Unlocking £3.5M Profit Uplift with Retail Clearance Optimisation

Introduction

To thrive in retail’s fast-paced environment, companies must relentlessly reinvent themselves through bold innovation and unwavering dedication to understanding and fulfilling the changing priorities of customers and the business. At QuantSpark, we relish the opportunity to apply advanced analytics and new technology in a commercial setting regardless of the size of the challenge. One crucial aspect of retail management is the efficient clearance of discontinued stock – a task that, until recently, lacked the right tools and strategies. Enter the Client Clearance Tool, a revolutionary solution developed by QuantSpark for our retail client, designed to transform the way clearance operations are conducted.

Solving Clearance Stock Build-up

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. The Client Clearance Tool was developed by QuantSpark to solve a major business problem for a retail client - ineffective clearance of marked-down stock resulting in excess inventory.

Unveiling the Big Idea

The journey towards creating the Client Clearance Tool began with a simple yet profound question during the discovery phase: “Why is there a build-up of General merchandise clearance stock in our warehouse?” In response, we identified two areas of immense value where we could craft innovative solutions to address this problem.

The Power of Predictive Modelling

To tackle these challenges head-on, the Client Clearance Tool applied predictive modelling. Historical SKU sales data played a pivotal role in crafting the optimal markdown strategy. What did “optimal” mean in this context? It meant ensuring that all stock was sold within the given clearance window while retaining the maximum possible profit. This innovative approach transformed clearance operations, making them more precise and profitable than ever before.

We conducted a thorough Pareto analysis revealing that a significant percentage of the challenges in making effective markdown decisions stemmed from a specific subset of SKUs. These SKUs fell into categories such as home ware and furniture, and others with minimal seasonal impact. Interestingly, the analysis also highlighted that seasonal SKUs enjoyed a more straightforward process of being discontinued, exited, and sold. This was due to the inherent nature of seasonal goods, which come with clear clearance deadlines. Take Halloween, for example. The external factors, including additional marketing and the seasonal demand for Halloween products, created a sense of urgency that propelled effective strategies by Merchandising teams for clearing this stock.

Key Innovations Achieved

• Sales uplift forecasting: Predicted impact of discounts on sales volume.
• Automated data cleaning: Diagnosed and guided resolution of data quality issues.
• £3.5m profit uplift opportunity: Through data-driven markdown strategies.
• Long-term product roadmap: Laid the foundation for ongoing innovation.

Building the Client Clearance Tool

Workflow Optimisation

The final solution was a fully productionised web application hosted on the client’s AWS infrastructure that allowed end users to log in using their secure single sign-on credentials. The tool allowed end users to drag and drop their excel clearance list into the web application using an easy to use, clean user interface. The application would then clean the excel file, diagnosing data quality issues and the advising on resolution steps. Following end user resolution, the app would generate a final clearance list, allowing end users to action the markdown with full confidence in the accuracy of the list.

Markdown Strategy Model

The model was delivered as a proof of concept ready to be fully productionised into the workflow Streamlit web application. The model proved the efficacy of the methodology and the ability to generate recommendations across all of the in scope SKUs, proving out the potential return on investment through making data driven decision for SKU level markdown strategies.

Conclusion: How our Client Clearance Tool can work for other retailers

In conclusion, the Client Clearance Tool represents a pivotal moment in the retail industry’s evolution. It was born from the desire to solve complex business problems, enhance decision-making through predictive modelling, and optimise clearance operations by using data and insights. As the retail landscape continues to shift, tools like the Client Clearance Tool will remain indispensable, empowering retailers to make smarter, more profitable decisions.