Value Target Analysis — Part 3

The Value Target Framework

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The Value Target Framework is a synthesis of the jobs-to-be-done concepts suggested by Christensen (2016a) and Ulwick (2016) as well as other contributors in the fields of entrepreneurship, marketing, economics, and psychology. In the following sections, we lay out the concepts and working components of this framework which consists of:

  • Jobs-To-Be-Done Concepts
  • The Progress Map
  • Value Targets
  • Moments of Struggle

Jobs-To-Be-Done Concepts

Individuals make progress in their lives and businesses to the extent that they are able to take the necessary job action to obtain or achieve desired results and to avoid unwanted results. These wanted and unwanted results are the customer’s success outcomes. For any customer job, three kinds of success outcomes are possible — functional, emotional, and social. A functional success outcome is a tangible or objective result of job action and, as such, can be observed and measured. An emotional success outcome is a subjective result of job action that has to do with how a person wants to feel or doesn’t want to feel. A social success outcome is a subjective result of job action that has to do with how people want others to perceive them or not to perceive them. Most jobs are associated with some combination of functional, emotional, and social success outcomes.

People and organizations execute jobs by means of job solutions — combinations of resources that together enable them to take the necessary job action to generate their success outcomes. Job resources can be products and services provided by companies as well as other kinds of non-provider resources such as data/information, knowledge, skills/abilities, forms of assistance from other people like friends and family, government allocated resources (money, rights, services, and so forth), and natural resources (water, animals, land, wind, sunlight, and inorganic and organic materials).

Because people and organizations have limited time, energy, money, and other resources to execute jobs and virtually unlimited jobs to get done, they seek out job solutions that minimize the use of those resources. But they also want job solutions that effectively generate their success outcomes. At the extremes, efficient job action that fails to generate success outcomes is useless. Job action that effectively generates success outcomes via inefficient job action is not practical. Thus, it can be said that any job executor desires job action that is both efficient and effective. We call this job economy, and it is the driving force that continually compels customers to seek out job solutions they perceive to be the best value for getting jobs done

Customers’ experiences using any job solution are positive to the extent that they perceive the solution is relatively efficient in terms of the time, effort, and resources they have to put into job action and how effectively job action generates their success outcomes. A job solution that is very efficient but falls short on success outcomes is a poor experience. Likewise, a job solution that generates the expected success outcomes but involves investing too much time, effort, and resources into job action is also a poor experience.

The Progress Map

Because the universal goal of all people and organizations is job economy, everyone wants to execute any job as an ideal process that produces the best overall experience. When job execution is delineated in a way that is agnostic or independent of any job solution or job circumstance, it defines this ideal process — which is common or universal to all job executors (Bettencourt, 2008). An ideal job process is comprised of a number of logical steps that must be accomplished to generate the customer’s success outcomes, and it represents what we call the logic of progress.

A Progress Map delineates the logic of progress for a particular job and is generic or universal in nature because it makes no reference to:

Job circumstance — situational and motivating factors relating to job execution or job execution contexts.
Job solutions that could be used to get the job done.
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Since people and organizations buy and use job solutions they perceive to be the best value out of competing solutions, they must use some kind of criteria to evaluate these solutions. Once a Progress Map is delineated for a particular job, then it’s possible to define what customers want to happen and don’t want to happen at each job action step and the success outcomes they expect to generate. These are the customer value metrics (CVMs) that characterize the value customers want when they execute a job. As such, customer value metrics are the critical performance dimensions of job execution that determine the overall customer experience (Bettencourt, 2008). For this reason, CVMs are the basis for how people and organizations gauge the job economy of any solution.

One or more CVMs are associated with each job action step (job action CVMs), and they define value in terms of job action efficiency — the amount of time, effort, and use of resources required to accomplish each step (Bettencourt, 2010). Success outcome CVMs define value in terms of job action effectiveness — the extent to which expected functional, emotional, and social success outcomes are generated by job action. These metrics are the criteria used to evaluate satisfaction with current solutions-in-use and to compare the value of competitive solutions-in-use. Customer value metrics ultimately determine which solutions get hired to get jobs done and which solutions get fired.

