Developing a Mini Product Roadmap for Breathe ESG (ESG Startup)

About:

BreatheESG helps companies enhance their sustainability performance using a data-driven approach.The current product offerings include tools and features that enable businesses to track their sustainability metrics, identify areas for improvement, and generate reports following the frameworks. Following are the different products:

• ● Breathe ESG:
• ➔ Assists companies in adhering to comprehensive reporting frameworks such as GRI, TCFD, SASB and many more to achieve their environmental, social, and governance (ESG) goals.
• ➔ Materiality Assessment: Governance, Sustainability or Societal factors likely to affect the financial or operating performance of the business.
• ➔ Data Management Software: ESG metrics, KPIs for projects. API connections supported.
• ● Breathe Impact: Targeting the CSR industry, essentially helping companies track and improve their CSR initiatives through this platform.
• ➔ Dashboard to track yearly CSR plans and monitor them in real time
• ➔ Measuring & visualising each project’s/program’s progress.
• ➔ Quantifying the progress and measuring them against benchmarks using in-house scoring system and streamlining data management in a secure environment.
• ● Breathe Zero: (Coming Soon)
• ● ESG Advisory Services: Targeting the Sustainability Consulting industry, serving as a pipeline for the adoption of Breathe ESG products that will assist the companies with their sustainability endeavours.
• Feature: ESG Performance Predictive Analysis
• Proposed Predictive Model:
• Leveraging online sources (Libraries, APIs) to ingest historical and real-time news articles, tweets, and other digital publications along with privately disclosed data (Consumption of Natural Resources, Emissions, Wastage, Governance Metrics etc.), the ML+ NLP model will classify the topics & metrics into the three ESG categories and weigh each piece of information according to its importance to the ESG performance & sector of a particular company over a period of time. For small businesses with limited online data sources, they can input their own historical ESG data and details on ESG initiatives like community engagement efforts to obtain predictions about their future ESG performance.
• This feature enhances the Breathe ESG platform by enabling users to make data-driven decisions and improve their sustainability practices. It will also improve the existing features such as materiality assessment and ESG scoring mechanism. Hence, the data that will be used for analysis includes:

Public Sources:

● Online Feeds (News Articles, Tweets, Employee Reviews & Blogs)

● Company’s Official Reports (Sustainability Reports, Annual Reports etc.)

Company Disclosures (Private → Provided by company to Breathe ESG):

● Emissions Data

● Data on Natural Resources Consumed (Water, Energy Consumption & Sources etc.)

● Details on ESG/CSR Initiatives

Model Output:

The model output can be used in several ways:

● Future ESG Performance Prediction and score improvement recommendations.

● Comparative Analysis: The model can analyse data from various companies within the same industry or sector, enabling users to compare their ESG performance against industry benchmarks and mitigate any associated risks.

● It will help gauge the online public sentiment in real-time across ESG factors.

● Identifying all the factors that affect ESG scoring and identify possible Scope 1,2,3 issues.

● BreatheESG can extend this service to assist companies in exploring their viability for participating in carbon markets.

● This tool along with the database acquired can further strengthen BreatheESG’s advisory services.

Use Case & User Story: Use Case: Predictive Sustainability Planning for a Small Manufacturing Business

User:

Rohit — Sustainability Manager at a Small Manufacturing Business

Background: Rohit works for a small manufacturing business that specialises in producing eco-friendly packaging materials. The company has limited online presence and publications but is committed to improving its sustainability practices and reducing its environmental impact.

Goal:

Enhance sustainability practices and make data-driven decisions specific to the manufacturing industry using the ESG Performance Predictive Analysis feature.

User Story:

As Rohit, the sustainability manager at our small manufacturing business, I am eager to use the ESG Performance Predictive Analysis feature in the Breathe ESG platform. With a focus on eco-friendly packaging materials, I believe this feature can provide valuable insights for our business growth.

Using the platform, I provide our historical ESG data, including emissions, resource consumption, waste management practices, and eco-friendly initiatives. The feature analyses our data using machine learning, predicting our future ESG performance and comparative analysis against the manufacturing industry benchmarks.

