High Level Design
Overview
Ecommerce companies are constantly thinking of ways to improve service to their customers, especially avoid delays when delivering products. Therefore, it is crucial for these companies to identify reasons for delays to minimize them as much as possibleGoals
Improve service to customers
Objectives
- Minimize delivery delays
KPIs Architecture
| Objective | KPI’s | Measures | Data source |
| Minimize delivery delays
|
On time delivery rate | ([# of Late/OnTime],[Late/OnTime])/count([Order ID]) | Orders |
| Break by Reasons for delay | ([# of Late/OnTime],[Late/OnTime]) | Orders, DelayReason | |
| Delivery Rate by Origin | ([# of Late/OnTime],[Late/OnTime])/count([Order ID]) | Orders, Warehouse | |
| Delivery Rate by Destination | ([# of Late/OnTime],[Late/OnTime])/count([Order ID]) | Orders, Customers | |
| On time delivery rate by Delivery Provider | ([# of Late/OnTime],[Late/OnTime])/count([Order ID]) | Orders, DeliveryProvider | |
| On time delivery rate by Period | ([# of Late/OnTime],[Late/OnTime])/count([Order ID]) | Orders | |
| % Deliveries on time | ([# of Late/OnTime],[Late/OnTime])/count([Order ID]) | Orders, DeliveryType | |
| Avg delay (days) | ([Average DayDifference],[DayDifference1]) | Orders, DeliveryType |
Entities Relationship Diagram
Data Connectors
