Replenishment
Automatically creates purchase and transfer orders based on accurate demand forecasting. Reduces manual work that goes into order creation and improves order accuracy resulting in increased sales and less money tied in stock.
Purchase Plans
Create purchase plans for future periods to increase vendor collaboration and information sharing. Purchase plans can be created and edited for any defined group in the system.
Exception Management
Create your own exception reports to identify items that need special attention, for example potential stock-outs, late deliveries, high forecasting errors, slow movers, etc.
Container Optimisation
Create and apply your own custom constraints to fill up containers so that the shelf life of all ordered items is the same without breaking volume, weight and number of pallets constraints.
Improve Your Service Levels
The AGR replenishment module uses the Forecasting Engine to calculate future sales and stock requirements and an accurate safety stock calculation. This calculation is dependent upon the variability of the products history and the required confidence level. The end result is the required Purchase order proposal that will best satisfy the forecast taking into account outstanding orders / inventory, lead times and supplier min order quantities. Order proposals can be automatically confirmed into Dynamics NAV or review and amend before authorising the feed back into NAV to create the actual PO within the requisition worksheet.
Manage Your Data Easily
Data is replicated on a daily based from the ERP system into the AGR SQL database. Information on demand can be calculated for LS Retail POS data or from order receipts from warehouses or crossdocking locations. Once accumulated, the look and feel of the data is graphical to enable the user to get an extensive view of the items performance, both on SKU and variant level.
View Historical and Forecast sales and stock
On the following figure, historical data and future estimates are presented graphically. One can view historical inventory development, historical sales figures, future forecasts, undelivered orders and projected inventory levels. Data can be viewed on daily, weekly or monthly level and various demand elements can be manipulated directly from the web user interface.
