Facing significant spoilage due to unreliable data on temperature excursions during transit, this leading chocolate company struggled with quality compliance in their shipments. A three-part solution combined 24×7 supply chain monitoring, transporter collaboration, and company oversight. By implementing real-time data tracking, predictive analytics, and proactive intervention, the company drastically improved its cold chain compliance, reducing spoilage and enhancing overall logistics efficiency.
Unreliable Data Leading to Spoilage in Chocolate Shipments
The chocolate foods that the company deals in needed proper spoilage/condition monitoring. They were facing an inability to understand the cause of temperature excursions in these shipments. They wanted to catch the underlying cause of the condition excursion causing spoilage. The biggest challenge was to locate the point of breach and thus prevent impact on product quality in transit. Let’s look at the two most significant challenges this company was facing in its chocolate supply chain.
The Challenge
Unreliable Data Leading to Spoilage in Chocolate Shipments
The chocolate foods that the company deals in needed proper spoilage/condition monitoring. They were facing an inability to understand the cause of temperature excursions in these shipments. They wanted to catch the underlying cause of the condition excursion causing spoilage. The biggest challenge was to locate the point of breach and thus prevent impact on product quality in transit. Let’s look at the two most significant challenges this company was facing in its chocolate supply chain.
1. Breach in Quality Compliance:
The chocolate giant observed spoilage in some of their consignments, but the data that their 3PLs were sharing painted a different picture. The data they had was delayed, second-hand, inaccurate, and unverifiable.
Many packages were reaching the destination spoiled because of temperature excursions that went unchecked in the absence of better monitoring. They received visibility data from their 3PLs, and though the data showed quality compliance being met, it wasn’t reflecting the number of spoiled packages reaching the depots. The logistics team of the chocolate company had no way to verify the data that the 3PLs shared. The challenge was the unverifiable, inaccurate second-hand data, which was practically not serving the purpose, and ultimately spoiled packages due to temperature excursion.
A lot of times, data wasn’t even available/accessible. For instance, when devices like data loggers didn’t work, they didn’t have data. Or, when using market vehicles that they had no control over, the data was delayed.
The sensors that the transporters used were placed inside the AC vent, which meant that the vendor report would always paint a positive picture even if the temperature at the door was not fit for the consignment. Sometimes, the company even received incorrect data from the transporter, which could be due to intentional forging to save them from the repercussions of unmet Service Level Agreements (SLAs).
2. Lack of actionable Information:
The delayed and inaccurate compliance data meant no actions were taken in time. The chocolate and confectionery company depended on vendors and transporters for data; some of these vendors had real-time visibility data, and some didn’t. Moreover, the company didn’t have access to all the data — all the vendors had different setups, some didn’t even have a proper process for data transmission, and some had data recording devices that lacked timely transmission.
In short, there was no parity on getting data and no single unified dashboard on visibility that the company could access. Due to the lack of proper resources and unavailability of real-time visibility on the shipment’s location and condition, the company could not make timely decisions. They would mostly come to know about a delay or spoilage only once the shipment would reach the destination when they couldn’t take any corrective action. All they could do was arrange for another consignment to cover up the shortage, which added to the overall costs.
Basically, the company was getting second-hand, unreliable, and sometimes even inaccessible data received from transporters to check quality compliance. There were instances of delayed and spoiled packages, and no action could be taken because of a lack of intelligent analytics. They usually came to know about the problem when the damage was already done. The data couldn’t even be cross-checked. The existing system was clearly not working.
What this Chocolate Manufacturer Was Looking for
The product they were transporting was very temperature sensitive, and even the slightest temperature excursion could mean compromise with quality. Thus, the company was looking for a reliable partner for temperature monitoring. The two most significant factors that mattered for them were:
A. Reliability:
There were many solutions available in the market, but they wanted to ensure the credibility of the solution provider. For them, it wasn’t about tracking and tracing with devices alone. They wanted both operational as well as qualitative reliability.
