Big Data Implementation for Successful Daily Supply Management

Big Data

The year 2020 is considered the year of the supply chain. All prospects of businesses have been exposed and challenged and many businesses have been affected by it. Side effects of supplier data problems are very costly and far-reaching.

According to the research findings of 2021, there is a high risk on effective suppliers’ relationship management and assurance this is becoming even more challenging. 41% of firms need advance shipping to keep critical supply lines flowing.

36% of firms are losing revenue due to supply shortages.

Only 26% could predict risks at their supply base.

11% realized brand reparations directly resulting from supplier issues.

Solution for supply chain and procurement executives to prepare for success might be found in investing time and resources to make sure that supply chain and procurement teams are empowered by a cleansed, coordinated, and improved big data foundation.

Researchers report that a 15-20% increase in ROI can be achieved by introducing big data to enterprises’ business analytics. One of the most commonly discussed topics in today’s time is big data. Many companies are majorly focusing on the evolution of this trend.  With the help of big data, managers are able to make the best decisions. It is easy to make complex decisions when armed with data and tools to gather insight.

The applications of big data represent a new era in the PSM field as it merges and links all relevant information, resulting in speeding up strategic and operational procurement activities significantly. This trend is the source of meaningful information aiding the supply chain stakeholders to gain increased and improved insights. Big Data also helps in gaining a competitive advantage by maximizing speed and visibility that in turn results in improved supply chain relationships and increasing supply chain agility.

There are few companies that have been able to transform the way of management of supply chains by applying big data analytics.

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