— UTILIZING AI TO CREATE BOTH A REACTIVE & PROACTIVE PLATFORM
orchid: logistics reimagined
Produced in partnership with SAS, Orchid is a hypothetical logistics software that focuses on simulating & enacting changes through a digital twin to prevent yield loss; protecting the profit of Deca Foods. Featuring striking 3D models and a sleek dark-mode, color-accessible interface, Orchid is an ideal product for monitoring and adjusting multiple nodes for any employee of Deca.
OBJECTIVE
Creating a feature within a software suite that tackles food waste for a fictional Deca Foods, focusing on simulation and enactment to forge a proactive response to potential disaster.
AUDIENCE
Luigi, the Logistics Manager at Deca. He has 15 years of experience in the field and has struggled with sudden disasters as a result of the current lacking, outdated, and unreliable suite.
TEAM
Tucker Baumgartner - 3D Modeling, Video Editing, Ideation
Peyton Tucker - Wireframing, Ideation, Prototyping
Vaishnavi Parni - Prototyping, Ideation, Research
MY ROLE
Ideation
Wireframing & Animations
Prototyping & Visual Design
One of the preliminary screens created during our refinement stages
background
THE ASSIGNMENT, THE GOAL, & THE RESEARCH
Since this is a SAS-sponsored project, the prompt was provided by their design team. With a timeframe of around 2 1/2 months, we were presented with the task of creating a feature within a larger software suite that focused on simulating and enacting alternative solutions. Our team began by creating the 'worst-case' scenario to pull out potential pain and gain points that we would later address with our interface proposals. Pulling from video games for inspiration, Orchid took shape.
market research
CURRENT IOT SUITES & HOW WE DIFFERENTIATE
Before diving into ideation, we first looked at existing IoT suites and how each product tried to market its advantages over other competitors. We specifically focused on Azure and Particle since one is Azure is considered a standard for some companies and Particle is marketed for start-ups who can't necessarily afford an investment like Azure. We assessed their UIs, the sensors they offer, and general novelties that make them unique in order to see what Orchid could potentially fill the gaps for.
the persona
From a set of 3 pre-made personas, we decided that having a logistics manager be our target user made the most sense for Orchid. Overseeing the transportation and inventory management for Deca Foods, Luigi can reliably use our application to gauge how each region (down to specific farm plots) is performing and what factors can improve rice production. Though we focused on Luigi, we made sure that the platform was also easy to navigate for the remaining two personas.
the process
FIGURING OUT WHAT ORCHID WILL BE
We knew that we would be creating a platform that monitored and stored data so that any simulation that is run is as accurate as possible. Current IoT systems rely heavily on an internet connection, which could easily be wiped out by a storm. This would leave users without any data, turning to educated guesses and shots in the dark in order to find solutions until connection could be regained. We first began by creating a detailed user journey map that pinpointed any problems that Luigi would encounter without a proactive platform.
the user journey
This user journey served as the blueprint for the rest of our project. We determined that focusing on rice provided us with plenty of opportunities and allowed us to solidify our storyline. Rice is a staple crop that does not require much maintenance in post-production and it happens to be that India is predicted to become one of the biggest, if not the biggest, producers of rice in the next several years. Having Deca Food's rice infrastructure set in India also provided us with unique logistical challenges as India is a developing country and the rice production relied heavily on monsoon cycles to properly grow. With an unexpected monsoon occurring as a result of climate change, Luigi needs to be able to predict the previously unpredictable.
ideation
Taking time to develop low-fidelity wireframes, visual design guidelines, and solidifying our timelines allowed us to strengthen our foundation as we headed toward final edits and screens. We mapped out key screens that followed our updated user journey and used them as markers in the final set of wireframes. With the push from a SAS employee during a critique, we searched for colors that were high contrast enough in order to increase the accessibility of our product as well.
An early screen of Orchid
developing orchid
Once we decided on a visual language, we moved forward with finalizing details and correcting the hierarchy of each element. This aided us in creating a polished final deliverable - every major screen was edited using feedback so every in-between screen could use the same framework. This allowed us to flesh out the capabilities of Orchid to the degree that we needed them.
WHAT ORCHID IS
An innovative mobile & desktop platform that augments logistics management with artificial intelligence. Using live, sensor, and historical data paired with predictive machine learning, Orchid helps make quick decisions with precision. Each workspace reflects the user and the recommendations presented to them to simplify (or expand upon) the inventory management system.
WHAT ORCHID FEATURES
A dynamic abstract map paired with an equally dynamic sidebar. As a user zooms in, they are presented with more data about the hexes in view. Orchid also knows that user intervention is key to solving logistics problems, so any decision made by a human or Orchid's AI is kept in a log that allows for easy reverting and general management for Deca Foods.
the final product
HIGH-FIDELITY SCREENS & INTERACTIONS
We developed 48 high-fidelity wireframes for our final product, accompanied by two 3D models that showcase a more detailed view of each farm and connecting railways. These screens showcase Luigi's interaction with both a mobile and desktop interface that allows him to properly prepare Deca Foods for the looming monsoon.
the mobile app
This mobile app serves as an on-the-go touchpoint in case of emergency. Luigi interacts with this when he is sent a push notification that alerts him of the potential monsoon, giving him the opportunity to make quick decisions that can lessen the damage on Deca's farms. In our scenario, Luigi is off the clock when he is alerted of dangerous weather conditions, so this app allows him to send out an advisory bulletin to the farmers in India. Utilizing (conveniently placed) AI-generated action recommendations, he can simply swipe left or right to enact or discard certain options.
the desktop application
Orchid's capabilities are fully captured in the desktop application. Here Luigi can simulate and enact changes to Deca Foods' system using AI and machine learning to simplify the experience. To avoid overwhelming Luigi with too much data, the interface's details scale by how zoomed in a user is on the map. With Twin Mode (the simulation mode!) and a system that is constantly evolving, Luigi can easily trust Orchid to provide him with recommendations that accurately reflect his own decision-making. All decisions are accounted for in the "Log" tab as well, allowing Luigi the option to revert user or system-made changes before or after committing them to the live system. Orchid is designed to suit each user, so if someone at Deca that is not in the logistics department needs to use Orchid, it will shift to make their experience the best it can be.
takeaways
VISUALIZING DATA IN A MORE... INTERESTING WAY
Having the chance to work alongside SAS was an incredibly unique experience that I am honored to have had. Approaching this project with two game enthusiasts (one of them being myself) and with high ambitions, I knew that we could accomplish what we set our minds to even with only a couple of weeks. I am very proud of Orchid and my teammates! Tackling data visualization with the only boundary being that our deliverable had to demonstrate simulating & enacting changes to a system gave us the opportunity to explore a different approach to logistics software that has capabilities that graphs and lines of data cannot show. This partnership with SAS opened our eyes to the current and future potential of sensor data and artificial intelligence, leaving us excited for what is to come for design.
the video