Competing Against Luck


Clayton Christensen

Progress not problems

  • Customers don’t have problems, they struggle to make progress

  • theory helps understand the how and why instead of trial and error


  • quantitative data doesn’t tell you about the situation customers are in

  • nor does it tell you why they chose one product over the other

Situation and circumstance

  • situation and circumstance have more of an effect on whether your product or service can help a customer make progress

  • don’t use a bicycle in a motor race

  • something that’s well designed for one situation can be a total failure in others

  • the context of the situation matters

Progress, not products

  • A Job is defined by the progress people are trying to make in particular circumstances

  • Jobs have inherent complexity

  • Jobs include the functional, social, and emotional forces that cause people to make tradeoffs when making choices

  • great innovation insights come through depth, not breadth


  • helps you understand the cause and effect of the choices customers make during their struggle

  • deconstructing complex experiences into binary data destroys meaning that allows us to understand the causal mechanism

  • jobs is about clustering similar stories instead of segmenting details

  • there’s always more than one solution to a Job, including taking no action

  • circumstance actually changes the competitive field

  • blue ocean strategy (don’t compete on features, compete for different situations)

  • build the right set of experiences in how customers find, purchase, and use your product

  • non-consumption is often the biggest competitor

Negative Jobs

  • this is when someone wants to make progress by not doing something

  • fruitful situation to explore

Job Hunting

  • enabling something new can often be more valuable than producing something new

  • uncovering jobs adds narrative – language and causality

  • tells you which pieces of information are needed, how they relate, and how they can be used create value

  • in order to hire a new solution, by definition customers must fire the suboptimal solution or compensating behaviour

  • this includes doing nothing

Loss aversion

  • the forces compelling change must outweigh the forces opposing change for a customer to switch

  • people’s tendency to want to avoid loss is twice as powerful as the allure of gains

  • it’s rare for people to be able to articulate what they want, but they can tell you about their struggles

Big and little hires

  • big hire: The moment you buy a product

  • little hire: The moments you actually use the product

  • failing in Little Hire moments pushes people towards a new solution

Product versus experience

  • businesses succeed because of the experiences they enable

  • not the features and functionality the business offers

  • rare that the product itself is the source of long-term competitive advantage


  • consider who shouldn’t use your product to avoid a mismatch in expectations

  • you can lose an understanding of the job when trying to add new benefits and features


  • if you can’t describe what you are doing as a process, then you don’t know what you are doing

  • processes can’t be seen on a balance sheet

  • processes are much harder for competitors to reverse-engineer

Evolve how you solve the job

  • make it work

  • make it good

  • make it cheap

  • make it good and cheap

Active vs passive data

  • passive data is soft or in the context of the struggle (qualitative)

  • active data is easy to track, feels real (quantitative)

  • mistaking the model created by active data for the real world of passive data is poison for innovation

Surface growth

  • inclined to sell more products to existing customers, leading them to lose focus on the job that brought them success in the first place

  • several competitors who focus only on one job, as you expand you find you’re not the best at solving any job

Confirming data

  • healthiest mindset for innovation is that nearly all data is built upon human bias and judgement

  • models compared to real world

Job focused organization

  • what get measured, gets done

  • this is only useful if what’s being measured is helping the customer make progress

  • jobs provide a compass for how to shape solutions but is also a filter for what not to do

Theory of jobs

  • a job is a construct

  • an abstraction that’s rarely directly observable

  • it’s intentionally precise and there are boundaries to the theory

  • not everything that motivates us is a Job to Be Done

  • well-defined jobs are expressed in verbs and nouns, not adjectives and adverbs

  • not at the right level of abstraction and you’re not uncovering a job if only products in the same class can solve the problem