Exploring Design Thinking in developing a dispatch mobile application prototype

Project Proposal Report

Contents
1. Introduction 3
2. Scope, Aims and Objectives 3
3. Methodology 5
4. Project Plan 6
5. Risks and Limitations 8
6. Literature review 8
7. References and Bibliography 15
8. Appendix 16

1. Introduction

This project is about designing and developing a prototype of a Dispatch App for the On-Field Engineers for an IT Company where I am currently employed. The design will be human-centred and will emphasise user experience. The process will start by establishing a series of questioners and interviews with stakeholders involved, developing personas and use cases and afterwards implementing the obtained data in to designing an application prototype in Adobe XD. An agile approach will be used in order to achieve the final design.
The idea of this project appeared as a solution for a major problem that appeared at my workplace. Currently I am employed as On-Site Administrator for the printers within a major organization. We are responsible with maintaining and raising break fix calls for the printers within this company. As the back-office department is still relying on Excel Spreadsheets to keep track of the break fix tickets, quite often there are cases when the engineer is being sent without the proper information or not all the required parts. Also, there is no appropriate way on keeping track of the ticket details, parts required, or engineers assigned to a specific case. My aim is to design an application using an UX approach which will allow to assign Break Fix tickets to a specific engineer, track the engineer position, manage parts required, track ticket progress etc. More requirements will probably be identified during the research phase.

2. Scope, Aims and Objectives

The scope of the project is to develop an UX Design based Dispatch Mobile Application prototype using a design thinking approach. The final product will not be a functional developed application as the focusing is mostly on UX designing phase. The final prototype will be an Adobe XD application which will show menu interaction and navigation of the Dispatch application.
Aims:
1. Project documentation
Objective:
– To find similar projects
– To research different UX design methodologies
– To evaluate UX design research methodologies
– To schedule project tasks

2. User research following UX methodologies
Objectives
– To conduct interviews
– To set up questioners
– To organize focus groups
– To organize card sorting groups

3. Analyse data
Objectives:
– To Brainstorm
– To identify user needs
– To create User Personas
– To create User Stories

4. Design Wireframe
Objectives:
– To set layout and structure
– To hierarchically order the information
– To determine navigation and motion
– To get feedback
– To improve
5. Design Prototype
Objectives:
– To choose colour palette
– To create an Adobe XD prototype

6. Test and improve
Objectives:
– To test prototype
– To get feedback
– To improve prototype
– To create final product

3. Methodology

As the inspiration for this project begins with an issue in the company that I am working in, a design thinking strategy will be followed in order to develop an Adobe XD prototype which will show navigation and interaction between the application windows.
During the research stage, users’ needs will be established through surveys like interviews, questioners, focus groups etc. All the survey participants will need to fill a Non-Disclosure form. Qualitative and Quantitative data collected will be used to create user personas and user stories. Based on this, the Wireframes will be created and afterwards a prototype. Both wireframes and prototype will get feedback from the involved stakeholders and improved accordingly.
For developing the Dispatch Mobile Application, I will use UX design principles following the 5 planes strategy:
– Surface plane
– Skeleton plane
– Structure plane
– Scope plane
– Strategy plane (Garrett, 2011)

Figure 1: User Experience Planes

4. Project Plan

• Milestones:
– Surveys
– Analysis
– Design
– Test
– Implement

• Resources:

– Laptop
– Microsoft Office software
– Adobe XD
– Wireframe design software
– Interview locations
– Focus group locations

• WBS

• Gantt Chart

5. Risks and Limitations

Risks:
– Hardware failure – might lead to loss of data
– Missing or confusing information – can lead to wrong understanding of users’ needs
– Bad data analysing – can lead to wrong understanding of users’ needs
– Not enough survey participants – sample size might me to small for quantitative research
– Time constraints -not respecting the task deadline highlighted in Gantt Chart might lead to future delays

Limitations:
– Software limitations – required training in order to use Adobe XD.
– Research limitations – Sample size, implementation of data collected, lack of similar projects
– Work force limitations – one person might be overwhelmed by the amount of work, especially during the survey phase
– Time limitations – project deadline

