Missing ESG Data: How to Respond When You Don't Have Everything
The questionnaire asks for forty-seven data points. You have complete information for maybe fifteen. Partial data for another ten. The rest? You've never tracked it, don't know where to find it, or aren't sure it applies to your business.
This is normal. The gap between what customers request and what suppliers can provide is enormous, especially for companies responding to ESG questionnaires for the first time. Customers know this. The platforms hosting these assessments know this. No one expects a 75-person manufacturing company to have the same data sophistication as a multinational corporation.
But how you handle gaps matters. Here's how to respond professionally when you can't provide everything.
Understand Why Gaps Are Acceptable
Customers aren't collecting ESG data because they enjoy paperwork. They're collecting it because CSRD requires them to report Scope 3 emissions and supply chain sustainability. Their regulators and auditors want to see that they've made reasonable efforts to gather supplier data.
"Reasonable effort" doesn't mean 100% response rates with perfect data from every supplier. It means systematic outreach, documented responses, and continuous improvement. Your incomplete response—if professionally presented—fulfills their compliance need. Your silence does not.
What matters is:
- You responded (demonstrating engagement)
- What you provided is accurate (they can use it confidently)
- You explained what's missing and why (transparency)
- You indicated plans to improve (trajectory)
A partial response with clear explanation beats a complete response with guessed numbers.
Categories of Missing Data
Not all gaps are the same. How you handle them depends on why the data is missing.
Data that exists but you haven't gathered yet
This is the best-case gap. Your energy bills exist; you just haven't compiled them. Your HR system tracks training hours; you just haven't run the report. These gaps close with effort and time.
Response approach: "We have not yet compiled this data for the reporting period. We expect to provide this by [date]." Then actually do it.
Data you've never tracked
Your company has never measured water consumption separately from general utilities. You've never calculated employee commuting emissions. This data could theoretically exist but doesn't.
Response approach: "We do not currently track this metric. We are evaluating implementation for the 2025 reporting period." Be honest about whether you actually plan to track it.
Data that doesn't apply to your business
A service company doesn't have manufacturing waste. A domestic supplier doesn't have ocean shipping emissions. A B2B firm may not have consumer product end-of-life data.
Response approach: "Not applicable—[brief explanation]." Example: "Not applicable—as a professional services firm, our operations do not generate manufacturing waste."
Data you can estimate but not measure
You know approximately how much your employees drive for business but don't have precise records. You can estimate waste volumes based on bin pickups but don't have weight data.
Response approach: Provide the estimate with clear methodology. "Estimated at 2,400 km per month based on average reported mileage × employee count. Actual tracking system planned for Q2 2025."
How to Present Partial Data
Structure and transparency make partial data useful.
Lead with what you have. Don't apologize upfront for gaps. Present your actual data first: "Our 2024 Scope 1 and Scope 2 emissions totaled 127 tonnes CO2e based on measured energy consumption." Then address what's missing.
Explain your methodology. For any numbers you provide, briefly note how they were calculated. "Scope 2 calculated from utility records using 2024 DEFRA grid emission factor for Germany."
Flag estimates clearly. Never mix measured and estimated data without distinction. If 80% of your response is measured and 20% estimated, make clear which is which. Tables can include a "Data Quality" column (Measured / Estimated / Not Available).
Provide confidence levels if relevant. For sophisticated customers, you might note: "High confidence: Scope 2 electricity data. Medium confidence: Fleet fuel consumption (estimated from expense reports, not direct measurement). Not available: Upstream supply chain emissions."
Estimation Methods Customers Accept
When exact data doesn't exist, reasonable estimation is better than blanks.
Extrapolation from partial data
You have nine months of energy bills but three are missing. Extrapolate based on the average of months you have, adjusting for seasonality if relevant. Note: "October-December estimated based on average consumption from January-September."
Industry averages as proxies
You don't know the carbon intensity of materials you purchase, but published databases provide industry averages. Using an average emission factor for steel, plastic, or transportation and applying it to your known quantities is acceptable methodology. Note: "Material emissions estimated using [database] average factors."
Activity-based estimation
You don't track employee commuting, but you know you have 50 employees and average commute distances are published for your region. 50 employees × average 25 km commute × 220 working days × 0.17 kg CO2e/km = estimate. Show the calculation.
Spend-based estimation
For supply chain categories where physical data doesn't exist, financial data can proxy. If you spent €100,000 on professional services, published factors convert spend to estimated emissions. This is lower quality than activity data but better than nothing.
The key is documentation. Customers using your data in their reports need to understand how it was derived. "Estimated" without explanation is useless. "Estimated based on [method]" is actionable.
What Not to Do
Don't guess without basis. Making up a number because the field can't be left blank is worse than leaving it blank. Fabricated data misleads customer reporting and can create audit problems.
Don't round to suspiciously clean numbers. Reporting exactly 100 tonnes CO2e or exactly €1 million in environmental spend looks estimated even if it happens to be accurate. Report actual figures.
Don't hide uncertainty. If your data quality is poor, say so. Customers would rather know they're working with estimates than assume precision that doesn't exist.
Don't claim policies you don't have. If the questionnaire asks "Do you have an environmental policy?" and you don't, say no. Don't upload a generic template you grabbed from the internet. This is audit risk.
Don't ignore questions entirely. An empty field with no explanation looks like you skipped it. A field noting "Not currently tracked—under development" shows engagement.
Sample Response Language
For data not tracked: "[Metric] is not currently tracked in our data systems. We plan to implement tracking for this metric beginning [quarter/year]."
For data not applicable: "Not applicable to our business model. As a [description of business], we do not [relevant activity]."
For estimated data: "Estimated at [value] based on [methodology]. We are implementing direct measurement systems for future reporting periods."
For partial data: "Complete data available for [portion]. Remaining [portion] estimated based on [approach]. Full data coverage expected from [date]."
For complex gaps: "Our current data systems capture Scope 1 and 2 emissions comprehensively. Scope 3 categories [list] are not yet tracked. We are prioritizing Category 1 (Purchased Goods) and Category 6 (Business Travel) for 2025 implementation based on preliminary materiality assessment."
Using Gaps to Plan Forward
Your missing data tells you exactly what to work on.
If you couldn't answer energy questions easily, set up monthly utility tracking. If employee data was scattered across departments, establish a central HR data repository. If you had no environmental policy to reference, consider whether creating one makes sense.
The ESG response checklist outlines what data sophisticated customers expect and where it typically lives. Using this as a guide for what to track going forward transforms next year's response from gap-filled to comprehensive.
Gaps in your first response are normal. Gaps in your fifth response to the same customer suggest you're not taking this seriously. The trajectory matters.
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