ARS Forecast Analysis Report
This report is designed to provide a flexible and customizable way to analyze invoice data for the purpose of calculating the Average Quantity per Month (Avg Qty per Month) for the Auto Replenishment System (ARS). This only applies if you are using Stocking Objectives to create your Re-Order Points in the ARS.
This report allows users to filter the data based on specific criteria such as customer and date range, thereby narrowing down the dataset to focus on relevant transaction history.
Purchase Order System
Vendor Request for Quote System
Automatic Replenishment System
Auto Replenishment Maintenance
ARS Forecasting Analysis Report
An essential feature of this report is the ability for users to manually select individual invoice lines and toggle their inclusion status. Each invoice line can be marked as either 'Yes' or 'No,' with 'Yes' indicating that the invoice line should be part of the calculation of the Avg Qty per Month, and 'No' indicating exclusion from this calculation for Stocking Objective and Max Stocking Objective.
This level of control is particularly useful because it allows users to exclude certain invoices that might distort the true average. For instance, one common scenario involves large, one-time purchases that do not reflect the typical purchasing behavior of a customer. Including these significantly larger purchases could inflate the average quantity per month, leading to overly optimistic inventory forecasts and potential overstocking.
To illustrate, consider a client who regularly orders around 100 units per month, based on their historical usage. If, during the analysis period, they receive a single large purchase of 24,000 units from a different customer, the raw data would suggest an average of around 2,100 units per month—an apparent spike caused entirely by that singular event. Such a distorted metric could lead to unnecessary over-purchasing, tying up capital and storage space on an anomalous order. To prevent this, the user can mark the invoice line for the 24,000 units as 'No,' effectively excluding it from the calculation. As a result, the Avg Qty per Month remains at its historical level of 100 units, maintaining a realistic and reliable basis for future planning.
Another practical application of this feature involves scenarios where a client loses a customer, they had been stocking inventory for. Here, the user can run the report filtered specifically to that customer and set the date range to match the historical period under review—be it a specific number of months or the entire history available. The user can then streamline the process by selecting the 'Set All to No' option, often accessed via the F4 key, which toggles all invoice lines to be excluded from the Avg Qty per Month calculation. This ensures that the calculation accurately reflects the current market reality and removed the influence of orders that are no longer relevant, leading to more precise inventory and ordering recommendations.
After you filter the appropriate invoices, you will be asked to update
In summary, this report acts as a powerful tool for managing inventory based on precise, customizable data analysis. Users can easily filter, select, and exclude specific invoice lines to calculate an accurate and meaningful Avg Qty per Month. These capabilities allow for refined inventory planning, preventing overstocking caused by anomalous transactions or outdated customer data. This flexibility ensures that inventory control measures are based on the most relevant and realistic purchasing behavior, ultimately supporting better supply chain management and resource allocation.
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