When mining for diamonds, one metric ton of rock must be scrutinized to turn up one gram of diamonds. Data mining in food manufacturing can be equally as tedious. Isolating critical pieces of information can be cumbersome, but when identified, it brings prominent value through insights and mitigating risk. Food quality and supply monitoring professionals are often focused on product performance trends over time. So even with a strategic food quality and safety monitoring program, critical values can get lost in the mean when trending big data. Finding the anomalies requires continuous monitoring and countless hours of research through thousands of data points daily.
Overlooking values outside of protocol can quickly spiral into a product performance or brand safety catastrophe. For example, say that Clucker’s poultry supplier is producing raw chicken fillets for Feather’s fast food chain. One shift produces five fillets with thickness measurements exceeding specification. These fillets are distributed to the restaurant and cooked according to protocol. However, the standard cook time does not account for the increase in size, so an overage in a quality attribute has now escalated to a food safety concern. So how can food quality and safety professionals ensure they never overlook a supplier’s oversight again?
Introducing QualMap’s Threshold Notifications
QualMap is a solution that uses analytical intelligence to manage your supply chain data. As a user you have the ability to apply threshold notifications to the data flowing into the solution.
- Eliminate the research and guesswork. Utilizing threshold-based notifications allows you to receive an alert in real-time when a performance threshold has been breached.
