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SDT2012 (PK2.2): How to underpin the service design process with quantitative data
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SDT2012 (PK2.2): How to underpin the service design process with quantitative data



This presentation was part of the SDT2012 - the 1st international conference on service design and tourism, Innsbruck/Austria, August 23-24, 2012. For more info on the conference and other ...

This presentation was part of the SDT2012 - the 1st international conference on service design and tourism, Innsbruck/Austria, August 23-24, 2012. For more info on the conference and other presentations visit: www.sdt2012.com. All rights reserved by the author(s):

Josef Schmid, Management Center Innsbruck (Austria)

Josef Schmid is MCI alumnus, devoted to undertake research in the field of service design and tourism. He supported MCI as a scientific assistant in the international research project “Service Design in Tourism”. Josef is the author of an award-winning master thesis and co-authored research papers on service design topics.

How to underpin the service design process with quantitative data: Applying the adaptive conjoint analysis as a reflective method in a service design project of a tourism SME
Service Design practices are generally based on qualitative data and research methods. The objective of the presentation is to exemplify how the adaptive conjoint analysis can be integrated in a Service Design process to also gain quantitative data. This approach allows a broader perspective and helps to make well-grounded decisions. After the introduction of a selection of common service design methods, the focus will be on the procedure of an adaptive conjoint analysis. The audience will hear about the single steps of an adaptive conjoint analysis and possible pitfalls. Using the example of a service provider in the field of tourism will make the Pecha Kucha presentation practice-oriented.



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  • 1. (20)Dear ladies and gentlemen,I’m glad that I may tell you a little bit about a new idea.The idea of implementing a quantitative research method in a SD process. So in the next few minutes I will showhow a conventional SD process looks like and how you can integrate an ACA.
  • 2. (20)What is SD? For me SD is a structured process to develop or improve services. It’s about using certain tools and techniques to find out what customers actually want. So it’s nothing really new;it’s more a guideline to identify consumer preferences.
  • 3. (19)This is how a classical SD process looks like. It can be divided into 4 different phases but the lines are often overlapping.It all starts with the EXPLORATION,followed by the CREATION, the REFLECTION and finally the IMPLEMENTATION.
  • 4. (16)The exploration phase is about showing the status quo. Meaning to list everything that already exists to get the big picture. So this first step is important to identify resources that can be used for new or improvedservices.
  • 5. (19)The importance in the creation phase is to develop new ideas. Sometimes ideas derive already by looking at the findings of the previous phase because it becomes obvious where a service needs to be improved. At this stage I would say: “The more ideas the better”
  • 6. (20)The purpose of the reflection is then to identify the few very good ideas. These are services the customer is also willing to pay for. For instance an airline can not just double the leg room if their passengerswon’tpay for it.So reflecting is about picking services that provide a real value.
  • 7. (17)Ideas that are assessed as worth implementing are finally realized during the implementation phase. This last step will show the achievement of the undertaken SD process. SDtools such as blue-prints or role-plays help to smooth out final problems.
  • 8.(18)Now what’s the new approach?The idea is to integrate the ACA in the reflection phase of the SD process to get also quantitative data.This makes it easier to objectively pick the most promising services.
  • 9. (20)But what exactly is an ACA?The ACA is a researchmethodto find out what a customersubconsciouslywantsthemost.Imagineyouwanttobuy a newcar. Theyare all kindofsimilar but yet not the same. Andnowthereare so manycriteriathatinfluenceyou.
  • 10. (20)For instance the brand and its image, color, price, horsepower and so on.But instead of asking how important every single criterion might be, it‘s about evaluating the whole package. Just like making a decision in real life.And this approach is called decompositional.
  • 11. (18)And that means that everyone has to decide between different offersuntil the computer can finally calculate clear preferences for each participant.This reveals, which criteria are unexpectedly over or under rated.But now how does such a process look like?
  • 12. (20)It’s a 5 step process.And after each phase the survey software automatically creates packages that matchmore and more the participants preferences. So making a decision gets constantly harder.Using the example of a hotel, I’d like to show you how such an analysis can look like.
  • 13. (20)In phase 1, participants have the chance to exclude unimportant criteria.This first step helps to reduce the length of the survey without loosing critical information. For example a hotel guest, who doesn’t care about a 24h room service, can cross this offer out.
  • 14. (15)Coming to PHASE 2 -The task here is to specify the importance of the remaining service attributes. So a person could say that a room with balcony is most important,followed by high-speed Internet and last a flat screen TV.
  • 15. (20)In Phase 3, the software presents 2 service attributes, and the tester has to pick 1. So the option here is either a room with balcony or one with a flat screen TV. According to this information the software starts calculating the priority of each attribute.
  • 16. (19)Phase 4 is about comparing packages.Let’s say there’s a “junior suite, with balcony for $300” and a “standard room, with flat-screen TV for $200”. Now what do you prefer. Such a paired comparison is repeated until the software recognizes a clear tendency.
  • 17. (20)In phase 5 participants finally say how likely they would book one of the displayed offers. This last question helps to determine the validity of the survey.If there’s an inconsistency, it might be necessary to exclude a questionnaire to ensure representative results.
  • 18. (19)I did a single case study, which showed valid research results of the ACA. But even more interesting is, that the whole SD process works perfectly fine to prepare such an analysis,because it already filters the best ideas along the way.
  • 19. (20)Hence, the two approaches - SD and ACA - complement one another perfectly. So if you plan a conjoint analysis, I highly recommend to apply a few SD tools before hand. I’m sure this improves the quality of the research significantly.
  • 20. (18)Now what do you need to succeed. You need a computer, an online based survey software and a bunch of people who are willing to participate.It also helps to have knowledge about the procedure of an ACA and some change because costs can quickly skyrocket.That‘s it. I very much appreciate your attention.

SDT2012 (PK2.2): How to underpin the service design process with quantitative data SDT2012 (PK2.2): How to underpin the service design process with quantitative data Presentation Transcript

  • Pecha KuchaHow to underpin the service design process with quantitative data Josef Sebastian Schmid
  • What is Service Design?...an approach to find out what customers really want Structured process User centered Co-creative
  • Process
  • 1. Exploration Who is my Who are myFindings customer? competitors? What do I What do I offer? NOT offer?
  • 2. Creation Idea 1 Idea IdeaThink-Tank 2 Idea 3 Idea 5 Idea 4 6 Idea .....
  • 3. ReflectionExtra leg room Evaluation Is my customer willing to pay???
  • 4. Implementation Put all together Realisation
  • What‘s the new approach? ACA Adaptive Conjoint Analysis
  • What‘s relevant?Possible Criteria Price ShapeBrand Color Interior Design Etc. Guaranty Sound System HP
  • What‘s different?ACA Standard D e e.g. buying C c a new car Service/Product o o m m p p A: HP o o Criteria Criteria B: Color s s A B i i t t i i 1. 200 HP Attribute Attribute Attribute o o 2. 220 HP 1 2 3 n n 3. 250 HP a a l l
  • 5-Phases of an ACA
  • Phase 1 Source: Sarova Hotels
  • Phase 2 Priority 1 Priority 2 Priority 3Source: hotel.de Source: C.H. Chisholm Source: Burford Designs
  • Phase 3Source: hotel.de Source: C.H. Chisholm
  • Phase 4 Source: Marine Suites Hotel
  • Phase 5
  • Insight SD ACA Process Survey filters the results best help to concepts reflect
  • The perfect match AdaptiveService ConjointDesign Analysis
  • What you need to succeedComputer Internet Survey-Software Tester Knowledge Money