Kano Survey

Kano surveys embrace a set of market research tools used for three purposes: 1 To improve existing products, services, or processes or to create less expensive versions of existing products, services, or processes (called Level A surveys). 1 To create major new features for existing products, services, or processes (called Level B surveys). 1 To invent and innovate an entirely new product, service, or process (called Level C surveys).

used for three purposes:

• Level A surveys: to improve existing products, services, or processes or to create less-expensive versions of existing products, services, . or processes
• Level B surveyst: create major new features for existing products, services, or processes
• Level C surveys: to invent and innovate an entirely new product, service, or process.

(Get06, ch14, table 14.15) | | Absent |||||| | Present | | Delighted | Expected it | No feeling | Live with it | Do not like it | | ^ | Delighted | Q | A | A | A | O | | ^ | Expected it | R | I | I | I | M | | ^ | No feeling | R | I | I | I | M | | ^ | Live with it | R | I | I | I | M | | ^ | Do not like it | R | R | R | R | Q | 'Expected it' is actually:'Expected it,and likes it.'

Kano surveys are used to classify product, service, or process features into one of six categories(Git06, ch5.4). $ One-Dimensional (O): User satisfaction is proportional to the performance of the feature; the less performance, the less user satisfaction, and the more performance, the more user satisfaction. $ Must-Be (M): User satisfaction is not proportional to the performance of the feature;the less performance, the less user satisfaction to the feature, but high performance creates feelings of indifference to the feature. * So it might be a kind of must be this, and no higher? Though it's more of a One-dimensional until a certain upper level the it stays the same. So it's a max customer satisfaction thing??? $ Attractive (A): Again, user satisfaction is not proportional to the performance of the feature. However, in this case, low levels of performance create feelings of indifference to the feature, but high levels of performance create feelings of delight to the feature. * So the feature is worthless until you reach a certain level. $ Reverse (R): The researcher's a priori judgment about the user's view of the feature is the opposite of the user's view. $ Indifferent (I): The user is indifferent to the presence and absence of the feature. $ Questionable (Q): The user indicates conflicting responses with respect to the feature. For example, the user desires that the feature is both present and absent. $ One Dimensional (O): User satisfaction is proportional to the performance of the feature; the less performance, the less user satisfaction, and the more performance, the more user satisfaction. $ Must-Be (M): User satisfaction is not proportional to the performance of the feature; the less performance, the less user satisfaction to the feature, but high performance creates feelings of indifference to the feature. $ Attractive (A): Again, user satisfaction is not proportional to the performance of the feature. However, in this case, low levels of performance create feelings of indifference to the feature, but high levels of performance create feelings of delight to the feature. $ Reverse (R): The researcher's a priori judgment about the user's view of the feature is the opposite of the user's view. $ Indifferent (I): The user is indifferent to the presence and absence of the feature. $ Questionable (Q): There is a contradiction in the user's response to the feature.

Additionally, Kano surveys are used to determine how much regular users desire a new feature (cognitive image) by asking them what percentage increase in costs over current costs they would be willing to accept to have the new feature. There are three "tolerable cost increase" distributions in practice: $ Uniform distribution: The uniform distribution shows that 80% of a market segment will pay at least a 10% cost increase to obtain the feature described by the cognitive image under study. Cognitive images exhibiting this distribution can be used to develop ideas for completely new products. $ Triangular distribution: The triangular distribution shows that 60% of a market segmentwill pay at least a 10% cost increase to obtain the product feature described by the cognitive image under study. Cognitive images exhibiting this distribution can be used to develop ideas for major new features of existing products. $ J-shaped distribution: The J-shaped distribution shows that 10% of a market segment will only pay a 10% cost increase to obtain the product feature described by the cognitive image under study. Cognitive images exhibiting this distribution can be used to improve features of existing products.

Level A Survey -- Improved or Less Expensive Designs

(Git06, ch14.) Level A surveys are used to improve existing products, services, or processes or to create less-expensive versions of existing products, services, or processes.

gather Voice of the Customer data from the market segments selected for study by team members.

Voice of the Customer data are either reactive or proactive. Reactive data reaches an organization as a direct result of doing business.

• complaints,
• compliments,
• product returns or credits,
• product/service sales preferences,
• contract cancellations,
• market share,
• customer defections/acquisitions,
• customer referrals,
• closure rates of sales calls,
• web page hits,
• problem or services hot line calls,
• technical support calls,
• accounts receivables where customers refuse to pay as they do not believe the service/product was as expected,
• and sales data.

Proactive data arrives only if an organization collects it through positive action, such as

• data gathered through interviews,
• focus groups,
• surveys,
• comment cards,
• sales calls,
• market research,
• customer observations,
• benchmarking,
• or dashboards.

