Introduction: The Billion-Dollar Flop
In 1984, the development team at IBM believed they were on the precipice of a revolution. They had spent 18 months of intensive labor on the PCjr, a product the Washington Post predicted would quickly become the “standard by which all other home computers are measured.”
The reality was a cold shower. The day after its release, the Wall Street Journal declared the PCjr a “flop.” It was a public humiliation that cost IBM over a billion dollars and left a permanent blemish on its reputation.
This story is not an outlier. Research from firms like Simon-Kucher & Partners shows that between 72% and 83% of all new product introductions fail to meet expectations. The central problem isn’t a lack of talent or capital; it is that most companies treat innovation as an art form—a game of chance fueled by gut feel. To move beyond this, we must accept a new thesis: Innovation is not an art. It is a rigorous science of addressing “Jobs-to-be-Done” (JTBD) using specific, measurable metrics.
The “Needs” Mystery: Why Your Team is Speaking Different Languages
If you ask your product managers, marketers, and engineers to define a “customer need,” you will likely get a dozen different answers. In our research, we found that 95% of product teams do not agree on what a “customer need” actually is.
Most teams treat needs as vague “benefits,” “problems,” or “features.” In the JTBD framework, a need is defined as a Desired Outcome—a measurable metric that a customer uses to judge success while getting a job done. Without a shared language, teams move in opposite directions, like a crew rowing a boat in a circle. As Harvard marketing professor Theodore Levitt famously noted:
“People don’t want to buy a quarter-inch drill. They want a quarter-inch hole!”
When you define needs as measurable outcomes—such as “minimize the time it takes to get the songs in the desired order for listening”—you stop guessing and start engineering value.
The “Ideas-First” Trap: Why Brainstorming is Often a Waste of Time
Most companies follow an “ideas-first” approach: they brainstorm hundreds of concepts and then “fail fast” to see what sticks. This is inherently flawed. It is the equivalent of a sharpshooter firing into the dark, hoping to hit a target they haven’t even defined. Expecting this to work is like expecting a doctor to recommend the right treatment without knowing what is wrong or what the symptoms are.
Mathematically, the “ideas-first” approach is doomed. In any given market, a customer has between 50 and 150 desired outcomes. The probability of an idea randomly hitting 15 or more unmet needs without knowing what they are is one in 14 million.
| Approach | Methodology | Success Rate |
|---|---|---|
| Ideas-First | Brainstorming, guessing, and “failing fast.” | ~17% Success* |
| Needs-First | Defining metrics and strategy before ideation. | ~86% Success |
*Note: While the average success rate for traditional methods is 17%, various studies show a range from as low as 1% to 59% (PDMA).
Your Customer is Not a Single Person: The Three Jobs-to-be-Done Roles
A common mistake, particularly in B2B sectors, is viewing “the customer” as a single entity. To achieve predictability, you must recognize that the customer is actually a triad of roles:
- The Job Executor: The person using the product to get the core functional job done. In a medical context, this is the Surgeon.
- The Product Lifecycle Support Team: The frequently overlooked groups who execute “Consumption Chain Jobs.” These are the Nurses and Bio-meds who must receive, setup, interface, upgrade, and dispose of the equipment. Innovation here—such as making a tool easier to sterilize—can revolutionize a market.
- The Purchase Decision Maker: The person using a financial lens to decide which solution to acquire. This is the Hospital Administrator, who cares about metrics like “reducing the patient’s length of stay.”
B2B companies often struggle because they fail to distinguish between the surgeon’s need for “precision” and the administrator’s need to “reduce morbidity rates.”
Stability in Chaos: The Job Stays, the Technology Fades
Innovation feels chaotic because technology moves so fast. However, “Jobs” are remarkably stable over time and geography.
Consider the job of “listening to music.” Over decades, we have transitioned from phonographs to cassettes, CDs, MP3s, and streaming services. The technology—the delivery vehicle—changed constantly, but the job remained exactly the same. By taking a solution-agnostic view, companies can stop reacting to disruption and start predicting it. If you focus on the job rather than the product, you can identify the next wave of technology that will get the job done better or more cheaply before your competitors do.
The 86% Success Rate: Turning Innovation into a Science
The transition from “luck” to “science” is best evidenced by the Outcome-Driven Innovation (ODI) methodology. While traditional innovation success rates hover around 17%, an independent study of 43 Strategyn clients found that products launched using the ODI process had an 86% success rate.
The “Secret Sauce” is breaking the Core Functional Job into a Universal Job Map. Regardless of the industry, every job consists of eight fundamental steps: 1. Define → 2. Locate → 3. Prepare → 4. Confirm → 5. Execute → 6. Monitor → 7. Modify → 8. Conclude.
Within these steps, we uncover 50–150 “Desired Outcome” statements. These follow a strict syntax to ensure they are measurable and actionable: [Direction of Improvement] + [Performance Metric] + [Object of Control] + [Contextual Clarifier] (e.g., “Minimize + the likelihood that + the music sounds distorted + when played at high volume.”)
When you know exactly which of these 150 metrics are currently underserved, ideation becomes trivial. As marketing legend Philip Kotler put it:
“I call him the Deming of Innovation because… Tony has turned innovation into a science.”
Conclusion: The Future of Your Growth Strategy
The path to predictable growth requires a fundamental shift in perspective. It means moving away from the “art” of brainstorming and toward the “science” of a reproducible system. When you treat the customer’s job as a process that can be broken down, measured, and optimized, you replace the humiliation of a “billion-dollar flop” with the confidence of a calculated win.
As you look at your current roadmap, ask yourself: “If you broke your core product down into the ‘process’ your customer is trying to execute, which of the 100+ metrics are you currently ignoring?”