Compliance Solution
Table of Content
Scenario
Drova is preparing to launch an MVP solution to support the newly released AASB ASRS
2 standard.
I provided consulting services and recommended them a strategic plan to build a compliance solution aligned with AASB ASRS 2 standards.
I) Product Vision and Strategy
I.1. Product Vision
Details
I.1.1 Vision Statement
Empower Australian SMEs to turn AASB ASRS 2 climate reporting into a strategic advantage for resilience and sustainable growth.
I.1.2 Vision Alignment
The product vision aligns with Drova’s focus on resilience and sustainability, providing practical tools that empower businesses to understand and manage climate-related risks and opportunities.
I.1.3 Long-Term Role
The long-term role of Drova’s AASB ASRS 2 compliance solution within the Drova platform:
Function as a comprehensive compliance hub, centralizing regulatory standards.
Provide data-driven insights for informed strategic decision-making.
With scalability and customization, it will grow with user needs and ensuring ecosystem integration with existing systems.
Focus on continuous improvement and adaptation, it will stay ahead of regulatory changes, offering competitive differentiation with innovative compliance solutions.
Aim to create long-lasting value, fully supporting Drova’s vision and mission
I.2. Key Product Goals
To define the key product goals for the next two quarters (Q1 and Q2), I have structured them using the OKR framework.
Details
Q1 - O1 | Launch a Secure, Reliable, and Compliant solution aligned with AASB ASRS 2 Standards |
-KR1 | Deliver 65% of MVP core features for AASB ASRS 2 compliance by the end of Q1, covering essential areas: Governance, Strategy, Risk Management, Metrics & Targets, and Scope 1, 2, and 3 emissions, as outlined in the feature roadmap. |
-KR2 | Develop a compliance readiness checklist and educational resources aligned with AASB ASRS 2 Standards by the start of 2025. |
-KR3 | Conduct early structured feedback sessions and rollout testing with 1 to 2 pilot customers and produce an improvement report by the end of Q1 to prepare for broader rollout. |
Q2 - O1 | Enhance Product Features and Security |
-KR1 | Expand feature set to complete the remaining 35% of MVP core features; other lower priority features and incorporate enhancements from the early improvement report by mid-Q2. |
-KR2 | Conduct structured feedback sessions and phased rollout testing with 3 to 5 pilot customers by mid-Q2 and produce a comprehensive improvement report to address feature refinements, usability, scalability, and stability. |
-KR3 | Pass a security audit and achieve 100% compliance with data privacy standards by the end of Quarter 2. |
Q2 - O2 | Increase Adoption and Customer Satisfaction |
-KR1 | Implement an in-product simplified onboarding flow and customer support & training program (including video tutorials, documentation, and a support portal) by mid-Q2 to assist with onboarding and usage. |
-KR2 | Achieve 80% adoption rate among targeted pilot customers by the end of Q2. |
-KR3 | Reach a 85% customer satisfaction rate as measured by post-implementation surveys, focusing on usability, feature effectiveness, and overall experience. |
II) Prioritization and Feature Roadmap
II.1. Feature Mapping
Details
AASB ASRS 2 Standards - Mandate | Potential Customer Needs & Pain Points | Feature Aspects |
Governance: Disclose roles and responsibilities for climate-related oversight. | - Need: Clear oversight and accountability for climate strategies.
- Pain Points: Lack of structured frameworks leads to unclear roles and insufficient accountability. | Governance and Documentation Framework |
Strategy: Identify climate-related risks and opportunities, including impacts on business model and transition plans. | - Need: Strategic planning to mitigate risks and leverage opportunities.
- Pain Points: Difficulty in assessing climate impacts on long-term business viability and adapting business models accordingly. | Scenario Analysis and Modeling Tools |
Risk Management: Detail processes for identifying, assessing, and managing climate-related risks. | - Need: Continuous monitoring of climate-related risks.
- Pain Points: Lack of real-time data and insights makes it challenging to stay updated on evolving climate risks. | Compliance Dashboard |
Metrics and Targets: Report Scope 1, Scope 2, and Scope 3 emissions. | - Need: Accurate tracking of emissions and reduce the cost and complexity of compliance.
- Pain Points: Complex data collection and categorization processes increase costs and compliance burdens, especially for Scope 3 emissions. | Data Collection, Automated Scope Classification, Analysis and Reporting |
II.2. Feature Prioritization
II.2.1 MVP Core Features & Prioritization
Details
Data Collection: Some companies prefer to upload their data directly - Others share data with Drova through established channels - Certain companies offer limited access to specific climate-related data - In some cases, Drova should collaborate with third-party providers to gather necessary data, especially when direct access is not feasible.
