PKeye™ Mobile Operations Monitor

Our proof of concept (POC) effectively allowed for testing instruments to use the PKeye to send text and email notifications, accompanied by a video, to lab staff in the event of an instrument testing fault. 

A select group was identified for beta testing and user research using the PKeye POC. Due to heightened safety precautions, beta testers were asked to maintain experience diaries. These diary studies revealed recurring themes among users, providing valuable insights into user goals.

Our initial findings from the PKeye POC user research enabled us to communicate opportunities to PerkinElmer. PerkinElmer had a clear vision for PKeye: to enhance laboratory efficiency. By aligning this vision with our user insights, we defined three business objectives. Utilizing existing metrics, we established baselines for key results supporting out business objectives and collaborated with PerkinElmer to determine the degree of improvement needed—categorized as "minimal," "moderate," and "significant." We then identified  metrics suitable for each  key result.  Each objective was documented in a one-page summary, detailing key results and projected product phase.

We proposed a Future State Blueprint that addressed the necessary infrastructure to tackle key insights collected:

• Remote Monitoring Capabilities: Ensuring compliance with social distancing guidelines and reducing the number of  staff on the floor.
• Consumable Monitoring: Managing low stock levels and interfacing with the ordering platform for clients contracted with PerkinElmer.
• Seamless Integration: Ensuring compatibility with existing laboratory infrastructure to facilitate real-time reporting and minimize disruption.

Upon PerkinElmer's approval of the Future State Blueprint, the development team initiated technical spike work while the experience team focused on solutioning additional key insights .

Collaborating with subject matter experts (SMEs) and leveraging data collected during user research, we designed and tested desktop and mobile prototypes with Lab Technicians and Lab Managers to provide solutions for:

• Fault Prevention: Reporting on types of faults by user and directing repeat fault types among users to additional training.
• Faster Fault Resolution: Cataloguing user notes on fixes and enabling user forwarding faults to floats.
• Lab Performance Reporting: Allowing managers to view sample processing times, projections for samples processed within specific durations, and historical data by custom ranges or trends in intake.

Prototype testing results were evaluated using Single Usability Metrics and assessed against key results related to applicable objectives. In instances where progress indicated that key results might not be achieved within six months post-MVP release, concepts were iterated and retested to achieve more favorable outcomes. Features proposed were then compiled into a backlog.