Importance of Jtbd for Innovation

What if we reimagined the Double Diamond through the lens of Jobs-to-be-Done? 🤔 Product Management is about mastering various methodologies and knowing when to apply them. No single framework fits all scenarios - the key is understanding how different approaches can complement each other to drive better outcomes. I have been learning and practicing the art and science of Innovation through the concepts of JTBD, Human Centered Design, Design Thinking, Customer Driven Innovation, Continuous Discovery, Product Discovery, Lean, etc., I've found these methodologies aren't just related, they're deeply interconnected pieces of the same puzzle. I took the classic double diamond design thinking framework and applied JTBD to it and here is how it looks in my view. While the double diamond model divides the journey into Problem → Solution spaces, the evolved version speaks the language of jobs and outcomes 💎Left Diamond: Transformed from problem-finding to "Jobs & Outcomes" - focusing on understanding what customers are trying to achieve in their contexts. 🌉The Bridge: "Opportunity Statements" replace "Problem Definition" - shifting from fixing issues to unlocking potential. Opportunity Statements are what Tony Ulwick calls "Hidden Growth Opportunities". These statements guide our innovation direction. 💎Right Diamond: Maintains the Design/Develop and Iterate/Deliver phases, but shifts validation focus to measuring how effectively we enable customers to achieve their desired outcomes. This framework moves beyond problem-solution thinking to create value through deep understanding of customer progress and success metrics in the form of jobs and outcomes. Have you integrated different innovation frameworks in your work? What have you learned? Would love to hear your experiences! #innovation #JTBD #designthinking #productdiscovery

The deeper we get into building AI Agents, the more I’m realizing that the Jobs to be Done (JTBD) framework is the perfect approach for specifying agent capabilities.   Why? Because AI agents aren’t just about the underlying tech—they’re about solving real, meaningful problems for users. The JTBD framework asks us to focus less on feature checklists and more on the objectives: What "job" does the user need done? In what context? What are the success criteria?   This mindset reframes how we:   - Define Agent Use Cases (not just "what CAN it do," but "what SHOULD it do to deliver value") - Prioritize Capabilities (design for actual outcomes and impact) - Measure Success (tied to completion of real-world jobs, not just transactions or clicks)   When we center the design process on JTBD, we’re much better positioned to build agents that fit seamlessly into workflows, anticipate user intent, and drive real adoption.   Curious to hear from others working in the agent space: How are you defining agent capabilities? Has JTBD or a similar approach helped shape your roadmap?   #ArtificialIntelligence #JobsToBeDone #ProductManagement #AIProductDesign #AIWorkflow #DigitalTransformation

Decoding the Language of Innovation: Part 16 Every week, I decode one innovation concept/term through a Jobs-to-be-Done lens. The goal is to align your organization around a common language of innovation; one that will enhance its value creation efforts. This week's concept/term is: "Functional Job-to-be-Done" Let's get into it. Since we know innovation starts with understanding what customers are trying to accomplish, it follows that a functional job-to-be-done is defined as: The underlying process an end user is trying to execute, which: - Is the focal point around which a market is defined - Remains stable over time (unlike solutions) - Has no geographical boundaries - Is solution-agnostic (not tied to specific products) For example: - "Restore blood flow in a blocked artery" (not "use an angioplasty balloon") - "Cut wood in a straight line" (not "use a circular saw") - "Pass on life lessons to children" (not "read a parenting book") Why it matters: When defining markets, you should start by asking "what process is the customer trying to execute?" Depending on how you define the job will dictate your innovation focus. If you define it too narrowly, you'll miss opportunities; if too broadly, your insights won't be actionable. Using a Jobs-to-be-Done lens, effective innovation requires: - Defining the job at the right level of abstraction - Breaking it down into discrete job steps - Capturing desired outcomes for each step - Measuring how well current solutions get the job done Using this definition will help your business: - Focus innovation efforts on a stable target - Discover unmet needs across the entire job - Create solutions that address the complete job - Set a long-term vision for your organization See you next Friday for the next edition of Decoding the Language of Innovation! — Thanks for reading! This was part 16 of my weekly series: Decoding the Language of Innovation. Where every Friday, I decode one innovation concept/term by looking at it through a Jobs-to-be-Done lens. With a common language of innovation, your company can: - Align in the same direction - and the right direction - Make better products - Grow revenue - And beat the competition Follow me here - @tonyulwick - to get my post in your feed every Friday.

