If there is one thing that big data has been especially helpful with, it's predictive analytics. The massive amounts of information that companies now collect allow them to understand their supply chains in a way that was close to science fiction not so long ago. With the right software, this information can also be integrated with ERP systems so that it's not a siloed look at the supply chain, but an overview of the entire company.
This naturally plays an important role in predicting changes in demand and determining staffing levels. However, predictive data can also be used to prepare for the unexpected. In a video interview with Supply Chain Brain, C.J. Wehlage, vice president of high-tech solutions at Kinaxis, said the key to success in the modern supply chain is to "know sooner and act faster."
Data Must Be Available Instantly
To know about supply chain interruptions and volatility sooner, organizations need access to automated data collection solutions that provide information in real time. The more time it takes to identify a problem, the further through the company it has spread. With data collection software, processes can be measured and products traced throughout the warehouse and beyond. This information can also be used to develop a clearer picture of an organization's suppliers and third-party logistic partners.
The data can be analyzed and compiled to form trends so even c-level executives can exam it and determine if an interruption is possible. Companies can also plan more effectively for crises that they cannot predict. Information about second- and third-tier suppliers can help form a plan of action so that members of the supply chain are not scrambling when a disaster strikes.