The Innovation Problem Nobody Wants to Talk About
Every large company in the DACH region has an innovation process. Most of them have several. There are stage-gate models, design thinking workshops, hackathons, venture boards, innovation labs, and — the latest trend — AI-powered idea generators. The one thing most of them share: they do not reliably produce successful products.
The data is consistent and damning. Depending on the study you cite, somewhere between 72% and 95% of new products fail to meet their revenue targets. McKinsey, BCG, and the Product Development and Management Association have all published variations of this number. It has not materially improved in 40 years.
Outcome-Driven Innovation — ODI — is the exception. Developed by Tony Ulwick beginning in 1991, ODI has achieved an 86% success rate across more than 1,000 innovation initiatives. Not 86% of ideas generated. Not 86% of projects started. 86% of products launched.
That is not a marginal improvement. That is a structural difference.
What Exactly Is Outcome-Driven Innovation?
ODI is an innovation strategy and process that uses customer-defined outcome metrics to identify, prioritize, and address unmet market needs. It is grounded in Jobs to Be Done theory and converts that theory into a quantitative, repeatable methodology.
The core insight: customers do not want products. They want to achieve outcomes when they execute a job. A surgeon does not want a better suture — she wants to minimize the time it takes to close a wound while minimizing the likelihood of tissue damage. A construction site manager does not want a better crane — he wants to minimize the time it takes to position a load at the target location while minimizing the risk of load instability during transport.
These outcomes are measurable. They can be captured in a standard format, surveyed across hundreds of customers, and scored to reveal which ones are most important and least satisfied. The resulting data tells you — with statistical confidence — exactly where to innovate.
Companies fail at innovation because they don’t know what a customer need is. They say they’re customer-centric, but they can’t write down a single need that’s unambiguous, stable over time, and measurable. ODI solves that problem.
The Problem ODI Solves
To understand why ODI exists, consider how most companies make product decisions today.
The typical process: Product management collects input from sales, customer support, and a handful of customer visits. Marketing runs a survey asking customers to rate features. Engineering adds their technical wish list. Everything goes into a backlog. Someone — usually the loudest voice in the room or the highest-ranking executive — decides what gets built.
This process has three fatal flaws:
1. It confuses solutions with needs. When a customer says “I want a bigger display,” that is a solution statement — not a need. The need might be “minimize the time it takes to read measurements in low-light conditions.” If you take the solution statement at face value, you build a bigger display. If you understand the need, you might add a backlight, redesign the information hierarchy, or create a heads-up display. The solution space is dramatically larger when you frame the problem correctly.
2. It has no mechanism for prioritization. Even if you capture real needs, you still have to decide which ones to address. “All of them” is not a strategy. Without quantitative data on importance and current satisfaction, you are guessing. And the guesses tend to be biased toward whatever the most recent customer said, or whatever the CEO’s pet project is.
3. It produces anecdotes, not data. Three customer visits do not constitute research. They constitute anecdotes. And the danger of anecdotes is that they feel compelling — a vivid story from a frustrated customer feels more real than a spreadsheet of survey data, even when the spreadsheet is 100 times more representative.
ODI eliminates all three flaws. It captures needs as desired outcomes (not solutions), quantifies their importance and satisfaction (enabling prioritization), and does so across hundreds of customers (producing statistically valid data).
How ODI Differs from Other Innovation Approaches
Versus Brainstorming and Ideation Workshops
Brainstorming starts with a blank page and asks “What should we build?” ODI starts with 50–150 quantified customer outcomes and asks “Which underserved outcomes should we target?” The first produces ideas that need validation. The second produces ideas that are pre-validated by the target data.
Versus Traditional Market Research
Traditional market research asks customers what they want, which features they prefer, or how they would improve existing products. This generates solution-contaminated data. ODI captures outcome statements — metrics of success that are independent of any solution. This is not a subtle difference. It is the reason ODI research stays relevant for 5-10 years, while traditional market research is stale within months.
Versus Design Thinking
Design Thinking builds empathy through observation and produces rapid prototypes through iteration. It is excellent at generating creative solutions but poor at prioritizing between them. ODI provides the quantitative prioritization that Design Thinking lacks. The two are complementary: use ODI to identify which outcomes to target, then use Design Thinking to generate creative solutions for those specific outcomes.
Versus Lean Startup
Lean Startup says “launch fast and iterate.” This works in software, where the cost of an iteration is a sprint or two. It is risky in medical devices (regulatory cycles measured in years), industrial equipment (tooling costs in millions), and any market where “fail fast” means “waste $10 million fast.” ODI front-loads the learning, so you iterate on paper before you iterate in metal and plastic.
