Should Reltio prioritize expanding its data sources for the Master Data Management platform or focus on improving the existing data quality and matching algorithms?

Introduction

The trade-off we're examining today is whether Reltio should prioritize expanding its data sources for the Master Data Management (MDM) platform or focus on improving existing data quality and matching algorithms. This decision is crucial for Reltio's product strategy and will significantly impact our customers' ability to manage their master data effectively. I'll analyze this trade-off by considering various factors, including business context, user impact, technical feasibility, and resource allocation.

Step 1

Clarifying Questions (3 minutes)

• Context: I'm thinking about Reltio's current market position. Could you share how our market share compares to our main competitors in the MDM space?

Why it matters: Helps determine if we need to focus on differentiation or catch-up Expected answer: We're in the top 3, but not the clear leader Impact on approach: If we're not the leader, might lean towards expansion to differentiate

• Business Context: Based on our revenue model, I assume expanding data sources could potentially increase our pricing tiers. Is this aligned with our current pricing strategy?

Why it matters: Influences the financial impact of the decision Expected answer: Yes, more data sources could justify higher pricing tiers Impact on approach: Would strengthen the case for expansion if aligned with pricing strategy

• User Impact: I'm curious about our user segments. What percentage of our customers are actively requesting more data sources versus improved data quality?

Why it matters: Helps prioritize based on customer demand Expected answer: Mixed feedback, with a slight lean towards data quality improvements Impact on approach: Would need to balance both aspects, potentially favoring quality

• Technical: Regarding our current architecture, how modular is our system for adding new data sources compared to upgrading our matching algorithms?

Why it matters: Affects the feasibility and timeline of each option Expected answer: Adding sources is easier, but algorithm improvements have more long-term impact Impact on approach: Might suggest a phased approach, starting with quick wins in data expansion

• Resource: Can you give me an idea of our current team's expertise? Do we have more data integration specialists or data science/algorithm experts?

Why it matters: Influences our ability to execute on either option effectively Expected answer: Balanced team, but slightly more integration expertise Impact on approach: Might lean towards expansion initially while building up algorithm expertise