🔍 𝗜𝗳 𝘆𝗼𝘂 𝘄𝗮𝗻𝘁 𝗰𝗼𝗻𝗳𝘂𝘀𝗶𝗼𝗻 𝗶𝗻 𝗽𝗿𝗼𝗱𝘂𝗰𝘁 𝗺𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝗮𝗻𝗱 𝗺𝗮𝗿𝗸𝗲𝘁𝗶𝗻𝗴, 𝘁𝗵𝗲𝗻 𝗰𝗼𝗻𝗳𝗹𝗮𝘁𝗲 𝗨𝗦𝗔𝗕𝗜𝗟𝗜𝗧𝗬 𝘄𝗶𝘁𝗵 𝗖𝗨𝗦𝗧𝗢𝗠𝗘𝗥 𝗢𝗕𝗝𝗘𝗖𝗧𝗜𝗩𝗘𝗦 Have you ever seen a product designed after extensive discovery interviews, Voice of the Customer research, or even a big qualitative + quantitative study… only for the end result to fall flat? I see it all the time; and it's really frustrating, because the root cause is that executives and product managers don't even see the problem. They are so eager to get started and "talk to customers," but - especially if they've been in the same industry a long time... it's a blind spot. To be clear, it’s not because the team lacked effort, talent, or budget. The trouble starts at the very beginning when... 👉 We don’t separate Product Jobs (how the product fits the buyer’s journey and daily use) from Core Jobs (the solution-independent goal that drove the customer to buy in the first place). When these two get mixed up, we lose the map. We don’t know whether we’re solving for usability, effectiveness—or both—and decisions become vulnerable to internal opinion, politics, and bias. Let’s take an example that’s sacred in JTBD lore: Dr. Christensen’s milkshake case study. 🚗 Product Job (Level 1): Consume the snack with one hand. The milkshake competes with other snacks (e.g., bananas, bagels) on ease of use during the commute. 🎯 Core Job (Level 2): Keep entertained during the commute. Now the milkshake competes with podcasts, phone calls, or music—anything that makes the drive more engaging. 👉 The milkshake wasn’t just food. It was a way to pass the time. ❗ The problems began with the customer interviews, and the lack of this distinction. The result: – We over-focus on usability or lifecycle support… or – We over-focus on functional outcomes… – But we fail to balance both strategically. ➡️ The Jobs-to-be-Done Pyramid™ fixes this. It gives us a clear structure so every interview question, insight, and design choice aligns with the right type of job: • Level 1: Product Jobs (acquire, use, maintain) • Level 2: Core Jobs (the fundamental purpose) • Higher levels: identity and emotional jobs With the Pyramid, we can chart a scientific, customer-centered path—not just the loudest internal voice’s preferred path. Not convinced this is a problem? The carousel below presents 5 reasons why conflating/combining usability with customer objectives can doom innovation, marketing, and even sales - right from the jump. But there's no reason to suffer! The Jobs-to-be-Done Pyramid™ clears this up. Among new releases on Amazon, The Jobs-to-be-Done Pyramid™ is currently: #1 in Product Management #1 in Consumer Behavior #8 in Marketing #jobstobedone #productmanagement #marketing

Misunderstanding Customer Needs = Innovation Failure Most innovation efforts fail because companies don’t truly understand what their customers want. They optimize existing products, chase trends, and build features based on gut instinct—turning innovation into a frustrating, costly guessing game. But it doesn’t have to be that way. This past Wednesday, I had the fun privilege of sharing "Lean JTBD"—how to unlock the secret of making products customers love—with 39 entrepreneurs and business leaders in a TIGER 🐯 Talk at Innovate New Albany. Big thanks to Neil Collins for hosting! Three takeaways: 1️⃣ People don’t buy products and services; they hire them to get their jobs done. 2️⃣ Customers CAN tell us what they want—if you ask the right questions. 3️⃣ If you don’t understand the “job” your customers are hiring your product/service to do, and where their needs remain unmet, then you’re inevitably missing the mark. And that's a completely avoidable mistake. Don’t ask customers what features they want; ask what they need to accomplish. That’s where true innovation starts; not with a "good idea." If you want to make innovation a repeatable business process, it has to start with understanding customer needs. The fastest way to innovate with confidence? Identify your target customers’ important unmet needs—before building anything. This eliminates guesswork and ensures strong market fit—at concept creation. Want to put these insights into action? I'm creating a free PDF: "The Lean JTBD Playbook"—a three-step guide to help you: ✔️ Choose the right growth strategy for product differentiation ✔️ Redefine your market for innovation ✔️ Obtain customer insights that matter Coming soon! Drop a comment or DM me with 'PLAYBOOK' and I’ll send it your way once it’s ready. #Jobstobedone #Innovation #ProductStrategy #differentiation #CustomerNeeds

