Innovation Myopia: Why Customer-Focused Companies Still Miss Breakthroughs

Last time, I wrote about why companies that have more operational knowledge than ever still make poor innovation bets. Today, I want to show you the pattern that causes this, a pattern so common it deserves its own name: Innovation Myopia.

Most companies know a lot about their customers. They conduct market research, analyze demographics, track behaviors, and run customer advisory boards. This knowledge helps them run their business efficiently.

But it doesn’t help them innovate.

Why? Because the knowledge that helps you deliver products and services isn’t the same knowledge that helps you innovate.

The Streetlight Effect

Innovation myopia happens when organizations use operational knowledge (knowledge about delivering today’s products) to make innovation decisions.

This follows a pattern psychologists call the “streetlight effect:” searching for something where it’s easy to look, rather than where it’s most likely to be found.

The name comes from an old joke about a drunk man searching for his keys under a streetlight. A police officer asks where he lost them. “Over there in the park,” the man says, pointing to darkness.

“Then why search here?”

“Because this is where the light is.”

This isn’t irrational. Searching where you can see is logical. The problem is that logic leads you to the wrong place.

Organizations have abundant operational data about current products and current customers. This data is easy to access, quantifiable, and actionable. Searching there feels productive.

But innovation insights don’t live in operational data. They live in understanding the job customers are trying to get done and the outcomes they struggle to achieve.

A Fundamental Principle

This distinction reveals a fundamental principle: the job (not the customer, not the product) must be the unit of analysis for innovation.

The unit of analysis is the focal point around which you organize your research and discovery efforts.

When operational data about customers and products is the unit of analysis, teams optimize current offerings.

When the customer’s job is the unit of analysis, teams discover breakthrough opportunities.

This myopia shows up in two common forms:

Product-Focused Myopia

This occurs when organizations define markets by product categories and optimize around product attributes: features, specifications, and cost.

Teams track which features perform best, which specifications customers prefer, and how products compare to competitors. This operational knowledge describes current product performance but reveals very little about why customers hire products or what job they accomplish and how they measure success.

Harvard Business School Professor Theodore Levitt warned of this pattern in “Marketing Myopia” (1960), observing that railroads failed because they defined themselves by what they made (trains and tracks) rather than the customer need they served: transportation.

Levitt’s insight: “People don’t want to buy a quarter-inch drill; they want a quarter-inch hole.”

This myopia artificially narrows the competitive landscape and locks teams into incremental improvements rather than breakthrough opportunities.

Customer-Focused Myopia

This occurs when companies rely upon operational knowledge for innovation instead of jobs-and-outcomes knowledge.

Organizations segment customers by demographics and psychographics. They track preferences, behaviors, and usage patterns. This helps them understand who their customers are and what they value.

Yet organizations can be genuinely customer-focused, studying demographics, psychographics, preferences, and usage patterns, and still lack the jobs-and-outcomes knowledge essential for innovation.

This traditional approach to segmentation reveals WHO buys, WHAT they currently prefer, and HOW they use existing products, but not WHY they hire solutions or WHICH outcomes they struggle to achieve.

Harvard Business School Professor Clayton Christensen demonstrated this in The Innovator’s Dilemma (1997) and The Innovator’s Solution (2003). Even genuinely customer-focused companies fail when they study the customer instead of studying the job the customer is trying to get done.

Customer attributes, preferences, and usage patterns describe current reality but lack predictive power for innovation.

For innovation, studying the customer without understanding the job they’re trying to get done is like studying the ocean when you need to know where to fish. It’s endlessly fascinating but not actionable for your purpose.

The Slack Example

Slack’s success shows the same pattern.

Incumbent communication tools had extensive operational knowledge about their users. They knew which features were used most, what integrations were requested, and how users organized messages. They used this knowledge to deliver increasingly sophisticated capabilities.

Meanwhile, teams everywhere struggled to collaborate effectively. Email created endless, fragmented threads. Information lived in silos. Critical decisions happened in conversations that disappeared.

Slack didn’t win with better operational knowledge. They won with jobs-and-outcomes knowledge: “teams seeking to collaborate seamlessly to move faster and stay aligned.”

This understanding of what people were trying to accomplish (not how they currently used tools) changed everything.

Endless email threads were replaced with searchable channels. Siloed conversations were replaced with transparent collaboration. Fragmented tools were replaced with integrated workflows.

Slack disrupted the industry by serving a job incumbents didn’t recognize existed.

The light is bright where your operational data lives. But your innovation opportunities are waiting in the darkness, in the jobs your customers are trying to get done and the outcomes they struggle to achieve.

What form of innovation myopia have you seen in your organization? Are you searching under the streetlight?

What I’m Working On

I’m collaborating with the Global Innovation Management Institute (GIMI) to create an ISO-certified Level 1 course on Lean JTBD OS that makes this approach accessible for innovation professionals and leaders. Lean JTBD OS is an AI-augmented innovation operating system that systematically uncovers customers’ unmet needs through qualitative discovery, transforming innovation from guesswork into a repeatable business process.

Want priority access when it launches? Email me and I’ll add you to the list.