The platform presents actionable insights tailored to our manufacturing business, highlighting our strengths such as energy efficiency and waste reduction efforts. It also identifies areas for improvement, such as emissions reduction strategies and sustainable sourcing practices.

With these insights, I make data-driven decisions, prioritising initiatives that align with industry-specific ESG goals and drive positive change in our business. The feature empowers us to proactively plan for the future, set achievable sustainability goals, and optimise resource allocation.

We can also learn from bigger businesses with large online presence regarding their progress in the sustainability realm as I can check on their progress from publicly available data ingested in consumer friendly format on BreatheESG website. We can also generate reports aligned with industry-specific frameworks, showcasing our efforts to stakeholders.

Thanks to the Breathe ESG platform’s ESG Performance Predictive Analysis feature, our small manufacturing business can enhance sustainability practices, reduce our environmental impact, and drive positive change. By leveraging data-driven insights tailored to the manufacturing industry, we contribute to a greener future while demonstrating our commitment to sustainable manufacturing practices.

Prioritisation:
The “ESG Performance Predictive Analysis” feature should be prioritised as a highest priority addition to the Breathe ESG platform:

The predictive insights and comparative analysis feature directly supports businesses in achieving their ESG goals. It enhances the platform’s value proposition and strengthens its position as a comprehensive solution for sustainability management.
This feature also provides a unique value proposition and competitive advantage compared to other existing ESG platforms. While current offerings primarily focus on tracking and reporting sustainability metrics, this feature goes beyond by leveraging machine learning techniques to offer predictive analysis and industry benchmarking. By prioritising this feature, Breathe ESG can differentiate itself in the market and attract businesses looking for advanced predictive capabilities.

Market demand for A.I. based tools are becoming increasingly important in the ESG space as companies seek to proactively manage their sustainability practices and demonstrate long-term value. By prioritising the ESG Performance Predictive Analysis feature, Breathe ESG can cater to this growing market demand and position itself as a leader in providing data-driven insights for sustainable decision-making.

Impact potential: The ESG Performance Predictive Analysis feature has the potential to have a significant impact on businesses’ sustainability practices. By providing actionable insights and identifying areas for improvement, it enables companies to make targeted interventions and drive positive change. This feature empowers businesses to optimise their resource allocation, set achievable sustainability goals, and contribute to a greener future.

Scalability and technical feasibility: While considering technical bandwidth and implementation constraints, the ESG Performance Predictive Analysis feature leverages existing data sources and utilises machine learning techniques for efficient data processing. This ensures scalability and minimises technical challenges in implementing the feature or making changes in future. Its feasibility makes it an attractive option for prioritisation within the platform.

Considering the strategic alignment, competitive advantage, market demand, impact potential, scalability, technical feasibility, user feedback, and use case relevance, prioritising this feature over other features or improvements at Breathe ESG would enable the platform to provide advanced predictive capabilities, differentiate itself in the market, meet growing market demand, and have a significant positive impact on sustainability practices of businesses

Product Roadmap for the Next Quarter:

● Research, Planning, and Design:

○ Conduct an initial analysis of existing ESG predictive analysis models and related A.I. techniques.

○ Identify relevant online sources (libraries, APIs) for data ingestion.

○ Define the scope and requirements for the predictive analysis model.

○ Develop the data ingestion pipeline to collect data from public and private sources.

○ Design the machine learning and NLP model architecture for classifying ESG topics and weighing their importance to predict ESG performance on sector specific scale for a company following the ESG frameworks.

○ Create wireframes and design prototypes for the user interface of the predictive analysis feature.

○ Differential pricing to be explored for various customer types such as NGOs, Small & Large Businesses.

● Development and Testing:

○ Implement the data ingestion pipeline to collect data from online sources and company disclosures.

○ Develop the machine learning model for topic classification and training weights according to their relevance to ESG performance of the company within its sector and an overall outlook.

○ Integrate the predictive analysis model with the existing Breathe ESG platform.

○ Implement the user interface for inputting historical ESG data and viewing predictive insights.

○ Conduct thorough testing of the predictive analysis feature, including data validation, model accuracy, and performance.

