Imagine you are waiting in line at a fast food establishment, behind a row of four cars. In this moment, you are hungry enough to eat a cheap hamburger, but not hungry enough to sacrifice your moral or ethical obligations. So, you pull out your mobile device and enter the name of a signature burger into you application. Your goal is to investigate just what is inside of the neatly packaged burger.
Forty seconds later, you roll out of the parking lot, never to eat at that establishment again. The meat, you discovered, cannot be traced to the source of any farm. The buns are linked to a company that was recently caught stuffing its bread with cotton. And the “natural” ketchup contains a whole page of chemicals that you cannot pronounce.
When product visibility is made possible through technology, two things happen: consumers become smarter about the choices that they make, and companies are forced to be held publicly accountable for every step of the manufacturing process. The first step is for food producers to gain intelligence from the the large amounts of data they collect throughout their operations and their co-packers’ operations. When the day comes where a consumer can pull out a mobile device and trace the origins of food that they would otherwise turn a blind eye to, it will be a victory.
Robust manufacturing quality control provides a system of checks and balances that companies can leverage to gain the trust of consumers. This is largely made possible through statistical process control, which gives manufacturers a framework for operational performance across every step of the supply chain. In food safety there is no margin for error, these systems can be a vital defense against contaminated foods and other adverse events.
Companies that choose to implement statistical process control software into their enterprise, and ensure quality control through automation have a leg up on competition. And, perhaps more importantly, consumers know exactly which brands to trust, and which brands to stay far away from.