Feature Aspect | Functionalities | Priorities | Rationale (For High Priority Feature Aspect/Functionalities) |
Data Collection, Automated Scope Classification, and Reporting | - Input Data Area (supports various format: Manual/CSV/Excel Templates/PDF/image) and Data gathering (both comprehensive and accuracy data) from the value chain (Data upload; API Integration- Integrate with SAP-ERP-IOT; Data partners)
| - High
| - Customer Impact: foundational requirement, as clients are under regulatory pressure - reduce the manual work - improve data accuracy - meet compliance standards - adds immediate value
- Commercialization Potential: easier to market - speak directly to customer pain points - maximizes the chances of early product adoption
- Market Competitiveness: highly competitive - positioning the product strongly against competitors
- Compliance Timelines: time-sensitive - strict deadlines, the need is urgent - attractive option for customers |
Governance and Documentation Framework | - Building templates aligned with AASB S2 - using ISSB-SASB standards (https://sasb.ifrs.org/standards/download/) | - High
| *I recommend quickly building AASB S2-aligned templates using ISSB-SASB standards instead of building templates from scratch. |
Compliance Dashboard | - Key metrics overview (some KPIs needed to be tracked from different offices/plants/departments) | - Moderate
|
Some more points:
Market competitiveness
- Currently no companies that have started the compliance process for ASRS AASB 2 - advantage of a pioneer (soon MVP basic compliance and good usability).
- Greenfield opportunity for companies like Drova to develop and launch the solution soon.
- Early adopters of this will have a competitive advantage in the market.
Compliance timelines
- Drova’s target customers are SMEs with 10-1,000 employees and $5-100 million USD in revenue, placing them in Group 3. AASB S2 standards apply to this group starting 1 July 2027. Launching the core compliance solution soon will allow time to refine product-market fit, execute the go-to-market strategy, and provide early value to customers as they prepare for compliance.
II.2.2 User Segmentation Strategy
Details
Phase | Focus | Rationale |
1. Early adopters | SMEs in High-Impact Industries (e.g., manufacturing, agriculture, mining). | They face high regulatory exposure and emissions, driving them to seek compliance solutions proactively. They invest resources and set industry benchmarks, providing early validation. |
2. Broader SME Segment | SMEs across High and Moderate-Impact Industries (e.g., retail, distribution). | This segment, influenced by larger industry players, is likely to adopt proven tools to meet standards and expectations, broadening the customer base for sustained growth. |
3. Service-Based and Low-Impact Industries | Service-Based SMEs (e.g., professional services, IT). | These companies have lighter compliance needs but a growing interest in sustainability, offering access to a new audience with minimal emissions tracking requirements. |
II.3. Feature Roadmap
6-month Feature Roadmap (Include milestones and dependencies)
***Note:
- For the best experience, I recommend accessing the link on a laptop or desktop computer and logging into your Miro account to view the full roadmap. Please find the detail feature roadmap in the Miro link here.
III) Customer Research and Validation
Detail - Persona
User persona:
Primary users: Compliance Officer, External Consultant, Financial Controller, Operations Manager, Head of ESG/CSO/ESG manager
Joey (Male) - Compliance Officer:
- Role: Ensures the organization meets regulatory requirements.
- Needs: Tools for compliance tracking, data gathering, and reporting.
- Pain Points: Managing complex regulations and ensuring timely reporting.
Phoebe (Female) - External Consultant:
- Role: Provides expert guidance on compliance implementation.
- Needs: Access to dashboards, data analysis, and progress tracking.
- Pain Points: Collaborating with internal teams and ensuring alignment with standards.
Monica (Female) - Financial Controller:
- Role: Oversees financial disclosures and ensures compliance impacts are reflected in financial reports.
- Needs: Integration of financial data with compliance metrics.
- Pain Points: Aligning sustainability data with financial reporting timelines.
Rachel (Female) - Operations Manager:
- Role: Manages day-to-day operations, ensuring compliance processes are integrated into workflows.
- Needs: Clear visibility into operational impacts of compliance actions.
- Pain Points: Balancing operational efficiency with regulatory requirements.
Chandler (Male) - Head of ESG:
- Role: Leads ESG strategy, ensuring regulatory compliance and sustainable practices.
- Needs: Consolidated ESG data, automated reporting, and risk insights.
- Pain Points: Data fragmentation, evolving compliance demands, high stakeholder expectations.
Buyer: Board of Directors (BOD)
Ross (Male) - CEO
- Role: Makes strategic decisions on compliance investments.
- Needs: High-level insights into compliance risks and progress toward goals.
