Literary Insights

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Here is a summary of the key points from the book “What Customers Want”:

The book argues that companies should move beyond simply being “customer-driven” and focus more on understanding customer “outcomes” - the jobs customers are trying to do and the results they want to achieve.
It advocates capturing customer input on outcomes, constraints and trade-offs rather than just product requirements. This allows companies to better understand unmet needs and prioritize opportunities.
Methods like outcome-based market segmentation and focused brainstorming are presented as ways to generate breakthrough concepts that create real customer value.
The concept of “value migration” over time is discussed - as outcomes improve, customer requirements change. This impacts opportunity identification and competitive analysis.
Prioritizing projects using a “customer scorecard” to evaluate concepts based on how well they fulfill customer outcomes and jobs is recommended.
Strategies around messaging, positioning products, targeting growth opportunities, and handling multiple stakeholders are discussed through an outcomes lens.
The book aims to provide companies a more systematic, predictable process for customer-centered innovation and new product development.
The author thanks the iniarski team for their valuable contributions and improvements to the innovation process, which have accelerated its evolution. Special thanks are given to Sandy Bates and Andrew Johnson for their editing efforts.
As peers, Matt Eyring, Mark Johnson, and Scott Anthony have provided friendship, support, and a rewarding partnership. The author wishes them ongoing success.
The deepest gratitude is expressed to the author’s son Anthony and wife Heather for their sacrifices to allow the book to be written, including sharing his joy, patience, and encouragement.
Over the past 20 years, the author has met many insightful, motivated and brilliant people who have taught him about innovation. He thanks all who have made this a joyful and meaningful experience.
The introduction argues that while customer-driven thinking is now standard, innovation success rates remain low at 50-90%. A new approach is needed to reduce variability in the innovation process and achieve higher success rates for breakthrough products.

So in summary, the author thanks various individuals and teams for their contributions to the book and lessons about innovation, while introducing the need for a new approach beyond traditional customer-driven thinking.

In the outcome-driven paradigm, companies focus on helping customers get jobs done (like farmers growing corn or carpenters cutting wood), rather than focusing directly on the customer.
Customers judge products based on how well they perform the job, using 50-150 “outcome metrics” like minimizing seed failures or saw kickbacks. These metrics are overlooked by customer-focused approaches.
Understanding customer outcome metrics allows companies to systematically identify opportunities, generate valuable ideas, and create products customers want.
For example, medical device company Cordis grew its market share by first identifying important unmet outcomes, prioritizing projects addressing them, optimizing messaging, and creating new products to satisfy remaining outcomes.
However, innovation is variable due to 8 factors: ill-conceived strategies, faulty data, missed opportunities, poor segmentation, wrong targets, poor marketing/messaging, poorly prioritized projects, and scattershot idea generation.
These factors introduce randomness and waste in innovation processes. Companies compensate by funding many initiatives and hoping a few succeed, but this is an undisciplined approach.

So in summary, focusing on customer jobs and outcomes rather than direct inputs allows for more systematic and predictable innovation, but variability is still introduced through common flaws in innovation processes and operations.

The book introduces the concept of “outcome-driven” innovation, which focuses on identifying customer outcomes or “jobs” that need to be done rather than specific features or solutions.
It outlines an 8-step process for outcome-driven innovation: 1) Formulate innovation strategy by determining target customers and type of innovation. 2) Capture customer outcomes and jobs rather than general needs. 3) Identify unserved outcomes that represent opportunities. 4) Segment markets based on shared unserved outcomes. 5) Generate concepts that fulfill important unserved outcomes. 6) Build business cases for concepts. 7) Develop and launch solutions. 8) Measure and improve customer satisfaction.
Key aspects include prioritizing opportunities by determining which outcomes are important but un/underserved, using outcome-driven segmentation to uncover new market segments, and focusing innovation efforts on fulfilling the most important unserved outcomes rather than incrementally improving existing solutions.
The goal is to make innovation more predictable and successful by directing efforts towards areas of true customer need rather than incrementally improving what already exists or guessing at solutions.

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

The purpose of segmentation is to group customers into segments based on common needs, wants or attributes so companies can better target their products and marketing.
Traditional segmentation methods like demographics are ineffective for innovation purposes because they don’t reveal what customers want or need from a solution.
Segmentation has evolved from demographic variables to psychographic and behavioral variables to gain more customer insights.
Outcome-based segmentation segments customers based on the jobs they want done and outcomes they want achieved rather than demographic variables. This reveals unmet or underserved needs.
To perform outcome-based segmentation, companies interview customers to understand the outcomes they care most about and map segments accordingly.
This approach addresses challenges in innovation and marketing by revealing opportunities to create customer value.
Job-based segmentation segments based on the functional job or job-to-be-done by customers rather than attributes. It is used when outcomes are well understood but the specific jobs are not.

