Resources Sector ESG Reporting on D23.io

Table of Contents

1. Why ESG Reporting Matters for Resources Companies
2. Understanding Scope 1, 2, and 3 Emissions
3. D23.io and Apache Superset for ESG Data
4. Building Your ESG Reporting Dashboard
5. Tailings and Environmental Compliance Tracking
6. Integrating Multiple Data Sources
7. Governance and Social Metrics
8. Audit Readiness and Regulatory Compliance
9. Implementation Timeline and Costs
10. Next Steps and Getting Started

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Why ESG Reporting Matters for Resources Companies

The resources sector faces unprecedented scrutiny from investors, regulators, and communities. Environmental, Social, and Governance (ESG) reporting is no longer optional—it’s a business imperative that directly impacts capital access, operational licences, and shareholder value.

Major institutional investors now mandate ESG disclosures before committing capital. In Australia, the ASX Corporate Governance Council has strengthened ESG expectations, and international frameworks like the Global Reporting Initiative (GRI) Standards have become the de facto baseline for transparency. For mining and resources companies specifically, environmental accountability around emissions, water management, and tailings safety has become non-negotiable.

The challenge isn’t understanding what to report—it’s consolidating fragmented data across mining operations, processing facilities, logistics networks, and corporate functions into a single source of truth. Most resources companies operate across multiple sites, jurisdictions, and regulatory regimes. A single copper mine might have scope 1 emissions from diesel generators, scope 2 from grid electricity, and scope 3 from shipping concentrates to customers. Without a unified reporting platform, tracking these metrics becomes a manual, error-prone exercise that delays disclosures and invites audit findings.

This is where D23.io’s managed Superset stack changes the game. Built specifically for Australian and Asia-Pacific resources companies, D23.io provides a pre-configured, enterprise-grade analytics platform that automates ESG data collection, consolidation, and reporting. Rather than piecing together spreadsheets and custom reports, your team gets real-time visibility into emissions, compliance metrics, and sustainability KPIs across all operations.

According to the Annual Trends Report 2024 from the Sustainability Institute, ESG integration is now the top priority for boards in extractive industries. Companies that report transparently and respond quickly to emerging sustainability risks outperform peers in equity valuations and operational efficiency. The window for getting this right is closing—investors and regulators expect audited, verified ESG data, not estimates.

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Understanding Scope 1, 2, and 3 Emissions

Before you can report emissions effectively, you need to understand what you’re measuring. The Greenhouse Gas Protocol, the global standard adopted by SASB Standards and most corporate sustainability frameworks, divides emissions into three scopes:

Scope 1: Direct Emissions

Scope 1 covers emissions you directly control—fuel burned in company-owned equipment, vehicles, and facilities. For a mining operation, this includes:

• Diesel consumed by haul trucks, dozers, and loaders
• Natural gas or fuel oil used in processing plants
• Methane vented or flared from underground mines
• Explosives detonated during blasting
• Fuel for on-site power generation

Scope 1 is typically the largest emissions category for resources companies. A single open-pit copper mine might generate 50,000+ tonnes of CO2-equivalent annually from diesel alone. The advantage of scope 1 is that it’s usually under direct operational control—you can measure fuel consumption at the pump, track equipment hours, and implement efficiency improvements quickly.

The challenge is granularity. If your mine operates 200 haul trucks across three shifts, you need real-time fuel data from each vehicle, not monthly summaries. Without automated data feeds from your fleet management system, you’re left estimating consumption based on hours worked—introducing compounding errors.