- Pain Points: Ensuring long-term sustainability without compromising profitability.
Others: Internal/External Auditor
Gunther (Male) - External Auditor
- Role: Reviews compliance processes and validates adherence to standards.
- Needs: Access to comprehensive audit trails and documentation.
- Pain Points: Ensuring accuracy and completeness of compliance reports.
III.1. Research Methods
Details
Methods
(Continuous feedback collection) | Channels
Phase 1: Initial rollout with existing customers.
Phase 2: Broader testing with potential customers. | Note
(Gather feedback on feature usability, initial reactions, real-world applications, key challenges, solution gaps, and alignment with compliance trends and standards). |
Qualitative | 1. User feedback in Product.
2. User interview with existing Australian SME customers.
3. User interview (potential customer) - I will prioritize engaging with primary users first.
4. Industry experts.
5. Sales team (gain deeper insights into the buyer) - Customer Support team | - Embed feedback form or setup “Give feedback” button in the product
- Drova’s user base
- I attend ESG/climate online events (focused on SMEs), use the attendance list to identify potential customers, and reach out to discuss the ESG domain further and invite them to participate in an interview. Ex:
https://www.linkedin.com/events/stayingaheadofsustainabilityrep7173295540644864000
- Drova’s Subject Matter Expert - Professional Networks
- Drova’s internal teams interact with customers frequently, providing them with valuable insights. |
Quantitative | 1. User data analytics in Product (feature adoption rates, frequency of use, time spent on tasks, etc)
2. Surveys and Questionnaires (Open-ended) | - Product event tracking (This may include a CSAT or NPS survey after users complete certain tasks).
- Attend ESG/climate online events (similar to point 3 above).
- Include CSAT or NPS in the surveys |
III.2. Key Hypotheses To Validate
Details:
No. | Hypothesis |
1 | The solution meets core compliance needs for AASB S2. |
2 | The solution is user-friendly and meets customer expectations in terms of ease of use and functionality. |
3 | AI-driven features provide significant value and efficiency improvements for users. |
4 | Customers are willing to pay for Drova’s compliance solution. |
III.3. Using Findings
Details:
To refine the compliance solution based on the findings from validating the hypotheses, I consider the following steps:
Actions:
Either pivot to propose a new solution or continue refining the current one.
If the proposed solution meets customer expectations, consider the following steps:
Address Compliance Gaps
Enhance User Experience
Optimize AI Features
Enhance Retention Strategies through Iterative Testing
Adjust Pricing Strategy
IV) AI Integration for Compliance
Details
No. | Method of using AI | Pros | Risks/Challenges when integrate to the platform | Mitigation Strategy |
1 | Integrate 3rd-Party Open Source AI (like OpenAI, Gemini, etc) | - Quick to implement and access powerful AI models without building from scratch.
- Lower initial development costs. | - Data Privacy and Security Risks
- A switch to a new model by the 3rd-party require adjustments to both the data and the prompting method - long-term risk. | - Need to obtain customer consent to share their data
- Develop AI model that runs locally, customizing for the customer without sharing data with third parties
- Data Encryption - Access Control - Data Anonymization - Compliance Monitoring
- Long-term risks still need to be considered |
2 | - Develop a Large Language Model (LLM) tailored to each customer, trained on the full context of their specific needs.
- 1 LLM model can be utilized to perform a variety of different tasks by prompt engineering. | - Customizable for specific business needs.
- Can handle multiple tasks efficiently once trained.
- Reduces dependency on external providers. | - AI hallucination
- Accuracy risk is very high especially for complicated tasks like evaluating risk vs. impact
- High Resource and Infrastructure Costs | - Use Retrieval-Augmented Generation (RAG)
- Use Advanced RAG - re-ranking
- Use Fine-Tuning
- Human in the loop (Human experts) to validate the accuracy
- Use Majority Voting to mitigate the risks. Ex: using 5 AI models for a single task; if they produce the same result, the accuracy is likely high
- Scale to a larger number of business customers by Infrastructure Optimization, Model Adaptation, etc |
3 | - Label Data for Supervised Learning
- 1 model will be designed to perform a specific task/feature. | - High accuracy (no AI hallucination) for specific tasks once trained properly.
- Easier to interpret and debug results as compared to unsupervised learning models. | - High Resource and Infrastructure Costs (GPU resources)
- Take time & effort to label data.
- Need to build different models to perform different tasks. | - Automate parts of the labeling process using semi-supervised learning or active learning techniques.
- Outsource labeling tasks or use crowdsourcing platforms.
