Despite our 80+ hour work week and tight timeframe, we cracked open Indi Young’s Mental Models. Mental Modeling is a methodology and design strategy that investigates the mental spaces of users to understand their patterns and behaviors. We believed mental modeling was applicable to synthesizing our data because it represents the goal of the user in the context of their domain (Young; 12.122). We knew that thoroughly understanding the mental spaces of our users would establish the foundation of our design.

“Designing something requires that you completely understand what a person wants to get done.” - Indie Young

After reading Mental Models, we applied the methodology to our research. First we thoroughly combed through the interviews pulling out data based on task. Task groups are divided into 5 sections: 

  • Task: Any action to accomplish a goal
  • Third party task: an action that someone else accomplishes
  • Implied task: an ambitious action
  • Philosophy: the why behind an action
  • Feeling: the way someone feels about a particular topic.

This was a tedious process considering the interviews were over an hour in length each and densely packed with data. However, pulling tasks provided a wealth of information regarding user insights.

The idea highlighted by Young was, rather than forcing tasks into predetermined categories, let the tasks organizes themselves into clusters of relative data. By doing this, the data highlighted common task flows, pain points and frustrations, and feature engagement and gaps in a highly structured layout. 

These included:

  • Disorganization of pertinent features such as inventory of links
  • Redundancies of inventory information
  • When working in teams, users can’t see when other users edited information such as auditing inventory and commenting on sitemaps
  • Lack of clarity of information in the auditing feature
  • Lacking the ability to export specific information: For example key words words, headers, and labels were non exportable
  • Lack of the ability to filter certain information

The visual formatting of the mental model included task groups, represented in towers, and mental spaces represented as a series of task groups. Below the mental spaces are boxes representing features within the software.

The mental modeling process allowed us to identify broad behaviors and frustrations relating to the user’s understand of Dynomapper. Furthermore, it allowed us to validate our assumptions and highlight usability issues. This includes the current dashboard and information architecture did not provide users with clear options, the software is lacking features that hinders the user’s work flow, and that users want a snap shot of information upon login in the form of a dashboard. 

 

Following the mental model, we developed a journey map out of the data gathered from the ethnographic interviews. We pulled data points from the mental model to portray a journey in which the user maps and redesigns a client website. We did this to underline the way in which a user engages with the software and to highlight features gaps, pain points, and opportunities. Creating the journey map was one of may favorite parts of the Dynomapper project because I felt I could emphasize my research skills and background in a creative and visually compelling form. 

 

After we tediously synthesized the data into a visual format, we developed a a problem statement and a set of design principles based on the research.  We emphasized the idea that scale matters in the digital world. Makers and managers dealing with massive projects deserve a product that can balance complexity with accessibility in dealing with unique challenges of scale.

We followed this with principles that guided our design and reflected our user's goals and mental spaces.

Design Principles:

  • Accommodating:
    • An accommodating approach guides managers/makers through the complex process of building great digital products.
  • Adaptive:
    • sitemapping can be utilized by a variety of different roles and we must adapt our approach to each as far as appropriate.
  • Precise:
    • precise details are required for outstanding executions of complex digital products

Crafting the problem statement and design principles, along with synthesizing  user data, allowed us to define priorities and align the scope of our project.

Project Scope & Priority:

  • Dashboard:
    • Provide an information snapshot to keep professionals up to pace
  • Inventory:
    • Reconfigure the inventory page preserving the original intention while giving the feature new life.
  • Teams Tab: we integrated all stakeholder related functions including user permissions, comments, and recent activity in one tab titled "team."
  • Analytics: Provide detailed analytics without irrelevant masses of data to hamper your work flow.

We presented our research and visual deliverables to our client after the research sprint. This was challenging because we had to explain the variety of issues highlighted within the software. Critical conversations are difficult, but because we had compelling research to back up our ideas, it was much easier to persuade the client to buy in on the design process.