Designing for Complexity: 5 Key Considerations in High-Fidelity Prototyping

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Complexity is often an unavoidable reality in design, particularly in fields like product design and user experience (UX). Whether it's intricate user interactions, multi-layered functionalities, or sophisticated user interfaces, navigating complexity is a fundamental challenge for designers.

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High-fidelity prototyping emerges as a powerful tool in this journey, offering a robust framework to tackle complexity head-on. In this article, we'll delve into the key considerations when designing for complexity through high-fidelity prototyping.

Key 1: Understanding Complexity

In projects like this, complexity goes hand in hand with the functionality that needs to be addressed. This is especially true regarding a unified system that connects different markets with their peculiarities and needs.

Key components of the system were meant to be Risk Identification, Demand Simulation, and Sales Visualization. At the same time, the system had to be uniform and universal. 

Understanding that each market had its peculiarities in production and supply chains added to the complexities. This, in turn, is reflected in the data structure. All of this was overlaid onto a role model that included a Planner, Market Leader, and Regional Leader. 

To avoid underestimation, we agreed to conduct a series of preliminary meetings with market representatives to update requirements and collect differences. The result was a consolidated document that we referred to throughout the project.

Image showing project achievements: 33 defined user stories, 2 developed personas, and 3 user roles model on a light beige background with dark blue text.
Summary of Achievements

Key Point: Underestimating project complexity carries risks of budget increase or termination of cooperation. 

Key 2: Deep Delve into Business Processes That Are Unique

Every business has its unique features and processes specific to it. Internal procedures and ways of working are quite complex to understand for an outsider. To understand the process from the user's perspective, it was important to first understand what the numbers meant, how to read tables, and where to look for patterns. 

We conducted a series of in-depth meetings dedicated to business nuances. We went through user flows and process details. At that point, we already had a complete picture of how the process worked and were able to identify pain points and areas for improvement as we progressed.

Image displaying key project insights: over 120 hours spent on discovery phase, 5 different markets analyzed, and 1 comprehensive understanding of business processes on a light beige background with dark blue text.
Key Project Insights

Key Point: It is critically important to know the process as well as the manager responsible for it. This way, you can be on the same page as the client and offer truly effective solutions.

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Key 3: Think Outside the Box

At this point, we determined that risk visualization was a key module of the system and an entry point. So, we focused on finding the most suitable solution. We needed to demonstrate the significance of risk considering the cost-to-volume ratio and the coefficient of additional factors.

After several iterations, we came up with the idea of visualization through bubbles where the size indicated significance. Taking into account user roles, we added two levels. For implementation, we chose the Reactflow library, which fully suited the task. We also considered the user's familiar pattern and added a tabular view for risks.

Image illustrating a bubble chart with the text 'Bubble chart' on the left and several dark blue bubbles of different sizes on the right, set against a light beige background.
Bubble Chart

Key Point: Explore the market of innovative tools and propose solutions that go beyond the standards, but do not forget about familiar patterns for users.    

Key 4: User's Always Right

In cases where the prototype needs to cover all markets and all user models, it is important to test hypotheses at early stages. If you do not do this, the risk of not meeting expectations is quite high. Organizing different meetings in different time zones is a difficult task for a manager. However, we did this and got several important lessons.

Despite the warning that we were using unrealistic data in the prototype, the testers still tried to interpret the prototype by reading the data. This led to an incorrect evaluation of the prototype. Nevertheless, we were able to gather the necessary data for improvement. We took into account the previous experience, and the following sessions were more meaningful.

Cultural differences among respondents should also be considered. We encountered a problem of interpreting the same information from different perspectives. The compromise was an extended risk table with a heat map where users could visually identify the degree of risks and their impact on the supply chain. 

Image showing user engagement metrics: 5 feedback sessions to gather feedback and over 30 processed actions-to-be-taken as a result of sessions with end-users, on a light beige background with dark blue text.
User Engagement

Key Point: Conduct feedback sessions as often as your schedule allows. Take into account the cultural differences of the respondents.

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Key 5: Scalability and Flexibility

Complex automation systems are inherent in large companies. In our case, it was a top-10 company in the Fortune 500. We worked on the PoC and understood that the system would need to expand in case of success, so we took this into account early and proposed using the popular AntD component library adapted to the company's brand book.

We also discussed further system development with clients and collected a backlog of potential features. Considering this, independent components were added to the system in the left panel without complicating the current concept.  

Key point: Considering the project's scalability potential and foreseeing future requirements is a strategic method for preventing potential issues in the future.

Summing Up Designing for Complexity

In conclusion, high-fidelity prototyping is a tool for visualizing and testing concepts and a strategic approach to solving complex problems.

Understanding the project's unique features, deep analysis of business processes, creative approach to choosing tools and solutions, constant feedback from users, and consideration of potential scalability and flexibility form the basis of successful prototyping.

Adhering to these principles allows designers to effectively address challenges and create products and interfaces that truly meet users' and business tasks' needs.

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Damian Rodziewicz
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