When Coffee and Kale Compete Become Great at Making Products People Will Buy

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Here is a summary of the key points from the provided text:

Creative destruction is accelerating as the average lifespan of S&P 500 companies has declined from 55 years in 1960 to around 20 years in 2015. New innovations constantly disrupt and replace incumbent products and companies.
When one innovation wins, another loses, as customers can only use one product at a time. For example, the author stopped going to a coffee shop for espressos after buying a home espresso machine.
“Sunk costs” and being tied to legacy business models prevent companies from adapting and innovating. Kodak is cited as an example - they invented the digital camera in 1975 but failed to commercialize it due to not wanting to cannibalize film sales. They went bankrupt in 2012 due to not adapting to digital photography.
Excuses around “why change what’s making us billions” prevent companies from embracing new technologies and business models. But change is inevitable due to creative destruction and disruption from new innovations.
The author argues focusing on the Job to be Done (JTBD) - understanding the customer’s struggle and motivation beyond technologies and products - is the key to successful ongoing innovation and avoiding obsolescence from disruption. It provides guidance beyond legacy business models.
The passage discusses some common pitfalls and misconceptions that can arise when companies rely too heavily on data and metrics in decision-making.
Figures and metrics like customer satisfaction scores, monthly active users, and revenue can provide useful information but are incomplete and can be misleading if not properly understood in context.
Products often compete with alternatives that are not direct replacements. For example, refrigerators compete with cheaper storage methods, not just other refrigerators.
Focusing only on current customer needs and expectations risks missing opportunities to solve customer problems in new, innovative ways. Customers’ underlying needs may change over time.
Changes aimed at visible metrics like attracting new customers can undermine the experience for existing customers if not considered carefully.
No product lasts forever and continued growth cannot be assumed or forced. Slowing growth does not necessarily mean something is wrong.
Intuition, understanding the full context, and accepting risks are also important aspects of management that metrics alone cannot replace. All models have limitations.

So in summary, the passage cautions against an overreliance on data and metrics in decision-making without also considering the limitations of data and broader contexts around customer needs and business realities. Both quantitative and qualitative factors are important.

Jobs To Be Done (JTBD) theory focuses on understanding customer motivation rather than what customers say they want or their demographics. It provides principles for innovators to help customers make progress.
The book is intended to serve as a comprehensive guide to JTBD, drawing on real-world examples from innovators who have successfully applied JTBD principles. It aims to clarify confusion around JTBD and provide consistent, reliable explanations.
JTBD views innovation through the lens of the “jobs” or struggles customers are trying to overcome in their lives. A job is a struggle or problem someone faces that they want to resolve to make their lives better. A job is “done” when the customer finds a solution that helps achieve the improvement they sought.
Understanding customer motivation from a JTBD perspective helps innovators focus on creating products and services that truly satisfy those jobs, rather than just incremental improvements to existing offerings. This can help drive more sustainable innovation success.
The book argues JTBD provides hope and clarity for innovators struggling to understand customer needs. If applied thoughtfully using the principles explained in the book, JTBD can help innovators improve their ability to create valuable new offerings for customers.
A Job refers to a customer’s emotional struggle or problem to be solved in order to improve their life situation. It describes an unsatisfactory current state and a desired better state.
Done means finding a solution that allows the customer to overcome the struggle/problem and achieve the better life or state they envision. It’s about moving from the current unsatisfying situation to the desired improved situation.
JTBD focuses on understanding the customer’s problem or struggle rather than pre-defining the solution. It takes a descriptive rather than prescriptive approach.
This differs from traditional approaches that may define customer motivations in terms of product attributes/features or tell the business what solution to create. JTBD seeks to understand the deeper human motivation or “hope” that drives customer behavior.
The origins of JTBD draw from theories of creative destruction, systems thinking, behavioral economics, and the work of thinkers like Schumpeter, Deming, Klein, Kahneman, and those who developed the original JTBD principles like Moesta, Palmer and Pied.
A Job is the customer’s emotional struggle to improve their life situation. Done means finding a solution that allows them to achieve the better life or resolution to their problem that they desire.

When you’ve solved the problem or struggle you were previously focused on, a balance is achieved. You are now free to focus your energy on improving other areas of life. Progress has been made, and that particular problem or challenge is resolved. Your work on that specific issue is complete.

The key aspect of JTBD is understanding the customer’s underlying motivation, not the specific activities, tasks or functions related to solving that motivation. Focusing only on functions, tasks and activities limits your thinking to current solutions, rather than imagining new innovative ways to solve the underlying motivation in a better way. A JTBD should describe the motivation or reason why customers act, not the how (specific tasks or functions). Keeping the motivation separate from solutions allows for consideration of a wide range of alternative solutions to meet the same underlying job. Functionality, tasks and activities will come into play later when developing actual solutions, but should not define the JTBD itself.

Here are the key principles of Jobs-to-be-Done (JTBD) discussed in the text:

Customers don’t want products or what they do, they want help making their lives better through progress. Focusing on functionality limits innovation opportunities.
JTBD focuses on describing customer motivation and struggles, not what products/services do. People have Jobs, not products. Products are solutions for Jobs.
Competition is defined by customers based on which solutions help make progress, not just functionality.
Innovation opportunities exist when customers use products in unexpected/compensatory ways.
Solutions come and go, but underlying Jobs/motivations tend to stay the same over time.
Favor measuring ongoing progress over end goals/outcomes. Customers judge success at every step.
Progress defines value; comparing contexts reveals how much value customers place on different solutions.
Solutions can provide value beyond the moment of use if they help enable future progress.

