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As manufacturing has become more data-driven and reliant on technology, pharmaceutical manufacturers have generated a greater volume of data across a growing number of enterprise systems, equipment, processes and functions.
To manage the vast amounts of data, manufacturers have invested in enterprise resource planning (ERP), manufacturing execution systems (MES), material requirements planning (MRP), quality management systems (QMS) and other core information systems.
In the course of these investments, however, the human element of shop floor data collection is often excluded, leaving people on the production line to continue managing paper or standalone systems to collect and analyze data relating to production and quality processes. When these processes remain paper-based and information sources remain siloed, data is often hidden or incomplete, rendering it useless.
Read the full article here: Avoiding the Ripple Effect of Bad Data: Quality and Manufacturing