Scope 2: Indirect Emissions from Purchased Energy

Scope 2 covers emissions from electricity, steam, heating, and cooling purchased from external suppliers. For resources companies, this is significant:

• Grid electricity powering processing mills, crushers, and concentrators
• Purchased steam for heap leach operations
• Chilled water for cooling systems

Scope 2 emissions depend entirely on your energy supplier’s grid mix. A processing facility in Queensland powered by coal-heavy grid electricity will have much higher scope 2 emissions than an identical facility powered by renewable energy in South Australia. Scope 2 reporting requires:

1. Monthly electricity consumption data from your utility bills
2. Grid emissions factors (tonnes CO2 per megawatt-hour) specific to your region and utility
3. Tracking of renewable energy contracts or certificates that offset grid electricity

The complexity multiplies when you operate across multiple states or countries. Each grid has different emissions factors, and factors change annually as grids decarbonise. D23.io’s managed stack handles this automatically, pulling grid factors from official sources and updating them without manual intervention.

Scope 3: Indirect Emissions from Your Value Chain

Scope 3 is the wildcard—it covers emissions from suppliers, customers, and transport that you don’t directly operate. For resources companies, scope 3 often includes:

• Shipping ore concentrates or refined products to customers
• Fuel and emissions from contractor equipment (drilling, blasting, haulage)
• Emissions from purchased goods (explosives, reagents, equipment)
• Emissions from employee commuting and business travel
• End-of-life emissions from products sold (e.g., CO2 released when customers smelt your copper concentrate)

Scope 3 is notoriously difficult to measure because it depends on supplier data you often don’t have. A mining contractor might operate haul trucks on your lease, but they control fuel consumption and maintenance. You need their cooperation to get accurate data—and they may not track it to your standards.

However, scope 3 is increasingly material. The TCFD Hub emphasises that investors want to understand full value-chain emissions, not just what happens at your mine gate. For commodities like copper and iron ore, scope 3 can exceed scope 1 and 2 combined, especially if products are shipped long distances or processed by energy-intensive customers.

D23.io’s approach to scope 3 is pragmatic: it provides templates for collecting contractor and supplier data, calculates emissions using standard conversion factors where direct data isn’t available, and flags high-risk scope 3 categories for further investigation. This lets you report transparently while acknowledging data limitations.

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D23.io and Apache Superset for ESG Data

D23.io is a managed analytics platform built on Apache Superset, specifically configured for Australian and Asia-Pacific resources companies. Rather than forcing you to build dashboards from scratch, D23.io provides pre-built ESG reporting templates that connect directly to your operational data sources.

What Is Apache Superset?

Apache Superset is an open-source business intelligence and data visualisation tool that lets non-technical users query databases, create dashboards, and generate reports. Unlike enterprise BI tools that require SQL expertise, Superset uses a visual query builder—you point and click to select metrics, filters, and chart types. The result is faster time-to-insight and lower operational costs.

For ESG reporting, Superset’s strengths are:

• Real-time data: Connect to operational databases and pull live emissions, consumption, and compliance data
• Multi-source integration: Combine data from your SCADA systems, fleet management, utility bills, and lab systems into a single view
• Audit trails: Every dashboard query, filter, and export is logged—critical for regulatory audits
• Role-based access: Restrict sensitive data to authorised users (e.g., only finance sees cost impacts, only operations sees facility-level emissions)
• Export and sharing: Generate PDF reports, export data for external audits, and share dashboards with stakeholders

The challenge with vanilla Superset is configuration. You need to understand your data schema, write SQL queries, design dashboards for non-technical users, and manage security and access controls. A typical Superset rollout takes 12-16 weeks and costs $150K+. For a resources company with 5+ mining sites and complex data flows, that’s a significant investment.

This is where D23.io changes the equation.

