Opsm 405 service management
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Ko ç Un iversity. OPSM 405 Service Management. Class 9: Service System Design Tools: Service Blueprinting Conjoint Analysis. Zeynep Aksin zaksin @ku.edu.tr. Service blueprinting. Activities Decision points Precedence relations Line of visibility Resources.

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OPSM 405 Service Management

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Opsm 405 service management

Koç University

OPSM 405 Service Management

Class 9:

Service System Design Tools:

Service Blueprinting

Conjoint Analysis

Zeynep Aksin

[email protected]


Service blueprinting

Service blueprinting

  • Activities

  • Decision points

  • Precedence relations

  • Line of visibility

  • Resources


Opsm 405 service management

Low complexity, high divergence


Opsm 405 service management

High complexity, low divergence


Opsm 405 service management

High complexity, high divergence


Defining terminology

Defining terminology

complexity vs. divergence

what is done? how is it done?


Opsm 405 service management

Understanding the link between positioning and service structureStructural change: reduce divergence

  • positioning: economies of scale

  • + : perceived increase in reliability

  • - : conformity, inflexibility


Opsm 405 service management

Understanding the link between positioning and service structure

Structural change: increase divergence

  • positioning: niche

  • + : prestige, customization, personalization

  • - : difficult to manage and control


Opsm 405 service management

Understanding the link between positioning and service structure

Structural change: reduce complexity

  • positioning: specialization

  • + : expert image, easy control

  • - : stripped down image


Opsm 405 service management

Understanding the link between positioning and service structure

Structural change: increase complexity

  • positioning: wallet share

  • + : maximize revenue generation / customer

  • - : customer confusion, decline in service quality


Example structural alternatives

Example: Structural Alternatives


Conjoint analysis motivation

Conjoint Analysis: Motivation

  • Objective: max profits=revenues-costs

  • Positioning (or repositioning) impacts both profits and costs

  • We said earlier: in a service concept all details matter

    • What do customers value?

    • How are trade-offs between attributes made?

    • Etc.


Conjoint analysis

Conjoint Analysis

  • Conjoint: joined together, combined

  • CONsidered JOINTly


What s so good about conjoint

What’s So Good about Conjoint?

  • More realistic questions:Would you prefer . . .210 Horsepower or 140 Horsepower17 MPG 28 MPG

  • If choose left, you prefer Power. If choose right, you prefer Fuel Economy

  • Rather than ask directly whether you prefer Power over Fuel Economy, we present realistic tradeoff scenarios and infer preferences from your product choices


Conjoint analysis1

Conjoint Analysis

  • Basic idea: the service can be broken down into a set of relevant attributes

  • Have consumers react to a number of alternatives

  • Infer

    • Importance

    • Most desired level

  • Estimation of an individual’s value system

  • Overall product judgements lead to value system through some data analysis technique


Services broken down into attributes

Services broken down into attributes

  • Credit card

    Brand + Interest Rate + Annual Fee + Credit Limit

  • On-line brokerage

    Brand + Fee + Speed of Transaction + Reliability of Transaction + Research/Charting Options

  • Ski area for ski resort

    pysical setting, distance, snow base, new snow, vertical drop, type of runs, challenge, size of area, facilities, ticket price, wait for lifts, type of lift, snowboards


Attributes have levels

Attributes have levels

  • Levels are mutually exclusive

  • Have unambiguous meaning

  • Keep number of levels low (3-5)

  • Try to balance number of levels across attributes


Example adapted from j curry

Exampleadapted from: J. Curry

  • Golf balls: driving distance, ball life, price

  • Alternatives

    • 275 yards, 54 holes, $1.25

    • 250 yards, 36 holes, $1.50

    • 225 yards, 18 holes, $1.75

  • Market’s ideal ball?

  • Ideal ball for manufacturing costs?


Rank the balls

Rank the balls

  • Distance

    • 275 yards Rank 1

    • 250 yards Rank 2

    • 225 yards Rank 3

  • Ball Life

    • 54 holes Rank 1

    • 36 holes Rank 2

    • 18 holes Rank 3

  • Doesn’t really tell us anything we didn’t know


Take 2 features conjointly

Take 2 features conjointly

Note: different tradeoffs made by each buyer. Only best and worst are the same.


Illustration by example source dolan 1999

Illustration by example (source: Dolan 1999)

  • Fitness facility design

    • Towel service: yes or no

    • Locker service

      • Small storage lockers permanently assigned plus large hanging ones for daily use

      • Mid-size only permanently assigned

      • No permanently assigned locker, large hanging locker with mirror inside door


Rank from most to least preferred

Rank from most to least preferred

Towel Service

Locker


Give utility points

Give utility points

Towel Service

Avg.

