Topic:

How can decision analysis support the decision making process in design thinking in selecting the most promising properties during the transition fromdivergent toconvergent thinking phases?

Executive Summary

Table of Content

Executive Summary

List of Figures

List of Tables

Index of Abbreviations

1.Introduction

2.Overview of Design Thinking and Decision Analysis

2.1.A New Approach to Problem Solving

2.1.1.What is a Design Thinker?

2.1.2.The Iterative Steps of Design Thinking

2.2.Decision Analysis

2.2.1.Decision Analysis Process

2.2.2.Multi Attribute Decision Making

3.Application Based on a Case Study

3.1.The Design Challenge

3.2.The Static Model

3.2.1.The Alternatives

3.2.2.Objectives and Measures of Effectiveness

3.2.3.Multi Attribute Decision Making

3.2.4.Sensitivity Analysis of the SAW Method

3.3.The Case Study’s solution

4.Conclusion

List of Literature

Statutory Declaration

Appendix

List of Figures

Figure 1: The IDEO process – a five step method (Kelley and Littman, 2004: 6-7)

Figure 2: Figure 3: The HPI process – a six step model (Plattner et al., 2009)

Figure 3: Fundamentals of Decision Analysis (Ralph L. Keeney, 1982)

Figure 4: Schematic form of a decision tree (Keeney and Raiffa, 1993)

Figure 5: A choice problem between two lotteries (Keeney and Raiffa, 1993)

Figure 6: MADM Decision Matrix

Figure 7: The tree main idea clusters

Figure 8: Decision Making Matrix

Figure 9: Decision Maker Matrix for the Design Challenge

List of Tables

Table 1: Different ways of describing design thinking (Lucy Kimbell, 2011)

Table 2: Realization of attributes in alternatives scale

Index of Abbreviations

DADecision Analysis

DCDesign Challenge

DM Decision Maker

DTDesign Thinking

HPIHasso-Plattner-Institute

HMWHow Might We

IWITMI Wonder If That Means

MADMMulti Attribute Decision Making

MCDMMulti Criteria Decision Making

SAWSimple Additive Weighting

1. Introduction

Everyone is in the need to make decisions every day. Those decisions may be shaped by an outstanding problem which just needs to be solved or it may just be the question whether to buy a new pair of shoes or not. Moreover, the problem may easily be solvable by a simple equation or there might be the necessity to formulate the problem in the first place since the difficulty is too diffuse to be absorbed. Due to the huge variety of different problems our society faces every day and with all divergent needs for a solution process, there is a constant need to draft and identify methods that support everyone in making decision. Undoubtedly, there are many methodologies and approaches out there that support the decision making process for daily small decisions that need to be made to life changing decisions. Decision analysis (DA), which is one of the formal methods and design thinking (DT), which is one of the innovative methodologies out there, are two instances of problem solving methods.

Both methods have been applied in similar fields, such as business, technology, and personal life but with divergent intentions. On the on hand, there is DT which is one of the more recent methodologies that helps to get from a problem to a solution with the support from a finite number of iterative steps that the design thinker will follow. Brown, who is the CEO of IDEO, describes DT as a method that is so powerful and implicit that can be used from teams broadly across the globe to create impactful innovative ideas that can be realized by the society or companies (Brown, 2010: 3). On the other hand, there is DA which is an approach that includes a variety of procedures that helps to find a formal solution to an identified problem and creates a more structured solution procedure. Howard was the person who shaped the term DA in 1964 and has been irreplaceable for the development of DA (Roebuck, 2011: 99).

This paper will combine DA and DT to investigate whether DA can leverage the DT process in order to find the most viable solution to a problem. Moreover, this paper will find out whether or not those two approaches can profit from each other. Selected procedures of DA will be integrated in the DT process by reference to a case study. Over and above, the solution generated by the DA technique will be compared with the chosen alternative in the case study that followed the regular DT process. Comparing those two outcomes, this paper will work out whether or not DA can support the DT process.

The second chapter is descriptive of the fundamentals of DA and DT. After the outline of the foundations, the third chapter will apply chosen DA procedures into the DT process on the basis of a case study. Moreover, the chosen alternative by the design thinking team in the case study will be analysed. In the final chapter, the major finding will be summarized and evaluated.