In summary, the key is understanding human motivation as problems to be solved, not just product features, in order to better meet customer needs and drive innovation.

Dan Martell applied Job to be Done (JTBD) thinking to successfully grow his company, Clarity, which connected entrepreneurs with experts. JTBD helped Dan improve his customer research, understand Clarity’s competitive positioning and value proposition, and identify which product features were most important.

Through JTBD-framed interviews, Dan learned customers saw LinkedIn, hiring individual advisors, groups, and conferences as alternatives to Clarity. This understanding of competition informed how Clarity could stand out. Dan also discovered customers valued the messenger over just the advice content, indicating the importance of connecting with a specific motivational expert.

Rather than asking broad questions, JTBD guided Dan to inquire about customers’ specific goals (the “Job”) and past solutions used. This revealed customers wanted a personalized connection to spur meaningful change, not just information. Armed with these insights, Clarity could effectively promote its ability to match entrepreneurs with the right expert for individualized support. In this way, applying JTBD principles helped Dan successfully grow his company.

Dan realized that customers using Clarity were not just seeking advice, but were looking to be inspired and motivated, usually by a particular successful entrepreneur they respected. This emotional motivation drove their desire to make a change.

Understanding this helped Dan and his team market Clarity by emphasizing it provided “on-demand business advice” from respected experts, differentiating it from more passive sources like LinkedIn or conferences that required waiting. They also highlighted Clarity’s lower cost compared to conferences.

This insight also helped Dan attract both advisors and customers to Clarity. For advisors, they focused on recruiting respected experts from sources like SlideShare. For customers, tapping into their desire to be inspired motivated them to use Clarity.

Additionally, Dan realized Clarity was tapping into larger budgets customers had for consulting, conferences, etc. not just lower-cost alternatives. This revealed Clarity’s true value.

Dan also discovered anxieties customers had about using Clarity effectively, like fear of not being prepared or experts not having good answers. Addressing these anxieties through guidance and expectations helped increase usage.

Finally, applying JTBD principles helped Dan validate ideas for new features by understanding if customers were already trying to solve that problem themselves in other ways. This saved building unnecessary features.

Anthony Francavilla is the co-founder of Form Theatricals, a company that helps theater productions grow and be successful.
He has applied the Jobs to be Done (JTBD) framework to better understand why people attend the theater and what motivates them.
traditionally, those in the theater industry don’t have much business experience or expertise in customer motivation.
JTBD has helped Anthony understand what really matters to theatergoers, what they see as competition, and how productions can improve to increase ticket sales and reduce costs.
He sought advice from an expert in interviewing customers named Boris. Boris introduced him to JTBD and said interviewing customers using JTBD principles could reveal the “job” theater patrons are trying to get done.
Learning about JTBD opened Anthony’s eyes to new ways of understanding customer motivation for the theatrical industry.

So in summary, Anthony is using JTBD to gain insights into what motivates theater attendance and how productions can better serve the “jobs” or motivations of their patrons. JTBD provided a framework to improve his understanding and strategy in the industry.

Anthony applied Jobs to Be Done thinking to help a children’s theater company understand what job parents were hiring the performances to do. He interviewed parents and learned they wanted help teaching their kids independence and teamwork in an entertaining way.
This insight helped revise the plays to better align with that job. The revised plays included storylines about working together to solve problems.
Anthony continued using JTBD with other clients. He found some patrons saw theater as a way to socialize and be part of the arts community, even if they didn’t work in that field.
This revealed another job - experiencing a diverse community. Some patrons enjoyed talking to artists at the shows.
With this insight, Anthony helped create a new subscription product. It put people in cohorts to see shows together and socialize, fulfilling the job of inclusive experience seeking. This made theater more accessible and affordable.
Overall, applying JTBD helped uncover deeper customer needs and jobs, which informed product revisions and new offerings to better meet those jobs.

Here are the key points from the case study:

JTBD (Jobs to be Done) theory helps understand customer needs and avoid wasted resources building unnecessary features.
Anthony advised a client to remove costly after-show tours since very few patrons knew about or cared about them. This saved costs and increased profits.
Mapping customer purchase journeys showed anxieties like bad reviews delayed purchases. Discounts alleviated anxieties and pushed hesitant customers to buy. So-called “impulse purchases” were actually considered purchases.
Parents used theater to strengthen family bonds and teach children life lessons through shared experiences. Understanding customer motivations allows innovating in old industries.
When understanding struggles or aspirations, dig deeper by asking how customers previously tried solving them and what progress would look like.
Discover what customers truly value at purchase/use time to avoid over-engineering. Remove unnecessary features to increase profits.
Address customer anxieties about cost, use, etc. just as vigorously as competing products. Find ways to mitigate anxieties.

So in summary, JTBD helps understand customer problems and motivations to create valuable solutions while avoiding wasted resources on unnecessary features. Addressing customer anxieties can also drive purchases and satisfaction.

Here is a summary of the key points from the case study:

Morgan started YourGrocer to address his struggle of not being able to shop at local grocery stores after work due to their closing hours. He teamed up with Bandith to test the idea.
They did preliminary customer interviews and tests which validated there was an opportunity, but they needed technical expertise. That’s when Frankie joined after being introduced to JTBD.
The team spent a week learning JTBD together and then interviewed 20 customers. This helped align the founders’ understanding of the problem.
Contrary to their assumptions, most customers were young families rather than young professionals. The team had to adjust based on actually learning who their customers were.
Interviewing customers uncovered that having a second child was often the triggering event that made grocery shopping very difficult and pushed them to seek alternatives.
Customers disliked the poor quality and lack of choice at supermarkets, and found other delivery services too expensive. YourGrocer aimed to address these issues.
The team confirmed customers valued convenience most, followed by ability to choose foods, while quality was now less important given tradeoffs.
Further interviews helped the team identify the messaging around convenience and choice that resonated most with customers.

