Scope 3 Data Collection 2026 | Thai Factories Also Collect

“We’re still struggling just to calculate Scope 1 and 2” is something we hear more and more often from Japanese-owned factories in Thailand. But almost without anyone noticing, Scope 3 data collection has landed on the desk of the Thai-side procurement and production control team, not the Japanese head office. The reason is simple: part of what counts as Scope 3 for the head office is the emissions of the Thai suppliers that the Thai factory itself orders from. In other words, a Thai factory is both a data provider to its parent company and a data collector from its own suppliers. Using a model case — an automotive parts factory in Chonburi province — this article counts, honestly, how to collect data from 42 tier-1 suppliers, and what happens when the data does not come in.

Scope 3 Data Collection Is No Longer Just Japan Head Office’s Job

When Thai factory staff hear the phrase “sustainability disclosure,” the first association is usually distance — “the head office is putting some report together.” A few years ago, that distance was largely accurate. Disclosure was the listed parent company’s responsibility, and a Thai manufacturing subsidiary was, at most, asked to report annual electricity usage once a year.

That sense of distance is breaking down for two reasons. The first is that the parent company’s consolidated emissions figures directly include the Thai factory’s emissions. Under the general accounting principles of the GHG Protocol, emissions from a subsidiary that is capital-affiliated and falls within the consolidation boundary — whether under the operational control approach or the equity share approach — are, in principle, booked into the parent company’s consolidated Scope 1 and Scope 2, not Scope 3. In other words, the electricity the Thai factory uses shows up in the parent’s disclosure documents as “Scope 2.” Once the parent company becomes subject to mandatory disclosure, the Thai factory will have to provide its own electricity and fuel data at a level of granularity that can withstand an audit.

The second reason is the subject of this article. The parts, materials, outsourced processing, and logistics that the Thai factory procures come from companies in Thailand and elsewhere in ASEAN that have no capital relationship with the parent company. Emissions from a business partner with no capital relationship are booked, from the parent’s perspective, as Scope 3. In particular, the portion that falls under Category 1, “purchased goods and services,” is the area where emissions are largest for many manufacturers.

And this Category 1 data cannot be collected directly by head office in Japan. It is the Thai factory that issues the purchase orders, and it is the Thai factory’s procurement staff who talk with supplier representatives in Thai on a daily basis. The moment head office says “please collect primary Category 1 data,” the work lands on the Thai side.

How the consolidation boundary is set — whether the operational control approach or the equity share approach is used — affects exactly where a company’s own Scope 1/2 ends and Scope 3 begins. This article describes the general way of thinking about it, but the actual consolidation treatment and boundary should always be confirmed with the parent company’s relevant department and with accounting and sustainability specialists.

Scope 1, 2, and 3 in Plain Operational Terms

Let’s clear up the terminology first. As explained in zeroboard’s overview of supply chain emissions, the GHG Protocol divides emissions associated with business activity into three groups.

Scope 1 and Scope 2 are self-contained — they can, in principle, be calculated from your own fuel receipts and electricity meters. We covered the calculation method and typical costs for this part in detail in our previous article, Visualizing CO2 Emissions – Scope 1 and 2 Calculation and Costs for Thai Factories. If you haven’t tackled that piece yet, read it first.

The problem is Scope 3. It is split into 15 categories, and every one of them happens outside your own company. It doesn’t appear on your own invoices — or if it does, only the amount in currency is shown, not the emissions. This basic fact, that the emissions aren’t recorded in your own books, is the root cause of why data collection is hard.

Of the 15 categories, the one that becomes a problem first for almost every manufacturer, without exception, is Category 1, “purchased goods and services.” As long as you’re buying parts, the emissions generated when those parts were made are treated as part of your own supply chain. The same zeroboard article notes that Category 1 is the largest single category of emissions for many manufacturers.

International analyses suggest that, for many companies, roughly 75% of emissions occur outside the company itself — among suppliers, in logistics, or with customers (Council Fire’s How Supply Chains Track Scope 3 Data, Normative’s Scope 3 supplier engagement). This is a general tendency that varies widely by industry and business model, not a figure you can apply directly to a single factory. Still, it points in one direction: even if you cut hard inside your own walls, you’re only touching part of the total.