- Optimize resource allocation by leveraging cloud-based infrastructure.| |
Some more notes:
- Processing data in formats like PDF or text is relatively straightforward. However, for formats like images, additional tools, such as Optical Character Recognition (OCR) for text extraction, may be necessary.
- Currently, LLMs rely on synthetic data, making the challenge of mitigating AI hallucination a major question within the AI research community.
- The entire AI scope is proposed through a combination of research and consultation with AI experts.
V) Cross-Functional Collaboration and Communication
Details:
Alignment Strategies
Regular, open and transparent communication
Communicate clear Product Vision/OKRs/New Update (either success or failure)/Any change/Everything
Publish all documentation in an accessible location
Share dashboard for visibility across teams
Integrate customer feedback loop
Agile Practices
With Engineers and Designers: Agile Methodologies - Scrum - Sprint-based
With Go-to-market team: Planning and Strategy Sessions - Regular Sync Meetings - Kanban Board - Product Demos and Training - Retrospectives - Launch Readiness Checklists
VI) Post-Launch Metrics and Iteration Plan
Details:
1. Metrics to Track
Adoption Rate (Number of New customers, Percentage of existing Drova customers adopting the solution, Activation Rate, Adoption Rate by Industry Segment, Time to adoption)
Engagement Rate (Retention Rate, Feature Usage Frequency, Active Users Rate, Session Duration, Task completion rate)
Customer Satisfaction / Referral (Customer Satisfaction Score (CSAT), Net Promoter Score (NPS), Referral Rate)
Revenue/User (Churn Rate, Subscription Conversion Rate, Return on investment (ROI))
2. Feedback and Iteration
Feedback Collection Methods
- Surveys: Use NPS and CSAT surveys.
- Interviews: Conduct 1-1 interviews or focus groups.
- In-Product Feedback Tools: Implement feedback tools within the product for real-time user input during their interaction with the product.
- Customer Support & Sales: Schedule periodic check-ins with CS and Sales team.
*** Combine with Usage Analytics (Feature Usage Data, User Behavior Flow)
Iteration Process
- Analyze Feedback: Use analytics tools to categorize and prioritize feedback.
- Implement Changes - Regular Release Cycles: Develop an action plan to address key issues and enhance features.
- Communicate Updates: Inform customers about changes made in response to their feedback.
VII) Appendices
References
References
AASB S2 Standard
Scope of AI integration
Consultation with experts in the AI industry and other research
The product with a complete set of features
The product with a complete set of features
Feature Aspect | Functionalities | Priorities | Rationale (For High Priority Feature Aspect/Functionalities) |
Data Collection, Automated Scope Classification, and Reporting | - Input Data Area (supports various format: Manual/CSV/Excel Templates/PDF/image) and Data gathering (both comprehensive and accuracy data) from the value chain (Data upload; API Integration- Integrate with SAP-ERP-IOT; Data partners)
- Automated scope identification and classification for Scope 1, 2, 3 emissions
- Pre-configured metrics calculators for Scope 1, 2, 3
- Comprehensive reporting - Auto-filled answers
- Data Assurance and Evidence Tracking (support Assurance Readiness - Evidences, Stakeholders or AI model validate each data point) | - High
- High
- High
- High
- Moderate | - Customer Impact: foundational requirement, as clients are under regulatory pressure - reduce the manual work - improve data accuracy - meet compliance standards - adds immediate value
- Commercialization Potential: easier to market - speak directly to customer pain points - maximizes the chances of early product adoption
- Market Competitiveness: highly competitive - positioning the product strongly against competitors
- Compliance Timelines: time-sensitive - strict deadlines, the need is urgent - attractive option for customers |
Governance and Documentation Framework | - Building templates aligned with AASB S2 - using ISSB-SASB standards (https://sasb.ifrs.org/standards/download/)
- Identify and categorize climate risks & opportunities
- Evaluate risks and analyze impact across the value chain | - High
- High
- High | *I recommend quickly building AASB S2-aligned templates using ISSB-SASB standards instead of building templates from scratch. |
Compliance Dashboard | - Key metrics overview (some KPIs needed to be tracked from different offices/plants/departments: Scope 1, 2, and 3 GHG Emissions/Total Emissions - Energy Consumption - Water Consumption - Waste Generated - Air Quality and Pollution Control - Number of Facilities and Reports - Suppliers Onboarded - Goals Progress)
- Compliance status updates
- Tracking of key data and analytics
- Real-Time Data Analytics
- Automated Alerts and Notifications | - Moderate
- Moderate
- Moderate
- Low
- Low | |
Scenario Analysis and Modeling Tools | - Scenario Library
- Scenario Testing
- Dynamic Scenario Updates | - Moderate
- Moderate
- Low |