From Manual to Automated: A Supply Chain (Optimization) Case Study
Client: Technology retailer
Solution: Technology solution delivery
A Fortune 500 technology retailer provides customers with multi-brand technology solutions. One of their key offerings is the buy-and-hold service, which allows customers to store inventory at the retailer’s warehouse until shipment is required. This service has become increasingly valuable due to pandemic-related disruptions in the supply chain.
However, despite the competitive advantage offered by buy-and-hold, the company was losing its edge and turning away from substantial business due to inefficient processing.
Despite generating significant annual revenue, the manual buy-and-hold process posed numerous challenges. Orders, warehouse processing, and shipments were managed through multiple spreadsheets, bypassing essential systems like the warehouse management system and order management system. This resulted in:
- Delays in the order fulfillment process
- Lack of omnichannel accessibility
- No visibility into real-time data
- Inability to quickly and accurately address customer requests
The company was experiencing employee turnover as operational teams and sellers were frustrated by the inefficient and manually intensive nature of the buy-and-hold process.
The Solution Kenway Delivered
Kenway provided the following deliverables to help the company remain competitive and achieve success:
Data strategy: Kenway performed a data analysis to identify gaps and determine which inventory data could be systematically acquired.
Extract, transform, load (ETL) process: Kenway developed a UI to capture essential data points identified in the gap analysis. Through an ETL process, this data was consolidated into a data mart.
Data aggregation and data modeling: Kenway constructed a flexible and scalable Power BI dataset that enables the data model to accommodate evolving organizational needs.
Multiple source data capture for reporting: Utilizing technical architecture diagrams, Kenway designed a data model in Power BI by leveraging data captured through the UI.
Data profiling and data cleansing: Kenway profiled the data by defining data rules, identifying distributions, foreign-key candidates, functional dependencies, embedded value dependencies, and performing inter-table analysis.
The Results of Supply Chain Optimization
With Kenway’s help, the technology retailer was able to:
Save 50 hours per month of non-value add time in manual processing/administration.
- Utilize 14 Power BI reports from one aggregated dataset to service various business areas that will now enable customer and operational team visibility.
- Achieve a 40% improvement in inventory and customer data quality throughout the process.
Download to the Case Study to learn more: From Manual to Automated. A Supply Chain (Optimization) Case Study.
If you’re ready to take the next step in optimizing your supply chain operations, connect with us to discuss how our data consulting experts can help your company achieve an automated operation.