D23.io’s Managed ESG Stack

D23.io is a pre-configured, managed instance of Apache Superset optimised for ESG reporting in the resources sector. Instead of building from scratch, you get:

• Pre-built ESG templates: Dashboards for scope 1, 2, and 3 emissions, water usage, tailings management, safety metrics, and governance KPIs
• Data connectors: Pre-configured connections to common systems (SAP, Maximo, fleet telematics, utility APIs)
• Emissions calculations: Automated scope 1, 2, and 3 calculations using latest GRI and TCFD methodologies
• Compliance templates: Dashboards aligned to ASX, SASB, and international ESG reporting standards
• Managed updates: D23.io handles software updates, security patches, and methodology changes—you don’t manage infrastructure
• Expert support: Access to ESG specialists and data engineers who understand resources sector reporting

The result is a 6-week deployment instead of 16 weeks, and a fully functional ESG reporting platform at a fraction of traditional BI costs. PADISO has deployed D23.io for multiple AU mining and resources companies, delivering working dashboards in fixed-fee engagements that cover architecture, data integration, semantic layer configuration, dashboard design, and team training.

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Building Your ESG Reporting Dashboard

A well-designed ESG dashboard is more than charts and numbers—it’s a decision-making tool that lets stakeholders understand performance at a glance and drill down into root causes. Here’s how to structure one using D23.io.

Dashboard Architecture

Start with a three-level hierarchy:

Level 1: Executive Summary — One page showing your top ESG KPIs: total emissions (scope 1, 2, 3), emissions intensity (tonnes per tonne of ore processed), water usage, tailings storage facility safety rating, and governance maturity score. This is what your CEO presents to the board.

Level 2: Functional Dashboards — Separate dashboards for operations, environment, social, and governance teams:

• Operations: Fuel consumption, electricity usage, equipment efficiency, contractor compliance
• Environment: Emissions by scope and facility, water balance, tailings metrics, biodiversity indicators
• Social: Workforce diversity, safety incidents, community engagement, indigenous affairs
• Governance: Board composition, executive remuneration, risk management, audit findings

Level 3: Facility Dashboards — Drill-down to individual mine sites, processing plants, and offices. Operations managers see real-time data for their facility and can compare against peers.

Key Metrics to Include

For a resources company, your ESG dashboard should track:

Emissions:

• Total scope 1, 2, and 3 emissions (tonnes CO2-e)
• Emissions intensity (CO2-e per tonne of ore, per tonne of product, per dollar revenue)
• Emissions by source (fuel type, facility, business unit)
• Year-to-date vs. target and prior year
• Trajectory to 2030/2050 net-zero targets

Energy:

• Total energy consumption (MWh) by source (diesel, natural gas, electricity, renewable)
• Renewable energy percentage
• Energy intensity (MWh per tonne of ore)
• Grid emissions factor (CO2-e per MWh) for your regions

Water:

• Total water consumption and discharge (megalitres)
• Water intensity (megalitres per tonne of ore)
• Water recycling rate
• Tailings storage facility water levels and pH

Tailings:

• Tailings storage facility (TSF) capacity utilisation
• TSF safety rating (based on ICMM or equivalent framework)
• Seepage and leakage incidents
• Downstream impact monitoring

Social:

• Workforce diversity (gender, age, indigenous representation)
• Lost-time injury frequency rate (LTIFR)
• Total recordable incident rate (TRIR)
• Community grievances and resolution rate
• Local procurement spend

Governance:

• Board diversity and independence
• Executive remuneration linked to ESG performance
• Audit findings and remediation status
• Policy and procedure compliance

D23.io’s templates include these metrics pre-configured. You simply map your data sources to the template fields, and the dashboards populate automatically.

Designing for Non-Technical Users

Your ESG dashboard will be viewed by executives, regulators, investors, and community leaders—not all of whom are data-savvy. Design principles:

• Use traffic-light colours: Green (on target), amber (warning), red (off track). Avoid grey or blue, which don’t signal urgency.
• Show trends, not just snapshots: A single number is meaningless. Plot emissions over the last 12 months with a trend line and target overlay.
• Provide context: Always show year-over-year comparison and variance to target. “Emissions up 5% vs. last year” tells a story; “1,245 tonnes CO2-e” doesn’t.
• Enable drill-down: Start with summary charts, but let users click through to facility-level or source-level detail.
• Explain methodology: Include a data dictionary showing how each metric is calculated, what data sources feed it, and any assumptions or limitations.

