A real-time monitoring system built to give operators visibility into temperature-sensitive shipments, enabling faster decisions and preventing product loss before it occurs.
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MY ROLE
I led the end-to-end product process on this project from stakeholder research and problem framing, to product strategy, solution design, and usability validation.
I worked across both the software dashboard interface and the physical hardware interface, collaborating with embedded engineers and cross-functional teams to ensure every part of the system addressed real operational workflows, not just screen-level interactions.
Company: Gricd (now Figorr)
Sector: IoT · Healthcare · Pharma · Agriculture · Logistics
Methods: Research · Stakeholder Interviews · Usability Testing · Cross-functional Collaboration · Design Strategy
Tools: Figma · Miro · Asana · Google Docs
Year: 2023
PROJECT OVERVIEW
WHAT IS GRICD ABOUT?
Gricd (now Figorr) is an IoT company that builds real-time monitoring systems for temperature-sensitive assets across healthcare, pharmaceuticals, agriculture, and food logistics.
Their technology combines physical sensors with digital dashboards, allowing businesses to track environmental conditions during transit and storage, prevent spoilage, maintain compliance, and reduce financial loss.
The core business challenge: how do you turn raw sensor data into decisions that operators can act on before damage occurs?
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THE PROBLEM
Cold-chain failures cost the global food and pharmaceutical industry billions annually. The core issue isn't the failure itself; it's that most operators find out too late to intervene.
Organizations handling temperature-sensitive goods often operate without real-time visibility into environmental conditions during transit or storage. This lack of monitoring makes it difficult to detect temperature excursions early, increasing the risk of spoilage, compliance violations, and financial losses.
Even when monitoring tools exist, they are frequently difficult to interpret, fragmented across systems, or too slow to support timely decision-making. Businesses needed a way to clearly see what was happening to their assets in real time and act before problems escalated.
PROBLEM FRAMING
STAKEHOLDER & USER ANALYSIS
The platform serves operations teams responsible for monitoring temperature-sensitive goods across distributed and often remote environments.
Through stakeholder discussions and observational research, we identified four primary user groups with distinct monitoring needs:
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Logistics Operators: Managing shipments across long-distance routes where real-time visibility is critical to preventing transit losses.
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Healthcare & Pharmacy Staff: Responsible for vaccine and medicine storage, where temperature deviation has direct patient safety implications.
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Food Supply Chain Managers: Overseeing perishable goods, where spoilage directly impacts revenue and compliance.
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Operations Managers: Responsible for cross-team reporting, regulatory compliance, and high-level asset oversight.
WHY THIS PROBLEM MATTERS
Cold-chain failures don't just affect inventory; they affect public health, operational costs, and regulatory compliance.
A delayed response to a temperature deviation can render entire shipments unusable. For organizations transporting vaccines, pharmaceuticals, or food products, visibility into environmental conditions is not a convenience; it is a necessity.
The value of a monitoring system lies not just in collecting data but in presenting that data clearly enough for operators to understand risk instantly and take action before the damage window closes.
PROJECT GOAL
The product goal was to shift operator behaviour from reactive damage reporting to proactive risk prevention.
To achieve this, the platform needed to enable operators to:
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See real-time environmental conditions across all monitored assets.
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Detect risks early through clear, prioritized alert states.
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Respond quickly with enough contextual information to act without delay.
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Monitor assets remotely with both environmental and location data
DISCOVERY & RESEARCH
RESEARCH & DISCOVERY
To understand user needs and real operational workflows, we gathered insights through usability sessions, stakeholder discussions, and observational testing of real-world monitoring scenarios.
We focused specifically on how teams monitored devices, interpreted alerts, tracked asset locations, and responded to anomalies across both the physical hardware interface and the digital dashboard.
“I don’t want to scan dashboards all day. I just need to know when something needs my attention.”
“If temperature changes happen overnight, I only find out in the morning and by then it’s too late.”
“Location matters as much as temperature. If I don’t know where the issue happened, I can’t fix it.”
“Alerts are helpful in critical moments, but if the alert doesn’t tell me what to do next, it will slow us down.”
KEY INSIGHTS FROM RESEARCH
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Operators consistently discovered temperature breaches too late to intervene; the system was informing rather than enabling action.
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Users struggled to interpret raw temperature data quickly enough to make real-time decisions.
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Alerts lacked contextual information, increasing the time between detection and response.
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Location visibility was as critical as environmental data; knowing where an issue occurred determined what action was possible.
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Hardware interfaces needed to be glanceable and legible in field environments, not just on desktops.
PROBLEM STATEMENT
Operators responsible for monitoring temperature-sensitive shipments need a way to quickly understand asset status, location, and risk levels in real time because delayed or unclear information prevents them from responding before product loss occurs.
How Might We
How might we help operators monitor shipment conditions in real time and take immediate action before product damage occurs?