Two Directions Pull the Thai Subsidiary Into Scope 3

Let’s separate the two directions mentioned above a little more precisely. Mixing them together in internal discussions is a reliable way to talk past each other.

The “providing” side is self-contained within the company. It’s hard, but the shape of the task is clear: get your own electricity meters and fuel receipts in order. This is the scope of our previous article.

The “collecting” side is a completely different animal. The counterpart is not your own employee but an independent company. It’s a request, not an instruction. And the party you’re asking may not even have the ability to provide the data in the first place. This is the focus of this article.

It’s also easy to overlook that these two directions run at the same time. Just as you’re closing out your own Scope 1/2 numbers to meet the parent company’s reporting deadline, you also need to be running supplier data requests. At a factory with only one person handling this, the moment the two collide in the same month, the workload becomes unmanageable.

The SSBJ Mandate Schedule — It Starts From Fiscal Year Ending March 2027 and Rolls Out in Stages

Now for the timeline — what’s needed by when. On January 8, 2026, Japan’s Financial Services Agency announced the schedule for mandating the sustainability disclosure standards set by the SSBJ (Sustainability Standards Board of Japan).

As of January 2026, roughly 70 to 80 Japanese companies have a market cap of 3 trillion yen or more (Mono Que’s 2026 outlook by solution area, Tokio Marine dR’s explanation of the mandate timeline, Sustainability Navi’s summary of the SSBJ standards).

Seeing that count, some people relax, thinking “our parent isn’t on that list.” But what actually matters in practice is one step further down the chain. Each of those 70 to 80 companies with a market cap of 3 trillion yen or more has anywhere from several hundred to several thousand suppliers. Once those companies start collecting primary Category 1 data, mid-size companies that are not themselves mandated become “suppliers being asked to provide it.” Only 70 to 80 companies are directly mandated, but the number of companies asked to submit data is many times larger.

The tier with a market cap of 1 trillion yen or more but under 3 trillion yen follows from fiscal year ending March 2028, and the 0.5-to-1-trillion-yen tier around fiscal year ending March 2029. Many Japanese manufacturing parent companies fall into one of these tiers. The preparation window that remains is not long.

Category 1 Is the Main Battleground for Supply Chain CO2 Data Collection

Trying to tackle all 15 Scope 3 categories at once guarantees you’ll stall. In practice, starting with Category 1 is the standard approach, for three reasons.

First, the volume is large. In manufacturing, emissions from making purchased goods tend to dominate, and leaving this out means you can’t see the overall picture.

Second, the entry point for the data is clear. Everyone in Category 1 is already in your own purchasing data. Who you ordered from and how much you paid is visible in your procurement or accounting system. It’s not like business travel or commuting, where you don’t even know who to ask.

Third, it connects to actual reduction levers. Once supplier emissions are visible, concrete options — design changes, switching suppliers — come into view. Some categories remain visible but not actionable from where you sit.

So this article focuses on Category 1. We will not put numbers or dollar figures on the remaining 14 categories here. Expanding outward once Category 1 collection is running smoothly is the realistic order of operations.

Model Case | Counting Suppliers at an Auto Parts Factory in Chonburi Province

From here we work through concrete numbers. What follows is our own original estimate, not figures from any real company. Focus less on the specific amounts and headcounts, and more on the structure of how you count and where the process gets stuck.

Picture a Japanese-owned automotive parts factory in Chonburi province, Thailand, with 150 employees. Its Japanese parent is a manufacturer listed on the Tokyo Stock Exchange, assumed to fall into the market-cap tier of 1 trillion yen or more but under 3 trillion yen — which puts fiscal year ending March 2028 disclosure obligations on the horizon.

This factory’s annual spending on raw materials and parts totals 480,000,000 THB. It has 42 tier-1 suppliers, spanning stamped metal, resin molding, surface treatment, auxiliary materials, and outsourced heat treatment — mostly Thai small and medium-sized companies.

When the factory asked all 42 companies, “Could you share last year’s emissions data?”, the results looked like this.

