Tailoring Assortment Strategies: How HIVERY Curate Transforms Store Execution
In the competitive Consumer Packaged Goods (CPG) and retail landscape, achieving the right product assortment strategy on the shelf is crucial for driving sales for vendors and retailers while satisfying customer needs. However, traditional methods often fall short in accounting for hyper-local demand and operational constraints. This is where HIVERY Curate comes into play, a tool utilizing machine learning and applied mathematics to simulate, analyze, and optimize assortment strategies at a granular store level. Through this use case, we will explore how HIVERY Curate—significantly impacted retail execution for a national retail chain, improving operational efficiency and sales performance.
As a category captain, this famous food production company, operating over 500 stores, struggled with underperforming categories, inconsistent inventory levels, and overstock issues while preparing planograms. Despite having vast store-level sales data, the retailer found it challenging to tailor assortment plans to meet local demand. The retailer sought to rationalize its SKU assortment, optimize space, and better align with consumer preferences.
The food production company partnered with HIVERY to leverage the power of HIVERY Curate. The project commenced with a comprehensive data integration phase where historical sales data, store attributes, and other relevant data were fed into the HIVERY Curate platform.
- Hyper-Local Assortment Planning: HIVERY Curate analyzed the data to provide hyper-local, retail-specific insights, enabling precise assortment plans per store. Through iterative simulations, Curate proposed optimized assortments that better matched local demand.
- SKU Rationalization: Utilizing real-world constraints and brand portfolio goals, HIVERY Curate aided in SKU rationalization, identifying underperforming SKUs for delisting and suggesting potential additions at the store level.
- Space Productivity Maximization: By evaluating the existing space utilization, product attributes of each SKU, and store attributes such as fixtures and merchandising styles, HIVERY Curate suggested modifications to maximize the productivity of the existing space, ensuring optimal shelf placement and category adjacencies.
- Scenario Planning for Growth Opportunities: HIVERY Curate facilitated scenario planning, allowing the retailer to simulate various strategies and assess the potential impact, from demand transfer across the portfolio to re-optimizing cluster strategies and planogram numbers.
- Supply Chain Optimization: While DC optimization was on the roadmap, HIVERY Curate provided insights into Days of Supply (DOS) at the store level, aiding in better inventory management and reducing overstock issues.
- Planogram generated: Once the strategy is decided, HIVERY Curate also generates the planograms, with close to 80% of the planograms ready for export into applications like JDA and others needing review.
Post-implementation, the retailer experienced a significant improvement in category performance, reduced stockouts and overstocks, and enhanced operational efficiency. The ability to simulate and qualify dynamic strategies led to more informed decision-making and a more streamlined execution process. Moreover, the retailer now had a robust tool for ongoing assortment optimization, setting a solid foundation for data-driven retail execution in the future.
What does this mean?
HIVERY Curate transformed the supplier's and retailer’s approach to assortment planning, enabling a more granular, data-driven, and proactive strategy. By tailoring assortments to meet local demand and optimizing operational processes, the retailer significantly improved sales performance and operational efficiency, showcasing the immense value and impact of HIVERY Curate in modern retail execution.