As supply chains continue to become a more integrated part of the enterprises they serve, managers can no longer ignore the importance of big data and predictive analytics. This data must not only be harvested and analyzed, but changes must occur afterwards. If a process is found to be inefficient, it must be improved as soon as possible.
Supply chains are also finding that collecting data is not just about quantity, but also speed. Data can go stale quickly. The longer the gap between when data is collected and when it's analyzed, the less accurate it is. The ability to gather information in real time means that managers must react to it nearly as rapidly. Responding to supply chain challenges expeditiously improves customer service, reduces costs and raises profits.
According to EBN, detailed research by IndustryARC predicts that the global big data market could reach $40.4 billion by 2018. The greatest investment in big data for supply chains in 2012 was made by companies in the manufacturing and services industries. Each accounted for roughly one-quarter of big data spend, followed closely by the retail industry.
Data Collection Key to Growing Enterprises
New methods of collection in the warehouse not only harvest data that can be used for analytical purposes in the office, but also save time on the warehouse floor. While the data can be used to improve processes, the method of collecting - with barcode scanning software and other technologies - frees up employees to focus on other tasks. This cuts down on time spent logging information from paper systems and greatly reduces the number of errors as well.
Other cost-saving measures of data collection come in the ability to improve inventory control and track merchandise before and after it has left the warehouse. This makes recalls easier and quicker to perform, reducing costs, fines and penalties. A fast recall also helps maintain current levels of brand reputation.
As a business grows, automated data collection can keep pace with increased volume without significant increases in resources or staff. While more employees may be needed to fill other positions in the warehouse, they can be trained more quickly and measured more effectively with new tools and software. Their training can also focus on the more skilled portions of the position, instead of how to accurately collect and record data with a paper-based system.