Across industries, manufacturers pride themselves on quality but put top emphasis on reducing overall costs. And while these may seem like conflicting priorities, they can be explained by the concurrent demands of the internal economic drivers of an organization and the external customer requirements for quality and efficiency. As such, these priorities are here to stay, especially as the consumer becomes increasingly empowered and publicly vocal. In recent years, product quality and safety have become tightly integrated with traceability and supplier scorecards. But for manufacturers with foresight to proactively implement a comprehensive traceability system before a contamination problem occurs, there is an opportunity to provide their organizations with the ability to dramatically improve response time, implement corrective measures, and minimize repercussions to the bottom line and the brand, should a problem arise.
In today's environment of Big Data and analytics, effective supply chain decision-making is only as good as the data influencing the decisions. Drawing actionable conclusions based on the best information possible is critical to maintaining a supply chain that is efficient and effective, but also acts as a continual driver of strategic and competitive advantage. But how can your organization ensure that the data used to draw conclusions and make decisions regarding the supply chain is clean, relevant and accurate?