So in summary, applying JTBD helped Morgan gain clarity on the problem, build team alignment, identify the right customer segments, and create effective marketing messages to attract customers.

Morgan used data from customer text messages and social media posts to understand what customers valued about his grocery delivery service YourGrocer. He learned they appreciated being able to shop from local stores they recognized and trusted.
Speaking to customers directly, Morgan discovered their main anxiety with the service was not knowing when their groceries would be delivered. But flexible delivery windows were offered - the issue was customers’ shopping habits of deciding purchases after confirming delivery timing.
Existing habits like last-minute trips to local stores presented competition for repeat business. Morgan addressed this by automating reminder emails to encourage regular ordering.
Customers’ job to be done was providing quality food for their family without stress and time spent shopping. YourGrocer solved this by eliminating the trade-off between food quality and family time.
Demographics alone did not capture who Morgan’s most committed customers truly were - families with multiple young children, not just urban professionals. Understanding the customer situation is more important than characteristics.
Demand is shaped by four opposing forces - push, pull, habit, and anxiety. Push and pull generate demand, while habit and anxiety reduce demand.
Push refers to external or internal forces that make customers unhappy with their current situation and motivate change. Examples include having a second child that makes grocery shopping difficult, or internal feelings of lack of motivation or frustration.
Pull refers to the idea of a better life and preference for a particular product that directs customer motivation. The idea of an improved life pulls customers to seek solutions, while preference for a specific product guides them to that solution.
Habit and anxiety are forces that resist change and reduce demand. Habit refers to getting comfortable with familiar routines, while anxiety refers to fears about changing routines or problems with new solutions.
Together these four forces interact in customers as they generate or reduce demand for solutions. Understanding all four forces helps create demand, understand why customers don’t buy, and make effective advertising.

Here is a summary of the key points from the passage:

Creating a business model is inherently difficult due to various unknown factors that influence customer choice.
Both pull (what motivates customers to seek solutions) and push (what motivates them to act) shape the job to be done (JTBD) and need to be understood. Variations in customer pushes lead to different criteria for evaluating solutions.
Attending a conference and using a solution like Clarity may both compete to fulfill the same JTBD, but depending on a customer’s specific push, one may be better suited than the other for that customer.
Generating demand requires appreciating the interdependence between pull and push forces. Tesla succeeded by first creating pull for an electric car through an attractive high-end model before producing more affordable options.
Failing to consider pull, the Tata Nano’s low price did not generate demand because it lacked desired features and quality.
Both demand-generating and demand-reducing forces must be understood, as the latter can prevent customers from adopting solutions even if dissatisfied with current options. Anxiety and habits are two key demand-reducing forces.
The iPod was hugely successful for Apple, selling over 55 million units by 2008 and becoming one of the most successful products ever.
However, in 2007 Apple announced they were killing off the iPod with the introduction of the iPhone. This was a surprise since the iPod was their best-selling product.
The reason Apple did this was because they recognized that while customers’ needs and wants may stay the same, the solutions used to satisfy them will change over time with new technologies.
Jobs (what customers are trying to get done) remain constant, but solutions (products) come and go. Apple realized mobile phones would soon satisfy the same needs as music players, so they proactively developed the iPhone to replace the iPod before another company did.
This showcases how thinking in terms of Jobs vs. solutions allows companies to be prepared for and drive technological change, rather than just reacting to it. It allows planning for the transition from old to new solutions so customers’ underlying needs continue to be met.
Apple developed the iPhone starting in 2004, years before iPod sales peaked in 2008. This shows they did not create the iPhone in response to declining iPod sales.
Apple’s CFO confirmed they intentionally developed the iPhone and iPod Touch to cannibalize sales of their own iPods over time. This strategy is known as “cannibalization.”
The introduction of the iPhone did indeed kill iPod sales, as the graph shows iPod sales declining sharply after the iPhone launch while iPhone sales grew rapidly.
This type of strategic cannibalization was pioneered by Apple and goes against traditional business thinking, which is to protect existing top-selling products. However, it allows a company to dominate new markets before others enter.
Joseph Schumpeter’s theory of “creative destruction” helps explain Apple’s logic. New innovations inevitably replace old ones as customers’ needs change. By leading this disruption itself with the iPhone, Apple remained ahead of competitors.

So in summary, Apple consciously developed the iPhone to displace its own iPod sales long-term, a bold strategic move explained by theories of creative destruction and technology disruption. This allowed Apple to shape the new smartphone market before others.