To summarize, a Progress Map:

Defines the success outcomes that all job executors expect by taking job action (although these may be prioritized differently among job executors).
Defines the ideal job process as a series of job steps that all job executors must accomplish to obtain or achieve their success outcomes.
Defines the customer value metrics that characterize the value customers want when they execute a job (although these may be prioritized differently among job executors).
Makes explicit how job action metrics predict success outcomes (key value indicators).

Because a Progress Map is universal in nature, it is relevant to any individual or organization trying to get that job done regardless of its unique characteristics, attributes, circumstance, or the solutions it currently uses or could use to get the job done. Delineating the universal logic of progress for a customer job is useful to innovators because:

Overlaying a customer job segment onto a completed Progress Map reveals how a customer’s unique job circumstance prevent a job from getting done well or at all.
It enables innovation teams to quickly establish relationships between job circumstance and dissatisfactions with solutions-in-use.
It makes apparent what competitive solutions certain customers may evaluate and ultimately hire to get the job done based on their common job circumstance. Knowing the solutions that your product/service competes with from the customer’s perspective is crucial for guiding innovation efforts (Christensen, 2016).

Progress Map Elements

Job action steps together represent the ideal process flow for getting a job done. This differs from a customer journey map that depicts what an individual or “customer persona” is doing as he/she uses a particular job solution. Job action steps, on the other hand, represent what all job executors must accomplish to successfully get a job done (Bettencourt, 2008).

Because it’s easy to confuse job action steps with the activities and tasks associated with solutions, we use two validation criteria to distinguish the difference:

  • A job action step must be necessary for any person or organization to successfully execute a job, not just some solutions. If there is a person(s) or organization(s) that does not have to accomplish a step to successfully execute a job, then it does not qualify as a job action step (Bettencourt, 2010).
  • A job action step must be necessary for all solutions that could be hired to execute a job, not just some solutions. If there is a solution(s) that does not have to accomplish a step to successfully execute a job, then it does not qualify as a job action step (Bettencourt, 2010).

The core action step generates the customer’s success outcomes. The job steps before the core step represent what must be accomplished to enable the core action step; otherwise the core action step can’t be done. The job steps after the core action step represent what must be accomplished to ensure that the core step was accomplished and can be repeated (Bettencourt, 2008). Thus, all steps before and after the core action step are subordinate, thus the term “core” action step.

Step contenders are potential job action steps. Multiple action step contenders may be proposed before an action step emerges that can meet the two validation criteria.

Customer value metrics (CVMs) are the dimensions of value associated with job action steps and success outcomes that collectively represent the value customers want when they execute a job. As such, customer value metrics are the critical aspects of job execution that determine the overall customer experience.

  • Job action CVMs are associated with each job action step and define value in terms of job action efficiency — the time, effort, and use of resources required to accomplish each step. They are directional metrics expressed as either reducing or increasing something relating to job action. For example: “Reduce the time it takes to check out,” “Reduce the time it takes to find the desired item,” “Reduce outdated information,” and “Increase the number of patrols in my neighborhood.” Job action metrics predict the satisfaction of success outcomes.
  • Success outcome CVMs define value in terms of job action effectiveness — the expected functional, emotional, and social success outcomes generated by job action. They are expressed as desired or unwanted occurrences and states. For example: “Avoid getting the flu” (unwanted functional occurrence), “I feel good about my smile” (desired emotional state), “I am respected for my expertise” (desired social state), “I don’t want to be embarrassed in front of my friends when such and such happens” (unwanted social state). Success outcomes are key value indicators that are predicted by job action metrics. As such, increasing the level of satisfaction for success outcomes can only be done by scaling in one direction or the other the job action metrics that predict their satisfaction.

Value Targets

Individuals are asked via interviews or a Web survey to rate how important each CVM is to them and how satisfied they are with that dimension of value vis-à-vis the solution-in-use. An analysis of these ratings results in a set of value targets for a customer segment that filter into one of four categories — undershot value targets, overshot value targets, must-be value targets, and indifferent value.

