Big Data analytics and supply chain evolution

Today, companies are filled with a huge amount of data about customers, suppliers and even potential markets due to the development of digital technologies. As they usually say, “information is power, but if you misuse this data, it becomes useless.” The saying is true when it comes to calculus in order to benefit key business opportunities, such as the supply chain.



A recent Accenture study of more than 1,000 senior executives found that while 97% understood how Big Data could benefit their supply chains, only 17% reported implementation. Here are some of the ways that Big Data can identify opportunities and revolutionize supply chain management in almost any organization.

Big Data Analytics

It was noted that the amount of data collected worldwide is growing at a rate of 59% per year. Big Data analytics is the process by which analysts study huge amounts of data to identify models and other useful information that can lead to better and more efficient business solutions. Big Data analytics was first used 20 years ago for marketing and sales purposes. Today, companies take the Big Data analysis to the next level and apply it to the company's operations, in particular, to their various supply chain problems.
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Current problems of the supply chain

Using Big Data at the supply chain level allows companies to improve their response to unstable demand and reduce the risk of the supply chain. Understanding that Big Data analytics, embedded in the depth of the supply chain, often creates efficiency and allows companies to overcome current threats. Spend Matters recently distributed the "5 Data-Driven Supply Chain Challenges to Overcome in 2016". These are the problems and how Big Data analytics can help with them.

• Better predictions of customer needs - according to Customerthink.com, more than 90% of dissatisfied customers do not return to a brand that did not meet their expectations. Providing superior service and timely delivery is now crucial to the business, and Big Data analytics can help companies understand customer desires and predict the level of demand.

• Improved supply chain performance - according to Accenture research, using Big Data analytics in operations can lead to an increase in supply chain efficiency of 10% or more.

• Improved supply chain risk assessment - Accenture study also reports that industry leaders recognize the importance of supply chain risk management, understanding the need for both greater visibility and predictability in their supply chains. Big Data analytics uses a combination of data history, scenario planning and risk mapping to assess potential problems and provide management of the early warning system.

• Better supply chain tracking - according to Ethical Corporation, 30% of surveyed companies report that tracking supply chain is one of the biggest problems. Big Data solves many of the problems associated with tracking, and also reduces the hours needed to access and manage product databases.

• Better agility and reaction time in volatile markets - being able to respond to market conditions quickly and meeting customer expectations is crucial. Accenture study reports that companies that use Big Data analytics in operations are 5 times more likely to declare a shorter delivery time.

Managing Revolutionary Supply Chains with Big Data Analytics

In addition to solving the specific chain supply problems cited above, Big Data has the potential to evolve business operations and results in many ways.

• Big Data analytics can be used to optimize the delivery network using geoanalytics.

• Using Big Data, companies can get a better idea of ​​how their supply chain decisions affect profits and financial goals.

• Big Data can allow companies to deepen their relationships with suppliers with more detailed supplier profiles, as well as identify opportunities for business expansion.