2. Overview of Design Thinking and Decision Analysis

2.1. A New Approach to Problem Solving

Design Thinking is an iterative and innovative approach to solve problems of all kinds that the society is facing. Moreover, it is a human-centred and at the same time investigatory process that puts its emphasis on collaboration, prototyping, and field research (Lockwood, 2010: xi). It is a set of fundamentals than can be applied by different people and to a huge range of problems (Brown, 2010: 7). DT is not a linear, but an iterative process in which the designers are constantly learning from mistakes and improving their ideas. Designers hope to find a linear model that will help them to understand the logic behind a design process; therefore, it is a constant search for decision making protocols that would support the designers’ processes (Buchanan, 1992). In sum, DT is a user-centred approach to solve a variety of problems with the aim to integrate people from various fields; ranging from consumers and business people to designers.

There are a variety of ways to describe DT, as illustrated in Table 1. According to Brown, DT is an organisational resource with the goal to create innovation. Cross describes the method as a cognitive style with the purpose of problem solving. Another famous definition concludes that “Design Thinking means thinking like a designer would” (Roger, 2009). However, the purpose and aim of DT is in its core identical, whether one is applying the processes modified by Cross or Brown (Plattner et al., 2009: 113).

Table 1: Different ways of describing design thinking (Lucy Kimbell, 2011)

Over the last five years, the term DT has become very present in our society. On top of that, DT is a new term in design and management circles, which shows the demand for creative and innovative methods across various sectors (Kimbell, 2011). Nevertheless, this method is still underdeveloped when it comes to applying design methods at the management level (Dunne and Roger, 2006). But why is the interest in design growing and the term has become ubiquitous? The society is facing a lot of challenges; from educational problems to global warming and economic crisis. Brown sees DT as a powerful approach that can be applied to a huge variety of problems and as a consequence creates impactful solutions to these challenges. On top of that he argues that design has become nothing short of a tactic of viability (Brown, 2010: 3). The method is not limited to the creation and design of a physical product, but it can also result in the conception of a process, tools to communicate, or a service (Brown, 2010: 7). Therefore, it is a method that helps to learn from mistakes and to find impactful and sustainable solutions.

2.1.1. What is a Design Thinker?

Many individuals have their own personal picture of what a designer is and mostly, would not associate themselves with such a term. Nevertheless, the expression designer is not only limited to creative graphic designers that are working in agencies. There are many professionals who would fall under the term designer, from people that are working in corporations and are trying to implement a new innovative way of thinking to people who are creating a new customer experience (Porcini, 2009). Mauro Porcini puts a lot of emphasis on the fact that describing design is a huge challenge, since design can be anything from recognizing impactful solutions to the personal experience that the answers will originate (Porcini, 2009).

According to Brown design thinkers have four characteristics in common (Brown, 2008):

1. Empathy

Design thinkers have the ability to walk in the shoes of someone else; they view situations from the perspective of other people. This talent allows them to see a lot of thing that others are not able to observe which leads to solutions that are especially tailor-made for the users.

2. Integrative thinking

Integrative thinking allows the design thinker to go beyond simple solutions by seeing and assembling all the noticeable coalitions to a solution. The ability to not confide on the processes that are characterized by an A or B choice, allows them to involve even antithetic solutions.

3. Optimism and Experimentalism

Design thinkers are individuals who are confident that to each existing solution there is another one which is more impactful and feasible for the corresponding stakeholders. By experimenting with new information and the existing circumstances and moreover, by asking the most powerful questions, design thinkers are able to ascertain long-lasting innovations.

4. Collaboration

Another key aspect of the design thinking process is the ability to collaborate with experts from a variety of fields. This talent allows to not only integrating the designers and producers, but also the end user. Moreover, a design thinker him/herself has experience in many different fields and is not only an expert in DT.

2.1.2. The Iterative Steps of Design Thinking

As already mentioned above, there are many ways to describe DT. On top of that, the process may sometimes be described in three, five or six steps in literature. For example, at IDEO, which is one of the leading design consultancies in the world, the designers are working with a five step model (Kelley and Littman, 2004: 6-7).

