Should MX prioritize adding more financial institutions to its data aggregation platform or focus on improving data accuracy for existing connections?

Introduction

The trade-off we're examining today is whether MX should prioritize adding more financial institutions to its data aggregation platform or focus on improving data accuracy for existing connections. This decision is crucial for MX's growth strategy and user satisfaction. I'll analyze this trade-off by considering the business context, user impact, technical feasibility, and resource allocation.

Step 1

Clarifying Questions (3 minutes)

• Business Context: I'm thinking this decision might be driven by competitive pressures. Could you share how our market position compares to other data aggregators in terms of institution coverage and data accuracy?

Why it matters: Helps prioritize which aspect gives us a competitive edge Expected answer: We're lagging in institution coverage but leading in accuracy Impact on approach: Would lean towards expanding coverage if true

• User Impact: Based on user feedback, I suspect data accuracy issues might be causing more frustration than limited institution coverage. Can you provide insights on our most common user complaints or support tickets?

Why it matters: Identifies which problem is more pressing for users Expected answer: Higher volume of accuracy-related issues Impact on approach: Would prioritize improving accuracy if confirmed

• Technical Feasibility: I'm curious about the technical complexity of these two options. How does the effort required to add new institutions compare to improving data accuracy for existing ones?

Why it matters: Helps assess resource allocation and timeline Expected answer: Adding institutions is straightforward, improving accuracy is complex Impact on approach: Might favor adding institutions if accuracy improvements are significantly more challenging

• Resource Allocation: Considering our current team structure, I'm wondering if we have specialized teams for institution onboarding and data quality. How are our engineering resources currently allocated between these areas?

Why it matters: Determines if we need to shift resources or hire new talent Expected answer: More resources in institution onboarding than data quality Impact on approach: Might influence timeline and feasibility of each option

• Timeline and Urgency: I'm thinking about our product roadmap and wondering if there are any upcoming features or partnerships that depend on either expanded coverage or improved accuracy. Are there any critical deadlines or dependencies we should be aware of?

Why it matters: Helps prioritize based on broader strategic initiatives Expected answer: Major partnership requiring expanded coverage in Q4 Impact on approach: Would lean towards adding institutions if true