The first step in formulating an innovation strategy is to determine the type of innovation to pursue, potential growth options, and where to focus in the value chain to maximize value creation.

There are four main types of innovation:

Product/service innovation - Improving existing products/services. Most companies need this to remain competitive.
New market innovation - Creating new markets by solving customer problems/jobs not addressed currently. Provides best growth potential.
Operational innovation - Improving inefficient business operations through creative solutions. Appeals to commodity or mature market companies.
Disruptive innovation - Using new technologies to disrupt existing markets filled with overserved customers. More difficult but may create new opportunities.

Growth options include focusing on existing versus new customers, as well as low-end disruption targeting overserved customers versus new-market disruption creating new customer segments.

The value chain should be examined to determine where to focus efforts to maximize value - production, distribution, customer interaction processes, etc.

An evaluation of these strategic factors is needed before developing solutions to ensure the right opportunities are pursued and failure risk is minimized down the line.

The customer-jobs matrix outlines four main strategies for innovation: help current customers do an existing job better, help current customers do new related jobs, help new customers do existing jobs, and help create new jobs for new customers.
Most companies focus on improving existing products for current customers. This involves understanding customer needs and addressing underserved outcomes.
Companies can also help current customers do new related jobs by identifying additional tasks customers want to achieve and enhancing products accordingly.
Targeting non-customers to help them do existing jobs can open up new markets, like personal copiers or blood glucose kits.
Helping new customers do jobs not currently served creates entirely new markets and products.
Companies must decide who the target customers are for value creation - the end user, purchaser, channel partner, etc. and focus on their outcomes.
Common mistakes are not considering the end user, only focusing on some customers but not all relevant ones, and relying only on intermediaries rather than directly understanding customer needs. Understanding needs across the whole value chain is important for innovation.
Businesses need to collect the right customer input data in order to successfully innovate and create products/services that customers value. This involves understanding what outcomes or metrics customers use to judge value when completing a job.
Companies often make mistakes in how they determine which customers to focus on in the value chain. They may focus on the wrong customer, exclude important customers, or rely on secondhand information rather than directly collecting customer requirements.
To formulate effective innovation strategies, companies must correctly identify who makes the most important judgments about value in the value chain and collect input data directly from those sources. This could include end users, buyers, channel partners, OEMs, etc. depending on the situation.
Overlooking important constituents in the value chain increases a company’s risk of product/service failure due to misunderstanding customer needs and wants. Considering multiple stakeholders with potentially conflicting outcomes adds complexity but can uncover more opportunities for value creation.
Collecting the right customer input data upfront is critical to successfully identifying opportunities, creating valued solutions, and driving the innovation process from ideation through evaluation and positioning. Companies often fail to capture the necessary types of data needed.

So in summary, businesses need to carefully determine the relevant customers in the value chain, directly collect the appropriate input data from priority sources, and consider the perspectives of multiple constituents to minimize innovation risk and unlock new growth opportunities.

Here are the key points:

Companies commonly collect feedback from customers in the form of solutions, specifications, needs statements, and benefit statements when gathering requirements.
However, this type of anecdotal and ambiguous feedback is not actually useful as inputs for innovation. It often leads to failures rather than avoiding them.
What companies need are insights into the jobs customers are trying to accomplish, the outcomes/metrics used to define successful job completion, and any constraints preventing customers from adopting new products/services.
Understanding jobs, outcomes, and constraints allows companies to create new value by helping customers perform more/different jobs, improving job completion rates, and removing obstacles.
Simply capturing vague “voice of the customer” statements is not sufficient - companies must become “outcome-driven” and focus on the right types of precise, measurable customer data to successfully innovate.

In summary, while companies commonly collect customer solutions, specs, needs and benefits as inputs, this feedback is ambiguous and doesn’t provide the right kind of actionable insight needed for innovation success. Companies should focus on understanding customer jobs, outcomes and constraints to drive valuable innovation.

The article discusses three types of information that are important for innovation: jobs to be done, desired outcomes, and customer value models.

Jobs to be done refers to the functional, personal, and social tasks customers want to accomplish in a given situation. Understanding customers’ jobs goes beyond the primary function to include related and supporting jobs as well. Breakthrough products often address multiple jobs customers are trying to get done.

