Another benefit of leveraging the visibility of lower level data across a broad range of warehouse functionality is the ability to provide unprecedented automated
business intelligence. WES' access to and collection of data from various warehouse points can be utilized to provide not only advanced reporting and live dashboard functionality but business intelligence tools such as predictive analysis, prescriptive analysis, and issue detection. The WES can feed data into its business
intelligence engine to be mined in near real-time so that DC operations can move beyond just being agile in response to changing conditions, to being proactive in making adjustments before conditions change. WES data can be analyzed to identify trends and predict operational conditions. For example, if operation peaks occur at the end of every month, warehouses can use WES feedback to ramp up staffing and equipment needs more efficiently to reduce overall costs. WES data can also be used to predict issues such as potential stock-outs or order fulfillment delays. Issue detection can also relate to preventative maintenance of warehouse equipment such as lift trucks, conveyor systems, etc. To illustrate this point, through analyzing vast amounts of data, the WES can predict when a conveyor motor may need to be replaced or when a lift truck may need servicing to reduce downtime. By collecting and analyzing data from various lower level warehouse points and taking proactive action, operation leads can use this functionality – which is unique to a WES – to make their facilities more efficient, safe and responsive to increasing
customer service requirements. == Arguments against WES terminology ==