White Paper
Solving Clearance Stock Build-Up
Developing a custom clearance tool to transform retailer operations, unlocking a £3.5m profit uplift opportunity
Insight into the decisions and technology needed to reduce excess clearance stock.
A key factor in the success of many retailers is the ability to supply to customers while keeping unsold stock to a minimum. Too much stock impacts production and storage costs, too little stock affects customer loyalty.
In this White Paper, we show how QuantSpark:
Took charge of the business challenge
We identified two key areas of urgent improvement for our clients: workflow optimisation and predictive modelling.
Workflow Optimisation: Creating a workflow tool to make General Merchandise clearance stock execution more efficient and accurate.
Predictive Modeling: Develop a sophisticated predictive model to recommend the optimal markdown strategy at the individual Stock Keeping Unit (SKU) level. This aimed to guide decisions on timing and discounts to maximise profitability and ensure stock cleared within the clearance window.
Built a Clearance Tool for our client
We built a a web application hosted on the client's AWS infrastructure. End users could securely log in and upload their clearance lists. The tool cleaned the data, diagnosed issues, and generated a final clearance list, ensuring accurate and efficient markdown execution.
Delivered results
Dramatic workflow improvement
The workflow tool reduced clearance list creation time by up to one hour, improving accuracy and saving time for the merchandiser.
Substantial profit uplift
Data-driven decision-making allowed the merchandiser to access a multi-million profit uplift opportunity annually. By modelling the optimal markdown strategy for each SKU, our client optimised strategies for maximum sell-through and profitability.
Foundation for long-term development
The Client Clearance Tool set the stage for ongoing innovation and a product development roadmap, extending its benefits to other retail categories such as clothing. The tool serves as a foundation to operationalise the PoC markdown predictive model, providing the merchandiser self-service access to the recommendations.
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