Situation
A global beauty and personal care brand had accumulated over 10,000 active SKUs across categories, channels, and regions. The merchandising and finance teams wanted to reduce assortment complexity without compromising topline performance or brand equity.
Many low-performing SKUs existed for strategic or marketing reasons (hero products, seasonal items, gifting lines, regulatory requirements), making it impossible to rely solely on revenue or margin as the basis for discontinuation decisions. The SKU-level data was fragmented across systems, and the manual effort required to assess trade-offs made the process slow, subjective, and difficult to scale across the portfolio.
Objective
The client needed a structured, scalable way to evaluate over 10,000 active SKUs and make defensible discontinuation decisions across brands, channels, and regions. Four goals shaped the engagement:
- Surface the true cost of maintaining low-performing SKUs, including the often-hidden operational burden of long-tail assortments.
- Protect strategically important items (hero products, seasonal lines, regulatory SKUs) from being unintentionally cut by a purely financial screen.
- Reduce manual analysis time to allow the organization to refresh its SKU portfolio more frequently and with more confidence.
- Deliver an interactive tool that product, marketing, and finance teams could use together to simulate impact and align on cross-functional decisions.
Approach
We built the rationalization model in layers, starting with data consolidation and moving through classification, strategic overlay, and dashboard delivery.
SKU scoring modelWe evaluated each SKU across three dimensions (sales volume, gross margin, and cost-to-maintain) to produce a composite performance score. This multi-factor approach prevented SKUs with low volume but high margin from being flagged incorrectly, and vice versa.
Quadrant classificationWe applied quadrant-based logic to segment the full portfolio into four groups: High Margin/High Volume (HMHQ), High Margin/Low Volume (HMLQ), Low Margin/High Volume (LMHQ), and Low Margin/Low Volume (LMLQ). Each quadrant received a default rationalization recommendation, with the LMLQ group forming the primary discontinuation candidate pool.
Strategic rationale overlayWe grouped SKUs by business rationale: hero, seasonal, gifting, regulatory, display, and other strategic categories. This overlay ensured that financially weak SKUs held for strategic reasons were clearly flagged and excluded from the discontinuation shortlist unless explicitly overridden by the team.
Interactive BI dashboardWe delivered a dashboard with toggles to test conservative versus aggressive rationalization thresholds, drill-down views by region, category, and channel, and a deep-dive table for top-performing SKUs with granular metrics. All outputs were designed for cross-functional use across product, marketing, and finance teams.
Figure 1SKU portfolio quadrant analysis: the four quadrants (HMHQ, HMLQ, LMHQ, LMLQ) segment the full portfolio by volume and gross margin. The Pareto curve (top right) shows that a small percentage of product codes drive the majority of gross profit, the core insight behind the rationalization case.
Figure 2Deep-dive table for high-contribution SKUs: gross profit, gross margin, units sold, mix of business, COGS, and gross sales by product code, filterable by quadrant, region, country, and channel to support SKU-level prioritization decisions.
Figure 3Channel-wise retail sales over three years (2016-2018): total sales broken down by Brand.com, FSS, and Retailer channels with year-over-year waterfall analysis and 3-year CAGR, identifying which channels are recovering and which are structurally declining.
Impact
The analysis revealed that approximately 60% of SKUs contributed less than 5% of total gross profit, a clear signal of assortment inefficiency that gave leadership the evidence needed to accelerate a rationalization initiative that had previously stalled on data access.
Manual analysis time dropped by over 70%. The team moved from multi-week, spreadsheet-based reviews to a structured, repeatable process that could be refreshed on a regular cadence. That speed unlocked a more proactive portfolio management discipline, rather than one-off rationalization exercises.
The strategic rationale overlay meant that brand, finance, and sales teams could align on discontinuation decisions without fear of accidentally cutting strategically important lines. The shared framework replaced fragmented, subjective debates with a structured, data-backed process, and the interactive dashboard made cross-functional alignment faster and more durable.