Desired outcomes are the specific metrics and measures customers use to evaluate how well a job is performed. Companies should capture 50-150 outcomes from customers to understand how a product can perfectly meet their needs. Outcomes define the customer’s value model and can be used to evaluate new product ideas.

Customer value models map out the process steps for a given job. Capturing desired outcomes for each step creates a precise framework for developing and marketing new products based on how customers evaluate the successful completion of a job. Understanding jobs, outcomes and value models provides critical insights for driving innovation.

Here is a summary of the key points about the outcomes model:

The outcomes model captures customer desired outcomes, which are statements that begin with “minimize” or “increase” and describe how well a job is getting done. Outcomes remain stable over time as fundamental measures of job performance.
Capturing outcomes, jobs, and constraints provides short-term and long-term guidance for companies on what technologies and ideas to pursue.
Outcomes are specific measures customers use to judge success at each step of a job. Multiple outcomes define success at each step.
Constraints are physical, regulatory, or environmental roadblocks that prevent customers from getting a job done or done under certain circumstances. Addressing constraints can uncover growth opportunities.
Companies use methods like interviews, focus groups, and observation to capture outcomes, jobs and constraints. The goal is to understand what information is needed, not the method itself.
Validating statements with customers in real-time helps avoid interpretation issues later on. Captured inputs are then prioritized and used to guide product development and innovation.

The overall desired outcome is to capture the fundamental measures customers use to judge job performance success, as well as constraints, to guide business strategy and innovation over the short and long term. Understanding outcomes, jobs and constraints provides direction on meeting customer needs.

For innovation efforts, companies need to precisely capture the right types of customer data - jobs, outcomes, or constraints. Simply gathering vague “customer requirements” is not enough.
The situations that commonly arise requiring different types of customer data input are: improving an existing offering requires outcomes for the primary job; determining related jobs as well requires capturing outcomes for other jobs; reinventing a product requires understanding what jobs customers are hiring products for.
Key opportunities for innovation come from understanding underserved outcomes, jobs, or constraints - things customers want but are unable to satisfactorily achieve. This represents gaps where additional value can be delivered.
Overserved outcomes are where value is already well delivered, representing potential for cost reductions or disruption.
Properly understanding and prioritizing opportunities based on underserved customer needs allows for a more systematic, outcome-driven innovation process rather than relying on vague ideas or opinions.

Companies often make three common mistakes when developing new products or improvements:

Making improvements in areas that are already well satisfied by existing products. For example, continuing to increase printing speed for printers even though customers are satisfied with current speeds. More improvements don’t necessarily add value.
Focusing improvements on outcomes that are unimportant to customers. This wastes resources and doesn’t address what customers really want.
Making improvements that negatively impact other important outcomes. Customers often focus on one problem without considering trade-offs, but changes made to address one outcome can hurt performance in other areas.

The article recommends using outcome-driven research and an opportunity algorithm to prioritize where to focus improvements. Companies survey customers to rate the importance and satisfaction of different outcomes. The algorithm calculates an “opportunity score” based on importance, satisfaction, and their difference. The outcomes with the highest scores (most important and least satisfied) represent the best opportunities for valuable improvements. This helps companies focus on outcomes that will truly benefit customers instead of pursuing changes in overserved or unimportant areas.

The opportunity algorithm identifies where markets are underserved and overserved based on importance and satisfaction scores for outcomes/jobs.
Underserved areas have high opportunity scores (above 15 is considered an extreme opportunity, 12-15 is “low-hanging fruit”). These indicate important outcomes that are not well satisfied.
Overserved areas have satisfaction scores higher than importance scores. Resources should not be allocated to these areas as there is little opportunity.
Value migrates over time as outcomes become more satisfied. Once an outcome is well satisfied, the opportunity score decreases and opportunities shift to other important but unsatisfied outcomes.
To succeed long-term, companies must track where opportunities exist at any point and develop solutions to address the most important unsatisfied outcomes/jobs, as value migration will displace solutions focused on overserved areas. The dynamic nature of opportunity scores predicts where value is migrating over time.
Traditional competitive analysis focuses on comparing product specs, but this assumes customers value the same attributes. It can lead companies to over-improve areas that are already satisfying customers.
Outcome-driven analysis compares products based on how well they achieve important customer outcomes. This gives unique insight into strengths/weaknesses and how well customer needs are actually being met.
It enables companies to identify specific strengths and weaknesses of competitors. This allows them to emulate successful strategies and avoid failing ones.
It indicates when competitors are directing resources to outcomes that are already satisfied or unimportant, so a company knows when it can let a competitor pursue an unpromising approach alone.
This type of analysis based on customer priorities, rather than just product features, provides a more effective basis for competitive decisions around positioning, communication strategy, product development, and knowing when not to follow competitors’ moves. It helps ensure resources are devoted to high opportunity areas.

