Laura Watanabe

Petrifilm™ Plate Manager

Overview

Petrifilm™ Plate Manager is a fully integrated hardware and software system for high-volume food safety labs — automating microbial testing analysis, reducing labor time, and minimizing human error across regulated environments where accuracy and consistency are required.

Company

Neogen/3M

Product

Petrifilm™ Plate Manager

Role

UX Design Lead

Year

2022-2024

Platform

Desktop PC application

Problem statement

Lab technicians using Petrifilm Plate Manager struggle with inconsistent test execution and hard-to-recover errors—often discovering mistakes only after a full run is complete. Without in-context guidance or clear workflow visibility, they lose confidence in their results and spend valuable time repeating tests.

The ideal outcome is a guided workflow that surfaces errors early, supports recovery in the moment.

Design Challenge

How might we create a guided testing experience that helps technicians prevent mistakes, recover quickly, and trust their results without relying on external support?

Objective

Design an MVP that simplifies workflows, standardizes outcomes across technicians, and improves confidence in results.

How I contributed

As UX design lead, I designed a content-aware software system that gives technicians real-time visibility into run status, progress, and results — reducing workflow interruptions through guided error resolution and structured review states that improved traceability and lab throughput.

Process

This case study follows each phase of the project in sequence.

Research ➜ Discover ➜ Define ➜ Ideate ➜ Design ➜ Validate

Target audience

Lab technicians are the primary users — often recent hires trained on-the-job by a manager, without a science or technical background. They work in crowded environments with limited counter space, processing up to 100K samples annually under time pressure. In this context, software reliability isn’t a nice-to-have: a confusing error state or an interrupted workflow doesn’t just slow someone down, it creates risk in a regulated testing environment where results need to be accurate and traceable.

The logos below represent customers across food safety, pharmaceutical, and environmental testing industries:

Proto-personas

Built from support ticket analysis, sales team interviews, and early customer conversations conducted in Q1 2023

Proto-Persona 01 — Jason Pemberton

Works in a food safety testing laboratory
Processes 100–300 samples per day
Performs routine microbial testing using Petrifilm plates
Responsible for reading, recording, and validating test results
Often works under tight turnaround times

“I want to spend my time testing samples, not copying data between systems.”
— Jason Pemberton

Receive and process samples
Incubate Petrifilm plates
Count colonies and verify results
Record findings
Submit results for review

Proto-Persona 02 — Shannon Anderson

Oversees daily laboratory operations
Manages technicians and testing throughput
Responsible for compliance, reporting, and quality assurance
Evaluates technology investments and workflow improvements
Reports performance metrics to leadership

“I need confidence that our data is accurate and that the lab can scale without adding unnecessary overhead.”
— Shannon Anderson

Monitor laboratory capacity
Ensure regulatory compliance
Review and approve results
Track productivity metrics
Optimize staffing and processes

Increase laboratory throughput
Reduce operational risk
Maintain compliance and audit readiness
Improve staff productivity
Standardize processes across technicians

Visibility into testing volumes and performance
Reliable and traceable data management
Automated reporting capabilities
Reduced dependence on manual workflows
Integration with existing laboratory systems

Manual processes limit scalability
Inconsistent data entry creates quality concerns
Difficult to identify trends across testing programs
High labor costs associated with repetitive tasks
Training new technicians requires significant effort

More samples processed with the same staff
Faster turnaround times
Consistent results across technicians
Easier audit preparation
Data that supports operational decisions

Research ➜ Discover ➜ Define ➜ Ideate ➜ Design ➜ ValidatE

Guerilla user testing

At this point in the project, we had a high-fidelity prototype ready and used the IAFP conference as an opportunity for early validation before committing to build.

Through moderated usability testing with real customers, we validated behaviors and system workflows using a high-fidelity software prototype paired with a hardware prototype.

Customer sessions

During the conference, we conducted guerilla usability testing with several key clients. This gave us an opportunity to receive immediate in-the-moment feedback.

I conducted a moderated walk-through with microbiologists or reps from each company.

2

Full workdays

17

Real-world customers

10

Minute testing sessions w/each participant

We found that half of participants weren’t able to integrate their LIMS independently. So we added onboarding documentation and removed the full self-service LIMS setup from the MVP, flagging it as a Phase 2 priority based on session feedback.

