Significant Judgement and Measurement Uncertainty

3. SIGNIFICANT JUDGEMENT AND MEASUREMENT UNCERTAINTY

In preparing these sustainability‑related financial disclosures in accordance with IFRS S1 General Requirements for Sustainability‑Related Financial Information and IFRS S2 Climate‑Related Disclosures, Carlsberg Malaysia Group applied several significant judgements and utilised estimation techniques that involve inherent uncertainty. These disclosures are intended to provide transparency into (i) areas where management exercised judgement, (ii) estimation methodologies, and (iii) limitations that may affect the precision of reported sustainability‑related information.

3.1 Significant Judgements in Applying ISSB Requirements

(a) Judgements in Identifying Material Sustainability‑Related Risks and Opportunities (SRO)

Management exercised significant judgement in determining which SRO may reasonably be expected to influence Carlsberg Malaysia Group’s business sustainability and financial prospects. Judgement was also applied when considering which metrics included within the disclosure topics (IFRS S1 — Responsible Drinking and Marketing, IFRS S1 — Energy Management and IFRS S2 — Climate Resilience), in the industry-based SASB Standards, were most material to our business sustainability. 

Key judgement areas include:

• Materiality Thresholds
  We assessed materiality using both qualitative and quantitative considerations, including:
  - potential financial exposure (e.g., revenue at risk, cost increases, capex impact);
  - likelihood and severity of disruption to brewery operations in Shah Alam;
  - stakeholder expectations (e.g., regulators, investors, customers);
  - local regulatory developments, including Malaysia’s trajectory towards net zero by 2050 and anticipated carbon pricing.

• Inclusion and Exclusion of Topics
Significant judgement was applied to:
- include physical climate risks related to flooding, heat stress and water scarcity;
- include transition risks arising from carbon tax, renewable energy adoption, supply chain decarbonisation and packaging sustainability pressures;
- exclude risks assessed as immaterial due to low likelihood or low financial exposure, such as climate impacts on upstream agricultural inputs not directly sourced by Carlsberg Malaysia Group.

• Determination of Relevant Time Horizons
We aligned risks and opportunities to short‑, mediumand long‑term business planning cycles (less than 5 years; 5–10 years; 10 years and more).

Judgement was required to determine which risks are sufficiently foreseeable for disclosure under ISSB. 

(b) Judgements on Aggregation and Disaggregation of Sustainability Information
To present decision‑useful information without obscuring material details, management applied judgement in determining appropriate levels of aggregation. Major considerations included:

• Consolidated vs site‑specific metrics
  Environmental metrics (energy, water, emissions) are presented on a group basis because operational processes are centralised at the Shah Alam brewery, covering production and logistic facilities, and variations across product lines do not materially influence sustainability‑related outcomes.

Scope 3 Category Selection 

Only Category 5 (Waste), Category 6 (Business Travel) and Category 7 (Employee Commuting) are disclosed due to current data availability and materiality. Categories with immaterial influence, unreliable data or where supplier‑level granularity is unavailable were not reported, pending data consolidation and verification.

Treatment of Non‑Financial Metrics 

Where reasonable, metrics that influence each other (e.g., electricity and thermal energy usage, or packaging material impacts) were presented together to reflect operational interdependencies.

(c) Judgements in Ensuring Connected Information

Management applied significant judgement to ensure alignment between sustainability‑related disclosures and the financial statements, including:

• determining how climate‑related assumptions (e.g., carbon tax projections, energy cost escalation) connect to financial statement inputs such aso impairment assessments, provisions and long-term capex planning;
• identifying areas where timing differences or differing data sources may lead to temporary inconsistencies (e.g., year-end cut-off for certain operational data vs financial reporting systems).

Despite these efforts, certain metrics may still diverge due to differences in reporting cadence, external datasets or estimations used. 

3.2 Measurement Uncertainty

The preparation of sustainability‑related financial information inherently involves estimation. The key areas of measurement uncertainty for Carlsberg Malaysia Group include the following:

(a) Uncertainties in Scope 3 Greenhouse Gas Emissions Estimates 

Estimating Scope 3 emissions involves multiple assumptions because data availability varies across categories. Sources of uncertainty include: 

• Use of Proxy and Self‑Reported Data Employee commuting estimates are derived from People & Culture’s data inputs and employees’ self‑declared travel behaviours, which introduces variability and sampling uncertainty.
  Business travel emissions require estimations based on claim records that may omit certain itinerary details (flight class, connecting legs). Waste‑related emissions (Category 5) depend on data extrapolated to annualise values.

• Emission Factors and Databases
  Emission factors are sourced from DEFRA, IPCC or other public databases, which may not fully reflect Malaysia’s grid characteristics, local waste treatment variation or regional commuting patterns.
• Lack of Supplier-Level Primary Data
  Supplier-specific emissions for packaging materials, transport distances and upstream production are not yet available. As such, management used regionally-appropriate generic factors which introduce estimation uncertainty.

• Absence of Sensitivity Data
Changes in key assumptions — such as employee commuting distance ±10% or waste composition variability ±15% — could materially shift estimates. Sensitivity analyses will be introduced in future years as part of planned data improvement initiatives.

(b) Measurement Uncertainties in Climate-Related Scenario Analysis
In conducting scenario analysis aligned with IFRS S2 requirements, management relied on multiple assumptions embedded within global datasets under the IPCC AR6 framework. Key uncertainties include:

• Climate Model Variability
Regionalised climate projections for Peninsular Malaysia carry uncertainty due to: 

• coarse spatial resolution of global climate models;
• limited local hydrological data;
• variability in projected rainfall and temperature patterns across models.

• Transition Risk Assumptions
Projections on carbon tax, renewable energy adoption costs, electricity tariff volatility and regulatory timelines are inherently uncertain and based on evolving national policy announcements.

• Judgements on Scenario Probability and Severity
  Assigning weightings or likelihood to scenarios (e.g., 1.5°C, 2°C, >2°C pathways) requires judgement because ISSB does not prescribe probability assessments and local policy direction remains fluid.
• Financial Impact Modelling Limitations
  The translation of climate impacts into financial estimates (e.g., additional capex for resilience upgrades, flood protection measures or increased energy costs) requires assumptions on:
  • future discount rates;
  • timing of physical impacts;
  • future raw material pricing volatility.

These inputs may change significantly with new data or regulatory developments. 

(c) Data Limitations and System Constraints
Across multiple metrics — including energy use, water consumption and waste generation — measurement uncertainty arises from:

• reliance on manual data submissions, particularly for waste contractors;
• varying accuracy of metering and monitoring equipment;
• estimation of missing data points where delays in third-party verification occur.

Management has implemented internal controls to improve data completeness but acknowledges that operational and system limitations still contribute to uncertainty.

(d) Future Improvements to Reduce Estimation Uncertainty

To enhance the precision of measurement and reduce uncertainty over time, the Group is undertaking the following initiatives:

• improving commuting survey methodology to capture more granular, verifiable data;
• improving integration of sustainability data collection
  systems with financial reporting systems.