Deming pointed out that firms like carburetor makers often improve the same product year after year without considering new innovations that could render their product obsolete. This leads them to be disrupted when a new innovation like the fuel injector is developed by others.
He predicted that the fuel injector would eventually be replaced by an even newer type of engine. This shows how solutions are constantly evolving due to creative destruction and competition between innovations.
Industries can be disrupted in unexpected ways when new innovations satisfy customer jobs/needs in a way that impacts other unrelated industries. For example, video conferencing technology hurt industries like travel, hotels and events.
JTBD theory shows that while solutions come and go, the underlying customer jobs/needs tend to remain more constant over time. So focusing on satisfying the job rather than a specific solution makes companies more resilient to disruption.
Successful innovators like Apple are proactive about disruption by replacing their own products before others can, as Apple did by transitioning from the iPod to the iPhone. This keeps the customer focus on the job rather than a particular solution.
Godrej, an Indian manufacturer, wanted to create an affordable household appliance for low-income Indians. They hired Clayton Christensen, who proposed making a low-cost refrigerator called the chotuKool as a “disruptive innovation.”
The chotuKool launched in 2008 but was a failure, only selling 15,000 units after 2 years. Godrej had to redesign, reposition, and relaunch it.
The main mistakes were that Godrej focused on developing a solution (refrigerator) before understanding customers’ needs. Their research showed customers didn’t feel the need for a refrigerator due to cost, space constraints, and reliability issues. But Godrej ignored these findings.
Following the “disruptive innovation” theory restricted Godrej’s view of competition only to other refrigerators, rather than considering alternatives like earthen pots that customers already used. This misunderstanding of the competitive landscape led to the chotuKool’s failure.
Theories like “disruptive innovation” oversimplify competition and don’t take a customer-focused approach to truly understand their needs and view of alternatives, as the Jobs Theory approach advocates. This caused Godrej to develop the wrong solution from the start.
Godrej, an Indian consumer goods company, tried to introduce an electric refrigerator called the “chotuKool” targeted at low-income rural Indians.
However, Godrej defined competition narrowly as other similar refrigerators, ignoring alternative solutions rural Indians were already using, like pot-in-pot vessels or buying vegetables daily.
Applying job-to-be-done theory, Godrej should have understood these alternatives as competition and that the chotuKool provided little value over existing solutions.
The chotuKool failed because rural Indians saw no need to spend $60-70 on it when free or low-cost alternatives worked well enough. This showed Godrej’s misapplication of disruptive innovation theory.
Similarly, personal computers were long considered to compete with and disrupt mainframe computers, but applying job-to-be-done analysis shows they actually served different markets and replaced different solutions. Mainframes remain highly profitable for specialized high-compute tasks even as PCs now dominate other domains. This highlights the importance of properly defining competition.
In the 1950s and 1960s, mainframes were large, expensive computers used mainly by large organizations for tasks like data processing and scientific calculations. They were operated by teams of “computer” operators and programmers.
Today, mainframes are still used for similar tasks like banking transactions, logistics systems, etc. Many of the same organizations rely on mainframes for critical operations.
In the 1980s when PCs first became popular, there was a misunderstanding that they were competing with and could replace mainframes. However, interviews with IBM executives at the time showed they saw no competitive relationship and viewed PCs as complementing rather than replacing mainframes.
Old PC commercials from the 1970s/80s never mentioned mainframes as a competitor or that PCs could do mainframe tasks. They positioned PCs as replacing products like typewriters, game consoles, etc. for productivity and personal use.
The rise of cloud computing in the 2010s saw some organizations like Johnson & Johnson fully migrate away from owning mainframes to using cloud services instead. But mainframe manufacturers like IBM are still highly profitable focusing on high-end customers.
In summary, while superficially similar as computers, mainframes and PCs have never really competed against each other due to their distinct uses in large organizations versus personal/small business productivity. The misconception of them as competitors came from a lack of understanding of their different roles.
Many bestselling business books that claim to provide recipes or formulas for innovation and business success have been criticized for being pseudoscientific and falling victim to logical fallacies. They tend to selectively highlight successful companies without providing objective evidence.
It is difficult to establish causation when attributing a company’s success to certain factors like culture or leadership. There are usually many small factors at play.
Innovation gurus who provide simplistic theories are essentially selling “cargo cult science” rather than rigorous scientific analysis. Their storytelling abilities can mislead people without scientific expertise.
One fallacy is “selecting the dependent variable” - only looking for evidence that confirms a predetermined theory while ignoring disconfirming evidence.
Properly defining competition is important for innovation but often overlooked. True competition comes from what customers will stop buying, not just products with similar features.
Innovators should talk to customers directly to understand competitive landscapes rather than make assumptions. They need to find evidence of customers directly switching from one option to another.
Many innovators overestimate that they are creating a new market, when existing solutions may already satisfy customer needs in alternative ways.
Understanding what budgets an innovation may take money away from helps assess revenue potential and guide investment decisions.
Competitive landscapes are dynamic so ongoing customer feedback is needed to refresh understanding of what truly competes to satisfy their underlying needs.
Omer Yariv was looking to create a new product at Transcendent Endeavors to help prevent adverse events in hospitals.
He used the Jobs-to-be-Done framework to focus on finding the customer with the strongest struggle/energy around the problem.
Through surveys and interviews, he determined that medical-surgical nurses struggled the most due to having to manage 4-5 constantly rotating patients each.
Key interviews looked for signs of emotional energy and frustration around their struggle to prevent adverse events.
Omer discovered nurses felt alone and liable for mistakes by others. They feared social and career consequences from adverse events on their watch.
This created strong motivation and energy among med-surg nurses to find solutions, signaling they were the best customer to focus a new product for preventing adverse events.

In short, by leveraging JTBD concepts like struggle, energy and system dynamics, Omer was able to zero in on med-surg nurses as having the strongest job needing to be done, setting the stage to create a useful product for that customer.

What’s the JTBD? The JTBD that Justin uncovered for Product People Club members was: Help me grow and track my business through expert advice and community support.

Members struggled with feeling isolated in their work and lacking objective feedback on their progress. They wanted a supportive community to help solve problems, share advice, and keep each other accountable to business goals.

