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What Went Wrong...

Examining the missteps of various software products across industries reveals common pitfalls that can derail even the most promising innovations. From inadequate market research and poor user experience design to insufficient testing and failure to adapt to technological advancements, these challenges underscore the importance of thorough planning and execution. The following section outlines specific cases, offering insights into how these factors contributed to their downfall and the lessons that can be gleaned to inform future endeavors.

Available Lessons:

200

Namely Core HR Platform

HRTech

Namely

The platform struggled with technical bugs, poor performance, and inadequate customer support, leading to low client retention.

WHAT WENT WRONG

  • Backend system instability

  • Lack of responsive support for troubleshooting

SIGNALS MISSED

  • High churn rates among early adopters

  • Rising volume of unresolved support tickets

HOW COULD THEY HAVE AVOIDED THIS

  • Improving system reliability through better architecture

  • Expanding customer success and support capabilities

TEAMS INVOLVED

Product, Engineering, Customer Success, Operations

AI Video Interviewing Tool

HRTech

HireVue

Faced backlash due to algorithmic bias, leading to inaccurate candidate evaluations and ethical concerns.

WHAT WENT WRONG

  • Insufficient AI training to eliminate bias

  • Lack of transparency in how candidates were assessed

SIGNALS MISSED

  • Early reports of algorithmic bias flagged in pilot tests

  • Candidate dissatisfaction with evaluation results

HOW COULD THEY HAVE AVOIDED THIS

  • Enhancing AI models with diverse training data

  • Introducing transparency and human oversight in assessments

TEAMS INVOLVED

Product, Engineering, AI, Compliance, Legal

Gusto Benefits Platform (Early Rollout)

HRTech

Gusto

The benefits management platform struggled with integration bugs and compliance challenges in multi-state markets.

WHAT WENT WRONG

  • Weak backend integration with benefits providers

  • Regulatory oversights for state-specific compliance

SIGNALS MISSED

  • High user complaints about enrollment errors

  • Delayed resolution of multi-state compliance issues

HOW COULD THEY HAVE AVOIDED THIS

  • Ensuring integration testing with third-party providers

  • Addressing compliance nuances for regional markets

TEAMS INVOLVED

Product, Engineering, Compliance, Customer Success

SAP SuccessFactors Compensation Module

HRTech

SAP

The software failed due to bugs in compensation calculations, resulting in payroll errors and frustrated HR teams.

WHAT WENT WRONG

  • Flawed logic in payroll and compensation formulas

  • Inadequate testing of edge cases for large enterprises

SIGNALS MISSED

  • Reports of payroll discrepancies during pilot phases

  • Customer complaints highlighting inaccuracies post-launch

HOW COULD THEY HAVE AVOIDED THIS

  • Expanding QA testing for complex compensation scenarios

  • Implementing robust safeguards for payroll calculations

TEAMS INVOLVED

Product, Engineering, Customer Success, QA

Glassdoor Company Analytics

HRTech

Glassdoor

The analytics tool for employers failed to deliver actionable insights due to inconsistent data and limited reporting capabilities.

WHAT WENT WRONG

  • Poor data accuracy in employer dashboards

  • Weak reporting features that lacked depth

SIGNALS MISSED

  • Early complaints about irrelevant or outdated data

  • Low renewal rates from enterprise customers

HOW COULD THEY HAVE AVOIDED THIS

  • Improving data accuracy through rigorous validation processes

  • Enhancing reporting tools with actionable insights

TEAMS INVOLVED

Product, Data, Engineering, Sales

LinkedIn Talent Insights (Initial Launch)

HRTech

LinkedIn

A tool for talent analytics faced criticism for inaccurate data reporting and lack of actionable insights for recruiters.

WHAT WENT WRONG

  • Weak backend algorithms generating incomplete reports

  • Misalignment with HR recruiter workflows

SIGNALS MISSED

  • User complaints about inaccurate or irrelevant data

  • Low adoption rates among recruiters

HOW COULD THEY HAVE AVOIDED THIS

  • Validating data accuracy through rigorous testing

  • Collaborating with recruiters to refine product workflows

TEAMS INVOLVED

Product, Data, Engineering, Design, Sales

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