If you lead sustainability or procurement at a retailer or distributor, you’ve probably had this conversation. You build a thoughtful supplier portal. You write a clear data request. You get on calls with the producers behind your top-selling SKUs. And then you wait. Some of the data trickles in. Most of it doesn’t. The producers you most need — the ones with the volume, the brand, the recipe — are the most reluctant to share.
The natural reaction is to assume bad faith, weak processes, or a missing carrot. Push harder. Add escalation paths. Tie reporting to commercial reviews.
It rarely works. And the reason is structural.
The paradox
Everyone in the supply chain — producers, distributors, retailers — wants transparency on climate performance. Not as a compliance exercise, but as a business driver. A producer who can show what sits behind a low PCF — supplier negotiations, recipe reformulations, investments in production processes, solar panels on the roof, waste reduced, logistics optimised — has a real story to take to market. That story differentiates them in tenders, supports premium pricing, and earns them shelf space they couldn’t otherwise win.
But the moment they share the underlying detail with a customer, two specific risks open up.
The first risk is margin squeeze. The buyer learns exactly where cost sits in the producer’s operation, and uses that knowledge in the next negotiation. Years of formulation work and supplier relationships become input to the next round of price talks.
The second risk is copy and circumvent. The buyer reproduces the product as their own private label, or skips a step in the chain by going directly to the producer’s upstream supplier. Either way, the producer has handed over the map to their own business.
The obvious workaround is to let producers calculate their own PCFs and just send the results. Activity data never leaves their environment; the customer gets the number it needs; the commercial risk disappears.
It doesn’t work in practice. Most producers don’t have the resources, methodology or tooling to calculate PCFs at scale across their assortment. The few that do produce results in different shapes and formats, with no representativeness indicator and no transparent data quality. Comparing the numbers is impossible: most often because no underlying data is provided, and even when it is, the differences in methods, system boundaries and emission factor libraries make like-for-like comparison practically out of reach. A retailer trying to roll the numbers up, or to benchmark two suppliers in a tender, has nothing it can actually use.
So producers want to be transparent on climate performance. They cannot afford to be transparent on the rest. And the obvious shortcut — self-reporting — leaves the customer with PCFs it can’t compare, can’t roll up, and can’t put in front of two competitors in a tender and expect either to accept the verdict, even when one of them loses.
That’s the paradox. Suppliers want to be transparent to show their good work and help drive their business, but if they are they will also hurt their business. It isn’t reluctance, and it isn’t bad faith. It’s a rational response to incompatible demands: be transparent about what you do, but don’t give away how you do it.
The paradox shows up in two layers most retailers underestimate.
Direct producers are willing to talk in general terms but fall silent when asked for the most sensitive activity data: the ingredient bill of materials and the specific suppliers behind those ingredients. Yields, energy intensities and transport modes are sensitive too, but it’s the recipe and the upstream supplier list that producers protect first.
Importers and distributors, who account for a large share of the assortment in many retailer portfolios, often can’t share the data even if they wanted to. Their producers have already declined to give it to them. The importer is sitting in the same paradox, one rung down.
The result: the more transparency you ask for, the less you get back.
Why pressure doesn’t fix it
Three approaches keep coming up in retailer projects, and all three run aground on the same rock.
“We’ll build a great portal.” A well-designed UI helps with reporting fatigue, but it doesn’t change the underlying calculus. The information being requested is still flowing from supplier to buyer. Better forms don’t make sensitive data less sensitive.
“We’ll mandate it.” Mandating disclosure as a condition of listing forces compliance only on the SKUs producers can’t afford to lose, in whatever minimum format they choose to submit. You end up with low-quality, inconsistent data and a deteriorating relationship.
“We’ll use averages until they share more.” Averages are fine for a baseline footprint and the disclosure boxes that go with it. They stop working the moment you need to identify real reductions or reward suppliers who are outperforming their peers. Two producers sitting in the same industry average look identical to your data, even when one is reducing year on year and the other isn’t. There’s no signal to act on, and no incentive for the strong performer to keep pushing.
