Sofvie Internal Dashboard

Challenge:

My team began our collaboration with Sofvie with their team explaining to us that they would like us to design a client/customer success operations dashboard with their Data Science team to serve as an internal tool for key stakeholders at Sofvie.

The stakeholder goals with this dashboard was to:

Aligning Design Expectations & Technical Requirements

The team provided us with an in-depth list of each data point expected in this dashboard, generated off of discussions they've had with the stakeholders of the company.

They confirmed that the users of this dashboard have different roles at the company including: The CFO, Client & Success, Quality & Services, and Sales. While this is the case, this dashboard should operate the same for any user.

This list outlined the data points that they believed were necessary for the Sofvie team.

User Interviews

With the time and this challenge in mind, we came to the idea of interviewing the key stakeholders of these different teams to learn more about what an ideal dashboard could look like that would aid them in making valuable business conclusions.

Discovering Hierarchies & Relationships

We created an open card sort activity on Figjam and wrote out each data point onto a sticky note.

After having a brief conversation with each key leader about their roles, current processes to come to the conclusions this future dashboard would aid in, and what their expectations were for this dashboard we prompted them with this to hear from their perspective and learn what groupings make sense and hold value to them .

Key Stakeholders are have conflicting understandings of this Dashboard

What we didn’t anticipate, however, was the division in what the key leaders had in mind for the level of complexity and information desired for this dashboard.

Too much data

In particular, during our last interview with the CFO we learned that he had something significantly more simple in mind and actually ruled out several data points included in the list due to confidentiality reasons. Essentially, he had envisioned a simpler version of the specs provided to us by the data analytics team and shared he will hold the most influence when it comes to the actual production of this.

Missing data

Additionally, during the interviews, stakeholders brought up new data points that they would find helpful as well viewing these points at a company level and site level and being able to compare the data to a different time period.

As we began to review the groupings from each key leader’s card sort, we were challenged with trying to find common ground in their results. Our approach was to utilize the home page as the area with the most important points among key leaders.

I came up with an idea of coloring all of the data points that at least 2 key leaders pulled out of the full list pink. Next I suggested creating three rows ordered by a hierarchy of influence. I put the CFO’s data points together that he saw as the ideal homepage and put the 2 key leaders and data science team under. From here we began to eliminate data points that did not seem to hold enough priority and could therefore be relocated to their respective tabs in the dashboard .

This approach ended up being effective and after considering all feedback from the team leads, we were able to provide suggestions on our end for when we next met with the data science team.

Making Executive Decisions

At this point, it was becoming more clear that the data science team’s specs may not align best with the CFO and the key leaders . We determined moving forward it would be best for us to pitch a modified version of our design that better aligned with all the feedback we recieved from all three groups of people at the company.

One major addition to the dashboard was introducing two levels to view all data on the dashboard. The first level was by company, allowing users to view statistics for a particular company and the second level was by site, allowing users to go into the multiple sites one company may have that are using Sofvie's products.

We also included a time range so that the user could not only compare during a custom range, but also allow a comparison of data points in a given time range to the previous week, 30 days, last billing period, etc.

After working through our card sort results/discussions, we grouped the data points into three pages: The Home Page, Engagement, and Customers.

Vouching for our Design

When we shared our low fidelity mockups with the data science team, we went through each chart and resolved all confusions and issues as they came up in one session.

Validating our Design

After completing our high fidelity prototype on Figma, we conducted a user test on the key leaders to assess the usability of the dashboard and observe their interaction with it.

Iterations

The feedback we received across all key stakeholders ended up being quite positive! Aside from minor fixes and suggestions, everyone was satisfied with the functionality of the dashboard and the information it provided and they were grouped.

In our final handoff we provided the team with all of the examples from Chart.js and Python for chart visualizations, all major/minor changes we made to the initial project specs, and all remaining uncertainties we had that were out of our scope of involvement and for their internal team to decide.

R E F L E C T I O N

Communication is Key

I learned as a designer and being part of this process from start to finish the value of talking to key stakeholders. Early on, we learned that there was a disconnect between the groups at Sofvie on what they wanted for this dashboard. Communication played a huge role in resolving this and checking in helped us keep everyone up to date and in agreement - it allowed us to improve this project for the better and resulted in a successful project that everyone was happy with!