78%

of participants

Initially had trouble loading plates and need help getting started.

High Barrier to Entry: Nearly 4 out of 5 users struggle with the physical action of loading plates and require initial guidance.

Create an onboarding walkthrough for plate loading to get users started

50%

of participants

Will need tech-support for Laboratory Information Management System (LIMS) integration.

Technical Integration Gap: Half of the participants cannot integrate with their Laboratory Information Management System (LIMS) independently.

Standardize LIMS with self-service configuration wizard (out of scope)

50%

of participants

Are currently adding barcode labels to each plate manually.

Manual Inefficiency: Half of the users are still manually labeling barcodes.

Automated barcode generation (out of scope)

Research ➜ Discover ➜ Define ➜ Ideate ➜ Design ➜ ValidatE

Core pain points

Each goal maps directly to a pain point identified in synthesis.

Inconsistent workflow & manual setup

Inconsistency in how tests are run and recorded can cause errors and lower confidence in results.

Fragile workflow continuity

Without clear recovery paths or visibility, technicians are forced to restart or guess at fixes.

Ambiguous results

A lack of contextual information makes it difficult for technicians to interpret results accurately or feel certain that a task is complete.

Fragile workflow continuity — technicians described ‘starting over’ as a default recovery strategy because there were no in-app checkpoints or clear error explanations.

Pain Point → Design Goal Mapping

Pain point

Inconsistent workflow & manual setup

Design goal

Efficiency & standardization

Guided workflows

Pain point

Fragile workflow continuity

Design goal

Operational resilience

Error & recovery handling

Pain point

Ambiguous results

Design goal

Informed completion

Review & validate results

Research ➜ Discover ➜ Define ➜ Ideate ➜ Design ➜ ValidatE

Design goals

Each goal maps directly to a pain point identified in synthesis.

Efficiency and Standardization

Minimize manual configuration by utilizing presets and automated inputs. This ensures high-volume processing stays consistent across all technicians, regardless of experience level.

Guided workflows

Operational Resilience

Eliminate workflow fragility by allowing users to pause and resume tasks without data loss. Provide clear, actionable feedback that empowers technicians to resolve errors independently and stay on the 'happy path'.

Error & Recovery handling

Informed Completion

Prioritize critical information at the point of need to reduce cognitive load. By surfacing only what is relevant to the current task, we ensure high confidence in final validation and successful completion.

Review & Validate results

Research ➜ Discover ➜ Define ➜ Ideate ➜ Design ➜ ValidatE

Iterative design

I facilitated two cross-functional workshops with R&D, sales, and the software engineering lead. We mapped the end-to-end workflows on a shared Miro board, identified technical constraints early, and aligned on MVP scope before moving into wireframes.

User interface design (UI)

I established component patterns for status indicators, error states, and result review that could be shared across the Reader Advanced and Automated Feeder workflows. Components were built in Sketch and translated into a reusable library with the development team to ensure consistency across the platform.

Collaboration tools:

Shared functionality and architecture

The Plate Manager software acts as the centralized hub, connecting via shared APIs to both the Petrifilm Plate Reader Advanced and the Automated Feeder — ensuring a single source of truth across hardware configurations.

Wireframe screens to facilitate discussion about requirements

Ideation for user to add more plates to the input bin

Displaying notifications in more than one place

Side-by-side views of legacy and new software

New plate manager UI | Legacy plate manager software

Research ➜ Discover ➜ Define ➜ Ideate ➜ Design ➜ ValidatE

User Acceptance Testing (UAT)

Validating all workflows before launch the product launch. Using 5 key workflows we invited 6 participants, internal experts (customer success, microbiologists & engineers).

Session takeaways

Initiate plate runs

Fast setup with minimal input

Observations

Users need a more explicit first action or system prompt—unclear starting cues increase cognitive load on entry.

50% of users needed help to get started despite the system being ready.

Review results

Clear outputs with high confidence

Observations

Plate images and details could be larger or zoomable to support quick identification.
The system should explicitly display to users all incomplete plates instead of requiring guesswork.

33% of participants encountered unexpected system errors during result review.

