Lesson 10 | How to interpret PCFs

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Welcome 👋

 

So, you’ve calculated your first PCF. Now what?

In lesson ten, you’ll find out how to: 

  1. Spot opportunities to reduce emissions in your value chain
  2. Turn PCF insights into practical improvement actions
  3. Use your PCF to communicate with customers effectively 
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Understanding PCF results

Let’s look at three ways to use the results of your product carbon footprint, sticking with our plastic resin manufacturer example introduced in Lesson 9.

1. Finding emission hotspots

Remember those Scope 1, 2, and 3 emissions from Lesson 1? Your PCF breaks these down to show exactly where your emissions come from, helping you to find hotspots and prioritize actions.

Our plastic resin manufacturer might see:

  1. Raw material production (60% - Scope 3)
  2. Natural gas for processing (25% - Scope 1)
  3. Electricity use (10% - Scope 2)
  4. Transport and delivery (5% - Scope 3)

2. Comparing with others

PCFs help you benchmark your product against:

  • Other products in your range
  • Industry averages
  • Competitor products (if available)

Example: Our plastic manufacturer might discover their resin has 20% higher emissions than similar products, mainly due to energy-intensive processing.

3. Planning improvements

Once you’ve spotted your hotspots, you can build out a reduction plan with specific actions to decrease emissions. It’s best to focus on your biggest emission sources first, as that’s where you’ll get the most impact for your effort.

Quick wins:

✅ Optimize production temperatures 
✅ Reduce material waste 
✅ Improve logistics efficiency

Longer-term projects:

🎯 Switch to renewable energy 
🎯 Upgrade to more efficient equipment 
🎯 Work with suppliers on lower-carbon materials

Building customer trust and transparency with PCFs 

Remember the primary data share outlined in Lesson 3? It can play a crucial role in building trust with your customers. Here’s how:

Understanding your primary data score

Think of this score like an accuracy rating:

  • High score = More reliable data
  • Low score = More estimated data

Example: Our plastic resin manufacturer's PCF might show:

  • 85% primary data score for natural gas use (direct measurements)
  • 40% primary data score for raw materials (mostly industry averages)

Using the score to improve

Low scores aren't necessarily bad, instead they show where you can improve. For our plastic resin manufacturer, this might look like:

Current situation:

  • Raw materials = Low score
  • Energy use = High score

Next steps:

  1. Request PCFs from key raw material suppliers
  2. Document which data points need improvement
  3. Plan how to collect better data next time

Tip: When sharing PCFs with customers, explain your data quality and improvement plans. This transparency builds trust and shows you're serious about accuracy. 

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Check your knowledge

Time to see if it all makes sense! Take the quiz to check your understanding:

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If your customers have asked you to complete M2030's Product Carbon Footprint Academy, taking this quiz will show them you're making progress. Your answers and scores will not be shared with them – only that you have taken the quiz.

📁 Free downloads

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