The ability to respond quickly to a recall alert is one of the biggest challenges buyers and suppliers face. What’s slowing you down? The problem can be traced back to inconsistent data.
Supply chains are complex with varying rules & regulations, outdated technology, manual systems, and siloed communication. But as food safety alerts become more and more common, you cannot wait any longer to find and implement a solution that closes the data gaps in your food traceability process.
We’re going to explore the industry’s data challenges and look at how new solutions can streamline and strengthen your entire supply chain so you’re prepared to act fast during the next food safety event.
Managing Data: A Logistical Issue
Effective, consistent data is crucial to your food traceability system, but managing that data, especially during a food safety event, is beyond challenging for both buyers and suppliers.
Whether you run a smaller business or a large corporation, every day you have to manage anywhere from hundreds to hundreds of thousands of different products from different trading partners from different parts of the country and world. That means you have a lot of data to manage and analyze at any given moment.
To compound that challenge, in many cases every trading partner uses a different process to store or maintain the data. This is where the issue can get out of control, putting your business and customers at greater risk, especially during a food safety alert.
Implementing Next-Level Data Technologies
What can be done to unify and manage all of this data so that food traceability can provide real-time, end-to-end visibility for an entire supply chain?
First, the data has to be digitized if it isn’t already. Once this is accomplished, you still aren’t capable of managing and analyzing all the information stored on your own. You need to go next level with your traceability technology and implement a solution that uses machine learning.
In a recently published Annual Review of Food Science and Technology, VOL. 12 titled Emerging Applications of Machine Learning in Food Safety, the authors state: “Food safety continues to threaten public health. Machine learning holds potential in leveraging large, emerging data sets to improve the safety of the food supply and mitigate the impact of food safety incidents.”
What is Machine Learning?
So what exactly is Machine Learning (ML)? Most of us utilize ML on a daily basis and don’t even realize it. Those recommendations you see on Netflix, every search you do in Google -- that’s all machine learning at work.
According to Investopedia, “Machine learning is the concept that a computer program can learn and adapt to new data without human intervention. Machine learning is a field of artificial intelligence (AI) that keeps a computer’s built-in algorithms current regardless of changes in the worldwide economy.”
In order for an AI-based machine learning system to work best, you need a large amount of quality data. And this is where it can take your food traceability process to the next level.
A Groundbreaking Traceability Data Solution
While there wasn’t a solution or applications in food traceability that included machine learning when the previously mentioned Annual Review was published, there is now.
iTradeNetwork, the global leader in perishables supply chain management, now offers the most complete traceability solution that includes new technology that relies on data and machine learning to close your traceability gaps and achieve full-path supply chain visibility.
This groundbreaking platform allows buyers and suppliers to leverage real-time data so they can collaborate faster, with surgical precision within seconds of an incident alert. Automatic notifications can be sent to suppliers and buyers at the same time, using the same data so the impacted product can be identified and removed anywhere it exists in the supply chain immediately.
Contact iTradeNetwork today to learn more about how we can unify your data to enhance food safety for your company, your supply chain, and most importantly, your customers.