6. Literature review

Some of the world major companies like Apple, Google, Samsung have adopted Design thinking approach in developing its products
Design Thinking is an iterative process in which we attempt to understand the consumer, question conclusions, and redefine problems to identify alternative strategies and methods that may not be immediately apparent to our initial level of understanding. At the same time, a solution-based approach to solving problems is offered by Design Thinking.
User Experience Design shares a lot in common with Design Thinking. For example, user comprehension utilising research methods, project, rapid prototyping, user testing. Differences are small. Design thinking is more system-level and struggles more with more difficult problems.
Design Thinking is an iterative process that is not sequential. It simply means that the design team is using their findings constantly to update, challenge, and develop their initial assumptions, understandings, and outcomes. (Plattner, Meinel and Leifer, 2013)
Design thinking has 5 main stages:
– Empathize— search for the needs of your clients.
– Define— Report the needs and concerns of your clients.
– Ideate—Challenge assumptions and concept forming
– Prototype—Start to create solutions.
– Test—Test your solutions

When seen from the bird’s point of view, Design Thinking is like an imaginative people management medication, UX Development is more oriented on products and services.
Using both principles in designing the Dispatch Application will help to improve the design of the final product in a significant way.

Figure 5: Fields of UX Design

Design Thinking involves a detailed consumer behaviour analysis. Based on both qualitative and quantitative research, concerns and issues are identified. The raw data is afterwards analysed and common points are identified building the user persona. Quantitative research offers numerical data gathered on structured models by means of analytical questions. This methodology may provide numerical data on the volume of the sample, but there is no depth, hence the need of qualitative research also.
In order to get a more comprehensive understanding on the application requirements for designing the Dispatch Application both qualitative and quantitative research methodologies have been combined.
Quantitative insights are a good foundation for business decisions guided by numbers and are always seen as’ rock-solid results. The figures for investors are therefore very compelling. Quantitative data, on the other hand, is often difficult to interpret accurately, since you know (or did not) only something happened but do not know why. Those who want to rely exclusively on quantitative data should therefore have a solid knowledge of statistical analysis methods in order to avoid making false conclusions.
Qualitative research is ideal for the presentation of individual studies in numerical analysis. This shows how people feel, their feelings and their motives. Of example, it is helpful to schedule and execute design / UI modifications. But it is very difficult to automate the evaluation and therefore a long-term method that is the main limitation for qualitative data. Because of the above drawbacks, only a small number of participants can be analysed, having less statistical power.
Despite the essence of their distinctions, qualitative approaches are better suited to answer questions on why or how to overcome a dilemma, while quantitative methods discuss how many problems and how many.

Figure 6: Questions answered by research methods across the landscape

Hybrid approaches use an innovative way of consumer use. For example, participatory development approaches enable users to engage with design elements that could form part of a consumer interface and rearrange them in order to discuss whether their ideas are better suited for their needs and why they have chosen.
Some methods on the map can shift one or more dimensions, and some even in the same analysis, to accomplish multiple objectives. Of example, field studies that concentrate on what people are saying or do (ethnographic interviews), desirability tests and the sorting of cards are both subjective and quantitative and eye tracking is possible in scripts or not. (Nielsen Norman Group, 2019)
Next stage is to analyse all the gathered data.
Perhaps the most critical part of the research is data analysis. Poor study yields incorrect findings that not only impair the research’s validity, but also make the results worthless. Data analysis techniques must be chosen carefully in order to ensure the conclusions are accurate and feasible.
As qualitative data consists of terms, explanations, images, objects and sometimes symbols, its analysis differ from the quantitative data analysis. The interpretation of such complex data is a complicated process and is therefore usually used for exploratory research and analysis.
For qualitative research the data analysis process is manual. The researchers usually read available data and find words that are used or repeated in order to identify patterns and connections.

Figure 7: Qualitative data preparation and analysis

Most common used methods to analyse qualitative data are:
– Content analysis
– Narrative analysis
– Discourse analysis
– Grounded theory
Turning raw data into meaningful information represents the first step of quantitative data analysis.
Preparing quantitative data consists of three phases:
– Data Validation
– Data Editing
– Data Coding
– Data Analysis
The two most common used methods to analyse quantitative data are descriptive statistics and inferential statistics.