The six companies that could submit data were all mid-size firms with their own Japanese or European capital participation, and had already built calculation systems in response to the same request from their own parent companies. The remaining 36 are locally owned or family-run processing shops, some of which don’t even track their monthly electricity usage.

Notice that the share by headcount and the share by procurement value don’t match. By headcount, only 14% can provide data — but by procurement value, that covers 35%. Larger accounts tend to be bigger companies, which are more likely to already have a calculation system in place. Flip that around, and the remaining 65% — 312,000,000 THB worth of procurement — is, for now, simply unavailable as data.

For reference, assume this factory’s own Scope 1/2 figures are as follows.

Comparing this figure of 1,000 t-CO2 with the Category 1 estimate we’ll calculate in the next section shows why supply chain CO2 data collection is unavoidable.

Primary and Secondary Data — Where the Practical Difference Shows Up

When suppliers don’t provide data, that doesn’t mean you have to give up on calculating anything. There’s a fallback: secondary data.

Primary data is emissions calculated by the supplier itself from its own actuals — how many kWh it used, how much of which fuel it burned, and the resulting CO2. It’s a measured figure.

Secondary data is estimated using an emission factor built from industry averages. A common approach uses a spend-based factor — a coefficient like “buying 1,000,000 baht worth of this industry’s products produces, on average, this much CO2,” multiplied by the procurement amount.

In practice, you’ll be mixing the two for the foreseeable future — primary data from companies that can provide it, secondary data filling the gaps for those that can’t. That’s not a compromise; it’s the current standard approach.

What you do need to understand, though, is what happens when you mix the two. We’ll put numbers on it in the next section.

Original Estimate | How Far Off Is a Secondary-Data-Only Projection

Back to the model case. Assume this factory’s spend-based emission factor is 2.5 t-CO2 per 1,000,000 THB — again, a hypothetical coefficient for the purposes of this original estimate.

First, here is the Category 1 estimate if all 42 companies are estimated using secondary data alone.

480,000,000 THB ÷ 1,000,000 × 2.5 = 1,200 t-CO2

Given that the Scope 1/2 total above was 1,000 t-CO2, Category 1 alone is 1.2 times that. Even after cutting hard inside your own factory walls, the emissions hidden behind what you buy turn out to be larger — and that’s the number for just one of Scope 3’s 15 categories.

Next, compare the portion covered by the six companies that provided primary data. Their combined procurement value is 168,000,000 THB, so the secondary-data estimate for them works out to:

168,000,000 THB ÷ 1,000,000 × 2.5 = 420 t-CO2

But the actual primary data submitted by these six companies totaled 294 t-CO2.

The gap is 126 t-CO2 — the secondary-data figure runs 30% higher (126 ÷ 420 = 30%).

The reason isn’t hard to guess. The six companies that could provide data were the ones that had already built calculation systems in response to the same request from their own parent companies — and companies with calculation systems in place have usually also worked on energy efficiency. In other words, they’re on the low-emissions side of the industry average. Multiplying by the industry-average factor overstates their emissions without ever seeing their actual effort.

What about the overall picture? The remaining 36 companies are still estimated using secondary data.

312,000,000 THB ÷ 1,000,000 × 2.5 = 780 t-CO2

Adding the six companies’ primary-data figure of 294 t-CO2 gives a blended estimate of:

294 + 780 = 1,074 t-CO2

Overall, the gap is 126 t-CO2, or 10.5% (126 ÷ 1,200 = 10.5%). Simply replacing six companies’ figures with primary data shifts the reported number by 10.5%.

What matters here isn’t which figure is “correct” — both follow the same valid calculation rules. The problem is that the same factory’s emissions for the same year shift by 10.5% depending on how much data you’ve managed to collect. If you report a number to the parent company without understanding this swing, then the moment primary data increases the following year, it can look as though emissions dropped even though nothing was actually reduced — or the reverse.

As Long as You Rely on Secondary Data, Reductions Can Only Be Shown by Cutting Purchase Volume

Secondary data has a structural limitation that’s more serious than its lack of precision. A spend-based factor is just a coefficient multiplied by procurement value. Which means there’s only one condition under which the estimate goes down: procurement value going down.

