How Big Data Analytics Affects Supply Chain Management

Using big data analytics to grow supply chain management Big data analysis is changing supply chain management for the better. The technology is producing quantifiable improvements in supply chain operations around the globe. Manufacturing logistics is an increasingly complex process, and companies are incorporating big data analysis to manage operations throughout their enterprises. As engineers create more innovative technologies, it is helping firms track and efficiently allocate their vast new resources, and even though big data is fledgling, it is making a positive and powerful impact on daily business operations.


Why Big Data Matters

According to veteran shipping executives, big data is a making a substantial impact in logistics and is poised to reshape the shipping industry. Almost all supply chain managers are familiar with the concept as well as how it can improve their production and distribution processes. Most consumers will cease patronizing a firm if they are not satisfied with their services or goods. By analyzing big data, firms will realize significant efficiency improvements and retain clients longer. For a third of all companies, tracking goods is an issue paralleled only by environmental issues. Big data can help companies increase their troubleshooting response efficiency by over 40 percent.

Big Data Makes Sense out of the Information Milieu

Big data analytics can consolidate and interpret the increasingly massive amounts of information produced by logistics operations. The information comes mostly from sources outside of an enterprise and varies in qualities such as size, interval, and structure. Innovative companies can use analytics to gather information from disparate data points and produce actionable reports.

Big Data Analysis Make Complex Logistics Work

Modern logistics is growing increasingly complex. Big data analytics allows companies to keep pace with supply chain logistics as the practice develops. Logistics experts can use the technology to share information as needed, allowing firms to produce more goods with unsurpassed efficiency.

The Technology Is Prevalent Throughout the Enterprise

Manufacturers are integrating big data analytic capabilities across their entire legacy systems. This incorporation mostly takes place across optimization, demand forecasting, planning and risk analysis platforms. To a slightly lesser – but still significant – extent, firms integrate big data analytics with:

  • 3D Printing
  • Computing processes
  • Location services
  • Logistics controls
  • Parcel tracking
  • Robotics
  • Wearable technology devices

Although very few supply chain executives actually incorporate artificial intelligence and cutting-edge delivery technologies into their big data analytic frameworks, an overwhelming majority of them predict that this will change in the near future.

Big Data Supports Business Model Enhancements

Big data analytics help companies optimize operational processes using location-based data. A recent case study reveals that one firm improved their delivery process by combining two service area frameworks. Using big data analytics, the firm executed a reorganization that decreased consumer wait times and increased troubleshooting efficiency. The study exemplifies how firms can increase production by analyzing their asset distribution and finding better ways to operate.

Big Data Facilitates Improved Operations

Firms are decreasing their response time to distribution network issues by using the enhanced reporting generated by big data analysis. Almost half of all companies utilizing the technology have enjoyed a ten percent increase in customer satisfaction and product demand. Over a third of these firms have improved their asset allocations as well as decision-making processes related to sales, operations and planning.

Big Data Improves Tracking Capability

Big data analytics enhances firms’ ability to track assets among countless resources. Using the technology, firms can quickly locate specific, concrete information for customers and vendors. This capability is a boon for manufacturers who need to retrofit or recall goods. In this capacity, big data can save firms thousands of labor hours.

An Expert Overview on Big Data Analytics

Supply chain analytics is not a new concept. However, the capability to produce meaningful insights with massive inputs using big data analytics is changing the logistics landscape; the technology is allowing firms to exploit massive, and formerly useless, unstructured data sets.

A 2013 Journal of Business Logistics report is the catalyst that caused supply chain experts to consider how big data can improve logistics operations. Today, the technology mines information from structured and unstructured data sets and provides logistical insights that were previously unavailable. Big data technology has made vast improvements between 2014 and 2016, but the technology is still very much in its infancy.

Supply chain management professionals around the world exploit big data analysis to improve company efficiency and reduce expenses. As supply chain management continues to increase in complexity, more logistics executives depend on big data analytics to make sense out of the information din. The technology is helping companies manage the many novel and effective innovations that have improved supply chain operations. and even though big data is a maturing technology, it is making a positive and powerful impact on daily business operations. As such, supply chain executives expect that the technology is permanent fixture in the logistics field.

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Sources

http://www.computerworld.com/article/3035144/data-center/overcoming-5-major-supply-chain-challenges-with-big-data-analytics.html

http://www.forbes.com/sites/louiscolumbus/2015/07/13/ten-ways-big-data-is-revolutionizing-supply-chain-management/#490f39383d38

http://www.forbes.com/sites/bernardmarr/2016/04/22/how-big-data-and-analytics-are-transforming-supply-chain-management/#732f2f2c4c2d

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