What are the best ways to evaluate your inventory forecasting models?

1 Forecast accuracy

The most obvious way to evaluate your inventory forecasting models is to measure how well they predict the actual sales or demand for your products. Forecast accuracy is usually calculated as the percentage of error between the forecasted and actual values, or the absolute value of the difference. You can use different metrics to measure forecast accuracy, such as mean absolute percentage error (MAPE), mean absolute deviation (MAD), or mean squared error (MSE). The lower the error, the higher the accuracy.

2 Forecast bias

Another way to evaluate your inventory forecasting models is to check for any systematic errors or deviations from the actual values. Forecast bias is the tendency of your models to overestimate or underestimate the demand for your products. You can use metrics such as mean error (ME), mean percentage error (MPE), or cumulative error (CE) to measure forecast bias. A positive bias means that your models are overforecasting, while a negative bias means that they are underforecasting.

3 Forecast value added

A more comprehensive way to evaluate your inventory forecasting models is to assess how much value they add to your business outcomes. Forecast value added (FVA) is the difference between the forecast error of your models and the forecast error of a naive or simple method, such as using the previous period's sales as the forecast. FVA measures how much your models improve the forecast accuracy and reduce the inventory costs and waste. A positive FVA means that your models are adding value, while a negative FVA means that they are worse than a simple method.

4 Customer feedback

A qualitative way to evaluate your inventory forecasting models is to collect feedback from your customers and stakeholders. Customer feedback can help you understand how satisfied your customers are with your product availability, delivery time, and service quality. You can use surveys, interviews, reviews, or social media to gather customer feedback and analyze their sentiments and expectations. Customer feedback can also help you identify any gaps or opportunities in your product assortment, pricing, or promotions.

5 Industry benchmarks

A comparative way to evaluate your inventory forecasting models is to benchmark them against your competitors or industry standards. Industry benchmarks can help you gauge how well you are performing in terms of market share, customer loyalty, and profitability. You can use data sources such as industry reports, trade associations, or market research firms to find relevant benchmarks and compare your forecast accuracy, bias, and value added with them. Industry benchmarks can also help you learn from the best practices and innovations of other retailers.

6 Continuous improvement

A proactive way to evaluate your inventory forecasting models is to continuously monitor and improve them. Continuous improvement is the process of reviewing your models regularly, identifying any errors or issues, and making adjustments or changes to improve their performance. You can use tools such as dashboards, reports, or alerts to track and visualize your forecast performance and identify any trends or anomalies. You can also use methods such as experimentation, testing, or optimization to refine and update your models based on new data or feedback.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?