Six Sigma team members use Level A studies to collect and analyze Voice of the Customer data to develop critical to quality characteristics (CTQs).

Two examples of the use of Level A studies are waiting times in a hospital and weights for chocolate bars.

Level B Survey Major New Features of Existing Designs

Level B surveys are used to create major new features for existing products, services, or processes.

a. STAGE ONE -- Collect Voice of the Lead User (VoU) and Voice of the Customer (VoC) Data 1 Select an innovation as the subject of a DFSS project and segment the market for it. 1 Identify lead users and heavy users in each market segment. 1 Collect VoU and VoC data concerning circumstantial issues from each market segment. a. STAGE TWO -- Analyze VoU and VoC Data 1 Classify "VoU" and "VoC" data as circumstantial or product-related data in each market segment. 1 Determine the critical circumstantial issues to regular users in each market segment. a. STAGE THREE Develop New Features 1 Determine the focus point for each circumstantial issue in each market segment. 1 Develop cognitive images (CTQs) for each focus point in each market segment. a. STAGE FOUR Evolve Strategies for New Features 1 Classify cognitive images (CTQs) by Kano category and cost distribution in each market segment. 1 Develop strategic themes for each cognitive image (CTQs) for selected market segments.

STAGE ONE: Collect "Voice of the User" (VoU) and "Voice of the Customer" (VoC) Data

STAGE ONE -- Step 1: Select an Innovation as the Subject of a DFSS Project and Segment the Market for It

The output for this step:

1 Select project 1 segment market 1 Select area to sample 1 select when to sample 1 select whom to sample, which stakeholders 1 Ask the following question "I feel _____ about the parking conditions in this particular lot." * 1. Extremely Satisfied * 2. Satisfied * 3. Neutral * 4. Dissatisfied * 5. Extremely Dissatisfied 1

A graduate student sampled 50 parkers in the Ring Parking Lot every hour between noon and 2:30 P.M. on April 29, 10:30 A.M. and 2:00 P.M. on April 30, noon and 2:30 P.M. on May 1, and 10:30 A.M. to 2:30 P.M. on May 2. These times were selected due to peak parking demand patterns. The week of April 29 was deemed a typical week for parking by the members of the team. The 50 parkers selected each hour were the first people encountered by the interviewer in each corner and center of the lot.

-### STAGE ONE -- Step 2: Identify Lead Users and Heavy Users in Each Market Segment These questions could really be asked in step one.

1 Identify experts * Whom do you regard as the person most expert in the use of this product, service, or process?(Git06,ch14) * Whom do you turn to when facing difficulties with this product, service, or process? 1 Once the external and internal expert(s) have been identified, the following questions: * Who are asked these questions? the lead users or the people in the parking lot or those that have identified the lead/heavy users * What is the point of these questions? * Who are the 'experts'? the lead/heavy users? a. What environment, images, emotions, needs, and wants come to mind when you think of lead users of this product, service, or process? Heavy users? a. For what purpose do lead users use this product, service, or process? Heavy users? a. How do lead users use this product, service, or process? Heavy users? a. Who do you regard as the person who exhibits the most ingenuity with the product, service, or process? How do they exhibit ingenuity? a. What are the characteristics of a lead user? Of a heavy user? 1 the experts are asked how lead and heavy users would benefit from resolving the problems that exist with the current product or service. 1 the team members construct a 'Lead User and Heavy User Characteristics by Market Segment' matrix 1 Identification of Lead Users and Heavy Users. * There are two approaches for identifying lead users and heavy users. a. ask experts to insert names and addresses of lead users and heavy users in a "Lead User and Heavy User Characteristics by Market Segment" matrix. a. In the second approach, for each market segment, team members develop a questionnaire based on "lead user" and "heavy user" characteristics. * The questionnaire should be distributed to a large sample of regular users. * Analysis of the questionnaire data involves doing a cluster analysis to identify lead users and heavy users.(Git06,ch14)

$ Lead users: are consumers of a product, service, or process who are months or years ahead of regular users in their use of the item and will benefit greatly by an innovation.(Git06,ch14) * Lead users are useful for identifying the unknown needs and wants of regular users necessary for creating innovative new features of existing products, services,or processes. * For example, a lead user of a hair dryer may attach a portable battery pack and use it as a body warmer at football games played in cold weather. $ Heavy users: are useful for identifying the needs and wants of regular users necessary for improving existing products, services, or processes

STAGE ONE - Step 3: Collect "VoU" and "VoC" Data Concerning Circumstantial Issues from Each Market Segment

gather "Voice of the User" and "Voice of the Customer" data by asking the following questions: 1 What emotions come to mind when you think about the product, service, or process? 1 What needs and wants come to mind when you think about the product, service, or process? 1 What complaints or problems would you like to mention about the product, service, or process?

