In 2011, HP killed a $1.2 billion innovation in just 49 days. I was the Chief Technology Officer who recommended buying it. What happened next reveals why smart people consistently destroy breakthrough technology—and the systematic framework you need to avoid making the same mistake.

HP had just spent $1.2 billion acquiring Palm to get WebOS—one of the most advanced mobile operating systems ever created. It had true multitasking when iOS and Android couldn't handle it, an elegant interface design, and breakthrough platform technology. I led the technical due diligence and recommended the acquisition because I believed we were buying the future of mobile computing.

Here's a question that should keep every innovation leader awake at night: How do you destroy breakthrough technology worth over a billion dollars in less than two months?

The answer isn't what you think. It's not about bad technology, poor market timing, or insufficient resources. It's about systematic thinking errors that intelligent people make when evaluating innovation under pressure. And these same patterns are happening in companies everywhere, right now.

I'm going to show you exactly how this happens, why your company is vulnerable to the same mistakes, and give you a proven framework to prevent these disasters before they destroy your next breakthrough innovation.

On my Studio Notes on Substack, I share the personal story of watching this unfold while recovering from surgery. In this episode, I want to focus on the systematic patterns that caused this disaster and the decision framework that can prevent it.

Read Studio Notes on Substack

Here's my promise: by the end of this episode, you'll understand the five thinking errors that consistently destroy innovation value, you'll have a complete decision framework to avoid these traps, and you'll know exactly how to apply this to your current innovation decisions.

Because here's what this disaster taught me: intelligence doesn't predict decision quality. Systematic thinking frameworks do.

Let me start with the fundamental problem that makes these disasters predictable. When the HP Board hired Leo Apotheker as CEO, they created what I call a “cognitive mismatch,” and it reveals why smart people make terrible innovation decisions.

Apotheker came from SAP, where he'd run a $15 billion software company. HP was a $125 billion technology company with breakthrough mobile platform technology. The board put someone whose largest organizational experience was half the size of HP's smallest division in charge of evaluating platform innovations he'd never encountered before.

But here's the crucial insight: the problem wasn't his experience level. The problem was how his professional background created mental blind spots that made him literally unable to see WebOS as an opportunity.

Here's what's dangerous: Apotheker couldn't see WebOS as valuable because his entire career taught him that software companies don't do hardware. His brain was wired to see hardware as a distraction, not an advantage. To him, WebOS represented exactly the kind of hardware business he wanted to eliminate.

Your expertise becomes your blind spot. You literally can't see opportunities outside your professional comfort zone.

And this is the first critical principle: Your job background creates mental filters that determine what opportunities you can even see.

And this pattern is happening in your company right now. Your finance team evaluates platform investments using metrics designed for traditional products. Your marketing team rejects concepts they can't explain with existing frameworks. Your engineers dismiss breakthrough ideas that don't fit current technical roadmaps.

The pattern is always identical: intelligent people using the wrong thinking frameworks to evaluate breakthrough technology. Let me show you exactly how this destroys innovation value.

WebOS died because of five predictable cognitive errors that occur when smart people evaluate breakthrough technology under pressure. These aren't unique to HP—I've seen identical patterns destroy innovation value across multiple industries.

The most dangerous mistake happens before you evaluate any options: framing the wrong decision question.

Apotheker was asking “How do I transform HP into a software company?” when the strategic question was “How do we build competitive advantage in mobile computing platforms?” When you optimize solutions for the wrong problem, you get excellent answers that destroy strategic value.

The Warning Sign: Your team jumps straight to evaluating options without questioning whether you're solving the right challenge.

Your professional background creates systematic blind spots about breakthrough opportunities.

Software executives see software solutions. Hardware leaders focus on hardware opportunities. Financial experts optimize for traditional metrics. This cognitive filtering happens automatically and distorts how you evaluate platform technologies that don't fit conventional categories.

The Warning Sign: Your evaluation team all have similar backgrounds and reach the same conclusions about breakthrough technology.

When executives become obsessed with major initiatives, everything else feels like a distraction.

Apotheker became obsessed with acquiring Autonomy, a software company that fit his transformation vision. This tunnel vision made everything else—including breakthrough mobile technology—feel like a distraction from his primary goal.

