Course: Organization Modelfor DT.

Use Visio , draw.io (diagrams.net), or Modelio tool to create a Use-Case Diagram Logistic Manager for the OnMart Superstore case study.

Case Study.

The logistics department is responsible for the logistics and supply chain network for OnMart Superstore. The department team members track the status of the warehouses, distributions centers, inventories, deliveries, delays, and returned products for the different zip codes that OnMart serves. The department tracks the connections between the cities, warehouses, distribution centers and the zip codes they serve within the OnMart supply chain network; the data graph below shows one of the distribution centers in Chicago along with the distribution centers associated with it and the zip codes that it serves.

The department is also responsible for creating contingency plans to cope with adverse weather conditions that might impact the daily operations for the warehouses, distribution centers and order deliveries.To ensure quality of service for its customers and continuous improvement for customer satisfaction, OnMart has requested to conduct a study to produce an analytical research report utilizing Facebook/Prophet package and Neo4j GDS library to address the following:

1. Forecast the number of returned orders for every warehouse 2. Forecast the number of delayed deliveries for every zip code 3. Forecast the number of delayed deliveries for every distribution center 4. Identify top 10 distribution centers with highest number of order returns 5. Identify top 10 distribution centers with lowest number of order returns 6. Identify top 10 distribution centers with lowest number of deliveries 7. To offload busiest warehouse with highest number of order returns, identify the warehouse that has the forecast for the highest number of order returns, and find its nearest neighboring warehouse that has the lowest number of order returns (consider 50-200 mile radius) 8. To offload busiest distribution center with highest number of delayed deliveries, identify the warehouse that has the forecast for the highest number of delayed deliveries, and find its nearest neighboring distribution center that has the lowest number of delayed deliveries (consider 1-20 miles radius)