Consider a concrete case. Suppose one of the 36 companies above installs solar panels on its roof, replaces an old compressor, and actually cuts its own emissions by 20%. That’s a genuine achievement. But in the model factory’s books, since it never received that company’s primary data, the reduction registers as 0 t-CO2 — because procurement value didn’t change.

This structure produces two unwelcome results.

First, suppliers have no incentive to reduce emissions. If the effort never shows up in the customer’s numbers, there’s less reason to spend money on energy efficiency.

The second is worse. For a company that only has secondary data, the only way to claim it has “reduced Scope 3” is to cut procurement value — switch to a cheaper supplier, or lower the spec to bring down unit prices. That will genuinely lower the estimate. But actual CO2 in the atmosphere hasn’t dropped by a single gram. If the cheaper supplier happens to be in a region that relies on coal power, real-world emissions could even increase.

This is exactly why a system for collecting primary data matters. Mono Que’s analysis also points out that while secondary data will continue to serve as a substitute for now, companies will increasingly demand primary data directly from key suppliers over the medium term, and suppliers that can demonstrate actual emissions reductions will become the ones chosen as trading partners.

The Practical Work of Collecting Scope 3 Supplier Data — Who, What, How Often

This is where the real work begins. The first thing to design in Scope 3 data collection isn’t the fine print of calculation rules. It’s four questions: who to ask, what to ask, how often, and in what format.

Who to ask. Approaching all 42 companies with equal intensity will burn out whoever is running the process. Rank suppliers by procurement value and designate the top group — the range that covers most of total spend — as your “priority group” for primary data requests. In the model case, six companies covered 35% of procurement. Fill the rest with secondary data for now, and widen the priority group the following year. Without this staged design, you’ll run out of steam in year one.

What to ask. This is where many teams go wrong. A request that just says “please tell us your CO2 emissions” almost never gets a response, because the recipient has no way to answer it. Ask instead for items they can answer straight from their own invoices — purchased electricity for the period, fuel types and quantities used, and their own annual revenue or shipment value. With these three items, you can allocate and estimate emissions on your own side. Ask for the raw material to calculate emissions, not for the emissions figure itself — that’s the practical trick.

How often to ask. Asking monthly wears the other side out; asking once a year loses both accuracy and freshness. Twice a year — once every half-year — is the realistic middle ground. Align the timing with the parent company’s reporting cycle so it’s fixed. Getting suppliers to the point where they think “oh, it’s about time for that request again” is directly tied to your response rate.

What format to ask for. This is the single biggest factor in workload. Ask without a standardized format, and 42 companies will send back 42 different formats — some in kWh, some in MWh, some by calendar year, some by fiscal year, some as scanned PDF images. As shown later, reconciling all of this eats an enormous amount of time.

One more point: state clearly, in the request itself, what the collected data will be used for and who it will be shared with. To a supplier, electricity usage and revenue are sensitive business information. A request with no stated purpose gets treated with suspicion and stalls. State up front that the data will be used for the parent company’s disclosure and that individual company figures won’t be disclosed to third parties, and your response rate will clearly improve.

Original Estimate | How Man-Hours Change Between Ad Hoc Excel Requests and a Standardized System

Let’s count the man-hours for requesting data individually by Excel, without a standardized format. This too is an original estimate.

That’s 3.5 hours per company. Across 42 companies, that’s 147 hours; running it twice a year, once per half-year, comes to 294 hours a year — close to two months of a single person’s time spent purely on collecting data.

By contrast, consider standardizing the format, building a web input form, making units and periods selectable fields, and automatically flagging entries that are obviously off by an order of magnitude.

That’s a saving of 226.8 hours a year. At an hourly rate of 450 THB for the person handling this, the value works out to:

226.8 hours × 450 THB/hour = 102,060 THB/year

On the other hand, building the system costs money.

The net annual effect is 102,060 minus 36,000, or 66,060 THB. Against the 234,000 THB initial cost, the simple payback period is:

234,000 ÷ 66,060 = 3.5 years

Man-Hour Savings Alone Don’t Pay Back Fast — The Other Value We Are Not Putting a Price On

We’re presenting 3.5 years as-is. As an investment criterion, that is by no means a fast payback. If you try to justify the internal budget on man-hour savings alone, this number becomes an obstacle.