3

Locker

4

0.5

3.33

1.67


Value system

Value system


Question you can answer

Question you can answer

  • Would this customer trade-off a storage locker on a daily basis for towel service?

  • Loss: 3-0.5

  • Gain: 3.33-1.67


In sum

In sum

  • Collect tradeoffs

  • Estimate buyer value system

  • Make choice prediction


Example output analysis source montgomery and wittink 1979

Example: Output analysis (source: Montgomery and Wittink, 1979)

Geographic Area

East .070

Midwest -.198

South -.321

West .449

Opportunity for Advance

Rapid .216

Moderate -.216

Business Travel

<= 1 night .163

2-5 nights .109

>=6 nights -.273

Range: .770

Range: .432

Range: .436

Attribute importance for business travel:

.436/(.436+.770+.432)

Importance analysis only relevant if attributes are in relevant ranges


What we can t say about the utilities part worths

What we can’t say about the utilities (part worths)..

  • >= 6 nights is unattractive to respondents

  • West is almost 7 times more attractive than East

  • <=1 night is more attractive than East

  • Why?

    • Arbitrary scaling within each attribute

    • Here utilities are scaled to sum to 0 within each attribute

    • Interval data does not support ratio operations

    • If count based then can say West is chosen 7 times more than East


Conjoint importances

Conjoint Importances

  • Measure of how much influence each attribute has on people’s choices

  • Best minus worst level of each attribute, percentaged:Vanilla - Chocolate (2.5 - 1.8) = 0.715.2%25¢ - 50¢(5.3 - 1.4) = 3.984.8%-------------Totals:4.6100.0%

  • Importances are directly affected by the range of levels you choose for each attribute


Output analysis pc example source dolan

Output analysis: PC Example(source Dolan)

Weight

<= 2 lbs 1.2

2-5 lbs .9

>5lbs 0.0

BatteryLife

1 hr 0.0

2hrs 0.2

4hrs 1.5

8hrs 1.5

Resolution

Below avg 0.0

Avg. .4

Above avg. .5

Price

1000 1.0

2000 0.5

3000 0.0

Product A: 2 lbs 1hr below average 2000

Product B: 5 lbs 4hrs average 3000

ProductC: >5lbs 8 hrs average 1000

Share of preference approach:

Prob. of choosing A: 1.7/6.6=26%

Prob of choosing B: 1.9/6.6=29%

Prob. of choosing C: 3.0/6.6=45%

Value of A= 1.2+0+0+0.5=1.7

Value of B = 1.9

Value of C = 3.0

Sum = 6.6

Market share: average purchase

probability across all subjects


Output analysis

Output analysis

  • Aggregate analysis

  • Segmentation analysis

  • Scenario simulations


Market simulation example

Market Simulation Example

  • Predict market shares for 35¢ Vanilla cone vs. 25¢ Chocolate cone for Respondent #1:Vanilla (2.5) + 35¢ (3.2) = 5.7Chocolate (1.8) + 25¢ (5.3)= 7.1

  • Highest value choice (first choice rule): Respondent #1 “chooses” 25¢ Chocolate cone!

  • Repeat for rest of respondents. . .


Market simulation results

Market Simulation Results

  • Predict responses for 500 respondents, and we might see “shares of preference” like:

  • 65% of respondents prefer the 25¢ Chocolate cone


Example source sawtoothsoftware

Example source: sawtoothsoftware

  • 9 cards, ranked by 2 volunteers

  • Copy of Excel spreadsheet available from course web site


Traditional conjoint designs

Traditional Conjoint Designs

  • Full profile: each service concept is defined using all attributes being studied

  • Full factorial: a design in which all possible product combinations are shown

  • Fractional Factorial: a fraction of the full factorial that permits efficient estimation of the parameters of interest)

    • From design catalogs

    • From software programs


Study design

Study design

  • Step 1: determine relevant attributes

  • Step 2: choose stimulus representations (how products will be described to respondents, full or partial)

  • Step 3: Choose response type (choice, ranking, rating)

  • Step 4: Choose criterion (liking, preference, likelihood of purchase)

  • Step 5: Choose method of data analysis


Summary

Summary

  • Blueprints for documentation

  • Analyze for complexity & divergence for positioning

  • Understand links between positioning and costs (service delivery system)

  • Conjoint analysis to assess customer valuations

  • Use output from conjoint analysis to link valuation, purchase, aggregate market share and profitability


Next time

Next time

  • Will continue Conjoint Analysis

  • Class will be held in the computer lab SOS Z13

  • Be on-time! Counts as in-class activity.

  • Will practice doing conjoint analysis via regression using Excel


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