Modeling in a UX context is about creating a structured understanding of the system, its users, and their interactions. The purpose is to approach system by identifying key parts and their dynamics, including different forms of interactions. Good UX demands understanding of individuals motivations and ambitions. At the same time it requires understanding of business goals and objectives. The purpose is to transform and map abstract ideas into concrete workable items. This enables teams (of any size) to structure the work so that it addresses user needs while meeting business objectives.
There are many options for modeling. For example:
The question is: which models should one use when working on a UX project? First, it is crucial to understand the motivation of the project itself: what is needed, who needs it, and why it is needed. The need then drives which modeling approaches is to be pursued. Second, the model should provide value in proportion to the investment size. Far too often certain modeling approach is selected without considering the long-term impact. For instance, high-fidelity mock-ups are not necessarily the cost effective approach, but it is often pursued regardless. Reasons vary, but what is common in these cases is the lack of focus on the project needs and context.
The information provided by different models might overlap. In some cases one model can sufficiently answer to questions from different problem area.
Next chapters lists the needs I have found out to be the most common ones. For each need, the suggested modeling approach is listed.
In order to bridge the gap between designers, developers, and stakeholders focus on these:
In large projects with diverse teams and stakeholders, complexity is inevitable. Models break down complexity into manageable parts:
Aim to anchor design in user needs and real-world contexts. By understanding motivations, environments, and challenges, teams can design solutions that solve actual problems.
Make abstract concepts accessible to all team members, including non-designers.
These are the models I believe provide best value for the effort. Remember that each abstraction does not necessarily require extensive deliverables. The modeling itself is not bound to any pre-determined document format. This gives the designer a freedom to choose the right approach. The fundamental philosophy in thinking is that the outcome, i.e. the actualised product or solution, is the primary intent. Everything else is just a description of the intent and should be treated so.
For comprehensive understanding, use journeys to map the overarching flow of user activities and decisions, align them with business goals and business processes, leverage contextual use scenarios to capture user needs and real-world context, employ user stories to describe features from the user's perspective, utilize use cases to define how the system should behave to fulfill those needs, and create prototypes to visualize, test, and iterate on potential solutions.
Steps in this guide can be followed in any order, though it makes sense to go from high abstraction level to lowest. Steps can also be omitted. Each of the activity provides value even if other activities cannot be executed for reason or another. The idea is to outline an activity space that would, if completed, provide solid foundation for succesful project.
Purpose
Key Components
Additional Considerations
This chapter gives an idea of what each object holds. For cross-reference and inspirational purposes the chapter includes models that are not in the "suggested models" chapter.
Attribute | Description | Example |
---|---|---|
Name | The overarching, end-to-end flow of user activities. | Resolving Equipment Downtime |
Stages | High-level phases users pass through during the journey. | Detection → Reporting → Diagnostics → Repair → Validation |
User Goals | Goals users aim to achieve at each stage. | Minimize downtime, restore operational efficiency |
Pain Points | Challenges or obstacles users face during the journey. | Delayed part delivery, incomplete logs |
Opportunities | Design improvements or solutions to enhance the journey. | Real-time data aggregation, predictive maintenance |
Randomness/Variability | Areas where the journey may deviate or introduce unpredictability. | Inconsistent IoT sensor data |
Mapped Business Process | Corresponding business workflow that aligns with the journey. | Equipment Maintenance Process |
Key Metrics | KPIs for evaluating the success of the journey. | Reduce Mean Time to Repair (MTTR) |
Attribute | Description | Example |
---|---|---|
Business Goal Name | The primary organizational objective guiding the project. | Minimize Equipment Downtime |
Objective Statement | A clear, measurable outcome tied to the business goal. | Reduce Mean Time to Repair (MTTR) by 20% |
Supporting Metrics | Quantifiable KPIs to measure progress toward the goal. | MTTR, MTBF (Mean Time Between Failures) |
Strategic Importance | Why achieving this goal is crucial for the business. | Ensures operational efficiency and reduces costs |
Dependencies | Factors or systems critical to achieving the goal. | Reliable IoT infrastructure, skilled technicians |
Attribute | Description | Example |
