How might Lynk refine its due diligence process for vetting experts to ensure even higher quality insights for clients?

Introduction

To refine Lynk's due diligence process for vetting experts and ensure higher quality insights for clients, we need to critically examine our current approach and identify areas for improvement. I'll outline a strategic plan to enhance our expert vetting process, focusing on key stakeholders, pain points, and innovative solutions.

Step 1

Clarifying Questions

• Looking at Lynk's position in the expert network industry, I'm curious about our current market share and growth trajectory. Could you share some insights on where we stand compared to competitors like GLG or AlphaSights?

Why it matters: Determines if we need to focus on rapid expansion or quality refinement Expected answer: Mid-tier player with 15-20% market share, growing steadily Impact on approach: Would balance quality improvements with scalability

• Considering the expert vetting process, I'm wondering about our current success rate in matching experts to client needs. What percentage of expert-client interactions result in positive outcomes, and how do we measure this?

Why it matters: Helps identify the scale of the problem and potential impact of improvements Expected answer: 70-80% success rate, measured by client feedback and repeat engagements Impact on approach: Would focus on improving the 20-30% gap for maximum impact

• Thinking about our client base, I'm interested in understanding the distribution between different industries or sectors. Could you provide a breakdown of our top client segments and their specific needs?

Why it matters: Allows us to tailor the vetting process to specific industry requirements Expected answer: Diverse client base with concentrations in finance, healthcare, and tech Impact on approach: Would consider industry-specific vetting criteria and expertise validation

• Regarding our current due diligence process, I'm curious about the average time it takes to vet an expert from initial identification to approval. How long does this process typically take, and where are the main bottlenecks?

Why it matters: Identifies potential areas for streamlining and automation Expected answer: 2-3 weeks on average, with bottlenecks in background checks and skill verification Impact on approach: Would focus on accelerating these specific areas while maintaining quality