Question

Recent business environment have been completely revolutionised by big data analytics, and it is just made up of four key concepts which are characteristics: value, velocity, volume, and diversity (Chen, Chiang and Storey 2012). The utilization of big data analytics can also produce insightful findings that would help businesses make better strategic decisions. The concept of the big data analytics has risen beyond the storage of numerous information and it has also made the use of the analytical methods iterative along with the ongoing trends of marketplaces in the world of the mobile applications (LaValle er al., 2011). For example, businesses in the digital world are able to analyse information immediately because of in-memory and Hadoop analytics' speed as well as their ability to analyse new data sources (Demirkan and Delen 2013). As a result, organisations throughout the world are now heavily relying on Big Data to guide business decision as well as improve and maximise returns of investment and operational performance (Chen, Chiang and Storey 2012). Because of it focuses on providing numerous new methods of integrating various technologies, big data analytics is a widely accepted or taken into consideration topic in engineering management courses and careers. This is because it has been transformed into an impressive innovation in the engineering field.

Focus on the area of business in supply chain and logistic technology, explain how does Big Data Analytics influence the business decision-making and business priorities as well?

Write in short essay including three paragraphs which are introduction, contents, and summary.

Answer 1

Big data analytics has revolutionized supply chain and logistics by facilitating improved decision-making and shaping business priorities. The ability to process large volumes of data at high speed allows for more efficient operations and a stronger competitive stance in a globalized market. The strategic use of big data is poised to continue shaping the sector's evolution.

Step-by-step explanation:

Introduction to Big Data in Supply Chain and Logistics

The advent of big data analytics has significantly transformed the supply chain and logistics sector, leading to enhanced business decision-making and redefined business priorities. By leveraging voluminous and diverse data at high velocity, companies gain valuable insights that foster strategic planning and operational efficiency. This data-driven approach is particularly crucial in the fast-paced digital era, where consumer preferences and global market dynamics can fluctuate rapidly.

Impact of Big Data on Business Decisions and Priorities

In supply chain and logistics, big data analytics aids in optimizing routes, predicting demand, improving inventory management, and anticipating potential disruptions. The integration of this technology has enabled businesses to become more proactive instead of reactive, ensuring a more agile and customer-centric supply chain. The emphasis on data has also shifted business priorities towards a more analytical and evidence-based approach, stimulating innovation and competitive advantage in an increasingly interconnected global market.

Summary and Future Outlook

Big data analytics has undeniably become an invaluable tool for businesses, especially within the realms of supply chain and logistics. It not only informs decision-makers but also guides the reorientation of business priorities towards efficiency, customer satisfaction, and market responsiveness. As the volume of data continues to grow and analytical tools evolve, the role of big data in shaping the future strategies of firms in this sector is set to further expand and deepen.