How Jobs Theory Can Guide Your Agentic AI Strategy In today’s rapidly evolving technological landscape, artificial intelligence (AI) is no longer just a tool for efficiency. It’s a core strategic driver for innovation and value creation. One way to think more deeply and strategically about designing an AI strategy is by leveraging the Jobs to Be Done (JTBD) theory, which centers around understanding what customers or users are trying to achieve in their lives. When applied to agentic AI, the next frontier of AI systems that operate with autonomy and contextual awareness, JTBD can serve as a foundational framework for designing impactful and user-aligned AI solutions. What is the Jobs to Be Done Theory? JTBD theory, popularized by Clayton Christensen, focuses on identifying the “jobs” people hire products or services to do. Instead of merely looking at demographics or product features, JTBD reframes innovation around the outcomes users want to achieve. For example, customers don’t buy a drill because they want it; they buy it because they want a hole in the wall. The drill’s “job” is to deliver that outcome. When applied to AI, the JTBD approach prompts us to think beyond AI capabilities and instead focus on what people are trying to accomplish with AI tools. What is Agentic AI? Agentic AI refers to systems designed to act autonomously to achieve specific objectives while adapting to their environment. These AI systems can anticipate needs, execute tasks, and make decisions with minimal user intervention. Examples include personalized virtual assistants, autonomous vehicles, and AI-driven process optimizers. Agentic AI shifts the paradigm from being a tool to becoming an active collaborator, enabling users to focus on higher-value activities. However, designing effective agentic AI solutions requires a deep understanding of the “jobs” users want the AI to perform and the context in which they operate. How JTBD Informs an Agentic AI Strategy Here’s how the JTBD framework can be applied to designing your agentic AI strategy: 1. Understand the Functional, Emotional, and Social Jobs Agentic AI should address functional needs and emotional and social outcomes. For example: • Functional Jobs: A customer might want an AI system to automate data entry or scheduling tasks. • Emotional Jobs: The AI could be designed to reduce stress or provide a sense of security, such as in the case of AI home assistants. • Social Jobs: Users may want AI tools that enhance their reputation or ability to collaborate effectively within teams. By understanding these dimensions, you can design AI solutions that resonate deeply with users. In conclusion, Agentic AI should be aligned with the broader progress users are trying to achieve. For example, A team might not want just a project management tool but rather an AI that ensures projects are completed successfully and on time by proactively flagging risks and suggesting solutions.

Ever heard the story of how McDonald’s cracked the code on selling more milkshakes? It's a classic case of customer discovery done right, and it perfectly illustrates the Jobs-to-Be-Done (JTBD) theory. JTBD is the idea that customers “hire” a product to solve a specific problem or job in their lives. McDonald’s wanted to sell more milkshakes, but their initial efforts weren’t moving the needle. So, they decided to dig deeper and figure out why people were actually buying milkshakes in the first place. Instead of relying on focus groups or assumptions, they observed what customers actually did—buying milkshakes early in the morning to solve a specific problem. Turns out, people weren’t just in it for the sweet treat—they wanted to kill time during their morning commutes. The milkshake wasn’t just a drink. It was a survival tool for battling boredom and hunger on the highway. So, what did McDonald’s do? They weren’t improving milkshakes in the traditional sense—they were optimizing them to better serve the specific job they were "hired" for. They made the milkshakes even thicker (to last the whole drive!) and added a bunch of convenient drive-through options in the mornings. Boom—milkshake sales shot up. The takeaway? It’s not always about the product—it’s about what need your product is fulfilling for your customer. McDonald’s wasn’t just selling milkshakes—they were selling a way to survive the soul-sucking experience of a morning commute. When you understand the job your product is hired to do, you can innovate not just by changing the product, but by improving how it fits into your customer's life.