The Warning Sign: Leadership dismisses promising innovations because they don't support the current primary initiative.

Platform technologies require different evaluation timeframes than traditional products.

Forty-nine days isn't enough time to build developer ecosystems, establish retail partnerships, or demonstrate platform traction. But pressure to show decisive leadership compressed HP's decision timeline artificially, creating the illusion of strong leadership while increasing the probability of strategic errors.

The Warning Sign: Your team is evaluating breakthrough technology using the same timelines as conventional product launches.

Innovation decisions require fundamentally different success metrics than traditional business evaluation.

HP focused on TouchPad sales numbers instead of developer adoption rates, user engagement patterns, or platform differentiation sustainability. They used product metrics to evaluate platform potential, which guaranteed they would see failure instead of recognizing early-stage ecosystem development.

The Warning Sign: You're applying traditional business metrics to evaluate breakthrough technology investments.

Here's what makes these errors so dangerous: they're invisible to the people making them. Smart teams use these flawed frameworks and feel confident they're making data-driven decisions while systematically destroying innovation value.

But these patterns are preventable. After analyzing hundreds of similar disasters, I developed a systematic framework specifically designed to avoid these thinking traps.

The DECIDE framework addresses each cognitive vulnerability that consistently traps intelligent leaders in innovation contexts. Let me show you exactly how it works and why it would have saved WebOS.

Most innovation failures begin with teams optimizing excellent solutions for poorly defined problems.

The Tool: Reframe your decision question three different ways. If all three point to the same choice, you're probably asking the right question. If they point to different choices, you need to determine which frame captures the real strategic challenge.

Examples of Different Frames:

HP's Application:

What This Reveals: The reframes show TouchPad was one product in a larger platform opportunity that deserved different evaluation criteria entirely.

Your professional background creates invisible filters that can systematically distort how you interpret breakthrough opportunities.

The Tool: If you hired someone with completely different expertise to make this decision, what would they choose? When the gap is huge, you need outside perspectives with different cognitive frameworks.

HP's Gap: Enterprise software CEO versus consumer platform strategy requirements. They needed mobile platform thinking, not enterprise software optimization, but never brought that expertise into the decision process.

The most dangerous assumptions feel like established facts and shape your entire analysis without being examined.

The Tool: What would have to be true for your least favorite option to actually be the right choice? This forces you to consider alternative interpretations of the same evidence.

HP's Assumptions: Platform businesses need immediate profitability, mobile computing won't dominate, differentiated operating systems can't compete with Apple and Google. All of these assumptions were provably false by 2011, but they drove the evaluation process.

Different types of decisions trigger predictable cognitive biases that distort evaluation in systematic ways.

The Tool: Which specific biases is your decision most vulnerable to? Create explicit countermeasures for each identified bias.

Common Innovation Decision Biases:

HP's Specific Traps:

Most innovation failures result from evaluating limited options well rather than evaluating good options poorly.

The Tool: Generate five genuinely different approaches before evaluating any of them. Breakthrough solutions often emerge from non-obvious alternatives.

HP's Missing Options: License WebOS to manufacturers, integrate into PC ecosystem, pivot to enterprise mobile, create hybrid hardware-software strategy. All had genuine potential but were never seriously considered.

Platform technologies require fundamentally different success metrics than traditional product evaluation.

The Tool: What evidence would predict success for this specific type of innovation? Use frameworks appropriate for breakthrough technology, not conventional business metrics.

HP's Error: They used quarterly sales performance and immediate profitability to evaluate platform potential. Platform businesses lose money initially while building network effects that create sustainable advantages later.

Let me show you how to use this framework with your current innovation decisions.

Step One: Identify Your Highest-Stakes Innovation Decision

What breakthrough technology, platform investment, or disruptive opportunity is your team evaluating right now? This framework applies to any decision where traditional business metrics might mislead about innovation potential.

Step Two: Run the Decision Question Test

Before evaluating any options, reframe your decision question three different ways. Are you asking “How do we minimize risk?” or “How do we maximize strategic opportunity?” The frame determines the solutions you'll even consider.