D23.io includes annotation tools that let you add explanatory text directly to dashboards. When emissions spike, you can note “unplanned power outage on 15 March—site ran on diesel generators for 48 hours.” This context is invaluable during audits and investor calls.

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Tailings and Environmental Compliance Tracking

Tailings management is the most material environmental risk for mining companies. A tailings storage facility (TSF) failure can destroy ecosystems, contaminate water supplies, and trigger catastrophic liability. Regulators, investors, and communities demand real-time visibility into TSF safety.

Why Tailings Monitoring Is Critical

The Fiscal Policy Instruments and Green Development report from the Asian Development Bank emphasises that environmental compliance—particularly around mining waste—is now a prerequisite for project financing and operational licences. A single tailings incident can halt operations, trigger multi-billion-dollar remediation costs, and destroy shareholder value.

Traditional tailings monitoring relies on manual inspections, laboratory analysis, and static reports. A geotechnical engineer visits the TSF quarterly, takes samples, and writes a report. By the time the report is finalised, conditions may have changed. Regulators and investors have no visibility into what’s happening between inspections.

D23.io’s tailings module automates this by integrating real-time sensor data:

• Piezometers: Measure water pressure within the TSF embankment. Rising pressure signals increased seepage risk.
• Inclinometers: Track embankment movement and slope stability.
• Water quality sensors: Monitor pH, conductivity, and contaminant concentrations in seepage and discharge.
• Rainfall and evaporation: Track water balance to predict TSF capacity and manage discharge.
• Drone surveys: Periodic photogrammetry to measure embankment geometry and vegetation.

These sensors feed data continuously to D23.io’s managed stack. Dashboards show:

• TSF status: Current water level, storage capacity utilisation, embankment stability rating
• Seepage trends: Historical seepage rates, current flow, and predictive alerts
• Water quality: Contaminant concentrations against regulatory limits, discharge compliance
• Maintenance schedule: Upcoming inspections, rehabilitation work, and closure planning

If piezometer readings spike suddenly, the dashboard flags it immediately. Your operations team gets a notification, investigates, and takes corrective action—before a regulator finds out. This proactive approach demonstrates due diligence and reduces audit risk.

Integrating Tailings Data with ESG Reporting

Tailings data feeds into your broader ESG narrative. Your ESG report should include:

• Tailings inventory: Number and classification of TSFs (active, inactive, closed)
• Safety rating: Percentage of TSFs meeting or exceeding ICMM safety standards
• Rehabilitation progress: Percentage of closed TSFs successfully rehabilitated and returned to productive use
• Downstream risk: Number of communities potentially affected by TSFs and mitigation measures in place
• Closure funding: Provision set aside for future closure and rehabilitation

D23.io’s dashboard integrates tailings metrics into your executive ESG summary, so board members and investors see tailings safety as a core ESG pillar, not a technical footnote. This alignment is increasingly important as ESG frameworks like SASB Standards for extractive industries weight tailings management heavily.

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Integrating Multiple Data Sources

A resources company’s data lives in silos: fleet telematics in one system, utility bills in another, lab results in a third, contractor invoices in a fourth. ESG reporting requires pulling all of this together.

Common Data Sources for Resources ESG

Operational Systems:

• SCADA (Supervisory Control and Data Acquisition): Real-time equipment data, power consumption, process metrics
• Fleet management: Fuel consumption, vehicle hours, maintenance logs
• Laboratory information management system (LIMS): Assay results, water quality, environmental samples
• Maintenance management (e.g., SAP, Maximo): Equipment downtime, repair records, spare parts usage

Energy and Utilities:

• Utility bills and consumption data (electricity, natural gas, water)
• Renewable energy generation (solar, wind output)
• Smart meter data (real-time consumption by facility or circuit)