There are ways to make the number look better — value the time at a manager’s hourly rate, convert the saved hours into overtime pay avoided, or assume a higher collection frequency to inflate the hours saved. But a number built that way stops being useful for decision-making, so this article presents it as it is.

So why recommend building the system anyway? The answer lies in the part we haven’t put a price on.

The real value of systematizing emissions data collection is being able to meet the conditions for staying in business with your customer. Once the parent company becomes subject to mandatory disclosure from fiscal year ending March 2028 and adds primary Category 1 data submission as a trading condition, factories will split into those that can respond and those that can’t. The loss for landing on the wrong side of that split is an order of magnitude larger than the man-hour savings.

But we are not putting a monetary figure on this value, because it requires too many assumptions about when the buyer will make the demand and at what threshold. The moment you start a calculation like “assume the probability of losing the business is low,” the estimate becomes nothing more than a stack of assumptions. We take the position that numbers you can’t actually verify shouldn’t be mixed into an investment decision, so we leave this unquantified.

The question worth weighing is this: on top of the man-hour savings that pay back in 3.5 years, you’re getting ahead of a demand that is almost certain to arrive within a few years. Together, do these justify the 234,000 THB initial investment? That’s not something the money alone can answer.

The Structure Behind Why Suppliers Who Can’t Provide Data Get Dropped

Let’s go one step further. This structure runs in two directions.

One is the risk of your own company becoming the side that “can’t provide.” Once the model factory’s parent company becomes subject to mandatory disclosure from fiscal year ending March 2028 and asks its consolidated subsidiaries to submit Scope 1/2 data, a factory that isn’t tracking monthly electricity use won’t be able to respond. This is the scope of our previous article, but with a concrete deadline now visible, it’s no longer something to put off.

The other is the effect of your own company becoming the side that demands data. Suppose the model factory adds emissions data submission as a trading condition for its tier-1 suppliers. That would affect the 36 companies that can’t provide data — 312,000,000 THB, or 65% of procurement.

Switching that 65% all at once simply isn’t realistic. Replacing a processing partner you’ve spent years refining quality with, just because it can’t provide data, will show up immediately as higher defect rates and missed deadlines. So in practice, this isn’t about switching — it’s about developing suppliers: teaching them how to report data, handing over the format, and filling it in together the first time. Who bears that burden is a conversation that will inevitably come up internally.

As Environment+Energy Leader’s article on Scope 3 data points out, Scope 3 data is fundamentally dependent on suppliers’ readiness, and many suppliers are not yet in a position to provide emissions data at the granularity and format needed to withstand an audit. This state does not resolve itself just because the requesting party waits.

And over the medium term, as Mono Que’s analysis states, suppliers that can actually demonstrate emissions reductions will become the trading partners of choice. Being able to provide data becomes the baseline condition, and actual reduction performance gets compared on top of that. Thai factories owned by Japanese companies will be playing “requester” and “the requested” at the same time within this structure.

Where Climate-Related Disclosure Stands in Thailand and ASEAN Right Now

Everything so far has been framed around the Japanese parent company. Let’s also check where Thailand’s own regulatory framework stands.

According to PRE Sustainable Consultancy Bangkok’s analysis and Tres Innovations’ practical reporting guide for ASEAN supply chains, the climate-related disclosure currently required in Thailand and across ASEAN remains centered on Scope 1 and 2. Financial regulators in each country are progressively rolling out climate disclosure aligned with the ISSB’s (International Sustainability Standards Board) S2 standard, but none have reached the stage of mandating Scope 3 across the board.

The same sources note, however, that companies should start preparing for Scope 3 disclosure now, because waiting until the requirement arrives leaves too little time to build supplier relationships.

For Japanese-owned manufacturers in Thailand, this time lag is actually an opportunity. Build a collection system now, while Thai regulation hasn’t yet demanded Scope 3, in response to the Japanese parent’s requirements — and by the time Thai regulation does move, the system will already be running. Conversely, if you keep fielding requests from Japan with one-off Excel files, you’ll end up doing the same work twice once both regimes arrive.