Put it to work Some tips from Justin’s use of JTBD:

Start by observing how potential customers currently solve the problem on their own through online forums, consultations, etc. to identify pain points.
Conduct interviews to learn what frustrations members faced in existing solutions and how their ideal experience would look.
Brainstorm experiences, features, pricing that address the specific struggles identified in the JTBD.
Continually gather feedback from members as the product evolves to ensure it stays focused on solving the core JTBD problem.

The key is to deeply understand the problem from the customer’s perspective in order to design a solution that truly addresses their struggles and creates value.

Justin created Product People Club to help solo entrepreneurs who felt lonely and isolated working on their products independently.
He found this opportunity by observing patterns in the questions and struggles expressed by his audience of entrepreneurs. The two main struggles he noticed were loneliness and lack of motivation to actually build products.
To test if this was a valid opportunity, he created a simple chat room product for $10/month. It quickly sold out, showing there was demand.
To further understand customers’ struggles, Justin interviewed early members. He found their struggle was managing feelings of isolation when first starting a business alone at home.
Having the community and ability to connect with others facing similar challenges through Product People Club eased their anxiety and boosted confidence. It fulfilled their job to be done of helping them manage isolation as solo entrepreneurs working to build businesses.

In summary, through observation, testing and customer interviews, Justin was able to identify and deeply understand a specific struggle solo entrepreneurs faced, and create a solution in Product People Club to address that job to be done. This followed the key principles of job-based thinking to identify a real customer pain point and provide value.

Justin started learning more about his customers by observing them, conducting interviews and surveys, and reviewing customer emails. This allowed him to understand solutions customers had already tried like networking groups, online courses, one-on-one coaching etc.
Studying past solutions helped Justin understand what customers valued and didn’t value in solutions. He learned they wanted help reaching revenue goals and having independent income from their products.
Justin realized he could help customers track their progress towards goals with a new Product People Club feature. He also saw an opportunity to help with marketing/promotion after customers launched.
Justin’s understanding of customers’ struggles, both current and future, allowed him to continuously innovate and deliver more progress to them. His focus on jobs-to-be-done helps him anticipate new needs and problems customers will face.

The key points are that Justin deeply explored customers’ struggles, both present and future, to better understand their needs and pain points. This informed his innovation approach and allowed him to continuously improve his solutions to deliver more progress to customers over time.

Ash Maurya developed the Lean Canvas tool to help entrepreneurs avoid “innovator’s bias” and create business models through an iterative process rather than upfront planning. It provides a one-page template to test ideas.
Applying JTBD principles, Ash interviewed a customer from Chile who was using the Lean Canvas in an unexpected way to get a bank loan. This led Ash to re-examine why customers were using the product.
Interviews with new and canceled customers showed some saw it as a short-term tool, achieving their goal and then leaving. Others adapted it for internal product development work.
Ash chose to focus on the core job of helping innovators build business models, rather than catering to multiple smaller uses that could bloat the product. Narrowing the job scope allows delivering more value to key customers.

The key points are that Ash used JTBD to understand unexpected customer uses, discover potential new jobs, and decide to serve the primary job of business model creation rather than expanding into other areas.

Here are the key points about systems and the system of progress:

Understanding systems helps explain the interdependencies between customer demand and producer supply. Customers’ Jobs drive the need for products and solutions, which producers aim to satisfy.
The system of progress has four main parts: customers, their Jobs and struggles, the solutions/products created to help with those struggles, and the producers/innovators that create the solutions.
The system is powered by forces of progress like technology improvements, life changes, competition, and marketing/availability of solutions. These continuously shape customer needs and producer opportunities.
The system operates as a continuous cycle - customers have needs, producers supply solutions, which leads to new customer experiences and needs, and so on in an ongoing process.
The concept of viewing innovation through a systems lens is not entirely new, but the JTBD framework provides a clearer way to understand customer motivations, producer opportunities, and how the system generates demand over time through the forces of progress.
Analyzing innovation challenges through a system of progress perspective can yield insights into meeting customer needs and discovering new opportunities.
Systems thinking views problems and solutions holistically by considering how all parts of a system interconnect and influence each other. This approach transformed Japan’s economy in the 1980s and revived Ford Motor Company.
A key principle of systems thinking is interdependence - how elements within a system are connected and affect each other. For example, the widespread use of the pesticide DDT by US farmers unintentionally caused declines in bird populations due to bioaccumulation up the food chain.
Understanding interdependencies is important for innovation. Successful innovations meet customer needs by optimizing how different system elements work together, rather than just improving individual parts.
The passage outlines a “system of progress” model to analyze customer needs, solutions, and the relationship between customers and producers. It has four interconnected parts: the customer’s job/struggle, their search for and selection of a solution, using the solution, and realizing an improved life.
Forces like push/pull factors influence a customer’s movement through this system. The cycle is continuous, as solving one problem often reveals new struggles and needs. Understanding these interdependencies is key to successful innovation and meeting evolving customer demands.

The passage discusses how gaining new independence through achieving something like buying a first car could unlock new aspirations like being able to take weekend road trips. It suggests thinking about how to plan these potential new weekend road trips. Some things to consider in planning them might include deciding on destinations, figuring out transportation and accommodation logistics, making an itinerary, determining a budget, etc. Planning the road trips could help take advantage of the new found freedom and help achieve the goal of having fun and exploring new places during weekends.