Figure 8: Quantitative data analysis methods

During the next stage, the defining stage, the design thinkers are synthesising first stage of study and results and are creating user personas. The use of personas is only one way of helping designers move towards the third phase, the ideation phase.
Personas have concrete archetypes to which you can test your project. Creating Personas will help to put the right questions and answer them in accordance with the stakeholders.
The third Design Thinking process stage, Ideation stage, it is significantly overlapping with the Define stage. Interpreting data and identifying challenges and ideas both guide potential solutions to be created. In the process development groups used in these two processes this similarity is reflected.
Some of ideation methods are: Brainstorming, Mindmaping, SCAMPER, Prototyping, Storyboarding, Sketching, Brainwalking, Bodystorming etc.
The next stage, prototype, provides a quick and inexpensive way to provide a model for customers to evaluate. For example, in 2015 Apple had built a prototype Apple watch that was a bigger version of the released product (a full-sized iPhone with a watch like strap attached).
Creating a prototype digitised or even on paper allows end users to view an item. For developers, direct input from customers provides valuable opportunity to observe responses and the design team can use the body language to optimise the final product. (Study.com, 2019)
Prototypes can take many forms and the only thing the different forms have in common is that they are both physical representations of collected ideas. They to be outdated iterations of a finished product, though. Clear diagrams or storyboards used to demonstrate a possible experiential option, rugged paper models for virtual implementations, wireframes, and role acting to provide an idea-provoking experience are model examples.
Prototypes can be simple and raw models with the purpose of early stage testing. They can also be fully developed and detailed for trials or pilot testing experiments.
It is an incentive for innovation to get a brand out into the world and test it in real time. During the testing phase, it can be seen if the problem has been framed correctly.
It is ideal to use a natural environment when running a user test on your prototype. It is critical that consumers use the prototype as much as possible in real life.
Early testing of prototypes is important so that you can quickly correct course if the product hypotheses are wrong.
If users experiencing problems, the design team must revisit its list of possible solutions and strategies so that new ways can be found to solve the same problem. Tests can also help to identify issues that have not previously been noticed. Feedback from users is invaluable; the iterative design process and solution fail without knowing what users need to perform their tasks and activities.
There are a range of directives that you can follow to help you prepare a test:
– Compare alternatives with your users
– Show, do not say, let your user understand you prototype
– Ask users to discuss their experience
– Watch!
– Ask questions on follow-up
– The last test will be our designed solution to the business problem.

The last test will be our designed solution to the business problem. The ultimate objective of each project in Design Thinking is to design a plan that satisfies the necessary, realistic and practical standards.

7. References and Bibliography

• Brannen, J. (n.d.). Mixing methods.
• Dorst, K. (2011). The core of ‘design thinking’ and its application. Design Studies, 32(6), pp.521-532.
• Garrett, J. (2011). The elements of user experience. Berkeley, Calif.: New Riders.
• Kummitha RKR. Design thinking in social organizations: Understanding the role of user engagement. Creative Innovation Management 2019;28:101–112.https://doi.org/10.1111/caim.12300
• Lewrick, M., Link, P. and Leifer, L. (n.d.). The design thinking playbook.
• Medium. (2019). Principles of Design Thinking- (Stages of Design Thinking). [online] Available at: https://uxplanet.org/principles-of-design-thinking-stages-of-design-thinking-b2cc219063ac [Accessed 8 Dec. 2019].
• Nielsen Norman Group. (2019). When to Use Which User-Experience Research Methods. [online] Available at: https://www.nngroup.com/articles/which-ux-research-methods/ [Accessed 7 Dec. 2019].
• Plattner, H., Meinel, C. and Leifer, L. (2013). Design Thinking. Berlin: Springer Berlin.
• Razzouk, R. and Shute, V. (2012). What Is Design Thinking and Why Is It Important?. Review of Educational Research, 82(3), pp.330-348.
• Smashing Magazine. (2019). A Comprehensive Guide To Wireframing And Prototyping — Smashing Magazine. [online] Available at: https://www.smashingmagazine.com/2018/03/guide-wireframing-prototyping/ [Accessed 8 Dec. 2019].
• Study.com. (2019). The Prototype Stage in Design Thinking: Purpose & Importance | Study.com. [online] Available at: https://study.com/academy/lesson/the-prototype-stage-in-design-thinking-purpose-importance.html [Accessed 7 Dec. 2019].
• The Interaction Design Foundation. (2019). What is Design Thinking and Why Is It So Popular?. [online] Available at: https://www.interaction-design.org/literature/article/what-is-design-thinking-and-why-is-it-so-popular [Accessed 6 Dec. 2019].
8. Appendix

• Ethical Approval Form:

admin