$ Voice of the User: Gathered from the lead users. $ Voice of the Customer: Gathered from the heavy users.

STAGE TWO - Step 4: Classify VoU and VoC Data as Circumstantial or Product-Related Data for Each Market Segment

As team members collect circumstantial data, they also accidentally collect product-related data. Product-related data identifies the current expectations and perceptions of lead users and heavy users. This step involves classifying the collected data into product-related data. $ Product related data: Used for Level A studies. $ Circumstantial data: Used for Level B and C studies.

Classifying data as product-related or circumstantial takes practice.

• Product-Related Data

  • Puts sign on windshield: Engine won't start.
  • Stop people from backing out of parking spaces.
  • Add additional spaces.
  • Create one-way lanes, not two-way lanes, in parking lots.
  • Stop dangerous driving via patrols.

• Circumstantial Data

  • I am so annoyed and pissed off at being forced to drive like a manic.
  • I get anxious when I realize I have to come to the university and find a parking spot.
  • Annoyance.
  • Crowded.
  • Dangerous
  • People back up without looking. I beep my horn, but they don't hear me.
  • Racing to get to a spot before someone else.
  • Why aren't there more accidents?
  • I always try for a legal spot first.
  • Parking garage was full when I went to use it. I never went back to it.
  • The flow of traffic is crazy and scary.

STAGE TWO - Step 5: Determine the Critical Circumstantial Issues to Regular Users in Each Market Segment

Step 5 creates a survey that is given to a large sample of regular users to identify which circumstantial issues are critical to them. This is done when a large amount of circumstantial data results from Steps 3 and 4.

STAGE THREE -- Step 6: Determine the Focus Point for Each Circumstantial Issue in Each Market Segment

$ Focus points: are the underlying needs and wants (themes) upon which circumstantial issues are based. $ circumstantial data point: Afinity grouping

They are identified by using: 1 Create affinity diagrams: See also: AffinityDiagramCreation 1 organize the raw circumstantial data into: * major circumstantial themes. * TODO V What are these three entries??? * system * minor circumstantial themes. 1 Identify focus points a. technical investigations * Ask Tech Experts about a circumstantial data point a. lateral thinking. * Use ConceptFanTool to identify the focus points * Within each subject use the LateralThinkingHabbits to leverage the optimal for each subject. * So when asking the question: 'What alternative ways of achieving this purpose are there?' * Is that then when we in the concept fan take a step back, and then come up with newpoints?

| Raw Circumstantial Data | Affinity Diagram Circumstantial Themes and Their Raw Data Points| Focus Points | | | | |

Is the step back a kind of hidden 'Why'???

$ reference points: are general and nonspecific ways of doing things $ Direction: very broadest reference point. * The difference between a reference point and a direction is in the broadness of the reference point. $ Alternatives: ( Other ref point, found by going one step up from the org ref point, reference points * What (or the req) , and a direction * How (Implementation)

Focus Point-Encourage people to get to campus other ways (e.g., by bicycle). Lots of students and faculty live within easy cycling distance. But in order for a large number of people to commute by bicycle, some changes would be helpful.

• Cognitive Image-Develop a bicycle-friendly campus (bike pathways and racks, and shower facilities for sweaty bikers).

$ WHAT: (Initial Focus Point) Parking Creates Feelings of Stress Anger over time to find a parking space. Fixed spaces and variable demand creates a tense and frustrating environment. $ WHY: (Final Focus Point) Uncontrolled flow of traffic patterns create negative environment. $ How: (Cognitive Image) Create lots with one entrance and one exit. Install a counter system that adds one car to the count upon admission and subtracts one car from the count upon exiting from the lot. ...

STAGE THREE - Step 7: Develop Cognitive Images (CTQs) for Each Focus Point in Each Market Segment

This step actually creates potential innovations by translating focus points (user's underlying and unexpressed needs and wants) into detailed, unambiguous, qualitative statements of needs and wants in the language of design engineers. These statements are called cognitive images (CIs) or CTQs. The pathways available to translate focus points into cognitive images (CTQs) include:

• restating a focus point into one or more obvious actionable and designable ideas;
• design engineers using technical knowledge to restate a focus point into one or more obvious actionable and designable ideas;
• experts in the field under study use their product knowledge to restate a focus point into one or more actionable and designable ideas;
• team members use the "alternatives" or "concept fan" techniques to restate a focus point into one or more actionable and designable ideas.
  • uses each focus point as a reference point to create new alternatives as in Step 6