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Using Big Data Analytics to Improve Production
  • Most professional managers understand that Big Data analytics are needed to compete and be successful in a data-driven economy; because of this they are making investments in managing assets and data integration to achieve digital transformation to gain a competitive edge. This helps them to stay in business for a long time.

     

    Manufacturing is still the most important part of the world’s economic engine, even though the role it plays in developing and advanced economies have changed. In developing countries manufacturing remains the best way to provide jobs and transform societies. In developed countries, manufacturing is still important for job creation and in mature economies manufacturers drive productivity, with innovation and efficiency gains.

     

    Big Data is needed for efficiency gains and uncovering new insights to drive innovation. Manufacturers are now discovering new information and patterns that enables them to increase supply chain efficiency and identify variables, improve processes that affect production and grow their businesses.  Researchers have found that more manufacturers are planning to invest in big data and data analytics even though they are being pressured to reduce the costs, more as time goes by. Manufacturers and enterprising leaders know the stakes are high, they know they can’t compete successfully in a data-driven economy and they need to keep on investing in data integration and management assets to gain a competitive edge when digital transformation is achieved. They are constantly outdoing their competitors in an effort to increase their profits.

     

    Whenever the value of assets is maximized manufacturer’s profits can be relied on and asset performance gains will lead to big improvements in productivity- even when the asset performance is improved only on the margins. Focusing on asset maintenance gives companies the ability to continuously optimize asset performance.

    Data on asset performance is found in machine logs and a new dimension of things has been added to assets and sensors that are capable of measuring, transmitting and recording in real-time. This data is of great benefit to manufacturers, even though the sheer volume of information can be overwhelming. Machine data can be analyzed, cleansed and captured by using data analytics to reveal insights that can help to improve the performance of many companies.

    Big data can be used to drive predictive analytics and manufacturers can use the right information to schedule predictive maintenance and avoid costly breakdowns of assets and avoid unexpected downtime. Big data analytics continues having a significant impact on manufacturing. Big data has been reducing breakdowns and cutting unscheduled downtime for factories, causing manufacturers to see increased profits and business growth.

    Keep in mind that the capabilities of Big Data cannot be fully tested in the beginning. Start out with simple projects and move your way up. By working on a simple project, you will be able to see the potential of Big Data and how it can contribute to the success of your business. Big Data adoption should be broken down into different phases. These include aggregation of data, incorporation of simply algorithms, then turning the analytical algorithms into more sophisticated methods, automation of production management, and evaluation of the analytical models.

    We at NextBee can help you grow the use of Business Analytics in your organisation. Let’s talk today to discuss more.

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