Step Three: Audit Your Evaluation Team

Who's making this decision? What cognitive filters might their backgrounds create? Do you need advisors with different expertise to see opportunities your current team might miss?

Step Four: Challenge Your Obvious Assumptions

What would have to be true for the option you least prefer to actually be right? Those conditions might exist or be emerging faster than you realize.

Step Five: Identify Your Decision Traps

Is your team vulnerable to loss aversion? Anchoring on early data? Tunnel vision around other initiatives? Create specific countermeasures for each identified bias.

Step Six: Generate Multiple Approaches

Push beyond obvious choices. What would someone from a completely different industry do? What creative alternatives combine elements from different options?

Step Seven: Use Appropriate Evidence

Are you evaluating platform potential with product metrics? Breakthrough technology with conventional criteria? Innovation investments with traditional business frameworks? Match your evidence to your innovation type.

Download DECIDE Framework Toolkit

The DECIDE framework works because it addresses the specific cognitive vulnerabilities that consistently trap intelligent people in innovation contexts.

Traditional decision-making assumes you know the right questions to ask, can see opportunities clearly, and will use appropriate evaluation criteria. Innovation decisions violate all these assumptions. Breakthrough technologies don't fit existing categories. Platform investments don't follow traditional timelines. Disruptive opportunities can't be evaluated with conventional metrics.

The companies that consistently succeed at innovation aren't smarter—they use systematic frameworks designed for uncertainty, breakthrough potential, and non-obvious opportunities.

Three Companies Getting This Right:

Amazon evaluates platform investments with different metrics than product launches. They expected Kindle, AWS, and Prime to lose money initially while building long-term competitive advantages.

Google uses systematic frameworks to avoid identity bias in breakthrough technology evaluation. Android didn't fit their search advertising identity, but they evaluated it with platform-appropriate criteria.

Apple applies different decision frameworks to breakthrough products versus incremental improvements. They gave iPhone multiple years to build ecosystem momentum instead of expecting immediate profitability.

These companies avoid the systematic thinking errors that destroyed WebOS because they use decision frameworks designed for innovation uncertainty.

Here's the reality: this challenge isn't going away. Breakthrough technologies will continue emerging faster than traditional business frameworks can evaluate them. The companies that develop systematic innovation decision capabilities will capture enormous value. Those that rely on conventional thinking will consistently destroy breakthrough opportunities.

Your Three Action Steps:

First: Download the DECIDE Framework toolkit and apply it to your current highest-stakes innovation decision before evaluating any options.

Second: Audit your innovation evaluation processes. Are you using traditional business metrics to evaluate breakthrough technology? Conventional timelines for platform investments? Identity-driven thinking for disruptive opportunities?

Third: Build systematic innovation decision capabilities into your organization. Train your team to recognize cognitive biases, use appropriate evidence frameworks, and generate multiple creative alternatives.

Questions to Consider:

But here's the final piece of this story that shows just how costly these thinking errors can be: Leo Apotheker was fired on September 22, 2011—just 35 days after shutting down WebOS and eleven months after taking over as CEO. The board finally recognized the systematic thinking errors that had destroyed billions in value, but it was too late for WebOS.

The human cost of these decisions goes beyond stock prices and quarterly reports. There are real people who believed in breakthrough technology, fought for innovation, and had to watch it get destroyed by preventable thinking errors.

The complete personal story of watching this disaster unfold—including details about the brutal aftermath and why I still believe in HP despite everything—is in this week's Studio Notes over on Substack. 

Read Studio Notes on Substack

Remember: when you have breakthrough technology in your hands, the quality of your decision-making process matters more than the quality of your technology. Intelligence and good intentions aren't enough. You need systematic frameworks for thinking clearly about innovation under uncertainty.

The tools exist to prevent these disasters. The question is whether you'll implement them before your next WebOS moment.

Remember—in a world where billion-dollar innovations can be killed in 49 days, systematic decision frameworks might be your most valuable competitive advantage.

If you found this week's episode valuable, subscribe to the podcast or watch on the YouTube channel.

To learn more about HP's WebOS failure and the innovation decision-making framework, listen to this week's show: The $1.2 Billion Innovation Disaster: 5 Decision Mistakes That Kill Breakthrough Technology (HP WebOS Case Study).