Here are the key points about how traditional segmentation methods can be ineffective for innovation purposes:

Traditional methods like demographic, psychographic, behavioral, or industry-based segmentation arbitrarily group customers without considering their actual needs, problems, or desired outcomes.
This can lead companies to target “phantom segments” that are not truly homogeneous in their needs or likely to respond uniformly to new products/services.
Traditional schemes assume customers within a segment will all share the same requirements, but this is often not the case as customer needs vary widely.
Effective segmentation for innovation should uncover groups of customers with unique, underserved problems or outcomes they are trying to get done - these are termed “segments of opportunity.”
Traditional methods don’t necessarily surface these opportunity segments as they don’t consider customer jobs or desired outcomes directly.
By contrast, outcome-based segmentation as described can identify sizable groups of customers who truly share unique underserved outcomes and will likely respond similarly to targeted innovations.
This allows companies to focus product development on real customer needs rather than phantom segments defined by arbitrary attributes.

So in summary, traditional segmentation fails to surface the most promising targets for innovation by not considering customers’ actual desired outcomes or jobs to be done. Outcome-based methods are argued to be more effective.

Here are the key points about outcome-based segmentation:

It uses customers’ desired outcomes as the basis for segmenting the market, rather than solutions, specs, needs, benefits, etc.
It clusters customers based on the opportunity score for each outcome, which considers both importance and level of satisfaction. This forces the creation of segments that represent unique opportunities.
Motorola used this approach by first identifying customers’ desired outcomes, then surveying them to quantify importance and satisfaction for each outcome.
They selected 11 outcomes as segmentation criteria that showed the most variability in responses.
Cluster analysis placed respondents into 3 segments based on their outcome opportunity ratings.
Profiling the segments revealed their unique characteristics - one valued privacy, another clear communication in dangerous situations, the third coordinating activities.
This allowed Motorola to targeting, position, and message to each segment’s specific opportunities and needs.

So in summary, it segments based on outcome opportunities rather than solutions, in order to discover unique customer groups with underserved needs that represent new growth opportunities.

Until 1997, mobile radio products from Motorola and competitors took a one-size-fits-all approach and did not address the unique needs of different user segments. Motorola conducted outcome-driven segmentation and identified three key segments with distinct needs:

Users requiring privacy during communications.
Users involved in emergency/life-threatening situations.
Users needing communications to manage work assignments.

Motorola developed customized products for each segment, focusing on their unique needs and priorities. For example, the product for segment 1 included enhanced encryption, while segment 2’s product included emergency features like location tracking.

This approach led to better, more affordable products with increased customer satisfaction. It accelerated Motorola’s revenue growth to 18% in a stagnant market and secured its leadership position.

In summary, outcome-based segmentation allowed Motorola to optimize its products for each user segment’s specific needs and priorities, rather than taking a one-size-fits-all approach. This resulted in commercial success through improved products, lower prices, and higher customer satisfaction.

