Unifying the employee Travel Experience

Foundational Research Plan

The first step I took was to lay out an initial plan to better understand the problem. I wanted to establish what we needed to know before we could even start thinking about solutions; before we even started asking questions to our users. This helped structure our high-level questions that would be the groundwork for the research ahead.

To better illustrate the purpose of the research to the team, I wrote out goals showing how the research will help us better understand the current user experience. I also jotted down how different research tools could help gather different data points and perspectives. I set some high-level goals for the solution based on some assumptions that we knew at the time to help show the team what we were trying to do with this overall effort.

Company-wide Survey

I coordinated with Alaska Airlines’ internal communications team as a way to help distribute an initial survey to as many users as possible at once. They happened to be putting together a blog article focused on employee travel at that time, which worked out great because I could easily give them a link to the survey to add to their article.

The survey had a couple of key functions to perform:

• Gather data around the act of traveling itself. How often do our employees travel? Is it work-related or for pleasure? How much do they travel in-network versus utilizing other airlines to get where they want to go?

• Gather what tools our employees use throughout their experience.

• Expose some of the pain points and frustrations of the current experience.

• Gather thoughts and ideas others may have on how to improve the overall experience.

• Recruit employees who would be willing to participate in future research.

Over the course of a couple of weeks, we received 1,281 responses to the survey from across the whole company. We compiled this data into a one-sheet (below) calling out some key findings and grouped them by type (User Experience, Business Rules, and Kudos). These results from this broadcasted survey gave us our first look at the overall sentiments and experience of the employee travel experience from across the company.

Diary Studies

I gathered the list of survey respondents who opted in to help in future research. I then reached to them and was able to gather a small group of willing participants to document and capture their employee travel experiences. I set up the framework and expectations of the diary study and met with each person to go over it in detail. To help capture their input and feedback easier we set them up with a mobile app called Vox, which allowed them to easily capture photos, videos, text, and voice recordings of the key points throughout their diary study. Their apps were connected to our team’s Vox account, so their input was easily centrally gathered on our end of the study.

What this diary study allowed us to do is to see more deeply and intimately into these people’s employee travel experience. It was challenging, though, to maintain complete participation with each person. But, we had enough participation that we were able to condense the data into three ket personas and journey maps.

Personas

The next step was to synthesize all of our data captured from the survey and the diary study into something we could use moving forward. We built out three key personas to represent the participants from the research and the employees of Alaska in general. We made it a point to have each person differ enough in the role within the company, age, stage in career, their primary usage of travel, etc. This allowed these personas to efficiently cover as much ground as possible when using them as decision-making tools and lenses to represent our user’s perspectives throughout the design and testing process.

Journey Maps

The diary studies helps us see deeper and with a more focused eye into the nuances of the employee travel experience. We used our personas to help merge the diary study findings into journey maps. This exercise gave the team a set of tools to reference that showcased the employees task’s and tools being used throughout their travel experience.

Acting on the results

Among the many points exposed by the research, one of them highlighted the confusing way some of the vital content was displayed to employees. The position an employee stands on a flight’s standby list is one of the most important pieces of information for them to know when they travel. When looking into the different tools used an employee uses throughout their process, it was clear that this critical data was not represented consistently across touchpoints. This specific problem became the focus of our team since we owned one of those touchpoints; the employee travel mobile app, Hopper.

Mapping out the data

I wanted to look at the data outside of the tools to see what information was available to the employee at different points in time. This helped show what data was available when and the changes it goes through as it pertains to the context of the employee. Paired with what the goals of the employee are at each of these different points in time, I was able to establish what data should take priority.

Initial Sketches

With two different representations of the same data, both of which are important to the user, I explored how this data could somehow be combined within Hopper simplifying and clarifying the employee’s data source. The employee needs to see are their name and their boarding priority code, which determines where they fall on the priority list. They need to know where they stand and how that priority changes over time as the time to board approaches. After sharing and testing these ideas out with employees I was ready to take the sketches to the next step.

High-fidelity prototypes and testing

One of the things I learned from testing my initial sketches was that visually tying the employee’s name to their boarding priority code brought up privacy concerns from the business team and employees. It showed others what another employee’s boarding priority code is when those employees didn’t opt-in for that info to be shared. So I went through a series of high-fidelity designs and tested them with employees to see which design layout of the information worked best for them. The biggest improvement was how we explain to the user the reasoning behind the order of the priority list. The user could easily see if other passengers were revenue or non-revenue passengers. They could also see who on the list could bump them down if that other employee checked in to that flight. The new designs also explored combining everything into one list and giving the employee the ability to toggle between showing everybody on the list and showing only passengers who are checked in.

Final Design

The final design prototype shows a consolidated priority giving them all of the pertinent information at the right time in their journey. It successfully encapsulates and displays the data clearly for all stages of the employee’s journey making Hopper more reliable, trusted, and the only app an employee would need. This prototype was shared with the overall product team to best communicate how the new functionality and improvements should look and feel to the employees who use it.

Retrospective

One of the long-term goals and intentions of this research and design effort was to establish an ongoing improvement effort of the overall employee travel experience. The research done should be used and updated as a reference tool for further improvements. That said, there was a sense from the team after these designs were completed of, “okay, we solved the problem. We’re done.” I would’ve liked to push more to advocate that this product and experience is a living thing and should be continually attended to. To do that I could have better communicated the research to a larger audience to create more awareness around what problems we should be focused on solving for our employees. Regardless, this research and design effort was the first to reach out to as many employees as we did and to start the improvement process by capturing the bigger picture of the problem space itself.