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Case Study – Automation Analyst, Store Operations

Background:

An overhaul of the inventory receiving system at whole sale business organisation has been completed with the introduction of Fast Find Phase 4. This newly overhauled system now helps to provide new metrics that have never been gathered before for their Stores operations. These data sets fall into the following categories:

· Offload Performance – Duration for completing scanning (Truck Arrival, Scanning Started, Scanning Completed), Scan Rates (Cases per Hour, Totes per Hour), Discrepancies vs. Invoice, Performance by Distribution Centre

· Retail & Overstock Put Away Performance – Duration for completing primary filling to the retail floor from truck, put away rates (Carts per Hour, Totes per Hour, Pallets per hour)

· Load Insights – Load Mix (Floor, Warehouse, Special Handling), Products with No Retail Location, Cube Absorption

Problem Statement:

Given these are new metrics that have not been available previously, there is internal interest to provide insights on the Network for these data points to identify trends in performance and to determine the ROI of the project. Currently this data is housed in the web-based platform, Frontier, that is the inventory management system leveraged by CTR & Party City Stores. Data is queried and exported currently into xlsx and csv files and manually summarized for insights. There is potential to create a new data flow to a centralized data lake.

Activity:

Given the information outlined above, if you were tasked with leveraging this data to provide an executive summary with visuals and key insights on the network, how would you go about flowing this data in an efficient way and visualizing the insights. Please provide a summary of how you would accomplish this and feel free to provide visual examples or similar visualisations you may have done previously.