Description

A focused course, tailored for you

Issuer Climate Data for Index and Research Teams

Turn patchy issuer disclosures into climate datapoints an investment team trusts for index inclusion, factor models, and client questions.

Two issuers in the same sub-industry have scope-3 numbers an order of magnitude apart. The portfolio manager wants to know which one to trust before the next index reconstitution.

$199 one-time

Tailored to your situation. Access within 24 hours. 30-day money-back.

Includes a hand-built implementation playbook delivered alongside course access, generated for your specific situation.

Why this course

Issuer climate datasets fail under one specific pressure: a client, a PM, or a regulator asks why a number is what it is and the chain of provenance breaks. The CDP response was filed against a different boundary than the 10-K. The SBTi flag was current as of the last data pull but the company has since had its target validated, withdrawn, or marked as committed-only. The scope-3 estimate uses a sector-average intensity factor for one issuer and a supplier-engagement bottom-up for the next. The forward-looking pathway was modelled before the issuer's latest capex announcement. Each of those is defensible in isolation. None of them is defensible in a single methodology document without a reconciliation layer and a dated audit trail. The research seat owns that reconciliation. The course teaches the reconciliation as a repeatable discipline, not a one-off project, so the same dataset can carry an index, a factor model, a client report, and a regulator-facing methodology disclosure without three different versions of the truth.

What you walk away with

Read a CDP climate response against the same issuer's 10-K or 20-F and produce a reconciled scope-1, scope-2, and scope-3 estimate with a documented boundary.
Normalise scope-3 categories across sector-average, hybrid, and supplier-engagement estimation methods so two issuers in the same sub-industry are comparable.
Track SBTi status changes (committed, validated, removed, expired) at issuer level with a dated audit trail the methodology committee will accept.
Build an implied temperature rise calculation a client can reproduce from the underlying issuer pathway, sector decarbonisation reference, and base year.
Document the provenance chain for every issuer datapoint so a regulator question or a client query can be answered in one working day, not three.

The 12 modules

Module 1. The issuer-level provenance contract

What the research seat actually owes the product team. The shape of a defensible issuer datapoint: value, units, boundary, estimation method, source citation, source date, ingestion date, reviewer initials. Why this matters when an index goes into reconstitution and the methodology committee asks for one issuer's full chain in the meeting. Templates for the issuer datapoint record and the per-issuer change log.

Module 2. Reading CDP against the 10-K and the sustainability report

Three issuer filings, three different boundaries, three different reporting periods. How to pick the canonical boundary for index purposes and how to document the deviation when CDP and the financial filing disagree. Worked example for a multi-segment industrial issuer where the 10-K consolidates differently than the CDP submission, and the reconciliation note that a PM will accept.

Module 3. Scope-3 category normalisation across estimation methods

Scope-3 category 1 purchased goods reported as sector-average for one issuer, EEIO-based for the next, supplier-engagement bottom-up for the third. How to label the estimation method on the issuer datapoint, when to override the issuer-disclosed number with your own estimate, and how to flag the override so it survives the next refresh. Mapping table for the fifteen GHG Protocol scope-3 categories and the methods you will see in practice.

Module 4. SBTi status as a time-series, not a flag

An SBTi target that was validated last quarter and removed this quarter is two different datapoints. How to ingest the SBTi public register as a dated event stream, attach each event to the issuer record, and produce a status-as-of-date answer for any historical query. The fix for the most common error: a stale boolean SBTi flag that breaks back-tests when the index is reweighted.

Module 5. Implied temperature rise that a client can reproduce

The end-to-end calc from issuer-level forward pathway plus sector decarbonisation reference plus base year plus benchmark scenario to a single ITR number. Why the same issuer can land at 1.7 degrees under one sector pathway and 2.4 under another, and how to document the choice so the client recreates your number. Worked example across an oil major, an automaker, and a regional utility.

Module 6. Sub-industry reconciliation and the order-of-magnitude question

When two issuers in the same GICS sub-industry have scope-3 estimates an order of magnitude apart, the answer is usually disclosure boundary or estimation method, not real-world difference. How to run a sub-industry sanity check before the dataset ships, how to flag the outlier for review, and the short reconciliation note that lets the PM accept both numbers as defensible.

Module 7. Forward-looking pathway under capex and divestiture events

An issuer announces a major capex programme or a segment divestiture mid-quarter. The previously modelled pathway is now wrong. The discipline for re-modelling the pathway, dating the change, preserving the prior pathway for back-tests, and surfacing the change to the product team so the index methodology document carries the correct as-of date.

Module 8. CSRD, ISSB S2, SEC, and TCFD legacy in one issuer record

An EU-listed issuer filing CSRD with limited assurance is producing different artefacts than a US-listed issuer responding to SEC climate disclosure and a Japan-listed issuer publishing an ISSB S2-aligned report. How to map all of them into a single issuer record without losing the assurance level, the standard, or the filing date. The reconciliation layer that lets a multi-listed issuer carry one canonical dataset.

Module 9. Estimation models you build versus models you buy

When the issuer does not disclose, you estimate. The choice between a vendor model, a sector intensity model you maintain in-house, and an issuer-specific bottom-up estimate. How to document the model version, the input vintage, and the back-test result so the methodology committee can sign off, and the per-issuer note explaining why this issuer got this method.

Module 10. The client question that arrives at 16:30

A client asks why issuer X has a different temperature alignment in your dataset than in a competing provider. The hour-by-hour drill from the question to the defended answer: pull the issuer record, surface the boundary, the estimation method, the SBTi event log, the pathway version, the base year, and the sector reference. The reply template that closes the question without opening five more.

