forecasting is an important asset for any eCommerce business to have. It ensures that any items customers want to purchase are in stock, and that merchants aren’t left with a huge surplus of inventory going to waste. When done manually, this can be a tricky and time-consuming task. AI can help streamline this process, creating higher accuracy and reducing time taken to achieve results.

AI Inventory Forecasting

AI driven inventory forecasting works by analyzing historical sales data, real-time demand, and any other external data that might be necessary (for example, current trending products). With this information, it can provide automated assistance as to:

• Replenishment (time frames and quantities)
• Reducing holding costs
• Preventing stockouts

Let’s take a look at some steps to ensuring that your inventory forecasting works.

Gather Clean Data

The data is the most important part of ensuring that the AI can predict your inventory accurately. The more data it has access to, the more accurate the results can be. Examples of data that can be of use are:

• Historical sales
• Customer behavior
• Marketing data

Any real-time data ingestion that can be provided by an integration with a live analytics AI solution will also be of great help here.

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External Factors

As well as data, any external factors need to be considered when planning ahead. These can be things such as:

• Holidays
• Current trends
• Seasons
• Promotions
• Global events

These all influence consumer behavior, so need to be taken into account. For example, the buying patterns towards the end of the year with Thanksgiving and Christmas will not resemble those of mid-summer.

Gather AI Tools

Ensuring that you are using the right AI software for your needs is important. You should aim for AI based software that provides SKU-level, 30-90 day forecasts and is able to automate restocking. This will create the most seamless process for your business.

Monitor & Adjust

Even though AI is great at analyzing data, you will need to ensure that the results are being checked against the sales. This will increase accuracy of the models performance, and make sure that anything that has been missed is accounted for. The combination of AI plus manual supervision makes for a foolproof method of inventory management.

Conclusion

With these things considered, you should be able to set up an inventory forecasting system that keeps your customers happy, and that keeps your sales optimal. If a product is selling well, running out of stock early can be a big issue for brands. Conversely, having summer stock crossing over into the fall or winter months isn’t great for businesses either. The solution is planning ahead, and it’s great that AI can make this so accessible.