Submit new product ideas for Watson Commerce Offerings including Digital Commerce, Websphere Commerce, Watson Content Hub, Watson Commerce Insights, CPQ, Dynamic Pricing, Order Management, Inventory Visibility, Store Engagement and Watson Order Optimizer. Before you submit, please review existing ideas; if an idea close to yours already exists, it's better to add comments or vote on the existing idea. We will review your ideas and use them to help prioritize our product development. Best of all, the portal will automatically update you when the status of your idea has been changed.
Submit ideas for other Watson Customer Engagement Products:
• Watson Marketing
• Watson Supply Chain
Order Optimizer Dashboard additions for Stockout and Markdown avoidance
Add Inventory Model metrics to the Order Optimizer Dashboard.
Metrics should include but are not necessarily limited to those listed below.
Additional metrics in-time with current Shipping Model Dashboard (i.e. cumulative daily):
1. Current snapshot of stockouts projected to be avoided
2. Current snapshot of markdowns projected to be avoided
3. Current snapshot of ratio between incremental projected shipping & processing costs vs. projected stockout & markdown avoidance savings
Note: Current in-time metrics should be displayed at network level in the main screen as well as at node level if displayed in the pop-ups/map section
Added metrics trending over time (e.g. quarterly; likely a separate screen from the current Shipping Dashboard):
4. Projected stockout avoidance (total, avg per order, avg per day)
5. Projected markdown avoidance (total, avg per order, avg per day)
6. Predicted vs. actual stockout avoidance (percent)
7. Predicted vs. actual markdown avoidance (percent)
8. Average ratio between incremental shipping and processing costs vs. markdowns and stockouts avoided
9. % of orders sourced to optimal shipping cost node(s) -- i.e. projected shipping cost equal to an optimization done for shipping model at 100% and others at 0%
10. shipping cost (total, avg per order, avg per day)
11. processing labor cost (total, avg per order, avg per day)
12. orders (total, avg per day)
13. packages (total, avg per order, avg per day)
14. avg units per order
15. % of units sourced to DCs
16. % of units sourced to stores
Note: trends over time are assumed to be network level, but having capability to aggregate differently would be a nice to have
How will this idea be used?
What is your industry?
What is the idea priority?
Link to original RFE