Thermo Work | Tina Marie Zeng

THERMO FISHER SCIENTIFIC DATA DASHBOARDS

Role: UX Researcher, Wireframing, Testing

Project Type: Data Visualization Dashboards

Date: Mar 2023 - Aug 2023

Background: Thermo Fisher Scientific is a leading science company responsible for supplying analytical instruments and conducting clinical research studies. During my time at the company, I was the lead of an operations and logistics team where we were in charge of handling all equipment used in the vaccines department. One of the major pieces of equipment were pipettes. These were critical for assay use in order to meet client demands.

Challenge: There are around 1400 pipettes stocked in our department. All pipettes need to be sent out every 4-6 months for calibration and when they return from calibration, they must go through a receiving process. Analysts on my team must ensure that pipettes are sent out routinely and that each lab biosuite is always stocked appropriately so it doesn't interrupt client projects. This process generally takes about 20 hours each week for the team to complete.

**Due to privacy agreements some information cannot be shared, including images of the actual product**

Opportunity: Creating a data visualization dashboard that displays all pertinent information for users to access can help improve process efficiency.

RESEARCH

I held multiple meetings with my team to gather thoughts on what works, what doesn't work, and what could be improved with the current sending and receiving pipettes process.

We created a list of pain points:

Some pipettes are forgotten during send outs because analysts cannot locate expiring pipettes
Sometimes the cabinets are not stocked with enough stand by pipettes for analysts to replenish biosuites with
There are two buildings that have to go through this send and receive process, but there's not an effective way to monitor both.
Some pipettes are out for calibration for too long and need to be escalated to the vendor, but there's no way to track this

We were able to outline a new process overview:

Analysts will drop expiring pipettes off in a designated cabinet for an Equipment designee to send out for calibration. Upon drop off, analysts will also grab newly calibrated pipettes to place back into lab. For all ODD numbered biosuites/labs, analysts will be dropping pipettes off the FIRST WEEK of the month for calibration. For all EVEN numbered biosuites/labs, analysts will be dropping pipettes off on the THIRD WEEK of the month. We need our pipette dashboard to have parameters that will allow us to monitor this process and solve the problems listed above.

DESIGN

Through our research, we were able to identify specific pain points. I gathered a small group of my team to perform a how might we exercise to brainstorm possible solutions to the pain points. Once we finished the exercise we were able to outline necessary functions of our dashboard:

Track WHERE pipettes are located – which labs, which biosuites
Track HOW MANY and WHAT KIND of pipettes are on standby in Building A
Track HOW MANY and WHAT KIND of pipettes are on standby in Building B
Track HOW MANY and WHAT KIND of pipettes are expiring in Building A Labs

- Track Odd Biosuites/Labs (Week 1 Trade-in) vs Even Biosuites/Labs (Week 3 Trade-in)

5. Track HOW MANY and WHAT KIND of pipettes are expiring in Building B Labs

- Track Odd Biosuites/Labs (Week 1 Trade-in) vs Even Biosuites/Labs (Week 3 Trade-in)

6. Track HOW MANY and WHAT KIND of pipettes are out for calibration

How do these functions solve our pain points?

For 1:

Allows members to find any pipettes that were forgotten during send outs by having specific locations available

For 2 & 3:

Allows members to ensure each cabinet is stocked appropriately

For 4 & 5

Allows members to monitor throughput in Building A and B for specific trade-in weeks
Can see how many and what kind of pipettes are going to be dropped off, which allows members to check to see if there are enough standby pipettes available for analysts to trade in
Can anticipate high/low throughput weeks

For 6

Allows members to see how many pipettes are out for calibration
Can see how many have been out for calibration for too long, which allows for escalation to vendor

WIREFRAMING AND MOCKUPS

With a concrete list of features mapped out, I moved on to creating wireframes of the data visualization dashboard. This required a lot of back and forth with our developers to see what ideas could be built out and what couldn't be. I started with paper wireframes and eventually moved over to digital ones to send off to the developers.

I designed a home page that includes

a grand overview at the top: how many pipette expiries in Building A, how many expiries in Building B, how many on standby, how many are out for calibration.
- clicking into any of the overviews will allow you to drill into it to view specific details
an expiry charts feature where an overview of Building A vs Building B expiries is shown.
- There are additional filters available to sort between Week 1 and Week 3
a pipette table feature where specific details of each pipette will be listed including the type of pipette, its biosuite location, calibration date, and expiration date
- includes search bar and filters
inventory function that displays:
- a side by side comparison of what type of pipette is stocked in the cabinets and what will be traded in from labs.
- Has an additional feature that displays a side by side comparison of what is stocked in the cabinets and what will be traded in Week 1 or Week 3.
- includes filters to sort between buildings and weeks
**last function is private

USABILITY TESTING

Once the prototypes were built out by our developers, I was able to test it along with a few other members from my team. The main insights from our tests included:

1. Filters are critical for data visualization dashboards. We want our users to have flexibility in how they want to view the data. It's important to include options that provide different perspectives while moving the user closer to the solution.

2. Some of the functions of the filters were not intuitive. The directions on how to apply them are not clear.

3. Some of the screens came out looking cluttered and can easily overwhelm the users. It's important to figure out how to simplify things to create an easier navigation flow.

ITERATIONS

We went through several cycles of iterations and testing to ensure that all parts were moving correctly. The final iteration was reviewed by myself, a couple department managers, and a few other members from my team. Once everyone was in agreement, we released the final product to my entire team for use.

FINAL PRODUCT

The final product was received well by the team and proved to be effective. The team originally spent around 20 hours a week for sending and receiving. This was cut back to 5 hours a week with the help of the data visualization dashboards. Users were able to locate all information critical to performing their tasks easily instead of searching meticulously through database systems before.

**image below is not of real product due to privacy agreements

KEY TAKEAWAYS

This project was an overall huge success for our company. We were able to increase efficiency by 75%. The time we saved from tasking on sending and receiving pipettes was reallocated to other high priority tasks that needed support.

Lessons Learned

Defining clear pain points allows for clear solutions.
User flows are important blueprints for designing processes
It's important to work closely with developers and stakeholders to understand which features can be built out.
Simpler designs tend to be more intuitive designs, which will always save time and resources for the company.