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Understanding the usability of SmartLab in the Quality Control lab

Background

SmartLab is a web-based management platform specifically designed to streamline and enhance operations within Quality Control Laboratories. Developed as a comprehensive solution, SmartLab aims to support a wide range of activities involved in the quality control lab. 

SmartLab has been successfully implemented in more than 100 laboratories worldwide, establishing itself as a trusted tool for efficient lab management. 

In March 2021, a prominent pharmaceutical company in Los Angeles recognized the potential of SmartLab to optimize their quality control lab's operations and decided to implement the platform. With the expectation of enhancing productivity and streamlining processes, the company embraced the solution. However, after it's deployment, management soon realized that the anticipated utilization of SmartLab was significantly low. This realization prompted the need for an in-depth examination of factors contributing to the underutilization of the platform. 

By conducting a thorough UX case study, the company aimed to identify the pain points, challenges, and user experience barriers hindering the effective adoption of SmartLab within their organization. 

Problem Statement

The implementation of SmartLab in the quality control lab of a pharmaceutical company in Los Angeles has not resulted in the desired level of user adoption. Currently, analyst are not incorporating SmartLab into their daily workflow, which undermines the company's efforts toward digitalization and automation. The objective is to gain an understanding of the analysts reluctance to use SmartLab and identify strategies to increase its utilization within the quality control lab, thereby maximizing the company's investment in a more digital and automated workforce. 

My Role

UX Researcher

Timeline

3 Months

Tools

SurveyMonkey, Microsoft Teams, Miro

Methodology

Survey, Usability Test, User Interviews

Objectives

One

To understand the reasons why analysts in the lab are not utilizing SmartLab. 

Two

To evaluate the usability of SmartLab from the perspective of the analyst.

Three

To identify any pain points, challenges or usability issues that may hinder the analysts adoption and utilization of SmartLab. 

Participant Recruitment

To ensure comprehensive insights and representation across all shifts, the recruitment process for this study involved multiple stages.

Firstly, a survey was distributed via email to all shifts, including day, swing, night, weekend swing, and weekend night shifts, targeting a total of 44 analysts. The purpose of the survey was to gather preliminary information and identify potential participants for further stages of the study.

For the subsequent user interviews and usability tests, supervisors played a key role in participant selection.

Survey

To investigate the reasons behind underutilization of SmartLab in the lab, we conducted a survey using SurveyMonkey. The survey consisted of both qualitative and quantitative questions to gather insights from analysts. The qualitative responses were then organized and analyzed using Miro to identify common themes and perspectives. 

A total of 18 analysts participated in the survey. 

Qualitative:

  1. In your own words, what is SmartLab and what value does it bring into our lab? 

  2. What was your first impression when you first started using SmartLab? 

  3. If you could improve one thing about SmartLab, what would it be? 

  4. Many people are currently not using SmartLab. In your opinion, why do you think that is?

  5. How can we get more people to start using SmartLab?

Quantiative:

  1. Using SmartLab, how comfortable are you assigning tasks to yourself?

  2. Using SmartLab, how comfortable are you adding “Lab Support”?

  3. Using SmartLab, how comfortable are you re-assigning tasks to yourself?

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Insights: Survey

Navigation Challenges

Analyst reported difficulties in navigating the SmartLab platform. They found it challenging to locate specific features, access relevant information, and move seamlessly between different sections or modules within the system. 

Complex and difficult to understand

Participants expressed frustration with the complexity of SmartLab, finding it difficult to understand and operate. They indicated a need for clearer instruction, intuitive interfaces,  and simplified workflows to enhance their comprehension and ease of use. 

Perceived increase in workload

Analyst expressed concerns that instead of alleviating their workload, SmartLab created additional work. They reported experiencing inefficiencies, increased data entry efforts, and a lack of integration with existing laboratory processes, resulting in a perceived negative impact on their productivity. 

User Interviews

User interviews conducted in the this study aimed to understand the the feelings and thoughts of SmartLab usage from the the perspective of the analyst. We wanted to: 

1. Understand the user's perspectives. The interviews provide an opportunity to gather firsthand insights and feedback from the analyst who interact with SmartLab on a regular basis. By capturing their perspectives, experiences, and challenges, we can gain valuable insights into how the platform alights with their needs and expectations. 

2. Explore ways SmartLab can be successfully integrated into the analyst workflow. By understanding the current process, responsibilities, and pain points enables us to identify opportunities.to optimize and streamline the adoption of SmartLab within their daily routines. 