Adding an extra feature, like a hole in the handle of a pan, does not necessarily help customers cook better on its own. However, it can help the pan integrate and work better with other complementary products, like a rack made by the same company. This increases the overall value for customers within the product system.
Businesses should think of themselves as delivering a combination of products that work together, rather than standalone products. When products integrate well as a system, it provides more value to customers and helps drive progress.
Major successes like the iPhone didn’t just rely on the product alone, but the whole ecosystem around it, like the App Store. As businesses evolve, they should look for complementary products and services that build on their existing solutions.
Providing options that help fill gaps or solve problems that come before or after a company’s core product in the customer journey can open up new opportunities. The system perspective helps identify these overlooked areas for innovation.
Customers’ stated wants, needs and preferences often do not reflect what will actually help them make progress or improve their situation. This is because customers are limited in their understanding of complex system dynamics and interdependencies.
Innovators should study how customers interact with and move through broader systems, not just focus on stated preferences. Understanding system dynamics and interdependencies is important.
Small changes to products or services may not actually improve the system if they don’t impact important interdependencies. True innovation sometimes requires systemic changes rather than tweaks.
Customer needs and wants will change as the systems they are part of change over time. What customers say they want now may be obsolete if systems change in important ways.
Examples are given of companies like Spirit Airlines, Apple, and early smartphone makers who did not just focus on stated preferences but changed systems in ways customers did not predict but ended up benefiting them.
Improving how customers interact with and progress through relevant systems, like via better information or tools, can increase adoption and satisfaction even without changing core products themselves.
Studying real customer behaviors within systems, not just words, helps identify leverage points for improving the system as a whole through innovation. Stated preferences are unreliable guides.
Change requires producers to adapt existing products or create new ones to address changes in the system. An example given is a software company adapting their game creation software to work on smartphones when that became a major platform.
When customers can no longer use their preferred solution due to a disruption, it forces them back to square one to find a new solution. This happened with real estate brokers and mortgage bankers when their relationship was made illegal, creating an opportunity for a new platform.
Systems have fragile interdependencies and are susceptible to cascade effects, exposing products to more risk of disruption. Examples include how damage to one satellite can cascade and destroy many others, and how a flaw in the Android operating system affected 900 million phones.
Fragile interdependencies, like a tight coupling between a software product and Adobe Flash, can drag down demand if the interdependent technology declines. Taking an integrated approach like Apple controls both hardware and software reduces this fragility compared to using a modular approach like Android.
Cascade effects within a system, like the multiple downstream impacts of the shift from film to digital photography, contributed to Kodak’s decline as the effects gained momentum over time. Smartphones created cascade effects across many systems through converging functions.

Applying JTBD top-down involves introducing the concepts to others in a leadership position, such as introducing it to one’s team as a founder or product manager. Key aspects include:

Being a practitioner of JTBD first before teaching others. This establishes credibility.
Insisting on doing customer research like jobs-to-be-done interviews before making major decisions like starting a new company.
Just practicing JTBD without explicitly labeling it as such, and separating data collection from data synthesis/interpretation to allow others to draw their own conclusions.

Applying JTBD bottom-up involves influencing peers and coworkers, such as creating an internal JTBD-themed meetup group or volunteer workshop. The key is to lead by example and create opportunities for hands-on learning and practice.

The competing for the consumer’s wallet not just with beverages and other impulse categories, but also with data services on smartphones.”80 refers to how companies providing consumer products and services now compete for spending/purchasing not just against similar product categories, but also against spending on smartphone data/connectivity plans and digital services since consumers access many offerings via their phones.

The person introduced JTBD principles to their team by having them join customer interviews at their company’s usability lab. This helped the team see the value in understanding customer struggles firsthand.
The person then gave a presentation to the wider company titled “Why People Fire Meetup” which showed photos of customers who stopped using the product along with quotes from them about their struggles. This generated ideas from the audience on how to address the problems.
The presentation was an effective way to introduce JTBD principles to the wider company without directly “selling” a new process. It focused on customer insights they had gathered through applying JTBD.
Local JTBD meetups and getting informal groups together are suggested as ways to learn from and share experiences with others interested in JTBD. The person offering assistance is also available as a resource.

The key takeaways are how the person introduced and gained acceptance for JTBD principles within their organization by focusing on actual customer insights and problems, rather than presenting it as a new process up front. Gathering data directly from customers through interviews was important to demonstrate the value of JTBD.

Honest offers a wide range of natural household and childcare products, including cleaners, detergents, soaps, diapers, wipes, etc. They aim to provide families with toxin-free products to create a safe home environment for children.
In addition to individual products, Honest offers subscription bundles where customers can choose bundles of related products like “diapers and wipes” or an “essentials” bundle.
The article describes two groups of customers who were struggling the most - new parents and parents with environmentally sensitive children. They felt overwhelmed by conflicting advice and unsure which products were truly safe.
When imagining life being better, parents described wanting to enjoy parenthood without worry and spend less time researching products. They wanted to reduce arguments with spouses over product choices.
Before Honest, customers mixed multiple brands and spent time seeking various advice. When they started using Honest products, they stopped those previous behaviors and hired the Honest brand to solve their struggles.
The subscription model helps customers develop habits using Honest products as a solution set touching on various parenting struggles, with each product like an individual software feature solving a piece of the job.

So in summary, it describes customers’ struggling moments in choosing safe products and how Honest positioned itself as a complete solution set to free parents from that stress and uncertainty.