Job-based segmentation is used to discover entirely new markets by identifying groups of jobs or tasks that people are trying to accomplish but are unable to do so satisfactorily with current products/services.
The process is similar to outcome-based segmentation, but uses jobs/tasks instead of outcomes as the basis for defining segments.
Companies conduct research to understand all the jobs people are trying to get done, then determine which jobs are both important and underserved/unsatisfied. These represent potential new market opportunities.
Microsoft used this approach by surveying PC users to identify all jobs/tasks, then determined which were important but underserved. Potential new markets of opportunity were uncovered this way.
Once a potential new market is identified, further outcome-based research is done to understand the specific outcomes people desire within that job/task and which outcomes are underserved, to guide innovation and development.
In summary, job-based segmentation is used to discover entirely new markets by focusing on groups of jobs/tasks, while outcome-based segmentation focuses on opportunities within existing markets defined by outcomes.
Coloplast, a Danish medical device company, applied outcome-driven thinking to its US skin and wound care division.
Competitors focused on faster wound healing, but Coloplast discovered biggest opportunities were preventing issues that could worsen wounds, like wet/moist skin.
Coloplast targeted these “preventing complications” outcomes through new positioning, product development and pipeline prioritization.
This unique positioning helped them achieve double-digit growth in a mature market within 6 months.
Understanding which outcomes had the best opportunity for improvement gave them a strategic advantage.
Broad opportunity themes that all customers agree are important and no competitor has addressed provide the best growth chances.
Even unrelated opportunities can represent growth if their opportunity scores are high enough.
A big single opportunity (score >15) is best addressed with a new ancillary product rather than product improvement.
Mature markets may have few opportunities but some outcomes unnecessarily increase costs - these are opportunities for cost reduction.
Long-term opportunities require new technology and are good research targets.
When broad opportunities are tapped, segment-specific strategies like targeting multiple segments or developing a platform for multiple solutions can drive further growth.
Motorola’s Radio Products Group used an outcome-based approach to limit the number of technology platforms needed for their mobile radio line. This reduced development and support costs by tens of millions over the life of each product.
It is better to first target the least challenging customer segments that have the most opportunities addressed by relatively few new features/solutions. This allows you to satisfy the entire segment and make progress on more demanding segments.
AIG used this approach by first targeting their least demanding agent segment, then the next least demanding, using the same features for both and moving closer to the most demanding segment each time.
You can also target segments that represent attractive price points - go after the lowest price point segment first where you can satisfy needs within a profitable business model before competitors.
Pursuing underserved outcomes allows companies to define a unique and valued competitive position that separates them from others in the market.
Companies sometimes fail to target opportunities because they don’t like the answers, it threatens managers’ jobs, or developing new competencies is not a priority for managers. They may try to invalidate the data or commission conflicting studies. But ignoring opportunities is not good for business growth.
Offerings should deliver all the performance that customers need, but no more, so customers aren’t paying for unused functions.
There are several types of broad market opportunities, including related opportunities forming a theme, unrelated opportunities representing growth areas, addressing a single opportunity with a new ancillary product, and overserved outcomes unnecessarily increasing costs.
Segment-specific opportunities revealed through outcome-based segmentation provide additional growth avenues.
Knowing which opportunities to target for growth dramatically impacts subsequent company actions and allows focused investment of resources to create solid customer value.
Companies can better exploit current products by communicating advantages in satisfying targeted underserved outcomes, bringing products/services in development to market that address opportunities, and developing longer-term ideas targeting remaining opportunities.
Effective messaging connects product features to underserved outcomes customers want achieved. Companies must understand market opportunities, have products addressing them, recognize relevant features, and refine messaging accordingly. This allows optimized sales from current offerings by communicating true value to customers.
Companies can determine if their products address underserved customer outcomes through external customer satisfaction surveys or internal assessments by cross-functional employee teams.
Bosch circular saws were found to significantly outperform competitors in minimizing time for bevel adjustments, an important but underserved outcome.
To communicate this competitive strength, Bosch needs to identify which product features specifically enable faster bevel adjustments (e.g. detents).
Companies should evaluate their current messaging to see if it focuses on unimportant, overserved, or already satisfied outcomes.
Effective new messaging either aggregates related underserved outcomes under a higher-level theme (like Coloplast’s “preventing complications” theme) or highlights how a specific feature addresses a key underserved outcome (like Bosch’s saws’ detents enabling quick bevel adjustments).
While emotional appeals can work for some products, focusing first on clear functional benefits that address important but underserved customer needs often generates better results, as Motorola discovered with its failed emotional branding approach for cell phones.
Motorola failed to recognize that their cell phones were functionally complex products, unlike cosmetics or perfumes which have relatively simple functions. For cell phones, improving basic functions like call quality was still an important opportunity.
The marketing experts at Motorola mistakenly tried to emulate Procter & Gamble’s model of emotional branding, which works well for simple, low-function products. But cell phones require a focus on continually delivering superior functionality to build loyalty.
Different industries fall into different quadrants based on the functional and emotional characteristics of their products:
- Cosmetics/perfumes are low function but high emotion, so focus on emotion works.
- Electronics/software are high function but low emotion, so focus must be on functionality.
Motorola incorrectly assumed the P&G emotional branding model would transfer to their high-function product market without considering functionality needs.
In general, messaging strategies should prioritize functionality for high-function products and only consider emotion after functionality is highly developed. Motorola failed to see this.
The marketing experts overlooked the fact that cell phones were not simple products like perfumes but rather required delivering ongoing functional improvements to satisfy users.

