For Inovalon's INDICES clinical data registry, should we prioritize expanding the breadth of data collected or improving the depth and granularity of existing data points?

Introduction

The trade-off we're examining for Inovalon's INDICES clinical data registry is whether to prioritize expanding the breadth of data collected or improving the depth and granularity of existing data points. This decision is crucial for the registry's effectiveness and value proposition. I'll analyze this trade-off by considering the product context, stakeholder impacts, metrics, and potential outcomes.

Step 1

Clarifying Questions (3 minutes)

• Based on the current market trends, I'm thinking data breadth might be more valuable for certain use cases. Could you share insights on how our customers typically use INDICES data?

Why it matters: Helps align our strategy with customer needs Expected answer: Mix of use cases, some requiring broad data, others needing depth Impact on approach: Would inform which direction provides more immediate value

• Considering our revenue model, I'm assuming we charge based on data access. Is there a difference in pricing for broader vs. deeper data sets?

Why it matters: Directly impacts revenue potential of each option Expected answer: Premium pricing for more granular data Impact on approach: Might lean towards depth if it significantly increases revenue per customer

• Looking at user behavior, I'm curious about query patterns. Do users typically access a wide range of data points or drill deep into specific areas?

Why it matters: Indicates which approach aligns better with user needs Expected answer: Varies by user type, but trend towards deeper analysis Impact on approach: Could prioritize depth for key user segments

• From a technical standpoint, I'm wondering about our data integration capabilities. How easily can we onboard new data sources vs. enriching existing ones?

Why it matters: Affects feasibility and timeline of each option Expected answer: Established processes for both, but new integrations take longer Impact on approach: Might favor depth if it's significantly faster to implement

• Regarding our team capacity, are we better equipped to handle data expansion or enrichment projects?

Why it matters: Influences which option we can execute more effectively Expected answer: Team has more experience with data enrichment Impact on approach: Could lean towards depth to leverage existing expertise