Business
Challenge:

  • Client is one of the leading retail giants in GCC having outlets across multiple geographies with portfolio of over 100K SKUs across departments like FMCG, Electronics, Garments, Household etc.
  • As a key player in the retail sector, the client operates in a highly competitive environment; The company's success is deeply intertwined with its ability to effectively manage product display, maximize sales opportunities, deliver a top-notch customer experience and maintain strong relationships with suppliers.

Problem statement

  • The client encountered challenges with the product assortment and merchandising of even the top- performing SKUs, significantly affecting sales, customer satisfaction, and supplier relationships
  • The client lacked a mechanism or tool in place to recognize specific products in their inventory that were encountering problems related to assortment, hindered their ability to take corrective actions and optimize their product assortment effectively.

Objective

  • Create a system for flagging Top SKUs having potential assortment issues and generate alerts to prompt merchandisers to take corrective actions if needed.
  • Develop a monitoring system that thoroughly assesses the extent and scale of issues pertaining to product assortment, including spectrum of SKUs affected by this issue, quantifying opportunity losses, evaluating the efficacy of implemented actions, and ensuring the daily updating of this information.

TurnB Approach


EDA & Analytical Dataset creation:

  • Sales and inventory data at SKU-store level were explored and combined to form a analytical dataset. Metrics indicating SKU performance & inventory status were derived from raw data to get an overall understanding at SKU level. Evaluated SKUs based on key metrics such as sales days, stock availability, Avg. sales gap, Average daily sales.

Logic Building:

  • SKUs were classified based on performance & special attention was given to identifying SKUs with high performance
  • Developed logics to detect assortment issues among SKUs by analysing their inventory status and real- time sales performance. The average time gap between SKU sales was taken into account for precise identification of products experiencing assortment issues.

Metrics Identification and Dashboard Design:

  • Developed metrics to evaluate the magnitude and scope of challenges related to product assortment
  • Metrics encompassed a comprehensive analysis of the range of SKUs impacted by the issue, quantification of potential opportunity losses, assessment of the effectiveness of implemented strategies.
  • Designed report in such a way that, it could be sliced and diced with ease at Store - Product department - Product category – Supplier - Brand levels.
Approaches background
Infograph

Implications

  • The dashboard empowered users to take timely actions, ensuring proper display for top-performing SKUs.
  • Identification of zero-sales SKUs facilitated proactive measures to prevent them from transitioning into non-moving dead stock.
  • The resolution of disputes between clients and suppliers stemming from inaccuracies in the presentation of products eligible for rental display rebates has been significantly reduced.
  • Previously, personnel had to invest significant time and effort manually checking shelves for each product's display stock. With the introduction of the dashboard, SKUs having inefficient
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