Here is a summary of the key points about prioritizing projects in the development pipeline:

Companies often have more development projects in the pipeline than they can realistically handle due to a lack of proper filtering. This makes prioritization difficult.
It is challenging for companies to determine which projects will truly address market opportunities and satisfy customer needs since they often do not fully understand customer outcomes and which are underserved.
Companies feel pressure to hedge their bets by funding many projects simultaneously so they don’t miss potential opportunities. However, this spreads resources thin.
Once projects are started and funded, it can be difficult for companies to terminate projects that are no longer high priority or seem unlikely to succeed.
The article describes an outcome-driven methodology for prioritizing projects based on how well they address targeted, underserved customer outcomes identified by the company. Projects that satisfy important outcomes are prioritized for resources to reach the market quickly.
This approach aims to deliver winning products customers want, get them to market faster, and reduce wasteful spending on projects that don’t satisfy real needs - providing an operational competitive advantage. It helps companies focus resources on their most promising opportunities.
Projects are hard to kill because managers and champions want to believe in their project’s success, even without strong evidence. Their conviction and enthusiasm spreads throughout the organization.
Companies spread limited resources too thinly across many projects, so few receive the resources needed to move quickly. This allows competitors to launch faster.
To identify winners and losers, companies should understand customer needs, know which are most important/least satisfied, and target opportunities.
Projects in development are evaluated against target outcomes to estimate customer satisfaction levels. Products should address all outcomes, while features impact specific outcomes.
Evaluation results show which projects increase satisfaction the most and should receive continued/accelerated funding. Projects that don’t address targets should have funding halted.
Features that significantly improve satisfaction for important outcomes deserve continued funding, even if their overall score is low. Projects could also be improved by adding high-scoring features.
Prioritization ensures efforts that deliver the most customer value get to market quickly.

Here is a summary of the key points regarding pipeline prioritization:

Products and initiatives in the pipeline should be evaluated based on how well they address targeted, underserved customer outcomes identified through opportunity analysis. Initiatives that perform best in satisfying the highest priority outcomes should receive accelerated funding.
Initiatives that fail to address any of the targeted outcomes are not creating customer value and may need to be deprioritized or redirected.
Projects aimed at outcomes that are unimportant to customers or already overserved should be considered for cancellation as they are not opportunities for additional value creation.
Competitive intelligence on upcoming rival products allows assessment of threats and weaknesses to factor into priority decisions. Initiatives addressing large opportunities or competitive weaknesses may need to move up in priority.
Other factors like cost, risk, effort required are also evaluated to select the initiatives that deliver the most value for least investment.
Regulatory changes can trigger a shift in priorities to ensure compliance.
Pipeline prioritization helps focus resources on initiatives most likely to generate customer value andcompany revenue by solving important unmet needs.
When done effectively, companies can achieve three important business objectives simultaneously through innovation - delivering winning products customers want, getting products to market more quickly, and reducing unnecessary development expenses.
However, many companies struggle with traditional brainstorming and product development approaches. They have difficulty determining which concepts will address market opportunities, feel compelled to cover all bases, find it hard to kill projects once started, and fail to resource projects for quick launches.
The solution is an outcome-based approach to prioritize projects. Managers should evaluate projects based on how well they address targeted customer outcomes that are currently underserved, as well as those that don’t address outcomes or address overserved outcomes.
This evaluation process involves determining what projects to evaluate, selecting an evaluation team, having the team evaluate initiatives, and assessing results to create a prioritized list of initiatives based on customer value and revenue potential.
Focused brainstorming and the customer scorecard are introduced as better ways to generate and evaluate concepts. Focused brainstorming directs creativity toward specific underserved outcomes, while the customer scorecard quantifies a concept’s expected value compared to existing options.
These approaches allow companies to devise breakthrough concepts that satisfy customer needs and determine which concepts are likely to succeed before significant development, improving innovation success rates.
When companies understand which customer outcomes are underserved or overserved, they can focus their innovation efforts on creating solutions that deliver new value in targeted ways.
With employee ideation sessions focused on specific underserved outcomes, companies report generating valued solutions over 90% of the time.
Some best practices for focused brainstorming include: staying laser-focused on targeted outcomes, aiming for breakthrough improvements rather than incremental changes, using constraints to stimulate creativity, quickly eliminating unworkable ideas, and optimizing the best ideas for cost, effort, risk and sustainability.
Constraining ideas to not increase product costs can paradoxically drive more innovative solutions, as occurred when Bosch removed the power cord from circular saws.
The goal is to generate one or two breakthrough ideas per outcome that achieve very high customer satisfaction while also meeting practical criteria like low development costs. With focus and filtering, companies can systematically innovate to address important unmet customer needs.
Traditional concept evaluation methods like internal assessments, qualitative customer assessments, quantitative customer assessments, and selective assessments are ineffective at properly evaluating new product and service ideas.
Internal assessments only look at fit with the existing business and fail to consider customer outcomes. Qualitative customer assessments like focus groups have issues like customers not being aware of all their desired outcomes, lack of technical understanding, and failure to reach consensus.
Quantitative customer assessments still rely on preselected ideas rather than evaluating all possibilities. Selective assessments can be influenced by politics rather than objective evaluation.
To effectively evaluate ideas, companies should use a customer scorecard approach. The scorecard lists all identified customer outcomes in priority order of undersatisfaction. Proposed ideas are then objectively judged by teams on how well they satisfy outcomes and the total value they deliver can be quantified. This allows companies to predict success before launch based on addressing important customer needs.
Companies use outcome-driven methods to evaluate new product/service concepts and ideas against customer priorities to determine which will create the most value.
One company, J.R. Simplot, used this method to evaluate french fry ideas and improve their best concept. It changed their development priorities and allowed them to pursue ideas they otherwise wouldn’t have.
The method involves defining customer desired outcomes, quantifying importance and satisfaction levels, and calculating “opportunity scores” to identify priorities.
Concepts are then evaluated based on how much they improve satisfaction of priority outcomes. Generally concepts need 5-10% improved value to succeed, or 20%+ for dramatic growth.
Pratt & Whitney used this method to evaluate investing in a new shop floor logistics system. They defined outcomes, surveyed customers, and saw the system only improved a low priority outcome, so looked for other ideas.
Concepts are scored by multiplying weighted opportunity scores by estimated satisfaction improvements to calculate total value delivered. The highest scoring concept is usually pursued.