Environmental Monitoring:

• Tailings sensor networks (piezometers, inclinometers, water quality)
• Air quality monitoring (dust, emissions)
• Water monitoring (discharge, recycling, quality)
• Biodiversity surveys and habitat mapping

Contractor and Supply Chain:

• Contractor timesheets and equipment logs
• Supplier invoices and delivery records
• Third-party certifications (ISO 14001, responsible sourcing)

Human Resources:

• Payroll and headcount data
• Training and competency records
• Safety incident reports
• Diversity and inclusion metrics

Financial and Governance:

• General ledger (environmental spend, remediation costs)
• Board and committee minutes
• Policy and procedure documentation
• Audit reports and management responses

D23.io’s Data Integration Approach

D23.io uses a “hub-and-spoke” architecture: data flows from source systems into a central data warehouse, where it’s standardised, validated, and made available to Superset dashboards.

The integration process:

1. Audit existing data: Understand what data you have, where it lives, and what gaps exist
2. Design data model: Map source systems to a standardised ESG data schema
3. Build connectors: Create automated pipelines (APIs, database replication, file imports) that pull data daily or in real-time
4. Validate and reconcile: Cross-check data for consistency and accuracy (e.g., total fuel consumption should match invoice totals)
5. Create semantic layer: Define business logic so users can access metrics without writing SQL
6. Build dashboards: Layer visualisations on top of the semantic layer

For example, to calculate scope 1 emissions:

• Pull daily fuel consumption from fleet telematics (litres of diesel per vehicle)
• Reconcile against fuel invoices from your supplier
• Multiply by emissions factor (2.68 kg CO2-e per litre of diesel)
• Aggregate by facility, business unit, and company level
• Compare to prior year and target

This entire calculation runs automatically every night. Your team doesn’t manually enter fuel data into spreadsheets—it flows directly from source to dashboard.

PADISO’s D23.io consulting engagement includes a detailed data integration phase where we audit your existing systems, design the data model, and build the connectors. The $50K fixed-fee engagement delivers a fully functional D23.io instance with data flowing from your key systems, ready for dashboard development.

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Governance and Social Metrics

While environmental metrics (emissions, water, tailings) often dominate ESG discussions, governance and social metrics are equally material to investors and regulators.

Governance Metrics

Governance covers board composition, executive remuneration, risk management, and compliance. Key metrics for resources companies:

Board Composition:

• Board size and independence (% independent directors)
• Gender diversity (% female directors)
• Tenure diversity (mix of long-serving and new directors)
• Industry expertise (% with mining/resources experience)
• Committee structure (audit, remuneration, ESG oversight)

Executive Remuneration:

• CEO pay ratio (CEO salary vs. median employee salary)
• Percentage of executive bonus tied to ESG targets
• Specific ESG KPIs in executive scorecards (e.g., LTIFR, emissions reduction, diversity targets)

Risk Management:

• Risk register completeness (% of material risks identified and monitored)
• Audit findings and remediation status
• Internal control effectiveness rating
• Insurance coverage for key risks (environmental liability, operational interruption)

Compliance:

• Policy and procedure compliance (% of employees completing mandatory training)
• Regulatory breach incidents (zero-tolerance indicator)
• Whistleblower complaints and resolution rate
• Third-party audit results (ISO 14001, ISO 45001, etc.)

D23.io’s governance dashboard integrates data from your board management system, HR system, and audit function. Board members can see real-time compliance metrics and identify governance gaps before they become audit findings.

