For Soroco's Task Mining solution, should we emphasize automated task discovery features or invest in more customizable manual configuration options for enterprise clients?

Introduction

For Soroco's Task Mining solution, we're facing a critical trade-off between emphasizing automated task discovery features or investing in more customizable manual configuration options for enterprise clients. This decision will significantly impact our product strategy, user experience, and market positioning. I'll analyze this trade-off by examining the product context, stakeholder impacts, metrics, and potential outcomes to provide a strategic recommendation.

Step 1

Clarifying Questions (3 minutes)

• Context: I'm thinking about the current market landscape for task mining solutions. Could you share insights on our main competitors and their focus areas (automated vs. manual)?

Why it matters: Helps position our strategy relative to market trends Expected answer: Mix of approaches, with larger enterprises preferring customization Impact on approach: Would influence our differentiation strategy

• Business Context: Based on our revenue model, I assume enterprise clients are our primary target. How does our pricing structure currently account for automated vs. manual features?

Why it matters: Aligns product strategy with revenue goals Expected answer: Premium pricing for advanced customization options Impact on approach: May suggest a tiered feature approach

• User Impact: Considering enterprise client needs, what's been the feedback on ease of implementation for automated vs. manual configurations?

Why it matters: Addresses potential adoption barriers Expected answer: Mixed feedback, with larger clients valuing customization despite complexity Impact on approach: Could lead to a hybrid solution with guided customization

• Technical: Regarding our current architecture, how scalable is our automated task discovery compared to supporting extensive manual configurations?

Why it matters: Assesses long-term feasibility of each approach Expected answer: Automated discovery more scalable, manual configs require ongoing support Impact on approach: Might suggest focusing on improving automated features' flexibility

• Resource: Given our current team structure, do we have more expertise in machine learning for automation or in creating enterprise configuration tools?

Why it matters: Aligns strategy with our core competencies Expected answer: Stronger ML capabilities, but growing expertise in enterprise tools Impact on approach: Could influence the balance of investment between the two areas