So in summary, it’s a quantitative, outcome-driven process to systematically evaluate concepts against customer needs and identify the highest value opportunities for development.

P&W evaluated customer outcomes to determine the value delivered by different offerings using a concept score from 0-100%. Their existing offering scored 48.3% while a competitor scored 53.4%.
A proposed new shop floor logistics system would only improve their score to 49.8%, much less than their 10% goal. It also did not address top improvement opportunities.
P&W realized they needed a more innovative solution to significantly improve customer satisfaction and regain lost market share.
Over two days, they generated 10 new ideas that addressed priority outcomes like order status updates and part tolerance changes.
Their proposed solution incorporated these ideas to score 66.7% - a 38% improvement over existing and 25% above competitor. It also required half the investment of the original proposal.
If opportunities cannot be addressed by current/pipeline offerings or brainstorming, P&W sends them to R&D. This ensures R&D focuses on important customer problems, creating value if successful. It allows prioritizing and aborting less important efforts.

So in summary, focusing R&D on unmet customer outcomes guides innovation efforts towards developing solutions that create meaningful value for customers.

Companies can address unmet customer needs and opportunities through either developing new products/features internally or acquiring technology through licensing or acquisitions from other companies.
Traditional idea generation and brainstorming methods often yield inadequate results because they are unfocused, solicit too many ideas, and lack a way to properly evaluate ideas.
A better approach is to focus ideation sessions specifically on addressing the identified unmet customer outcomes. Guidelines include staying focused on targets, aiming for breakthrough ideas, constraining thinking to spark creativity, quickly eliminating bad ideas, and optimizing the best idea.
Properly evaluating ideas is crucial. Following an outcome-driven method avoids common pitfalls by having objective company members, not customers, assess how well each idea satisfies all the important customer outcomes.
Getting the innovation process right through an outcome-driven paradigm can lead to more breakthrough solutions being developed in less time and with fewer resources, improving the company’s bottom line and productivity.
Adopting this approach requires companies to change how they think about innovation, focusing on understanding customer jobs and outcomes rather than needs and preferences. It also requires separating the roles of marketing and development.
Traditional ROI metrics may not fully capture the value of customer research, but understanding customer outcomes is critical for ensuring resources are focused on winning products.
Market researchers should play a more proactive role as strategists to uncover opportunities, inform product development, and ensure opportunities are addressed. Companies like Microsoft conduct this type of research without being asked.
Adopting outcome-driven innovation should be viewed as an infrastructure investment to improve the innovation process and gain a competitive advantage.
Existing networks like Six Sigma teams can help initiate outcome-driven innovation by conducting research and facilitating idea generation.
Ineffective past approaches like QFD should be abandoned in favor of directly capturing customer outcomes and metrics.
Innovation data is a valuable asset that needs to be better shared across the organization so everyone can focus on creating value.
Internal process innovation projects are a good way to start applying outcome-driven thinking with little risk.
Customer satisfaction studies can be repurposed by adding outcome-focused questions.
Discovered opportunities should be treated as sacred and acted upon, not questioned or ignored.