Social Metrics

Social metrics cover workforce and community impacts. For resources companies:

Workforce:

• Headcount by location, role, and employment type (permanent, contractor)
• Gender representation (overall and by management level)
• Indigenous employment (% of workforce and management)
• Age diversity
• Turnover rate and retention by role

Safety:

• Lost-time injury frequency rate (LTIFR): injuries per million hours worked
• Total recordable incident rate (TRIR): all injuries including near-misses
• Fatalities (zero-tolerance metric)
• Contractor safety incidents
• Safety culture survey results

Training and Development:

• Percentage of workforce with current competency certifications
• Training hours per employee
• Leadership development pipeline
• Apprenticeship and graduate programs

Community:

• Community grievances (number and resolution time)
• Local procurement spend (% of total procurement)
• Community investment spend (education, health, infrastructure)
• Indigenous consultation (% of major projects with free, prior, and informed consent)
• Resettlement and livelihood restoration (for projects affecting communities)

The Gender Equality Index 2023 from the European Institute for Gender Equality benchmarks gender equality across sectors. Resources companies typically lag in gender diversity, but those making progress outperform on talent retention and safety culture. D23.io’s social dashboard helps you track progress and identify underperforming areas.

Linking Social and Governance to Financial Performance

The strongest ESG reports demonstrate that social and governance improvements drive financial results. For example:

• Companies with LTIFR in the bottom quartile have 15% higher productivity and lower absenteeism
• Companies with gender-diverse management teams have higher innovation rates and faster decision-making
• Companies with strong board governance have lower regulatory risk and capital costs

D23.io’s semantic layer lets you build these correlations. You can overlay safety metrics against production efficiency, or diversity metrics against employee retention, to show stakeholders that ESG isn’t just compliance—it’s a value driver.

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Audit Readiness and Regulatory Compliance

ESG reporting is increasingly subject to external audit. Investors, regulators, and third-party assurance providers scrutinise your data, methodology, and controls. A single data error or missing documentation can delay your annual report or trigger a qualified audit opinion.

Building Audit-Ready Systems

Audit readiness requires three things:

1. Data integrity: Source data is accurate, complete, and traceable
2. Methodology documentation: You can explain how every metric is calculated and justify your assumptions
3. Control environment: You have processes to prevent and detect errors

D23.io supports all three. Here’s how:

Data Integrity:

• Every data point in D23.io is tagged with its source system, import date, and any transformations applied
• Reconciliation reports automatically compare source data to dashboard metrics, flagging discrepancies
• Access logs show who viewed, exported, or modified data, and when
• Version control tracks changes to calculation logic over time

When an auditor asks “where did this number come from?”, you can trace it back to the original source system with full documentation.

Methodology Documentation:

• D23.io includes a built-in methodology library where you document how each metric is calculated
• You can reference GRI Standards, TCFD Hub, or your own company policies
• Calculation logic is version-controlled, so you can show how methodology evolved over time
• Assumptions (e.g., emissions factors, conversion rates) are documented and easily updated

Control Environment:

• Role-based access ensures only authorised users can modify data or calculations
• Approval workflows require sign-off on major changes
• Audit trails record all changes with timestamps and user IDs
• Automated validation rules catch common errors (e.g., negative values, outliers)

Compliance with ESG Frameworks

D23.io dashboards can be mapped to multiple ESG frameworks simultaneously:

• GRI Standards: The most widely adopted global ESG reporting framework. GRI 308 (supplier environmental assessment), GRI 401 (employment), GRI 403 (occupational health and safety) are particularly relevant to resources companies.
• SASB Standards: Industry-specific standards for extractive and minerals processing. SASB defines 20+ metrics that are material to investors in mining companies.
• TCFD: Task Force on Climate-related Financial Disclosures. Focuses on climate risk governance, strategy, risk management, and metrics. Increasingly required by stock exchanges and regulators.
• ASX Corporate Governance Council Recommendations: Australian listed companies must disclose against ASX recommendations or explain non-compliance.
• Sector-specific standards: ICMM (International Council on Mining and Metals) guidance on tailings, water, and biodiversity.

D23.io’s dashboard templates include mapping to all major frameworks. When you report emissions, the dashboard automatically shows which GRI, SASB, and TCFD metrics you’re satisfying. This alignment speeds up audit preparation and reduces the risk of missing required disclosures.

