Should Escalent's healthcare analytics prioritize broader market coverage or more granular data on specific therapeutic areas?

Introduction

The trade-off between broader market coverage and more granular data on specific therapeutic areas is a critical decision for Escalent's healthcare analytics product. This choice will significantly impact our value proposition, user satisfaction, and market positioning. I'll analyze this trade-off by examining product understanding, potential impacts, key metrics, experimentation, and decision-making frameworks.

Step 1

Clarifying Questions (3 minutes)

• Context: I'm thinking our current market position might influence this decision. Could you share our current market share and main competitors in the healthcare analytics space?

Why it matters: Helps determine if we need to differentiate or consolidate our position Expected answer: Mid-tier market share with 2-3 major competitors Impact on approach: Would influence whether we focus on breadth or depth to stand out

• Business Context: Based on our revenue model, I assume broader coverage might increase our total addressable market. How does our pricing structure currently work - is it per therapeutic area or a flat rate?

Why it matters: Affects potential revenue impact of each option Expected answer: Tiered pricing based on depth of data and number of therapeutic areas Impact on approach: Would help quantify the financial trade-offs of each option

• User Impact: Considering our user base, I'm guessing we serve both large pharma companies and smaller biotech firms. What's the current split between these segments, and how do their needs differ?

Why it matters: Different user segments may value breadth vs. depth differently Expected answer: 60% large pharma, 40% smaller firms; large pharma values breadth, smaller firms need depth Impact on approach: Would inform how we balance the needs of different user segments

• Technical Feasibility: I'm assuming expanding breadth or depth would require significant data processing capabilities. How scalable is our current data infrastructure?

Why it matters: Determines the technical feasibility and cost of each option Expected answer: Current infrastructure can handle 30% increase in data volume without major upgrades Impact on approach: Would influence the timeline and resource allocation for implementation

• Resource Allocation: Given the potential scope of this decision, I'm thinking this might require a dedicated team. What resources (budget, headcount) are available for this initiative?

Why it matters: Helps determine the scale and speed of implementation Expected answer: Budget for 5-7 FTEs over 6 months Impact on approach: Would shape the ambition and phasing of the chosen strategy