Big data has the potential to revolutionise manufacturing. By analysing vast amounts of information in real-time, manufacturers can improve quality and output while reducing waste. This approach, known as ‘advanced analytics’, is already being used by some companies to optimise production processes.

One example is a semiconductors company that used data from equipment sensors to predict potential failures, thereby reducing downtime. Similarly, an aerospace company used advanced analytics to streamline its assembly line, leading to a 10% increase in productivity.

Big data can also help manufacturers understand customer behaviour and preferences. For instance, a car manufacturer analysed social media posts to identify features that customers value most in their vehicles. This led to the development of a new car model that met these specific needs.

Furthermore, big data can enable manufacturers to manage their supply chains more effectively. By analysing real-time data from suppliers, companies can anticipate potential disruptions and take action to mitigate their impact.

Despite these benefits, many manufacturers have yet to fully embrace big data. The main barriers include a lack of understanding about how to use data effectively, and concerns about data security and privacy. To overcome these challenges, manufacturers need to invest in data analytics skills and establish clear data governance policies.

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