The passage discusses opportunities for innovation that address customers’ underserved needs and jobs. It suggests companies should make customers’ underserved needs and jobs the focal point of innovation efforts. While existing innovation processes and ideas have proven successful for many companies, there is still room for improvement. Continuous learning and feedback from using the outcome-driven innovation process can help further evolve and improve it over time. By committing to ongoing learning and sharing successes and failures, companies and the authors can work together to develop more effective ways of creating customer value and generating profits through innovation.

Traditional customer inputs like “needs”, “requirements”, “benefits” are not that useful for innovation because they are vague and don’t clearly define problems to solve.
Needs-based segmentation is not recommended as it incorporates many different types of inputs without clearly defining needs.
New-market disruption targets non-consumers who lack skills/wealth to use existing products.
New-market innovation creates new markets by solving problems for those struggling to get jobs done.
Operational innovation improves internal processes like manufacturing and distribution to cut costs.
Opportunities are jobs, outcomes or constraints that are underserved or overserved.
The opportunity algorithm quantifies opportunity based on importance and satisfaction ratings.
Outcomes are metrics customers use to measure job performance but don’t often articulate.
Outcome-based segmentation uses outcomes and their opportunity scores to group customers.
Being outcome-driven means focusing on underserved customer values (outcomes) to innovate.
Overserved are unimportant jobs/outcomes that are very satisfied, targets for cost cuts.
Qualitative research uncovers jobs, outcomes and constraints; quantitative measures importance and satisfaction.

Here are summaries of the articles referenced:

Slywotsky, Adrian J. Value Migration. Boston, MA: Harvard Business School Press, 1983.

This book discusses the concept of “value migration” where the sources of competitive advantage shift over time as industries and technologies change. It argues companies must continuously search for new sources of value.

Porter, Michael. “What Is Strategy?” Harvard Business Review, November–December 1996.

This influential article defines strategy as the creation of a unique and valuable position involving a different set of activities. It outlines Porter’s framework for formulating strategy including analyzing the five competitive forces that determine an industry’s attractiveness.

Ulwick, Anthony W. “Turn Customer Input into Innovation.” Harvard Business Review, January 2002.

The article argues customer requirements are difficult for companies to determine and customers don’t know what they want until they see it. It presents a method called “outcome-driven innovation” that uses ethnographic techniques to determine the outcomes customers are trying to achieve.

Yankelovich, Daniel. “New Criteria for Market Segmentation.” Harvard Business Review, March–April 1964.

One of the earliest articles on market segmentation, it argues markets should be segmented according to types of buyers and their decision-making processes, not just demographics. It stresses the importance of behavioral and psychological differences between customer groups.

Schindler, Robert M. “The Real Lesson of New Coke: The Value of Focus Groups for Predicting the Effects of Social Influence.” Marketing Research, December 1992.

The article analyzes the famous New Coke failure and argues traditional focus groups are not good predictors of how customers will react in real consumption situations due to social influence factors. It suggests alternative research methods that better account for social influence.

Here is a summary of key points:

Traditional segmentation approaches like demographic or job-based segmentation may not be effective for innovation as customer needs are always evolving. Segmentation should be focused on outcomes, needs and driving growth.
It is important to discover underserved or overserved market segments for disruptive innovation opportunities. Analyzing segments of high potential growth is also important.
Demanding or unattractive customer groups can sometimes reveal unique opportunities in mature markets.
Performing selective assessments and applying techniques like job profiling, TRIZ rules, lateral thinking can help with segmentation and identifying opportunities.
Segmentation should be guided by certain tenets like determining the best way to enter new markets or discover value for customers in new ways.
Techniques like Six Sigma principles, service innovation can help initiate outcome-driven innovation when determining the right segmentation approach.
The purpose of segmentation is to identify targets of value and maximize value creation for customers and the business over time. It is about interpreting market opportunities and developing effective targeting strategies.

#book-summary

What Customers Want Using Outcome-Driven - Anthony Ulwick