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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

HealthSuite Digital Platform

HealthTech

Philips

A cloud-based healthcare data platform faced challenges with integration, adoption, and proving value.

WHAT WENT WRONG

  • Poor integration with existing healthcare systems

  • Lack of clarity in product value proposition

SIGNALS MISSED

  • Resistance from hospitals due to complex onboarding

  • Limited traction during early deployments

  • User complaints about functionality gaps

HOW COULD THEY HAVE AVOIDED THIS

  • Early user research for better integrations

  • Step-by-step onboarding support for hospital IT teams

  • Pilot testing with feedback-driven iterations

TEAMS INVOLVED

Product, Engineering, Sales, Marketing

HealthVault

HealthTech

Microsoft

A platform for managing personal health records struggled to engage users and healthcare providers, leading to its shutdown.

WHAT WENT WRONG

  • Lack of product differentiation

  • Poor user experience design

SIGNALS MISSED

  • Low user adoption rates

  • Lack of provider buy-in during beta phases

  • User feedback citing confusion and lack of value

HOW COULD THEY HAVE AVOIDED THIS

  • Clearer positioning of product value

  • Streamlined user experience with guided workflows

  • Strategic partnerships with healthcare institutions

TEAMS INVOLVED

Product, Marketing, Design, Operations

HealthCare.gov Launch (2013)

HealthTech

HealthCare.gov (U.S. Government)

The federal health insurance exchange website crashed upon launch due to technical failures and lack of scalability.

WHAT WENT WRONG

  • Poor project management and coordination

  • Insufficient load testing for expected demand

SIGNALS MISSED

  • Delayed project milestones and incomplete testing

  • Multiple vendor miscommunications

  • Red flags during pre-launch user acceptance testing

HOW COULD THEY HAVE AVOIDED THIS

  • Stronger project oversight and phased rollouts

  • Robust load and performance testing under simulated demand

  • Streamlined vendor collaboration

TEAMS INVOLVED

Engineering, Product, Operations, Design, Customer Success

UP Fitness Tracker

HealthTech

Jawbone

Despite initial success, product quality issues, app reliability, and increasing competition led to failure.

WHAT WENT WRONG

  • Hardware reliability and syncing issues

  • Weak customer support for device failures

SIGNALS MISSED

  • High return rates and negative user feedback

  • Growing competition from Fitbit and Apple

  • Consistent technical complaints post-launch

HOW COULD THEY HAVE AVOIDED THIS

  • Focus on product quality and reliability testing

  • Improved support processes for failed devices

  • Competitive analysis and unique product positioning

TEAMS INVOLVED

Product, Engineering, Customer Success, Marketing

AI Chatbot Diagnosis Tool

HealthTech

Babylon Health

The tool, which aimed to replace initial GP consultations with AI, faced criticism for delivering inaccurate or unsafe diagnoses.

WHAT WENT WRONG

  • Inadequate training and testing of the AI

  • Prioritization of speed-to-market over accuracy

SIGNALS MISSED

  • Early reports of incorrect diagnoses from users

  • Overconfidence in AI replacing medical professionals

  • Regulatory concerns flagged but ignored

HOW COULD THEY HAVE AVOIDED THIS

  • Gradual rollout with real-world testing

  • Collaborating closely with healthcare professionals

  • Transparency about AI limitations

TEAMS INVOLVED

Product, Engineering, Design, CEO

Watson for Oncology

HealthTech

IBM

AI product aimed at providing cancer treatment recommendations struggled due to inaccurate results and misaligned expectations.

WHAT WENT WRONG

  • Poor training data and limited real-world testing

  • Overpromised AI capabilities to hospitals and doctors

SIGNALS MISSED

  • Clinical dissatisfaction during pilot implementations

  • Early warning from doctors about inaccuracies

  • AI performance misaligned with complex real-life cases

HOW COULD THEY HAVE AVOIDED THIS

  • Rigorous testing and real-world clinical trials

  • More realistic marketing of product limitations

  • Engaging frontline doctors to co-develop solutions

TEAMS INVOLVED

Product, Engineering, Sales, Marketing, CEO

Fractional Executives

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