● Deployment and Release:

○ Prepare the infrastructure for deployment, including necessary server resources and data storage.

○ Perform final quality assurance checks and bug fixes.

○ Coordinate with the development and operations teams for a smooth deployment process.

○ Deploy the ESG Performance Predictive Analysis feature to the Breathe ESG platform.

● User Onboarding and Support:

○ Communicate the new feature to existing and potential customers through marketing and communication channels.

○ Provide user documentation and resources to guide users in utilising the ESG Performance Predictive Analysis feature.

○ Conduct training sessions or webinars for users to familiarise them with the feature’s capabilities.

○ Establish a support system to address user queries and provide assistance during the onboarding process.

● Continuous Improvement:

○ Collect user feedback and monitor feature usage to identify areas for improvement.

○ Gather insights and analytics on the effectiveness and impact of the predictive analysis feature.

○ Iterate and enhance the feature based on user feedback and identified opportunities for optimization.

○ Continuously update the predictive analysis model with new data sources and techniques to improve accuracy and relevance.

Risk Assessment:

Potential risks or challenges during the implementation of the “ESG Performance Predictive Analysis” feature include:

● Data Availability and Quality: Obtaining reliable and comprehensive data from online sources and company disclosures may pose challenges. Some public sources may have limited data coverage or unreliable information, while private disclosures may vary in quality, completeness or can be biassed. Mitigation:

● Implement data validation processes to identify and address inconsistencies or inaccuracies in the data.

● Choose verified information sources to pull raw data.

● Collaborate with data providers to ensure data accuracy and establish data quality standards.

● Offer flexibility for users to input their own historical ESG data when online sources are limited (So our scrapers cannot be relied upon in that case)

● Model Accuracy and Performance: Developing an accurate and performant machine learning and NLP model can be challenging. Model training may require significant computational resources and expertise. There is a risk of model biases and limitations that may affect the accuracy of predictions. Mitigation:

● Conduct thorough model training and evaluation, using diverse datasets to minimise biases.

● Regularly monitor and fine-tune the model’s performance based on user feedback, ongoing data analysis and other ML variables such as improving feedback loops and learning rate.

● Technical Integration: Integrating the new feature within the existing Breathe ESG platform may pose technical challenges. Compatibility issues, system requirements, and potential disruptions to the platform’s stability can arise during integration. Mitigation:

● Conduct thorough testing and compatibility checks before integrating the new feature.

● Collaborate closely with the development and operations teams to address any technical issues promptly.

● User Adoption and Usability: Ensuring user adoption and a positive user experience with the new feature is crucial for its success. Users may require training and support to effectively use the predictive analysis capabilities. Resistance to change or lack of understanding can hinder adoption. Mitigation:

● Provide comprehensive user documentation, tutorials, and resources to guide users through the feature’s functionality.

● Inform users about the new feature through various channels (Email, WhatApp, In-App Banner)

● Conduct training sessions or webinars to familiarise users with the predictive analysis feature and its benefits.

● Offer responsive customer support channels to address user inquiries and provide assistance.

● Privacy and Security: Handling sensitive data from company disclosures requires robust privacy and security measures. There is a risk of data breaches or unauthorised access to confidential information. Mitigation:

● Implement strict data protection protocols and comply with relevant privacy regulations.

● Employ encryption and secure storage mechanisms to protect sensitive data.

● Conduct regular security audits and penetration testing to identify and address vulnerabilities.

● Scalability and Performance: As the user base and data volume increase, ensuring the scalability and performance of the predictive analysis feature becomes crucial. Insufficient infrastructure or slow response times can hinder user experience. Mitigation:

● Monitor system performance and optimise infrastructure to accommodate growing user demands.

● Utilise cloud-based solutions or scalable resources to ensure scalability in performance.

Aim: User Experience Analysis and Improvement Recommendations

Solution:

If users are having difficulty navigating the Breathe ESG platform, there could be several potential reasons for this issue:

● Complex User Interface: The platform may have a cluttered or unintuitive user interface, making it difficult for users to find the desired features or navigate through the various sections. It may also hinder the discovery of new features launched.

