For Diligent's ESG reporting solution, should we emphasize comprehensive data collection capabilities or prioritize user-friendly visualization and reporting tools?

Introduction

For Diligent's ESG reporting solution, we're facing a critical trade-off between comprehensive data collection capabilities and user-friendly visualization and reporting tools. This decision will significantly impact our product's value proposition and market positioning. I'll analyze this trade-off by examining our product strategy, user needs, technical considerations, and business implications.

Step 1

Clarifying Questions (3 minutes)

• Context: I'm thinking our ESG reporting solution is targeting mid to large enterprises. Could you confirm our primary market segment and if there are any specific industries we're focusing on?

Why it matters: Helps tailor our solution to specific user needs and regulatory requirements. Expected answer: Primarily Fortune 1000 companies across various industries. Impact on approach: Would influence data collection depth and reporting customization.

• Business Context: Based on market trends, I assume ESG reporting is a high-growth area for us. How does this product fit into our overall revenue strategy and growth targets?

Why it matters: Aligns product decisions with company-wide objectives. Expected answer: It's a key growth driver, expected to contribute significantly to revenue in the next 2-3 years. Impact on approach: Would justify higher investment in either comprehensive data or user experience, depending on what drives adoption.

• User Impact: I'm thinking our users range from ESG specialists to C-suite executives. Can you confirm our primary user personas and their key pain points?

Why it matters: Ensures we're solving the right problems for the right users. Expected answer: Primary users are ESG managers, with secondary users including CFOs and investor relations teams. Impact on approach: Would help prioritize between data depth and ease of use based on user needs.

• Technical: Considering the complexity of ESG data, I'm curious about our current data processing capabilities. How scalable is our backend for handling increased data volume and complexity?

Why it matters: Determines feasibility of expanding data collection without compromising performance. Expected answer: Current system can handle moderate increases, but significant expansion would require infrastructure upgrades. Impact on approach: Would influence the balance between expanding data collection and optimizing existing capabilities.

• Resource: Given the potential scope of this project, I'm wondering about our team's capacity. Do we have dedicated resources for both data engineering and UX/UI development?

Why it matters: Helps assess our ability to execute on either option effectively. Expected answer: We have a strong data team, but UX/UI resources are more limited. Impact on approach: Might lean towards data collection if that's where our current strength lies, or justify additional UX/UI investment.