Note that some aspects of Thailand’s specific application timeline and penalties are still under discussion. This article does not state deadlines that haven’t been finalized; always check the latest status against primary sources and specialists.

On-Site Measurement Data Becomes the Evidence Itself — The Role of OT and IoT Traceability

Finally, let’s connect this back to the factory’s own OT and IoT systems.

We’ve been talking about collecting data from suppliers, but the premise underneath all of it is that your own factory needs to be one that can provide credible data itself. Whether reporting electricity use to the parent company or handing a format to a supplier and explaining it, having nothing more than an invoice total carries little persuasive weight.

If you measure your own electricity by equipment or by process, several things fall into place at once. First, your Scope 2 reporting to the parent company is backed by actual measurement, not just invoices. Second, you can produce emissions per unit of production, letting you distinguish whether emissions rose because output grew or because efficiency worsened. Third — the most practically useful part — you can show suppliers an actual example of “here’s how we measure our own data.”

We’ve already described the measurement system itself in the context of energy management. For the flow from equipment-level electricity measurement through to investment payback, see ISO 50001 Energy Management 2026 – Payback Starts with Visualizing Electricity. Calculating emissions is just one output of that same measurement data.

This also fits naturally with traceability. A factory that records which lot was produced on which equipment for how many hours can allocate electricity use to that lot. When the day comes that product-level carbon footprints are demanded, the gap between a factory that already has this linkage and one that doesn’t will be enormous. Right now, this article is about Category 1 of Scope 3 — but product-level emissions disclosure is what’s coming after it.

Getting Started | Four Steps

Here’s a practical order for getting started.

Step 1 — Inventory your purchasing data. List the past year’s procurement actuals by supplier, in descending order of spend. Understand how many suppliers you deal with, and how much of total spend the top group accounts for. Without this list, you can’t decide who to approach first. Most factories can pull this from their accounting system in a day.

Step 2 — Estimate the whole with secondary data. Use a spend-based emission factor to estimate all suppliers first. Accuracy doesn’t matter yet. The goal is to see how large Category 1 emissions are compared with your own Scope 1/2. Once that number is in hand, internal priorities tend to shift.

Step 3 — Request primary data from the priority group. Set a priority group based on top procurement value and send a standardized-format request. Plan for a low response rate the first time around — it’s normal for less than half to come back even after requesting, explaining, and following up. Record what came back and what didn’t, and feed that into how you design the next round.

Step 4 — Make collection a recurring routine. Fix the timing, format, and follow-up schedule of the request, and run it as a twice-a-year cycle. Only once this is in place does the workload actually start to fall. Stop after the first request, and next year you’ll pay the same cost all over again.

A great many factories stall at Step 3, but that’s not a failure — a low response rate the first time is expected, and you should proceed on that basis. What’s actually dangerous is using a low response rate as a reason not to move on to Step 4, and slipping back into ad hoc Excel requests the following year.

Frequently Asked Questions

Where should we start with Scope 3 data collection?

Start by inventorying your purchasing data. A list of annual procurement value by supplier, sorted in descending order, tells you who to approach first for primary data. Starting with a deep dive into calculation rules tends to mean you never actually get started.

What if a supplier can’t provide emissions data?

For now, substitute secondary data based on a spend-based emission factor. Keep in mind, though, that because secondary data is proportional to procurement value, it won’t reflect actual reductions a supplier makes. In the model case, a secondary-data-only estimate of 1,200 t-CO2 dropped to 1,074 t-CO2 once six companies’ figures were replaced with primary data — a 10.5% difference.

Does the Thai subsidiary’s Scope 1/2 count as the parent company’s Scope 3?

Generally, no. Under GHG Protocol accounting principles, emissions from a capital-affiliated subsidiary within the consolidation boundary are, in principle, booked as the parent’s consolidated Scope 1/2. What’s booked as Scope 3 is emissions from business partners with no capital relationship. That said, treatment can vary depending on how the consolidation boundary is defined, so always confirm the specific treatment with a specialist.

Does systematizing emissions data collection pay for itself?