Undershot value targets are the customer value metrics that have been rated by a vast majority of interviewed customers as very important and not well satisfied by a solution-in-use. Undershot value targets indicate job action steps that consume too much time, effort, and resources and success outcomes that fall short of expectations — often referred to as customer pains, hassles, and disappointments that lead to a poor experience. These are dimensions of value that are not yet good enough and, as such, are the basis for customer priorities. For this reason, undershot value targets unequivocally indicate the additional value that customers seek from solutions to get a job done better.

If the undershot value of a particular solution-in-use reaches a certain dissatisfaction threshold, the push for job economy motivates customers to seek out another product/service that will satisfy their priorities. This push is an opportunity for some companies and a threat to others. For a company that can provide superior value, this is a big opportunity to pull dissatisfied customers away from an undershot competing solution-in-use to their product/service. If the undershot solution-in-use is your company’s offering, then this opens the door to competitors to pull your customers away — a perilous threat. Thus, undershot value drives the “energy” for demand creation. When the push of dissatisfaction meets with the pull of superior value, demand creation occurs on the winning side and demand destruction occurs on the losing side (Moesta & Spiek, 2014).

Overshot value targets are the customer value metrics that have been rated by the vast majority of interviewed customers as having little importance and are over satisfied by solutions-in-use. Beyond a certain point of satisfaction, customers cannot utilize additional value. Thus, overshooting increases the cost structure of a solution without increasing customer value. By scaling back the overshot features and benefits of a solution:

  • Resources can be better utilized to satisfy customer priorities (undershot value).
  • The profitability of the solution can be increased by reducing its cost structure.
  • The selling price of the solution can be reduced. A cost structure that is significantly lower than competitive solutions is an advantage since the selling price can be reduced without significantly eroding profit margin.

If an existing solution has enough overshot features and benefits, this can signal a disruptive innovation threat if the solution is your company’s offering. Conversely, this situation can signal a disruptive innovation opportunity if the solution is a competitive offering. The phenomenon of disruptive innovation follows a familiar pattern. Customers initially ignore overshot features and benefits. At some point, the overshot features create hassles for certain customers. The company increases the selling price of the solution to offset the costs of added features and benefits. Now the company has unwittingly made it harder and more expensive for certain customers to get a job done using their solution. As a result, these customers devalue the product/service and switch to a simpler and cheaper solution. This is the classic disruptive innovation scenario that is precipitated by overshooting (Christensen, 2016).

Must-be value targets are the customer value metrics that have been rated by the vast majority of interviewed customers as important and appropriately satisfied by solutions-in-use. Although these aspects of job execution are not a priority, satisfaction is expected on these CVMs at current levels. If these dimensions of value become less satisfied for whatever reason, they quickly become a priority. However, once satisfied, increasing the value of these CVMs will not increase the customer value of a solution, though the cost structure of a product/service will likely increase (Kano, 2003).

Because the customer value of a solution will decrease to the extent that customers are dissatisfied with these CVMs, they are the table stakes that must be met just to remain viable in the market. This is why these are called “must-be” value targets. Products and services that do not satisfy this expected value will suffer the consequences as customers will quickly devalue such offerings. The appropriate action is to maintain current satisfaction levels for these CVMs at the least possible cost (Witell, Löfgren, & Dahlgaard, 2013).

Indifferent customer value metrics have been rated by the vast majority of interviewed customers as having very low importance and very low satisfaction by a solution-in-use. At first glance, this doesn’t make much sense. After all, if the importance of a dimension of value is very low, then why is satisfaction even relevant? Stated a bit differently, customers aren’t sure or they’re not aware of how a product/service can help them get certain aspects of a job done. For this reason, they do not expect a solution to help them with these job aspects, and this translates to low importance and very low satisfaction on the rating scales for these CVMs (Kano, 2003).

We suggest that this can be explained by the fact that customer value is relative to what is possible at any given time via current solutions. Although customers are quite aware of the jobs they are trying to get done and their moments of struggle, they seldom know the best ways to get those jobs done in terms of solutions. Because customers are not professional innovators, they are not aware of the solutions that might be possible with a combination of available technology, design methods, and business models. This is the purview of companies to innovate job solutions for customers. Customers simply gauge value based on what they perceive is possible today via available solutions (Ulwick, 2005).