Figure 1: The IDEO process – a five step method (Kelley and Littman, 2004: 6-7)

However, at the Hasso-Plattner-Institute in Potsdam, the process consists of six steps. The two processes consisting of a different amount of steps only differ in their emphasis on the overall process and a different description but not in their principles (Plattner et al., 2009: 113). In order to describe the process which will later be applied to a case study, the thesis will focus on the six steps process described by Plattner et. al. (Plattner et al., 2009: 114).

Figure 2: Figure 3: The HPI process – a six step model (Plattner et al., 2009)

Understand

The iterative DT process starts with a phase called understanding, which includes defining the problem and explaining the scope. Defining the so called Design Challenge (DC) is crucial for the success of the method since the whole team working on the challenge needs to have the same understanding of the problem to be solved. Moreover, the target group needs to be identified by the team in order to be able to move to the next phase. In the first phase, the emphasis is put on obtaining the knowledge that is required to solve the formulated DC.

Observe

The aim of the second phase is to become an expert. The DT team observes all the existing solutions to the identified problem and challenges them; more specifically the team tries to improve their understanding why there has not been an adequate solution up to that point. The team tries to get a 360° degree view on the problem, integrating all participants and people affected. One of the main activities in this phase is the direct contact with the future users or clients of the product/service for the intended solution. It is crucial to involve the future users since those people are building the target group and know what their wishes, requirements, way of behaviour and needs are. In addition, the team needs to examine carefully the processes and ways of behaviour. In order to do so the team needs to walk in the shoes of the end users. In sum, the second phase emphasises the need to reproduce the end user’s ways of behaviour while being able to fully understand the end user’s perspective.

Point of View

The third phase, called point of view, is the stage where all the findings from the previous phases are interpreted and evaluated. Since in most cases the team has branched out in the second phase, this phase brings everyone together in order to exchange findings. The team will segregate the relevant facts from the dispensable information. This separation helps to define the point of view more precisely which will lighten the fourth phase for the whole team. A method which is often used at this stage is the creation of a persona. A persona is a fictive and ideal-typical end user of the product or service. During this exercise the whole team deploys their findings from the second stage, the observing phase, with the aim to find the right viewing angle on the DC. For the purpose of finding the right perspective, it is important to question and realign the problem from a huge variety of different viewing angles. Recapitulatory, during the third phase the team assembles the key aspects from the end users in order to be able to start finding ideas in the next phase.

Ideate

The ideation phase is characterized by the reorientation of the team’s thinking process from divergent to convergent thinking. In the beginning of the phase, the team is still in a divergent thought process – the group of people is generating as many ideas for a solution as possible. All these concepts should contain a potential solution to the DC and should not be debated by the team in the beginning. It is a phase during which the team experiments with a variety of ideas and invests in the creative thinking process by leaving as much room as possible for everyone to generate constructive ideas.

In contrast to the first half of the ideation phase, the second half is shaped by the convergent method. During the convergent thought process, the team’s goal is to identify the one solution or the best solutions to the DC. This process consists of logical steps towards the exploration of solution/s. There are some creative techniques on how to narrow down the ideas in the ideation phase, for example (Center for Care Innovation, 2013-2014):

1. Sticky note voting: Every team member gets three stickers and places those next to the ideas that are most viable and feasible to him/her. The ideas with the most stickers will be prototyped in the next phase.
2. Idea morphing: Each idea will be presented in front of the whole team. After each presentation the team is looking out for synergies to merge some ideas or mixing some elements.

In sum, during this phase the team generates ideas for the exploration of solutions with the help of the information gathered during the last three phases.

Prototype

This phase appears for many people to be really different to what they have been used to during solution oriented processes. The aim of this phase is to visualize the ideas for the users; thereby, the users are able to give feedback more easily and may also be able test the idea. The prototype should not be the perfect visible idea, but the preproduction model should be able to transfer the message, show the strengths and weaknesses of the idea, and moreover, it should help the team to improve the idea even further. It is a visualization of the idea with the use of, for example, modelling clay, paper, Lego figures, and any material that might be within reach. If the solution is a service function, the prototype might be a theatrical performance. Moreover, some teams create a virtual prototype if the idea that cannot be visualized in a real model. All in all, the intention of the phase is to make an idea come alive and visible to the users.