In the model case’s original estimate, the net annual effect was 66,060 THB against an initial cost of 234,000 THB, for a simple payback period of 3.5 years. Looking at man-hour savings alone, that’s not a fast payback. The main value of systematizing collection is being able to meet the conditions for staying in business, but because that value requires too many assumptions, this article does not put a monetary figure on it.

If our Japanese parent isn’t subject to mandatory disclosure, can we do nothing?

Not necessarily. Only around 70 to 80 companies are directly mandated as of fiscal year ending March 2027, but each of them has anywhere from several hundred to several thousand suppliers. It’s far more likely that you’ll be asked to submit data as one of those suppliers than that you’ll be personally exempt.

Summary

For Japanese manufacturers with factories in Thailand, Scope 3 data collection is no longer just something head office in Japan deals with. A Thai factory is both a provider of Scope 1/2 data to its parent company and a collector of Category 1 data from its own suppliers. It’s worth recognizing up front that these two directions run at the same time.

The regulatory timeline is concrete. Companies with a market cap of 3 trillion yen or more are mandated from fiscal year ending March 2027, the 1-to-3-trillion-yen tier from fiscal year ending March 2028, and the 0.5-to-1-trillion-yen tier around fiscal year ending March 2029, in that order. Only around 70 to 80 companies are directly mandated, but the number of companies asked to respond as their suppliers is many times larger.

In the model case, only 6 of 42 tier-1 suppliers could submit emissions data — 35% by procurement value. Estimating all suppliers with secondary data alone gives 1,200 t-CO2, but replacing six companies’ figures with primary data brings that down to 1,074 t-CO2, a 10.5% difference. The same factory’s numbers for the same year move depending on how much data was collected. And as long as you rely on secondary data, reductions can only be shown by cutting purchase volume — even a supplier that genuinely cut emissions by 20% shows up as 0 t-CO2 in the books.

Systematizing collection cuts 226.8 hours a year, worth 102,060 THB. Net of the 36,000 THB operating cost, that’s 66,060 THB a year, giving a simple payback of 3.5 years on a 234,000 THB initial investment. Looking at man-hour savings alone, that’s not a fast payback. The real value of systematizing lies in being able to meet the conditions for staying in business, but because that requires too many assumptions, we haven’t put a figure on it. All of this is an original estimate, not figures from a real company, so focus on the structure of how to count rather than the amounts themselves.

Start by sorting your own purchasing data by supplier, in descending order of spend. How many suppliers do you deal with, and how much of total procurement does the top group cover? Once that list exists, you already have half of what you need to begin Scope 3 data collection.

It’s fine if you haven’t decided where to start. TOMAS TECH works with Japanese-owned factories in Thailand on production control and energy management systems, and we’re happy to talk through inventorying your purchasing data and figuring out what to ask suppliers for, even before any decision to implement anything. Consultations that don’t assume implementation are welcome too — if you’d like to start by simply counting your own suppliers, reach out via our contact page.

References

• Mono Que — 2026 Outlook by Solution Area – Decarbonization and the Start of Mandatory Scope 3 Disclosure, the SSBJ mandate schedule and supplier data readiness
• Tokio Marine dR — SSBJ Sustainability Disclosure Standards Mandate Expected as Early as Fiscal Year Ending March 2027, the earliest mandate timing
• Sustainability Navi — 2026 Update – When Do the SSBJ Standards Become Mandatory, coverage and phased rollout
• zeroboard — What Is Supply Chain Emissions – Scope 1, 2, 3 Differences and Practical Points, definitions of Scope 1/2/3 and the 15 categories
• Council Fire — How Supply Chains Track Scope 3 Data, the general breakdown of supply chain emissions
• Normative — Scope 3 Supplier Engagement – Collecting Primary Carbon Data, supplier engagement in primary data collection
• Environment+Energy Leader — Scope 3 Data Depends on Suppliers. Most Suppliers Are Not Ready., supplier-side readiness
• PRE Sustainable Consultancy Bangkok — ESG Report 2026 – No Longer Just a Report, But a Test of Readiness, the current state of climate disclosure in Thailand
• Tres Innovations — Scope 3 Emissions in ASEAN Supply Chains – A Practical Reporting Guide, the practice of Scope 3 reporting in ASEAN