As technology and design advances, new solutions become available that can satisfy indifferent dimensions of value in ways that were not previously possible. We think of this area as having latent job value because potential value could take form at any time when the right resources come together. Just consider the progression from the portable CD-ROM music player to streaming music directly from Internet-based services. The portable CD-ROM player was the dominant design of the day. The exploitation of latent job value resulted in an entirely new dominant design, and it has been the solution paradigm ever since. Once it becomes apparent that an indifferent customer value metric can be better satisfied, it suddenly becomes undershot (Kano, 2003).

Indifferent value increases in importance because the additional value that it represents enables customers to get a job done better in ways they hadn’t considered before. When customers recognize what is possible, they want full satisfaction along those dimensions of value. A product/service that can satisfy indifferent value offers exciting features and benefits, or what the Kano model of customer satisfaction calls “delighter” attributes (Kano, 2003). Some contemporary tools/methods refer to this unexpected value as customer “gains.” Apple Computer became one of the largest and most successful companies in the world by turning latent job value into undershot value and then satisfying that undershot value better than competing alternatives.

The appropriate action is to either find a way to increase the importance of indifferent customer value metrics or minimize the cost associated with these CVMs until a way can be found to increase their importance. We suggest this is an area of emerging opportunities and should be carefully monitored and frequently discussed. Product teams should continually challenge themselves to find practical ways to satisfy indifferent value because it can be a real game changer. For example, satisfying indifferent value can re-invigorate a mature or commoditized product/service, increasing its market share and profitability.

Moments of Struggle

Even though people and organizations are trying to get the same job done, they can differ in the value they want from solutions to get that job done. The reason is that job circumstance causes certain customers to place more priority on some customer value metrics (CVMs) and less priority on other CVMs. Specifically, job circumstance consists of:

  • Situational factors — performance of a solution-in-use, job constraints (obstacles, barriers, compensating behaviors), unsatisfactory trade-offs (time, effort, resources, values, risk, success outcomes), and macro factors (events/occurrences, internal conditions/states, policies, compliance).
  • Job contexts — the time, the place, with or without whom/what the job is executed.

Job circumstance can cause customers to become dissatisfied with their ability to perform particular job action steps and/or to achieve particular success outcomes. They are not able to make the desired progress. Some individuals experience “pains” with a particular solution-in-use at certain job steps. Because these steps require too much time, effort, or resources, these individuals will want more value from a solution at those points in order to get the job done more efficiently. Likewise, if certain success outcomes fall short of what is expected, the individual will want more value from a solution to get the job done more effectively.

Undershot CVMs indicate where customers struggle to get a particular job done. We call these problematic aspects of job execution moments of struggle (MoS), and they collectively determine the level of dissatisfaction with a solution-in-use. To put a finer point on it, a moment of struggle is a problem caused by a job circumstance that customers experience when trying to get a job done with a particular solution-in-use. Moments of struggle prevent customers from getting a job done well. An undershot CVM indicates a moment of struggle and serves as the basis for how customers evaluate the performance of a solution at a certain point in job execution vis-à-vis the ideal job process.

Customer value metrics are used internally by companies to inform product/service design so that they can create customer demand for their offerings while also generating a healthy profit. However, customers don’t go around thinking about CVMs. They don’t know about them or that companies use them to define the value that customers want. Rather, a customer’s world centers around solutions-in use. No matter the job, all individuals around the world are using some kind of solution to get that job done. For example, all people eventually need to wash clothes (a safe assumption). In certain areas of the world, individuals get this job done by using a river and some rocks (a non-provider job solution). Other people get this job done via a washer machine (a provider solution). Preparing and eating a meal is another example of a job that everyone must do one way or another. Thus, all jobs are getting done with a solution-in-use.