1. Operational Reliability: They wanted to ensure device availability, battery level, reverse logistics, and the performance of the control tower team working closely with the transporters to make timely decisions.
They didn’t just want a medium to measure anomalies but a partner to ensure that those anomalies would reduce. They wanted a solution that could help improve cold chain compliance through better communication and data exchange between the company, the transporter network, and the control tower.
2. Qualitative Reliability: It was imperative for the company to ensure that the devices functioned well, calibrated perfectly, had suitable temperature sensitivity and GPS accuracy, and would send timely alerts to the right person. They wanted devices that provided reliable real-time data with a very negligible error percentage.
B. Scalability
The chocolate giant wanted a solution that wasn’t about tracking and tracing alone but would monitor location and condition — one that they could scale up to their desired level. At present, they were operating at a scale of 1,200 shipments a month from the manufacturing unit to depots using domestic transportation medium.
They wanted a solution that would allow them to scale to a larger number of shipments and more locations as per future product demand.
The innovative solution was a unique three-part approach to address the quality compliance and lack of actionability that the chocolate giant was facing due to unreliable and delayed visibility data.
The three-part approach consisted of
- 24×7 supply chain control tower effort
- Transporter effort
- Company point-of-contact effort
It was, in short, a three-fold effort that helped the company get verifiable real-time location & condition data and use intelligent data analytics for better logistics decisions. The 24×7 control tower used a combination of smart technology and human intelligence for timely actions.
The solution worked on identifying anomalies and collaborating with transporters with the support of the company’s logistics team, rather than just pointing out the breach. Any tracking device could have done the latter; what was required was a comprehensive end-to-end solution.
Unlike carriers’ sensors, the solution gave the customer the leverage to place devices anywhere, ensuring that accurate temperature is reported even at hotspots — typically near the door — and that the quality compliance requirement is always met.
Not only was the hardware provided but also an entire end-to-end solution, which ensured better visibility, reliability, and an overall package-level monitoring experience. Here’s how the solution helped:
- The battery-powered sensor devices placed in the truck helped them get real-time temperature data at the vehicle level.
- Both the transporter and the relevant logistics professionals from the company would receive timely pre-emptive alerts, enabling quick actions on anomalies.
- The 24×7 control tower helped them ensure improved compliance from their transporters and 3PLs by ensuring they met SLAs without fail.
- The company now knew where the loose ends were and could start penalising the transporter for non-compliance using the solution’s 3-way impact to their advantage. They now got a tight grip on compliance and shipment condition monitoring.
- They are now more proactive with predictive analytics. Decision-making was smarter and much simpler, backed by smart analytics.
- The company had finally moved from second-hand, delayed, and inaccurate compliance data to first-hand, live, and actionable compliance data.
- There was a visible spike in the compliance numbers, and even vendor relations improved.
- They now have better overall logistics efficiency with data from different departments that they specifically need from time to time.
The technology behind OKgo and control tower services are now helping the company see the condition of the in-transit products without being dependent on transporters. The solution is also helping the company’s logistics team to act proactively and maintain in-transit product quality. They know what was causing temperature excursion in their active cooling FTLs, have located the point of breach in their chocolate supply chain, and are averting it using predictive signals and more adequate compliance measures.
The three-part approach helped the chocolate company find and stop the breach, improve compliance, and reduce spoilage. Now they have what data loggers couldn’t provide — the intelligence to work in real-time to stop the breach proactively. They have improved their efficiency with relevant real-time visibility. Since they deal with condition-sensitive shipments, real-time visibility on location and condition has helped them make better delivery and rerouting decisions.
In short, they now have:
1. Reliability and scalability with verifiable real-time data
2. A single portal to monitor all their shipments
3. Better compliance — achieved 80%+ cold chain compliance
4. And ultimately — higher customer satisfaction
The company has journeyed from delayed and inaccurate compliance data to actionable, first-hand live compliance data. The biggest concerns — namely quality compliance and actionability — were successfully addressed, ultimately improving the ROI.
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