The ODI Framework: A Quick Overview
ODI follows a six-step process. Each step is covered in detail in The ODI Process: 6 Steps to Systematic Innovation. Here is the structure:
Define the market around the job to be done. Identify the core functional job, related jobs, and emotional/social jobs.
Discover customer needs. Conduct qualitative interviews using the Job Map framework to capture 50–150 desired outcome statements.
Quantify needs. Survey 180-600 customers to measure the importance and satisfaction of each outcome.
Discover hidden opportunities. Plot outcomes on the Opportunity Landscape to identify underserved and overserved clusters.
Formulate growth strategy. Based on the opportunity data, choose between differentiated, disruptive, dominant, discrete, or sustaining strategies.
Generate ideas and concepts. Use the underserved outcomes as specific design targets for concept development.
The process typically runs 12-16 weeks for a full engagement and produces actionable strategic direction — not a report, but a quantified roadmap.
Why the 86% Success Rate Is Real
Skepticism about the 86% number is healthy. Here is why it holds up:
The denominator is honest. Practitioners count every initiative where ODI was fully applied and a product was launched. They do not cherry-pick.
The method eliminates the largest cause of failure. Product Failure 101: you built something nobody needed, or something that addressed a need already well-served. ODI’s quantitative measurement of importance and satisfaction eliminates this entire category of failure. You know — before you write a single line of code or cut a single piece of metal — that the need exists and is underserved.
The success definition is reasonable. An initiative counts as successful if the resulting product meets or exceeds its business objectives (revenue, share, margin). This is not “we learned something” — it is “we launched a product that worked in the market.”
The track record is long. die ODI-Praxis has been applying ODI since the early 1990s. The 86% number is not based on a handful of projects — it spans hundreds of initiatives across industries including medical devices, consumer electronics, financial services, software, and industrial equipment.
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ODI and Tony Ulwick: The Origin Story
Tony Ulwick developed ODI in the early 1990s while working as an innovation consultant. He noticed that companies with the best engineers and the biggest R&D budgets still failed at innovation — and the common factor was that they did not have a reliable way to understand what customers actually needed.
Ulwick drew on W. Edwards Deming’s quality management principles (particularly the idea that outcomes should be measurable and controllable) and Clayton Christensen’s Jobs to Be Done theory (the idea that customers hire products to get jobs done). He combined these into a single framework that could be applied systematically.
The first formal publication of ODI was in the Harvard Business Review in January 2002 (“Turn Customer Input into Innovation”). Christensen himself endorsed the approach, and the two collaborated on refining JTBD theory.
Since then, Ulwick has published What Customers Want (2005) and Jobs to Be Done: Theory to Practice (2016), both of which detail the ODI methodology. has applied the method across industries and geographies, building the track record that supports the 86% success rate claim.
For a firsthand account from Ulwick, we recommend listening to episode #9 of our podcast, where Tony discusses the genesis of ODI and how the methodology has evolved over three decades.
Who Should Use ODI?
ODI delivers the most value in specific contexts:
High-stakes product decisions. When the cost of failure is measured in millions — tooling, regulatory approvals, market launch — you need confidence in the direction before you commit. ODI provides that confidence.
Mature markets with declining differentiation. When every competitor offers similar features, ODI reveals the outcomes that nobody is addressing — the white space that exists even in crowded markets.
Cross-functional misalignment. When R&D, marketing, and product management cannot agree on priorities, ODI provides a shared data set that replaces opinion-based arguments with evidence-based decisions.
Post-acquisition integration. When you have acquired a company and need to rationalize overlapping product lines, ODI shows you which outcomes each product serves best — and where consolidation or differentiation makes strategic sense.
ODI is less necessary when:
- You are exploring a genuinely new category with no existing job executors to survey
- The cost of iteration is very low (e.g., consumer mobile apps where you can A/B test live)
- You have fewer than 100 potential customers worldwide (though we have made it work with small populations)
Common Misconceptions About ODI
Next Steps
If ODI sounds like the missing piece in your innovation process, here is a reading path:
- Understand the process: The ODI Process: 6 Steps to Systematic Innovation
- Learn the language: Customer Desired Outcomes: The Building Blocks of ODI
- See the full picture: Outcome-Driven Innovation: The Definitive Guide
- Understand the theory: What Are Jobs to Be Done?
Curious Whether ODI Fits Your Situation?
Book a complimentary discovery call to explore how these ideas apply to your organization.