Here is a summary of the key points about team from the passage:

A Job Story describes a specific situation or problem a customer faces (trigger/context), what effect they want from a solution, and how their life will be better if the problem is solved.
Well-written Job Stories address three important questions: 1) What is the trigger or problem? 2) What effects should/shouldn’t the solution have? 3) How will life change for the better once the problem is solved?
Job Stories come from talking to real customers to understand their contexts, anxieties, experiences with existing solutions, etc.
The same Job Story can apply to multiple different types of customers who experience the same struggles, even if they have different attributes.
Job Stories do not describe tasks, activities or solutions. They describe the situation and motivate what customers want from a solution.
A Job Story diagram can be used to visualize how different customer contexts and forces of progress shape the customer’s overall job/struggle that a solution aims to help with. It connects situations to the overall job.
The diagram is a communication tool, not a specification. It aims to develop a shared understanding of customer jobs and touchpoints, not prescribe what to build.

So in summary, Job Stories provide important customer context to understand their problems and needs, and help connect specific situations to an overall job or struggle that solutions can help solve.

Here is a summary of the key points about hiring criteria and understanding customer data from innovation perspective:

Hiring criteria help connect customers’ struggles or jobs to be done to the solutions they choose. Just like hiring criteria in job searches, customers have certain criteria they look for in solutions.
Hiring criteria explain why customers choose different solutions for the same job to be done. Customers’ context and struggles shape their hiring criteria and priorities.
Hiring criteria show where trade-offs happen between solution attributes. No solution fulfills all criteria perfectly.
Good data is needed to understand hiring criteria and customer perspective. But large samples and triangulation don’t guarantee good data - it could lead to false conclusions.
Special cause variation (due to unique circumstances) needs to be differentiated from common cause variation (underlying customer preferences) when analyzing customer data.
Investigative methods for customer data should be selective and based on just cause. Quantitative data needs to be balanced with qualitative customer insights.
Hiring criteria act as a bridge between customer struggles and their consideration and choice of solutions in the “system of progress”. They help visualize how customers match jobs to solutions.

In summary, hiring criteria are a useful lens for innovators to understand customer decision making, but care needs to be taken to gather and interpret data correctly to avoid false assumptions. Both quantitative and qualitative data in appropriate amounts are important.

People tend to assume more data is always better, but this is not always the case, especially for understanding customer motivation and behavior.
Nature has bounded limits on variables and their interactions, so more data on natural systems usually provides clarity. However, customer motivation has practically unlimited variables that interact in complex and undefined ways.
As more data on unnatural systems like customer motivation is collected, variance increases nonlinearly compared to valid data. Spurious relationships are found more than authentic ones.
Innovation requires understanding how to change a system, not just study it as it currently exists. Collecting only relevant data related to the problem is better than accumulating all available data.
There are common cause and special cause variations. Common cause is normal day-to-day variation, while special cause comes from external factors. Innovators need to distinguish these to know when action is needed.
Personas that include superficial demographic data risk mixing common and special causes, obscuring insights. Actual usage data often shows more similarities than differences across groups.
it is better to use a few high-quality investigative methods consistently rather than many mixed methods, to limit collecting useless versus useful customer data. Restricting methods helps reduce bad to good data ratios.

The passage warns that collecting data without clear justification or purpose can lead to making changes that don’t actually improve the business and may even make things worse. It’s only worthwhile to investigate if you have “just cause”, which includes reasons like monitoring for issues, developing new products, understanding why customer usage is changing, or suspecting inefficiencies.

The methods used should focus on “revealed preferences” like what customers actually do rather than stated preferences of what they say. It’s better to understand the real reasons for changes in behavior. The data gathered should relate to customer struggles, how they imagine improving their situation, and trade-offs they are willing to make.

The customers investigated should be those exhibiting problems, like those who recently started or stopped using the product, to understand how to improve acquisition or reduce churn. Random samples won’t provide useful insights - the goal is actionable data to increase revenue.

Customer interviews are the best way to gather job-to-be-done (JTBD) data to understand customer needs and pain points.
Entire books are dedicated to effective customer interview techniques, so this chapter only provides a high-level introduction.
The topics covered are: basic structure and intent of interviews, types of questions to ask, models/frameworks that can be used, and a more general interview approach.
Customer research should focus on struggling customers and gather data on what they do/don’t value, their struggles, and how their lives could be improved.
Observational research techniques like ethnography are not recommended as they study customer habits, and habits change the brain such that it is less insightful for innovation purposes.
The brain is more active and insightful in its “sense-making” stage before habits are formed, so innovation work should focus interviews on understanding customer motivation and gathering strategic insights, not just observing current behaviors.
Customer case research (CCR) involves interviewing customers to understand their motivations and decision-making process, rather than just relying on what they say in surveys. It aims to uncover revealed preferences versus stated preferences.
Interviews should focus on changes in behavior, not just purchases. For example, stopping use of a product or using it more/less frequently. These indicate special causes for investigation.
The purchase timeline model structures interviews around key moments in a customer’s journey from realizing an issue to purchasing a solution. It helps identify jobs, events, decisions, and evaluations.
A more general timeline model focuses on the transition from an old habit to a new one, for any behavior change. It looks at triggering events, sensemaking, solution analysis, committing to change, expectation matching, and forming a new habit.
Both models provide structure but can be adapted. Experienced interviewers may not need models. The goal is to understand the customer’s perspective and reasons for changes in order to ensure the system is operating as intended.