Handle exceptions

Resolve issues without breaking workflow

Observations

The system should diagnose device maintenance by providing clear next steps to prevent workflow interruption.
Key transition points require guidance to support continuous workflow.
Exception handling should reduce cognitive load for technicians.

100% of participants struggled to locate the correct plates when handling exceptions.

Continue batch processing

Support uninterrupted, high-volume processing

Observations

Users need clear guidance to continue processing plates.

100% of participants hesitated or were unsure how to respond when the input bin is empty.

Respond to notifications

Surface issues without disrupting focus

Observations

Display actionable next steps to reduce reliance on tech support.
Users require contextualized errors to reduce confusion and improve trust in the system.

100% of participants experienced workflow interruptions when errors occurred.

System Usability Scale Score (SUS)

The chart shows how 7 individual users rated the system, plus an overall average.

Usability testing of the end-to-end flow returned an average SUS score of 62.71 across 7 participants — placing the experience in the "High Marginal" range and below the 68-point threshold considered acceptable.

While the majority of participants scored at or above 62.5, two users scored 50 or below, indicating friction significant enough to impede task completion. These results point to specific breakdowns in the flow rather than broad systemic issues, and suggest targeted design iteration is needed before the experience is ready for wider release.

Found issues

To understand what was driving the SUS score of 62.71, the results were synthesized into three themes that pointed to systemic gaps

— in how device states were communicated, how errors were handled, and how core interaction patterns held up under real use conditions.

Theme 1

Cross-device status inconsistency

The PPRA, R5, and software don't share a unified status language, leaving users unable to interpret system state during errors and transitions.

Theme 2

Error handling that blocks progress

Errors either prevent users from proceeding, use technical language without recovery paths, or surface at the wrong time.

Theme 3

Broken interaction patterns

Core UI behaviors didn't work as expected, undermining user confidence in the system.

Theme 1

Issues (2):

Suction cup failure: PPRA showed green, R5 showed blue, software showed red — three conflicting states with no shared meaning. The error could not be dismissed, blocking the user entirely.
Boot state not reflected in software: During startup, PPRA and R5 both show blue but software shows a generic connected state in white — not indicating the PPRA is still booting. Users have no visibility into whether the system is ready to use.

Theme 2

Issues (4):

Non-dismissible error state: A suction cup failure produced an error in software that could not be cleared, leaving users with no path forward.
Unfriendly modal messaging: A software failure surfaced a technical error code with no actionable guidance. A secondary dialog interrupted the flow mid-task without clear context.
PAF vacuum sensor failure (R5 only): Error dialog asked users to check the device, but hardware and software states were not synchronized — not enough context to act with confidence.
Toast banners surfacing at wrong moments: Notifications appeared during active work rather than at natural transition points, competing with task-critical information.

Theme 3

Issues (4):

Inconsistent error toast sizing: Toasts appeared at different sizes within the same session — signals design system gaps and erodes trust.
Grid view scroll broken: Scrolling only worked when the scrollbar itself was directly selected. Users could not scroll the page naturally, blocking them from browsing multi-plate results.
Default preset logic ignores user type: New users saw a pre-selected preset instead of a zero state. Returning users did not see their last-used preset. Stack names were auto-generated before a preset was chosen, creating data artifacts before the user made any intentional choices.
Wrong default view on R5: Software defaulted to single-plate view instead of grid view when connected to R5, mismatching user expectations for multi-plate workflows.

Hardware showing mismatched ready states

Multiple toast types, only some auto-dismiss

Modal won't dismiss and wrong toast behavior

Inconsistent toast banners

Preset name displayed at wrong time

System displayed wrong default UI

OUtcome

A walk-away solution

Petrifilm™ Automated Feeder introduces hands-free plate feeding. Allows technicians to continue other tasks reducing idle time between steps. The system runs in the background, automatically interpretating and sorting plates. The automated feeder can process up to 300 plates in approximately 33 minutes.

The software application was developed as part of the Petrifilm™ automation package and supports core tasks such as plate identification with barcode scanning, automated colony counting, and data capture. It integrates with existing laboratory information management systems (LIMS) and reduces reliance on manual data entry—helping ensure accuracy, traceability, and repeatability in regulated lab environments.

Types of Petrifilm Plates

AI Trained Plate Identification. The current system utilizes 11 individual algorithms, specifically trained to identify each plate type.