When customers struggle to get a job done, they want more value from a solution-in-use to resolve the moments of struggle that prevent them from getting the job done well. If they can’t get that value from the solution-in-use (i.e., a river and rocks or a laundromat), then customers are compelled by job economy to seek out other solutions that can provide the desired value, assuming there are other solution options available. Thus, it is dissatisfaction with a solution-in-use and the additional value that they seek in a solution that motivates their behaviors. These wants are customer priorities and they push individuals to search for, evaluate, fire, and hire job solutions (Woodruff & Gardial, 2008). Customer priorities provide the push motivation or “energy” that sets the stage for demand creation. When enough push energy meets the pull of superior value (a better solution), customers are compelled to hire a new solution (demand creation) and fire the solution-in-use (demand destruction) (Moesta, 2014).

To recap, job circumstance causes moments of struggle, which then drive customer priorities. Because undershot CVMs indicate MoS, they predict the customer priorities associated with these MoS.

Customer priorities are oriented around solution features and benefits — not value targets. If you were to directly ask individuals what they want, they will likely communicate customer priorities that are driven by various dissatisfactions with a solution-in-use. If this kind of customer feedback is accepted as the “voice of the customer,” this will constrain the focus of innovation to solution enhancement — adding, eliminating, or improving on the features and benefits of a solution-in-use. Value targets, on the other hand, focus efforts on combining and/or integrating existing and untapped resources into the best configurations or best solutions that maximize customer value at the lowest possible cost. Value targets drive effective innovation, whereas direct customer feedback does not.

Why Companies Undershoot and Overshoot Customer Value

Companies often undershoot and overshoot the features and benefits of their products and services due to ambiguity around what different customers value. One reason for this is that conventional customer segmentation methods group customers based on a combination of demographic, psychographic, and behavioral data because this data is readily available and conveniently analytic. The data has to do with the attributes or characteristics of the customers themselves, not the jobs they are trying to get done. This is problematic because customers’ buying behaviors change a lot more frequently than their personal characteristics.

The fact is that customer characteristics are poor indicators of customer behavior because the data does not reflect why customers make the choices they do. Although attribute data may correlate with customer choice after the fact, the data can never really predict what products and services customers will prefer (Christensen & Raynor, 2003; Christensen et al., 2005).

Conventional segmentation schemes use attribute data to define the average customer, a necessary fiction to target the needs for a segment. However, customers’ buying decisions do not necessarily conform to those of the “average” customer. Statistically, there will always be significant variation in attribute data because the data are normally distributed for any given customer population. This means that innovation efforts to satisfy the needs of the average customer will undershoot some customers and overshoot others.

The greater the variation in attribute data around the average customer, the greater the undershooting and overshooting problem. For this reason, innovation efforts that rely on attribute-based segmentation schemes will be hit or miss. Successful innovation requires much more precision than this.

Job-based Segmentation

A more effective approach for the purpose of creating customer demand is to segment customers around the jobs they are trying to get done. Job-based segmentation uses job circumstance as the primary basis of segmentation because this is what ultimately drives customer behavior. Attribute-based data is used as a secondary basis to create job executor personas. Segmenting around a job to be done is a more precise way to characterize the value that customers want because they are grouped based on common job circumstance. Because of this, the customers’ perception of value is highly uniform and therefore will not vary significantly within a job segment.

Once job circumstance is understood for a group of customers, an innovation team can predict what products/services these customers will prefer to get a job done today and well into the future. Further, the team can anticipate how changes in customer circumstance could change the customers’ perception of value and how such changes could, in turn, affect customer choice. This kind of predictive power gives a company a significant advantage over competitors because they can anticipate the value that customers want — even before customers know what they want. With this knowledge, a company can enhance their existing products/services and create new products/services that offer superior value relative to competitive solutions.

Competitors that cannot anticipate the value that customers want are left to scramble in reactive mode, causing them to reach the market late with inferior offerings. Many of these competitors adopt “fast follower” strategies aiming to free-ride on successful innovations. However, such competitors usually get shaken out in the early stages of the value lifecycle because they cannot generate enough total value (customer value plus profit) to remain viable in the market.

Continue to Part 4: Apply the Methodology


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