Prévoir vs. Excel: Why Fashion Teams Are Rethinking the Spreadsheet

Excel has served as the operating system for fashion retail for decades. It’s flexible, universally understood, reliable and effectively free. For financial planning and Open to Buy management, it remains indispensable.

Assortment planning is different because the challenge lies in deciding what products to carry, not just how many. Fashion is visual and contextual, but spreadsheets manage it through text and numbers. As collections grow more complex, critical context gets lost in translation. Teams are left with structure but no insight into what attributes and visual elements are driving sales.

This visibility gap is why merchandising teams are moving beyond static spreadsheets toward visual intelligence platforms like Prévoir.¹

1. Seeing Product, Not Just Describing It

A spreadsheet cannot see a product. A "red floral midi dress" exists only as text. It lacks proportion, color nuance, and silhouette. These distinctions matter to merchandisers deciding what products resonate best with their customers, but they disappear the moment they enter a cell.

Manual data entry and spreadsheet-based workflows are inherently error-prone. Research on spreadsheet accuracy has shown that even in controlled environments, human-generated spreadsheets frequently contain errors, with error rates compounding as complexity increases.²

Prévoir treats products as visual assets. The platform analyzes imagery directly to standardize attributes such as sleeve volume, contrast, and hemline across the assortment. This removes subjectivity from tagging and enables teams to evaluate performance based on what customers actually respond to rather than how an item was described months earlier.

The result is a more precise understanding of which visual details drive demand.

2. From Snapshots to Living Demand

Spreadsheets represent a single moment in time. Once a report exports from Shopify or an ERP, it immediately begins to age. Maintaining accuracy becomes a continuous cycle of re-exports, reconciliations, and workarounds.¹

This lag is costly for forecasting. Forecast accuracy remains one of retail’s most persistent challenges, particularly in fashion where trend shifts and seasonality add complexity. Research has shown that forecasting errors directly contribute to markdowns, stockouts, and excess inventory.³

Platforms built specifically for merchandising ingest data continuously and update in real time. Forecasts adapt to current sales velocity rather than relying solely on historical averages. Planning shifts from retrospective reporting to responsive decision-making.

3. Time Spent Maintaining vs. Time Spent Thinking

The true cost of spreadsheets is the labor they require. Merchandising teams routinely spend large portions of their week exporting data from multiple, fragmented tools, cleaning datasets, reconciling reports, and managing thousands of rows manually.¹

When foundational reporting and tagging workflows are automated, merchants can shift from assembling information to interpreting it. They can focus on connecting product performance to customer behavior, identifying emerging trends earlier, and curating collections with greater strategic clarity.

4. When “Free” Becomes Expensive

Excel carries no subscription fee, but its limitations introduce financial drag.

• Inventory bought too deep into attributes losing relevance.

• Early demand signals missed because reports lag reality.

• Missed opportunities buried in thousands of rows of data.

• Markdown exposure driven by outdated size assumptions.

Inventory distortion—overstocks and stockouts combined—cost retailers an estimated $1.77 trillion globally in 2023, underscoring how costly misalignment between supply and demand can be.⁴

Improving visibility into demand and product performance directly supports better inventory decisions. Research consistently shows that more integrated, data-driven merchandising processes can improve sell-through and reduce excess stock exposure.⁵

The Bottom Line

Excel is not disappearing. It remains an essential financial tool.

However, managing modern fashion assortments requires more than rows and columns.

The strongest teams understand the difference between accounting for a product and truly understanding it. Inventory may live in spreadsheets, but proactively managing product performance and planning collections demands visibility, integration, and intelligence.

Sources

1. McKinsey & Company, Jumpstarting Value Creation with Data and Analytics in Fashion and Luxury, https://www.mckinsey.com/industries/retail/our-insights/jumpstarting-value-creation-with-data-and-analytics-in-fashion-and-luxury

2. Raymond R. Panko, “What We Know About Spreadsheet Errors,” Journal of End User Computing, 1998; updated research summaries available via arXiv: https://arxiv.org/abs/0801.0715

3. Rajesh K. Tyagi et al., “Retail Performance Measures for Seasonal Fashion Products,” Journal of Fashion Marketing and Management, Emerald Publishing.

4. IHL Group, “Inventory Distortion Will Cost Retailers $1.77 Trillion in 2023,” Retail TouchPoints, 2023, https://www.retailtouchpoints.com/features/industry-insights/ihl-study-inventory-distortion-will-cost-retailers-1-77-trillion-in-2023

5. McKinsey & Company, Merchandising and Pricing Optimization in Retail; see also McKinsey State of Fashion Technology Report 2022 for documented improvements in full-price sell-through through digital tools.