None of these address why the data isn’t moving. They just change which side of the relationship absorbs the friction.
The principle that resolves the paradox
The paradox dissolves the moment you stop trying to move data and start trying to move results.
Five design principles for the model that resolves the paradox:
An impartial intermediary holds the methodology and the data. The model only works if the calculation sits with a neutral party that has no stake in the price negotiation. The intermediary guarantees methodological consistency across producers, runs the same emission factor library and the same calculation engine for every PCF, and is contractually responsible for keeping activity data out of the wrong hands and the right results in the right hands. The same intermediary becomes the channel through which a single dataset can flow to many customers: a producer reports once, and that data feeds every customer and every regulatory line, without retyping the same numbers into ten different formats.
Supplier-retained ownership. Activity data has to leave the producer’s environment — an intermediary needs it to run the calculation, and without that, comparison across producers isn’t possible. What doesn’t leave is ownership of that data. The intermediary processes it under contract; the customer receives results, not the recipe; and neither party can use the data for anything the producer hasn’t agreed to. Control of the asset stays where it started.
Results travel downstream, not data. What flows downstream to the customer is the calculated PCF and the breakdowns required for reporting (CSRD, SBTi FLAG, LSRS, retailer-specific cuts). Not the underlying recipe. The producer keeps the asset; the buyer gets the answer.
Primary-data share is visible on every PCF. Every calculated footprint carries an explicit indicator of how much of it is built on primary activity data versus secondary library averages. A customer reading the number knows immediately whether they’re looking at a producer-specific result or a generic stand-in. This is what makes the model self-reinforcing: a producer who collects more primary data — and who gets their own sub-suppliers to do the same — looks better than the producer who doesn’t, on the same shelf, in the same tender. Transparency about the inputs becomes a competitive advantage instead of a compliance cost.
The supplier learns from their own reporting. A model that only feeds the customer’s spreadsheet is a tax on the producer. One that also feeds the producer’s own understanding — what drives their footprint, which interventions actually move the number — turns reporting into a learning experience. Producers start engaging with it voluntarily: for product development, for conversations with their own sub-suppliers, for the next round of customer dialogue. The burden becomes a collaboration tool.
When these five are in place, the conversation with suppliers changes shape. You’re no longer asking them to give up something valuable; you’re asking them to participate in a model that protects what’s valuable to them and reduces their reporting burden at the same time. That’s a conversation that can actually move forward.
What this means for retailers right now
You don’t need to wait for an industry-wide platform to apply the principles. You can do three things this quarter:
Audit what you’re actually asking for. Look at the data fields in your supplier portal and separate the ones you genuinely need (activity inputs, country of origin, packaging) from the ones you’ve drifted into asking for because they were easy to add to the form. Every field that touches recipe-level information is a field that triggers the paradox.
Stress-test the tool you’re using or evaluating. Whatever platform you’ve adopted, or are picking between right now for supplier engagement, hold it up against these five principles before signing anything. Does ownership of activity data really stay with the producer, or does it land in your account by default? Is the calculation engine genuinely impartial, or does the vendor have a stake on either side of the trade? Does it deliver comparable, defensible PCFs across complex multi-tier value chains — not just simplified pilots — and has that been demonstrated on assortments at the scale of yours? A tool that can’t answer those questions cleanly will end up reproducing the paradox under a new logo.
Be honest about what averages can and can’t do. If your reduction strategy depends on producer-specific PCFs, you cannot get there with averaged data, however good the secondary library is. The path to producer-specific data runs through a model the producer is willing to use. There is no shortcut around that.
The reframe
The Transparency Paradox isn’t a barrier to building a PCF programme. It’s a design constraint that, once respected, makes the programme faster and the supplier relationship better than it was before you started asking.
The retailers who treat it as a barrier spend two years pushing on a door that opens the other way. The ones who treat it as a constraint design around it from day one — and end up with better data, sooner, from suppliers who are willing to participate again next year.
It’s the difference between transparency from your suppliers and transparency with them. The paradox only resolves in the second frame.