Test

During the testing phase the idea will be tried out with the user. The most important part of this step is that the idea will be tested with the end users and not only within the DT team itself. The testing phase is about identifying the idea’s strengths and weaknesses together with the end user. It is about identifying mistakes because only from these misconceptions the team can learn and further improve the idea, since it is all about the user who will be making use of the idea. Therefore, the team has to put a lot of emphasis on learning from that experience.

2.2. Decision Analysis

Every human being constantly takes decisions throughout the day. On the one hand, there are many minor decisions from the preference of food each day, the question if one should stay in bed or not, to the colour of clothes someone wants to wear. On the other hand, people face situations where they have to choose whether to take a job or not or which car they would like to purchase. Some decisions have a larger and more significant impact than others; therefore, it is important to understand the consequences of the decisions that are being made (Gregory, 1988: 2).

Decision Analysis is designed to help when dealing with difficult decisions by offering more structure and guidance (Clemen, 1996: 4). DA supports the decision making process: it helps to better and fully understand the obstacles that are connected with having to make a decision and, on top of that, helps to make better choices (Clemen, 1996: 3). Moreover, DA permits the operator to make any decisions in a more effective and consistent way (Clemen, 1996: 4). In consequence, DA is a framework as well as a tool kit for approaching various decisions. Nevertheless, the judgement of each DM differs from person to person. One DM may have a preference which manifests itself in the chosen attributes and alternatives. Another DM may not have a preference and, on top of that, the judgement skills may vary from DM to DM as well (Hwang and Yoon, 1981: 8).

According to Keeney, the DA approach concentrates on five fundamental issues that are elementary for all decisions (Keeney, 1982):

Figure 3: Fundamentals of Decision Analysis (Ralph L. Keeney, 1982)

In order to be able to address multidisciplinary problems, the decision problem is divided into several parts which are analysed and integrated during the DA process (Keeney, 1982). Over the last years, various approaches have been identified, such as the shaped DA process by Keeney or the Multi Attribute Decision Making (MADM) method. The later one supports the decision making when a finite number of alternatives have been identified with various, mostly conflicting attributes.

2.2.1. Decision Analysis Process

Over the last decades, many analysts have been working on modifying and improving the DA steps included in the process; therefore, there are many procedures out there with a common purpose: Choosing the best alternative. Keeney describes the DA process in five major steps (Keeney and Raiffa, 1993: 5-6):

1. Preanalysis

During the first phase the focus is on gathering the alternatives and clarifying the objectives. The decision maker (DM) faces a situation where there is indecisiveness about any steps that are relevant in order to solve the problem. At this stage the problem is already at hand.

2. Structural analysis

At this stage the DM is confronted with structuring the problem. There are several questions that the DM will need to answer; for example, what call can be made? What are the decisions that can be delayed? Is there specific information that supports the choices that could be made? Figure 4 shows a decision tree in which the abovementioned questions are systematically put into place. The decision nodes which are displayed as 1 and 3 (squared) are the nodes that are controlled by the DM and the chance nodes, shown as 2 and 4 (circled), are the nodes which are not fully controlled by the DM.

Figure 4: Schematic form of a decision tree (Keeney and Raiffa, 1993)

3. Uncertainty Analysis

The third phase, called the Uncertainty Analysis, starts with assigning the probabilities to each path that is branching off from the chance nodes (in Figure 4, these are the paths left and right from points 2 and 4). The assignment of the probabilities to the branches of the decision tree is a subjective procedure (Keeney and Raiffa, 1993: 6; Gregory, 1988: 172). Nevertheless, the DM makes the assignments by using a variety of techniques based on experimental data. These assignments will be checked for conformity.

4. Utility or Value Analysis

The objective of the fourth step is the assignment of so called utility values to each path of the decision tree, whereas these represent the consequences connected to that path. The decision path that is shown in Figure 4 represents only one plausible path. In a real problem, many factors will be associated with the path; such as economical costs, psychological costs as well as benefits that the DM considers r