---|---|---|
Process Name | The structured workflow contributing to a business goal. | Equipment Maintenance Process |
Stages | Key phases or steps in the process. | Issue Reporting → Task Assignment → Diagnostics |
Pain Points | Challenges or inefficiencies in the process. | Communication delays, lack of sensor data |
Opportunities | Areas for improvement to streamline the process. | Centralized tracking system, real-time updates |
Inputs/Triggers | Events or inputs that initiate the process. | IoT alert, operator report |
Outputs/Results | Expected results from completing the process. | Fully repaired and validated equipment |
Key Stakeholders | Roles involved in the process. | Maintenance technicians, managers, operators |
Attribute | Description | Example |
---|---|---|
Name | Persona's name. | Jane Doe |
Role | Their role or position. | Maintenance Technician |
Picture | Visual representation for relatability. | Photo or illustration |
Focus | Key aspect of their interaction with the system. | Diagnosing and fixing equipment |
Notes | Motivations, goals, and challenges. | Needs fast tools; dislikes ambiguity |
Attribute | Description | Example |
---|---|---|
Id | Unique identifier. | #001 |
Group | Logical grouping of related scenarios. | Diagnostics |
Persona | The persona interacting with the system. | John Smith (Maintenance Technician) |
Description | Narrative explanation of the scenario. | Diagnosing a malfunction in a conveyor belt motor. |
User Goal | What the user is trying to achieve. | Identify the root cause of the malfunction. |
Design Hypothesis | Early design ideas for supporting the scenario. | Include offline functionality and highlight probable errors. |
Attribute | Description | Example |
---|---|---|
Role | The type of user or stakeholder. | Maintenance Technician |
Action/Need | What the user wants to do. | Access real-time error codes from equipment sensors |
Purpose/Benefit | Why the user wants to perform this action. | Quickly diagnose and resolve malfunctions |
Full User Story | A complete statement of the story in standard format. | "As a maintenance technician, I want to access real-time error codes so that I can quickly diagnose and resolve malfunctions." |
Dependencies | Resources, systems, or conditions required for the story to work. | IoT-enabled equipment, diagnostic tool |
Outcome | The result or success criteria for the story. | Sensor data retrieved, root cause identified, and repairs initiated |
Attribute | Description | Example |
---|---|---|
Use Case Name | The specific user interaction or task. | Retrieve Diagnostic Error Codes |
Objective | The purpose or goal of the interaction. | Access sensor data to identify equipment errors |
Preconditions | What must be true or available before the use case can occur. | Equipment must be powered on, and sensors must be functional |
Steps | The sequence of actions required to complete the task. | 1. Open diagnostic tool → 2. Query sensor logs |
Outcome | The expected result or deliverable of the use case. | Error codes retrieved and displayed to the technician |
Pain Points | Potential challenges in executing the use case. | Network latency or missing sensor data |
Opportunities | Improvements to streamline or enhance the task. | Real-time fault aggregation, prioritization of critical errors. |
Dependencies | Tools, systems, or data required for the task. | IoT platform, diagnostic tool, centralized database |
Journey
Business Goal
Business Process
Persona
Contextual Use Scenario
User Story
Use Case
Functionalities
This document outlines a structured approach to UX design, focusing on creating meaningful deliverables and aligning design efforts with business objectives, particularly in industrial contexts. By leveraging key concepts like Journeys, Business Goals, Processes, Personas, Contextual Use Scenarios, and Use Cases, the methodology ensures clarity, consistency, and practical application throughout the project lifecycle.
By using these models as a basis for structuring design it is possible to align and glue design and development activities together to support common goal, which is (or should be) to build usable solutions to real problems. Centering the design activity to Contextual Use Scenarios is not a design or development paradigm, rather it is a modelling technique and deliverable format.
The approach can be adapted in almost any kind of development setting. The only thing needed is to select models and start defining them. The best part is that generating the definitions is always worth it for the designer, even if rest of the development pipeline is following other methodologies and conventions. If the modeling is based on the need the investement is never going to waste.
The approach aims to focus on the all aspects of solution design and development, but only producing relevant artefacts. By minimising unncessary work the final deliverables are made cost-effectively. The results are very likely to be intuitive and financial risks of the project are kept in control. Even in unfortunate cases where the project misses the mark it is unlikely to produce deliverable waste. This is because the idea is to generate only content that is useful in the context.