PRODUCT STRATEGY & APPROACH
To address the problem holistically, the solution was approached as a connected system rather than a collection of isolated screens. The platform needed to support three layers of interaction:
VISIBILITY LAYER — Monitoring & Status Awareness:
Operators needed instant clarity about what was happening across all tracked assets. The dashboard was structured to surface key environmental readings, device health, and status summaries so operators could understand the full system state at a glance without navigating across multiple screens.
RESPONSE LAYER — Alerts & Intervention:
Detecting issues isn't enough; operators must also be able to act quickly. The alert system was designed to visually differentiate normal, warning, and critical conditions, giving teams clear prioritization signals without requiring them to interpret dense data under pressure.
PHYSICAL LAYER — Hardware Interface:
Since the system includes field-deployed hardware devices, close collaboration with embedded engineers was required to design the on-device interface, ensuring critical readings were visible and readable in real-world environments and consistent with the digital dashboard.
SOLUTIONS
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Real-Time Monitoring Dashboard
The dashboard consolidates environmental readings, asset status, and device data into a single unified interface, reducing the cognitive load of monitoring multiple shipments simultaneously and eliminating the need to switch between tools or screens.
Device Monitoring Interface
Device-level monitoring screens surface battery level, environmental readings, and device status, directly removing operator uncertainty about whether issues are caused by the environment or the device itself.
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Smart Alert System
A three-tier alert system — normal, warning, critical — reduces response time by making intervention priority immediately visible. This prevents critical alerts from being overlooked or treated with the same urgency as routine notifications.
Geolocation Tracking
A live map view displays device locations alongside environmental data, giving operators spatial context for issues and enabling teams to coordinate responses faster based on where in the supply chain a problem occurred.
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Hardware Interface Collaboration
Working closely with embedded engineers, the device display interface was refined to ensure critical readings were legible, interaction states were unambiguous, and the layout supported quick interpretation during field use, bridging the gap between hardware feedback and dashboard information.
PRODUCT ADOPTION SUPPORT
PRODUCT DISCOVERY SUPPORT
To support hardware adoption beyond the core platform, the company website was redesigned to better communicate product capabilities, making it easier for potential customers to explore available devices, understand features, and make informed purchasing decisions. This ensured the digital marketing touchpoint aligned with the clarity and usability standards of the product itself.
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USABILITY TESTING
TESTING & VALIDATION APPROACH
To ensure the platform supported real operational workflows, usability sessions were conducted with users interacting with core monitoring features, including geolocation tracking, alert interpretation, and device status visibility.
Sessions focused on measuring how quickly users could interpret system states, locate issues, and determine next steps under conditions that reflected real operational pressure.
Working alongside engineers during hardware testing allowed evaluation of how users interacted with the physical device interface, ensuring consistency between hardware feedback and dashboard information.
Testing revealed three specific friction points:
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Unclear alert hierarchy causing prioritisation delays
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Delayed recognition of critical status changes due to insufficient visual differentiation
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Confusion between device states and environmental readings
Testing led to three specific iterations:
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Alert hierarchy simplified from five states to three, reducing decision time under pressure
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Critical status visual treatment made significantly more distinct from warning and normal states
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Device state labels rewritten for field readability, making them shorter, clearer, actionable
CONCLUSION
IMPACT
Although formal analytics tracking was not implemented at launch, qualitative feedback from operators and internal teams indicated meaningful improvements across the system.
Faster Risk Identification
Operators reported identifying critical temperature deviations significantly faster through improved visual hierarchy and clearer alert differentiation, reducing the window between detection and response.
Reduced Response Ambiguity
With three clearly distinct alert states, teams could immediately prioritise which issues required intervention, without scanning through dense or ambiguous status information.
Streamlined Workflow
Dashboard consolidation reduced the number of screens operators needed to check during a monitoring session, decreasing task completion time for routine status reviews.
Hardware–Software Alignment
Aligning the hardware and software interfaces improved operator trust in the system, making it easier to distinguish between device issues and environmental conditions.
Reduced Onboarding Time
New users required significantly less guided support to understand system states and alert behaviours, reducing time-to-productivity for new team members.
KEY TAKEAWAY
This project reinforced that monitoring systems must go beyond displaying data; they must enable quick understanding and action. Working across both hardware and software surfaces taught me how critical clarity, prioritization, and decision speed are in operational tools used in real-world environments. The most important decision on this project wasn't visual; it was structural: deciding what information operators needed to see first and what could wait.
WHAT I'D DO DIFFERENTLY
If I were to revisit this project, I would push earlier for analytics instrumentation, specifically tracking alert response times, dashboard interaction patterns, and the time between alert trigger and operator action.
Without that data, measuring the real business impact of product decisions remained qualitative. That's a gap I now build into my process from the start: defining what success looks like in measurable terms before a single solution is designed, not after.
I would also have advocated for a structured pilot phase with a smaller user group before full deployment to capture behavioural data early and use it to validate or challenge the product decisions made during research.