Module 11. Reproducibility, versioning, and the back-test that survives reweighting

An issuer-level dataset is only as good as its history. How to version the dataset, snapshot it at each index reconstitution, and run the back-test so a methodology change is visible in attribution rather than hidden in the data. The two failure modes (silent restatement and unversioned overrides) and the controls that catch both.

Module 12. Shipping the methodology document and the regulator-facing trail

The final artefact is a methodology document that an external assurance reader can follow. The structure that works: scope, boundary rules, estimation hierarchy, override policy, SBTi handling, ITR calculation steps, change log. The per-issuer appendix that lets a regulator or a client follow a single name from raw filing to published number. Templates for the methodology document and the per-issuer evidence pack.

How this addresses your situation

Specific modules that map to what you said you are dealing with.

A PM emails to ask why two same-sub-industry issuers have scope-3 numbers an order of magnitude apart, and you need a defended answer before the next reconstitution.

An issuer's SBTi target was validated, then removed, then re-committed across three quarters, and the back-test is breaking because the dataset carries a single boolean flag.

A client wants to reproduce the implied temperature rise number for one issuer and your current documentation does not let them recreate it from public inputs.

A regulator-facing methodology document is due and the per-issuer evidence pack does not yet carry the boundary, source date, and estimation method on every datapoint.

What you get with this course

Twelve written modules in the Art of Service learning environment.
Issuer datapoint record template and per-issuer change log template.
Scope-3 category normalisation mapping table for the fifteen GHG Protocol categories.
SBTi event stream ingestion pattern and status-as-of-date query template.
Implied temperature rise worked examples across an oil major, an automaker, and a regional utility.
Sub-industry reconciliation sanity-check pattern and outlier review note template.
Methodology document skeleton and per-issuer evidence pack template.
The hand-built implementation playbook tuned to your issuer coverage and your data stack.

What you will have in hand by Day 1, Week 1, Month 1

Within 24 hours: account in the Art of Service learning environment is provisioned and the hand-built implementation playbook is delivered alongside it.

Week 1: modules 1 to 4 cover the provenance contract, CDP versus financial filing reconciliation, scope-3 category normalisation, and SBTi as a time-series.

Week 2: modules 5 to 8 cover implied temperature rise, sub-industry reconciliation, forward-pathway updates under capex events, and multi-standard issuer records.

Week 3: modules 9 to 12 cover estimation model governance, the 16:30 client question drill, dataset versioning and back-tests, and the methodology document plus per-issuer evidence pack.

Before and after

Before

Issuer climate datapoints carry a value and a source but not a boundary, an estimation method, or a dated audit trail. A PM question or a client query takes three days to answer because the provenance has to be reconstructed each time.

After

Every issuer datapoint carries its full provenance chain on the record. PM questions, client queries, and regulator-facing methodology questions are answered in one working day from the same dataset that ships to the index.

What happens if you do not address this

The next methodology refresh ships with the same patchy provenance, the next reconstitution carries the same sub-industry outliers without a documented reason, and the next client question takes the same three days to answer. The longer the reconciliation layer is missing, the harder it is to retrofit because back-tests start to depend on the undocumented decisions.

Who it is for

Built for the climate or sustainability research analyst inside an index, ratings, or asset-management data provider. You sit between issuer-level raw filings and the product team that ships indices, factor models, and client-facing climate reports. You read CDP, 10-K, 20-F, sustainability reports, SBTi public registers, TCFD/ISSB-aligned disclosures, and regulator filings. Your output is a defended dataset, not a marketing chart. You answer to a methodology committee, an investment committee, or a client-coverage team, and the questions you get are always specific: why this issuer, this metric, this date, this number.

Who this is NOT for. Not for ESG generalists writing thematic pieces, not for stewardship teams running engagement programmes, not for sales engineers demoing a climate platform, not for issuers preparing their own disclosures. The course assumes you ingest issuer filings as primary source and ship structured datapoints downstream.

How it arrives

Text-based course in the Art of Service learning environment, plus downloadable templates and worked examples for every module, plus the hand-built implementation playbook delivered alongside course access.

Time investment. Three to four hours per module, paced over three to four weeks. Templates and worked examples are lift-and-adapt for an in-flight methodology refresh, so the course pays back inside the first refresh cycle.

Why $199 is the right number

Generic ESG analyst courses cover concepts without the issuer-level reconciliation discipline. Vendor methodology trainings teach a single provider's model rather than the underlying issuer-data work. Internal documentation usually captures the current state but not the discipline that produced it. This course is the discipline, written for the research seat that ships datapoints to product.

FAQ

Does the course assume any specific data platform or vendor?

No. The patterns are platform-neutral. The hand-built implementation playbook is tuned to your stack.

Is the scope-3 work GHG Protocol aligned?

Yes. The category normalisation table tracks the fifteen GHG Protocol categories and the estimation methods you will see in practice.

What does the implementation playbook actually contain?

A per-issuer-coverage walkthrough of the discipline: which issuers in your coverage need the reconciliation layer first, where the provenance chain currently breaks, and the templates pre-populated for your dataset shape.

Can I share the templates with my team?

Yes. The licence covers the seat and the team working alongside it on the same issuer dataset.

30-day money-back guarantee. If after a week of working through the materials this is not what you needed, reply to the receipt email and a full refund is processed. No questions, no forms.

Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.