Here are the key points about creating insights from job stories and customer interviews:

Analysis involves breaking things down into parts and studying the individual pieces, while synthesis focuses on understanding the whole purpose/system and how the parts work together. Both are useful but synthesis is more important for insight creation.
When analyzing data, it’s easy to focus too much on the individual details rather than synthesizing them into overall patterns and themes. Combining analysis and synthesis through the OSEMN framework can help avoid this.
There is no single “right” way to create insights - it depends on the goals of the research, how the findings will be used, and how the organization prefers to receive insights. Experience and trial/error are the best teachers.
Important not to rely too heavily on subjective judgments. The data should guide the insights rather than personal preferences. But subjectivity plays a role in how the data is gathered and synthesized.
The goal is to understand jobs to be done, pain points, and factors that create customer progress - not just describe individual experiences or parts of the system. Insights need to synthesize an understanding of the whole job/system.
Examples show how analytical thinking can miss the “why” if it just breaks things down without understanding the purpose and dynamics of the whole system/job. Synthesis is key to deriving meaningful insights.

In summary, properly synthesizing all the data into insightful patterns about jobs, pain points and progress factors - rather than just analyzing individual details - is important for effective insight creation from job stories and interviews. A combination of analysis and synthesis is generally best.

In the early 1980s, Ford cars cost more but performed worse than Japanese cars like Toyota. Ford engineers analyzed individual car parts but did not understand how the parts interacted as a system.
Each Ford part was engineered to high quality standards, but the parts were not optimized to work well together as a system. This led to cars that underperformed despite higher costs.
Intercom created software to help businesses interact with customers. It added a map feature that businesses enjoyed showing off. However, customers used the map more for impressions than accuracy.
Rather than improving map accuracy, Intercom made the map easier to share on social media. This made the map less accurate but increased customer usage and enjoyment.
The key lesson is that the whole system is more than just the sum of its parts. Ford focused too much on individual high-quality parts without considering interactions. Intercom improved customer experience by making the map worse at its intended purpose but better for an unexpected customer use case.
To truly understand customer needs, one must take a synthetic approach looking at the whole system and customer journey, not just analyze individual parts through functional decomposition.

Here is a summary of the key points from the chapter “Putting JTBD to Work”:

Ask customers about what they’ve done, not just what they want. Confirm their past experiences if possible.
Learn how customers view competition by asking the right questions.
Identify the specific emotional motivation or “job to be done” customers are seeking to accomplish.
Determine which existing budgets or expenditures a new product might displace or replace.
Create better marketing by speaking directly to customers’ jobs and motivations.
Focus on delivering emotional progress and outcomes, not just functionality.
Frame product challenges in terms of jobs to get buy-in from teammates/management.
Dig deeper into struggles customers face and how they’ve tried to solve them before.
Consider if anxiety is acting as a competitive force and find ways to reduce it.
Be skeptical of the idea of “impulse purchases” - there is no truly random decision.
Conduct JTBD research together as a team for better insights, motivation and consensus.
Study the “push and pull” factors influencing customer decisions and habits.
Investigate habits and anxieties customers have after identifying jobs.
Don’t rely solely on demographics; understand what customers truly value.
Create better advertising by speaking to those values revealed through JTBD research.

Here is a summary of the key points about push and pull marketing strategies:

Push strategies involve directly promoting and advertising products to drive customer awareness and demand. This can reduce customer anxiety by helping them visualize the progress/benefits of using the product.
Pull strategies focus more on addressing customer pain points and struggles directly. This can involve product trials, refunds, discounts to reduce anxiety around choosing a product.
For pull to work best, products need to address any habits or issues customers currently face in using competing products. The product needs to help customers along in addressing their underlying job-to-be-done.
Innovation opportunities are found by deeply understanding customer struggles, pains, and motivations. Offering a system or portfolio of products that work together to deliver progress on customers’ key goals and jobs-to-be-done.
Great advertising comes from speaking directly to customers in the moments they are struggling and need help progressing on a key job or goal. This taps into pull by addressing core customer motivations.
The chotuKool mini refrigerator was celebrated by Godrej before any units were sold. However, it ultimately failed in the market. Comments echo that disruptive innovations from large corporations often fail where grassroots innovations from the communities they aim to serve often succeed.
Navroze Godrej’s comment about the chotuKool becoming a lifestyle product and G. Sunderraman’s comments about targeting mid-level buyers and not expecting the poor to be the “pot of gold” are referenced.
Alternative solutions to the chotuKool like the MittiCool are mentioned as examples of successful grassroots innovations.
The sources and context for the various quotes are outlined, mostly coming from case studies and articles about Godrej and the chotuKool.
In summary, it discusses Godrej’s failed attempt at disruptive innovation with the chotuKool mini fridge and contrasts that with arguments that grassroots innovations from within communities tend to be more successful at serving those communities’ actual needs.

Here are summaries of the articles and resources:

(5) Nassim Nicholas Taleb discusses the distribution of p-values and how they are often misinterpreted due to overfitting. P-values alone don’t tell the whole story about statistical significance.

(6) Donald Geman, Hélyette Geman, and Nassim Nicholas Taleb propose using tail risk constraints based on entropy maximization as an alternative to traditional linear constraints in statistical modeling to better account for rare events.

B. Duncan’s and Scott Fortmann-Roe’s articles provide a good introduction to the concepts of overfitting, underfitting, and the bias-variance tradeoff in machine learning models. There is a classic curve that plots bias and variance against each other.

Shewhart originally called variation in processes “chance causes” and “assignable causes”. Deming renamed these to “common causes” and “special causes” to make the concepts easier to understand. He used the example of buses running late or early due to common vs. special causes.

Paul Adams describes how persona stories were accidentally invented at a company to help communicate insights about user research in a more engaging way.

#book-summary