Third-Party Assurance

Many resources companies engage external auditors to provide limited or reasonable assurance over ESG metrics. D23.io’s audit-ready design makes this process faster and cheaper:

• Auditors can access D23.io directly to review data and calculations
• All documentation and audit trails are available in one place
• Reconciliation reports and validation logs provide evidence of control effectiveness
• Historical data is preserved, so auditors can track methodology changes over time

This transparency reduces audit costs by 20-30% because auditors spend less time chasing documentation and more time testing key metrics.

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Implementation Timeline and Costs

A full D23.io ESG deployment for a resources company typically follows this timeline and cost structure:

Phase 1: Discovery and Planning (Weeks 1-2)

Activities:

• Audit existing ESG data and reporting processes
• Interview stakeholders (operations, environment, finance, investor relations)
• Define ESG KPIs and reporting requirements
• Map data sources and identify integration gaps

Deliverables:

• ESG metrics roadmap
• Data source assessment
• Implementation plan

Cost: Included in fixed-fee engagement

Phase 2: Data Integration (Weeks 3-4)

Activities:

• Build connectors to operational systems (SCADA, fleet management, LIMS)
• Set up data warehouse and semantic layer
• Implement data validation and reconciliation
• Test data accuracy and completeness

Deliverables:

• Data pipelines flowing to D23.io
• Reconciliation reports
• Data quality documentation

Cost: Included in fixed-fee engagement

PADISO’s D23.io consulting engagement covers this phase in detail, delivering a fully functional data stack ready for dashboard development.

Phase 3: Dashboard Development (Weeks 5-6)

Activities:

• Design executive summary and functional dashboards
• Build tailings, emissions, and compliance dashboards
• Configure role-based access and export templates
• Create methodology documentation

Deliverables:

• Live dashboards
• PDF export templates for reports
• User documentation

Cost: Included in fixed-fee engagement

Phase 4: Training and Handover (Week 6)

Activities:

• Train your team on dashboard usage
• Document data governance and update processes
• Establish SLAs for data quality and support
• Plan ongoing maintenance and updates

Deliverables:

• Training materials and recorded sessions
• Data governance manual
• Support SLA

Cost: Included in fixed-fee engagement

Total Cost and ROI

A typical D23.io deployment costs $50K in fixed-fee consulting, plus $2-3K per month in managed service fees (hosting, support, updates). This compares to:

• Traditional BI implementation: $150-300K upfront, 12-16 weeks, plus $5-8K per month in ongoing support
• In-house ESG team: $200-400K per year for dedicated ESG analyst and data engineer
• Consultant-led reporting: $50-100K per year for external ESG consultants to compile and verify data

ROI typically appears within 6-12 months through:

• Faster reporting: Dashboards reduce ESG report compilation time from 8-12 weeks to 2-3 weeks
• Lower audit costs: Audit-ready data and documentation reduce external audit fees by 20-30%
• Improved capital access: Transparent, verified ESG data improves investor confidence and reduces cost of capital
• Operational efficiency: Real-time emissions and compliance visibility enables faster decision-making and cost control

For a $1B+ resources company, a 2-week reduction in ESG report compilation saves $50-100K in internal labour. Improved audit efficiency saves another $30-50K. Better investor relations and lower cost of capital can be worth millions.

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Next Steps and Getting Started

If you’re a resources company looking to improve ESG reporting, here’s how to get started:

Step 1: Assess Your Current State

Audit your existing ESG reporting process:

• Where does your ESG data currently live? (spreadsheets, databases, reports)
• Who owns ESG reporting? (finance, operations, sustainability team, external consultants)
• What ESG frameworks do you report against? (GRI, SASB, TCFD, ASX, others)
• What are your biggest pain points? (data silos, manual compilation, audit delays, stakeholder requests)
• What’s your timeline for improvement? (next annual report, next investor roadshow, regulatory deadline)

Step 2: Define Your ESG Metrics

Work with stakeholders to agree on your material ESG metrics. Start with:

• Scope 1, 2, and 3 emissions
• Water and tailings management
• Safety (LTIFR, TRIR, fatalities)
• Workforce diversity and retention
• Board composition and executive remuneration
• Regulatory compliance and audit findings

Reference GRI Standards and SASB Standards for extractive industries to ensure you’re covering material topics.