● Lack of Information Hierarchy: The platform might not provide clear information hierarchy, leading to confusion about which sections or features are more important or relevant to the users.

● Inadequate Labelling and Terminology: Unclear or ambiguous labels for menu items, buttons, or sections can confuse users and make it challenging for them to understand the platform’s navigation structure.

● Limited Search or Filtering Capabilities: If the platform lacks robust search or filtering functionalities, users may struggle to find specific information or reports they need.

To pinpoint the problem, we can analyse different sources of data, including:

● User Feedback: Gather feedback from users through surveys, interviews, or user testing sessions. Ask specific questions about their navigation experiences, pain points, and suggestions for improvement.

● User Analytics: Utilise user analytics tools (e.g. Mixpanel) to track user behaviour, such as heatmaps, click-through rates, or session recordings. Analyse the data to identify patterns of navigation difficulties or drop-off points.

● Support Tickets and Inquiries: Review customer support tickets or inquiries related to navigation issues. Look for recurring themes or specific examples where users encountered difficulties.

● User Testing: Conduct user testing sessions with representative users to observe their interactions with the platform. Note where they face challenges, get stuck, or express confusion.

Solutions and Validation:

Potential solutions to address the navigation issues:

● Simplify and Streamline Navigation: Review the platform’s information architecture and simplify the navigation structure. Reduce clutter by removing unnecessary elements and prioritise important features.

● Quick Actions Bar and Banners: Important features & metrics can be highlighted at the top of the dashboard for easier visibility on different platform capabilities. Banners can be shown to provide information about current offerings & important updates.

● Improve Information Hierarchy: Clearly define the hierarchy of information and features based on user needs. Ensure that sections and features are logically organised, with important ones prominently displayed.

● Enhance Labelling and Terminology: Clear and concise labels that align with users’ mental models. Conduct user testing or surveys to validate the clarity and understanding of the labels.

● Extra Enhancements: These enhancements require more tech capability but will improve the overall user Net Promoter Score (NPS) by creating a seamless experience over the platform.

• Chatbot that can direct users to the features that they want and clear any common doubts they may have or else, create a support ticket directly.

Example Below:

• Keeping information hierarchy and streamlined navigation in mind, we can create a common dashboard which has ‘Snippets’ of information from every feature customised to user needs. For example: A company can have important ESG metrics, CSR Initiatives Progress and Predictive Analysis Graph in the Overall Dashboard screen. They can then check their details in the individual feature screens. On the right you can check how Mixpanel has multiple boards ‘Snippets’ on the dashboard.

To validate these solutions before implementation, you can employ the following methods:

● Prototype Testing: Create interactive prototypes or mockups that reflect the proposed changes to the navigation experience. Conduct usability testing sessions with representative users and gather their feedback on the improved navigation.

● A/B Testing: Implement variations of the navigation changes on a subset of users and compare their experiences and satisfaction with the existing navigation. Collect quantitative and qualitative data to determine the effectiveness of the proposed changes.

● Expert Review: Engage usability experts or UX professionals to evaluate the proposed navigation changes.

Wireframe:

Risk Assessment:

Potential risks or challenges associated with the proposed changes to the navigation experience include:

● Overwhelming Users: Simplifying the navigation structure may unintentionally remove important features or make it difficult for some users to find specific functionalities. Mitigation: Conduct user testing and feedback sessions to ensure the proposed changes align with users’ needs and expectations.

● Learning Curve: Existing users who are accustomed to the current navigation may experience a learning curve when the changes are implemented. Mitigation: Provide clear communication about the upcoming changes, offering tutorials, FAQs, Poachmarks and providing customer support to assist users during the transition period.

● Technical Limitations: Implementing advanced functionalities such as customisable dashboard and banners may require significant development resources or integration with external systems. Mitigation: Conduct a feasibility analysis before committing to the changes, ensuring that technical requirements can be met within the desired timeframe.

● Compatibility Issues: The proposed changes may introduce compatibility issues with certain browsers or devices. Mitigation: Conduct thorough cross-browser and cross-device testing to ensure the changes are compatible and provide a seamless experience across different platforms.