CASE STUDY: UPS
United Parcel Service (UPS) is an American multinational shipping & receiving and supply chain management company founded in 1907. UPS has grown to become a Fortune 500 company and one of the world's largest shipping couriers.
Service
Lead UX Designer
Client
UPS
Experience
User Research, User Experience, IA, Design Thinking, Visual Design, Interaction Design
THE IDEA
Automate the unload process and provide supervisors with a web based application that would advise in best protocol for scheduling, door assignment, and staffing to maximize business and user goals.
MY ROLE
Owned end-to-end user experience for multiple applications, with a focus on strategy to solidify product path. Worked with stakeholders, product owner, and developers, as a multi-disciplinary agile team. Collaborated with the entire team while facilitating a design thinking workshop at the corporate office in New Jersey, from conception to implementation and delivery.
User Research, User Experience, Visual Design, Interaction Design
THE TOOLS
Sketch, Figma, Mural, Axure, Abstract
THE APPROACH
From the start of the project we opted for a structured approach to product design, thus adopting a sprint framework. This helped us breakdown each step of the process into digestible and workable bits, giving us a clear vision of the project goals up front. Our efficiency improved, making us capable of quickly solving complex problems, which allowed us to produce a usable prototype in a shorter amount of time. I started on the discovery track, exploring opportunities while facilitating a design thinking workshop to align business needs and users.
PROJECT OVERVIEW
For UPS, supervisors' scheduling is everything. Knowing when to expect the arrival and departure of trailers, which doors to assign each trailer, and coordinating proper staffing, is a delicate balance. Supervisor's, many which had been long time employees, used only clipboards and daily printouts to manage this process.
THE PROBLEM
Guided by the above, we were tasked to help design and deliver a solution that would automate this process keeping user pain points and their journey in mind. After a discovery phase, we narrowed our findings. We discovered that a lot of the users had similar pain points with regards to when to schedule staff breaks, the most efficient unloading process, and how to efficiently utilize time. There was no official record of daily events, with the clipboard and paperwork discarded daily.
RESEARCH
To discover and better understand the supervisors' (users) needs, we took a multi-layered approach to research. The team agreed to get together for a design thinking workshop, where we'd codify our goals and constraints, before starting to draft wireframes or mockups. In addition to the design thinking workshop activities, listed below, we also did interviews with experts and users. Additionally we conducted a contextual inquiry by visiting a UPS package facility, to help gain an understanding of how supervisors interacted with technology in their current work environment.
DISCOVERY: EXPERT INTERVIEWS
In order to get a good overview about benchmarks, user journeys, current processes, and pain points, we conducted expert interviews with industrial engineers, and business experts. These interviews gave us in depth insights into the constraints of building an algorithm to support a trustworthy automated system.
DISCOVERY: USER INTERVIEWS
I lobbied for the team to gather a focus group of supervisors (end users). We were able to sit down with a control group of nine supervisors to ask open ended questions and gather information on pain points. This allowed us to better understand the tribal knowledge that the supervisor's depended on. Additionally, these interviews helped uncover why they weren't using the current apps at their disposal: because it slowed them down. Within the fast pace of the working environment, user's needed to be able to glance at a device and glean information. This focus group prompted me to the next step: a contextual inquiry, to better understand the workplace environment and flows.
DISCOVERY: CONTEXTUAL INQUIRY
Next, we further developed a strategy by seeking out contextual inquiries from a visit to a UPS package facility. There, we viewed the unload process in person in which we observed a fast paced environment, with multiple conveyor belts, running an operation with little room for breaks. Here, we observed that our users did not have the ability to be continually interacting with their phones while doing their essential work. The environment was fast paced, cautionary, and busy, with many of our users continually running from one end to the room to the other.
DISCOVERY: DESIGN THINKING WORKSHOP
Guided by the above research, we decided to gather the agile team together to boil down the essentials for this feature. I flew to New Jersey and set up a two day Design Thinking Workshop to include our team of stakeholders, business analysts, industrial engineers, and development to gauge what was feasible. Coming from an agile perspective, we engaged the business to loosely define requirements and key points to hit home. From "How Might We?" to card sorting, to persona creation, we defined the essentials to start working.
The team appreciated this process complimenting that it was the "quickest" way to collaborate and hear everyone on the team. I ensured that everyone was heard by utilizing different design thinking techniques to give everyone a voice, not just based on seniority.
EXPLORING OPPORTUNITIES TO UNDERSTAND
How might we...
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Make an algorithm to automate the unload process that is more efficient than what the supervisor's were already doing? Can we design something better than utilizing their current tribal knowledge, the simple clipboard, paper, and a pen?
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Make an application that gave notifications at the right time, keeping in mind the safety issues of a fast paced package handling center?
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Create an end-to-end experience that helps supervisor's plan, schedule, balance the employees, and work shift to maximize efficiency?
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Build trust and buy in with end users?
These "how might we" questions drove our exploration and experimentation for whiteboarding concepts.
EXPLORING DESIGN TREATMENTS
After our discovery phase I concluded that it would be most valuable for the users to see past, present and future trailers on the screen, to most effectively make informed decisions. We explored creating a gantt style view. After creating some paper prototypes to get immediate feedback from the supervisors, we found out that this design solution felt cumbersome for the fast paced environment. Remember, the facility they work in has multiple platforms, people, and packages coming out of trucks. Users needed a more comprehensive way to see the status at a glance.
Thinking further, I designed three options and broke down pro's and cons for each solution. Ultimately, after trying out the obvious timeline solutions I came up with, the third option below, encompassing all of the needs for the user to be able to glance at their phone during a very busy environment. Supervisor's simply didn't have enough time to constantly swipe left and right. Rather, they needed to see how many trailers have been unloaded, what trailer is currently being unloaded, how close it is to its completion, and the ability to see what trailer was coming immediately thereafter.
Unloaded empty trailers
Current trailer being unloaded
The final solution was a HUGE success with business. The ability to see the past, present, and future on the screen at once was a great help for busy supervisor's tasked to gauge important information fast.
Next Trailer in line to be unloaded
ITERATING & VALIDATING ASSUMPTIONS
After we prototyped the feature and had users test it through loops of feedback, we learned that the final design treatment was a success -- with positive feedback from users.
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With an agile approach, we continued to collaborate with the cross functional team to bring the design into production. In validating our design solutions through user testing, our solution showed a 17% increase in productivity of unloading trucks within the first two weeks of implementation. Comments from users were positive and as time passed, that confidence grew.
IMPACT
We successfully launched the feature in September 2019. There was certainly more iteration to be done to increase the ability of the algorithm for the feature to actually be useful to the supervisors (users). However, the overall design was solid and will continue to be more effective as the machine learning starts to take over and give more time-accurate results. The high impact is the data given back to leadership to better direct, pivot, and to better manage staffing and productivity. I am proud of our efforts and was honored to be a part of this project. They had an increase of 12% in productivity and this was only the beginning.