I was walking to meet friends and caught sight of a familiar scene. People cutting across grass instead of using the paved sidewalk behind them. That moment took me back to something Rebecca Sherrill shared with me almost 20 years ago and led to my first "ah hah" with UX and Product design. A university (University of California, Berkeley I think?) delayed laying sidewalks until they saw where students actually walked. Too often, I hear new ideas pitched as “better” or “more convenient". A slicker design or easier flow doesn’t matter if there’s no real reason to change. Sure this dirt path is more convenient but if you charged people money to take it will they still go that route? That’s where Jobs-to-Be-Done (JTBD) comes in. It’s not about guessing what people want. It’s about identifying those moments when people are looking for an alternative. And if they're paying for it, where are they struggling enough to spend money? I love Bob Moesta's saying "b*tching ain't switching" because I often found with customer discovery you identify problems, build a solution, and it doesn't build traction. The decision to switch isn’t made lightly. You’re not just competing against other solutions. You’re competing against habit, inertia, and anxiety. The status quo. You need to understand: - What’s pushing them to look for something new? - What’s pulling them toward a new solution? - What’s making them hesitate or stick with what they already know? This is why I love Bob Moesta's "switch" interviews. You could start with a hypothesis informed by JTBD, but I’ve found that teams often get too attached to their own thinking. It makes it hard to be honest when testing it. Starting with a clear focus area and then uncovering the actual Jobs-to-Be-Done through interviews helps avoid this trap. People can tell you what they do now or have done in the past. They’ll share the workarounds, the friction, and the inflection points that led to a change. That’s your gold. But they likely won’t be able to tell you where to lay the sidewalk. That part is our job. To understand what they’re trying to do, where they’re struggling, and then figure out the right solution to help them make progress. #JTBD #ProductManagement #UX #Discovery

Here's the latest iteration of how we're thinking about using customer research to shape what we build at Databox: First, we've been thinking about different "types" of research: 1. PMM conducts Jobs To Be Done (JTBD) research: qualitative research (calls with customers) to try and uncover what "jobs" prospects or customers have when it comes to using data. We try to keep it general - we're not trying to talk features, we want to understand the result they're trying to achieve. This is critical because if users don't have a job for a specific feature, they won't get recurring value out of it. We have a job outlined when we can complete a "When / I Need / So " sentence. When [ we meet with clients to report their performance ], I need [ a way to record what decisions we made, based on that performance ], so [ nothing falls through the cracks ]. The JTBD is in the "I need" statement. Now, just because we uncover a JTBD doesn't mean we're going to try and solve it. This is an example of one that probably doesn't make sense for us to solve. But if there's no underlying JTBD, there's no guarantee users will adopt the feature. So our goal is that everything we ship this year has an underlying, confirmed JTBD. 2. PMs conduct "concept validation" research: once we have an underlying JTBD, PMs try to come up with the best way to solve that job. They've got the most familiarity with the capabilities and limitations of the product, so it makes for them to explore the best way to solve it. But once they do, they need to validate that our users agree this is the best solution to accomplish their job. Customers may not agree this is the best solution, in which case we need to hear that early and go back to the drawing board to try again. 3. PMs conduct beta research: Once the early version of the feature or functionality is ready, PMs will test it with a handful of select users. This allows them to get constructive feedback and improve the product before it's sent to the wider user base. We're building out a more robust Beta program this year to help us with this. An idea for a feature can come from anywhere: intuition, competitors, feature requests, or our own JTBD research. But our aim is that each feature have a verified, underlying JTBD, and be validated with customers before we invest weeks (or months) into development. It's far from perfect. This is just our latest iteration on this process, so we don't claim to be experts at this. But I'm really excited about the updates we've made and how it'll help us bring customers even more value this year! Huge shoutout to Katja Pozeb for spearheading this process, our product team's willingness to roll with the punches, and Nicole Castillo for helping build out our customer research function very quickly last year.

One of the most powerful frameworks I recommend to early-stage founders we back at Big Sky Capital VC is Jobs To Be Done (JTBD). It shifts your mindset from obsessing over product features to truly understanding the real-world problems your customers are trying to solve. Instead of asking, “How do we sell this feature?”, JTBD pushes you to ask, “What job is the customer hiring our product to do?” The best B2B SaaS founders I work with take this seriously. They talk directly to users, uncover the functional, emotional, and social drivers behind behavior, and then map out those core jobs. When done right, it’s transformative—it leads to stronger product-market fit, clearer messaging, and much better retention. If you’re not already thinking this way, you should be.