Spirefly
Webinar

How a retailer identified 5 KPIs to monitor 40,000 products

18 Jun 2026 · 30 minutes

What you'll learn

  • How HEMA scaled a single-category pilot to a full nature assessment across 40,000 products — without waiting for perfect data.
  • How ecological hotspots were mapped to specific buying teams, turning abstract biodiversity risk into five concrete public commitments.
  • How Spirefly's AI cut HEMA's data processing timeline from four weeks to four days.

Speaker

  • Josine oude Lohuis

    Josine oude Lohuis

    Chief Product Officer of Spirefly

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How HEMA scaled nature assessments to 40,000 products

Connecting corporate sustainability goals to day-to-day retail buying decisions is harder than it sounds. In this webinar, Josine oude Lohuis (Chief Product Officer, Spirefly) walks through how Dutch retailer HEMA went from a single-category pilot to five public environmental commitments — without waiting for perfect data.

The challenge of nature assessment in retail

Carbon footprinting works with one metric. Nature and biodiversity assessments don’t. Sourcing teams have to navigate up to 15 environmental indicators across thousands of products, while keeping pace with CSRD, TNFD, and EUDR requirements.

HEMA partnered with Spirefly in 2022 to build a workflow that could actually scale.

Step 1: Don’t wait for perfect data

Many sustainability teams stall because they’re waiting for clean supply chain data. HEMA didn’t. Instead, they grew their data capabilities and their internal capacity to act at the same pace — starting narrow and expanding year by year.

  • Year 1: One product category, focused on identifying the biggest impact areas (fashion, water stress).
  • Year 2: Basic material data used to map and quantify regional water risks.
  • Year 3: A complete nature assessment across all 40,000 products, integrating country-of-origin and supplier data.

Spirefly’s AI cleaned the messy, unstructured input from ERPs and supplier spreadsheets. That cut HEMA’s data processing time from four weeks to four days.

Step 2: Make it actionable for buyers

Data that buying teams can’t act on gets ignored. HEMA solved this by matching specific ecological hotspots to the business units that could do something about them.

The Food & Grocery team focused on soil pollution and land use — coffee, cocoa, pork. The Fashion & Apparel team looked at water stress, tracing the cotton used in infant clothing back to high-risk sourcing regions in India. Instead of abstract metrics, buyers received a concrete problem and a practical step: shift to certified organic or regenerative cotton.

Step 3: Turn insights into commitments

Relying on generic industry averages makes it hard to show genuine improvement year over year. HEMA used their risk assessments to identify high-exposure areas, gathered primary data where it mattered most, and used trusted certifications to raise their standards. That process led to five public commitments:

  • Transitioning material weight to recycled, organic, or regenerative alternatives
  • Implementing clean wastewater standards for Tier 1 suppliers
  • Working with high-priority partners on energy efficiency
  • Scaling audits through verified, high-impact value chains
  • Mapping supply chains for deforestation-risk commodities ahead of EUDR

Key takeaways

Build your team’s capacity to act at the same rate your data quality improves — not after. Give each buying team one metric, one audience, and one action. And before making public commitments, use scenario planning to test how sourcing changes will actually affect your targets.

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