Step 3: Map Your Data Sources

Identify where each metric lives today:

• Fuel consumption: fleet management system or invoices?
• Electricity usage: utility bills or smart meters?
• Water: facility meters or lab samples?
• Safety incidents: EHS system or spreadsheets?
• Workforce data: HR system or manual headcount?

Note any gaps where data isn’t currently tracked. These are opportunities for improvement.

Step 4: Engage PADISO and D23.io

Contact PADISO to discuss your ESG reporting needs. We’ll:

• Review your current state assessment
• Recommend a D23.io configuration tailored to your operations
• Provide a fixed-fee quote for the implementation
• Schedule a discovery workshop with your stakeholders

Our team has deployed D23.io for multiple AU mining and resources companies. We understand the unique challenges of multi-site operations, contractor data, and regulatory compliance. We can have you reporting ESG metrics in 6 weeks.

Step 5: Implement and Iterate

Once D23.io is live, your team will:

• Use dashboards for daily operational decisions (emissions, safety, compliance)
• Generate monthly reports for management and the board
• Prepare annual ESG disclosures with audit-ready data
• Track progress against ESG targets and adjust strategy as needed

D23.io is not a one-time project—it’s an ongoing platform that evolves with your business. As you set new ESG targets, enter new markets, or adopt new reporting frameworks, we update the dashboards to reflect your changing needs.

Key Contacts and Resources

To learn more about PADISO’s ESG reporting services:

• Visit PADISO’s AI agency Sydney page to understand our approach to technology partnerships
• Review PADISO’s AI automation agency services to see how we apply data automation across industries
• Explore PADISO’s AI automation agency Sydney for case studies and client testimonials
• Read about agentic AI and Apache Superset integration to understand how AI can make your ESG dashboards even more accessible to non-technical users

For technical deep dives:

• AI and ML Integration: CTO Guide to Artificial Intelligence explains how data platforms fit into your broader technology strategy
• Agentic AI vs Traditional Automation shows how to automate ESG data collection using intelligent agents

For industry-specific insights, explore how similar transformation principles apply across sectors:

• AI Automation for Energy: Smart Grids and Renewable Energy Optimization covers energy efficiency tracking—directly relevant to scope 2 emissions
• AI Automation for Supply Chain: Demand Forecasting and Inventory Management applies to scope 3 logistics and shipping emissions

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Conclusion

ESG reporting is no longer optional for resources companies. Investors, regulators, and communities demand transparent, audited data on environmental impact, social responsibility, and governance quality. The challenge is consolidating fragmented data across multiple sites and systems into a single source of truth.

D23.io’s managed Apache Superset stack solves this problem. Rather than building dashboards from scratch or relying on external consultants, you get a pre-configured, enterprise-grade platform that automates ESG data collection, consolidation, and reporting. Scope 1, 2, and 3 emissions are calculated automatically. Tailings safety is tracked in real-time. Compliance with GRI, SASB, and TCFD frameworks is built in.

The result is faster reporting, lower audit costs, better stakeholder communication, and improved operational decision-making. A typical D23.io deployment takes 6 weeks and costs $50K—a fraction of traditional BI implementations, with faster time-to-value.

If you’re ready to transform your ESG reporting, contact PADISO today. We’ve deployed D23.io for resources companies across Australia and Asia-Pacific. We understand your data, your regulations, and your stakeholder expectations. Let’s build your ESG reporting platform together.