Analyst

“I feel like they should have made sure SmartLab was working first. SmartLab takes too long. What takes 4 steps, takes about 30 with SmartLab. I don't think that's efficient"

Analyst

"It's more work to use SmartLab than it is doing our job. The program doesn't work. I spent over an hour and a half looking for the sample to test, it turns out there was communication issue between SmartLab and LIMS. I didn't find out until three days later. "

Analyst

“They made us watch a 2.5 hour video without any hands-on training. It felt like they launched SmartLab and expected us, the analysts to figure it out on our own”

Insights: User Interview

Lack of knowledge and training

Analyst expressed a general lack of knowledge and understanding of how to use SmartLab effectively. The mentioned difficulties initiating tasks and expressed confusion about specific functionalities such as adding samples, assigning samples to themselves, and entering information. Additional, analyst found that the training provided for SmartLab to be challenging to comprehend. 

Insufficient Support

Analysts mentioned a lack of on going support and assistance after initial training. When issues arose, such as difficulties in locating samples, analysts were expecting to reach out to a Subject Matter Expert (SME). However, the availability of the SME was limited to specific days and times, resulting in delays and potential interruptions in their workflow. 

Learning Curve

Analysts mentioned that there was a large learning curve when learning SmartLab. One analyst mentioned the amount of time spent clicking around the platform to figure out its functionality. This suggested a less intuitive user experience. 

Participant 1

“The training was difficult to understand "

Participant 2

"I always feel stupid for not knowing how to use SmartLab. I always have to ask someone to help me" 

Participant 3 

“I learned SmartLab on my own and sometimes got help. But it took me awhile to figure it out. When I had time, I would just start clicking around and learned it that way”

Usability Test

The usability test conducted aimed to provide insights into the user experience and task completion with SmartLab. 

We observed the analyst while completing tasks using Smart Lab and we encouraged analyst to verbalize their thoughts and decision making process throughout the task execution. This approach provided insights into their user experience, identified challenges, and potential improvements. 

During the usability test, participants were asked to complete the following tasks:

1. Adding a sample: Analysts were asked to demonstrate how they would add a new sample to their list of tasks using SmartLab. 

2. Taking over a turned-over sample: Participants were presented with a sample that had been handed over by the previous shift, and they were asked to demonstrate how they would take over and assign it to themselves with SmartLab. 

3. Re-assigning roles: Participants were prompted to show how they would enter their role as the Work Flow Lead into SmartLab. 

A total of 3 analysts were chosen to participate in this study. Major findings from the participant are included below. Analyst are identified by their user number (e.g., P1 for user1)

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Insights: Usability Test

Lack of training

During the test, it was observed that P1 and P2 were unsure of how to initiate certain tasks in SmartLab. However P2 demonstrated the ability to utilize the Lab Support feature and log in a daily task for one of the laboratory tests. P3, on the other hand, confidently completed all tasks. 

P1 expressed confusion about adding a sample, assigning a turned-over sample, entering Lab Support, and found the training difficult to understand. P2 mentioned feeling inadequate and having to rely on others for assistance. P3 reported a learning curve of about a week or two and learned through self-exploration. 

SmartLab as additional work

Throughout the test, participants expressed dissatisfaction with SmartLab, stating that it created additional work and hindered productivity. Reasons included lack of training, samples not showing up, manual sample search, re-assigning assays against the SmartLab algorithm, and manual starting and ending of assays. 

P1 mentioned SmartLab being a waste of time and questioned the need for the program when LIMS, could provide the required data. P2 felt analyst were always busy and didn't see the need for SmartLab. P3 highlighted the time-consuming nature of learning SmartLab and the impact of staff shortage in the lab. 

Knowledge Gap

Despite a year after its implementation, a significant number of analyst still felt they did not know how to use Smart lab effectively. 

Conclusion

The findings of this study highlighted a few factors contributing to the low usage of SmartLab. 

  • Lack of Training

    • Initial training provided was a comprehensive video session that lasted over an hour. After the launch of SmartLab, analyst were left to find time for self-training, leading to inadequate knowledge and proficiency in using the platform. ​

  • Non-intuitive User Interface

    • The user interface of SmartLab was perceived as non-intuitive and not user-friendly. This made it challenging for analyst to self-learn and navigate the platform effectively. As a result, some analyst resorted to clicking around in an attempt to locate samples, assign or unassign task, which caused further frustration. ​

  • Lack of Support

    • The availability of support was limited, with only one Subject Matter Expert (SME) available during the morning shift and no support during the weekends. The lack of support hindered analysts's ability to seek guidance and resolve issues in a timely manner. ​

Next Steps

To increase SmartLab usage the following steps can be taken:

  • Perform a heuristic evaluation of SmartLab to focus on the usability and user interface to identify areas where the platform can be improved to enhance its intuitiveness, efficiency, and overall user experience

  • Implement recommendations derived from the heuristic evaluation to enhance the user experience and interface design of SmartLab. This may include simplifying complex user flows, improving navigation, and making the interface more intuitive and user friendly. 

  • Develop simple, accessible, and interactive trainings within the SmartLab program. 

  • Collaborate with the Global LIMS team to ensure seamless integration between SmartLab and the internal laboratory information management system so that samples logged in ot the system are accurately mapped and automatically populated onto the SmartQC dashboard. 

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