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Features of Supply Chain Analytics

The challenge today is how companies can best use the huge amounts of data generated in the supply chain networks. Businesses have begun turning to business intelligence and predictive analytic software solutions. Data Analytics solutions help companies gain a more in-depth knowledge of how their supply chain networks were performing. It enables them to make better decisions and to optimize their networks.

A typical supply chain accesses 50 times more data now than just five years earlier.

However, less than one-fourth of this data is being analyzed.

Furthermore, while approximately 20 percent of all supply chain data is structured and can easily be analyzed, 80 percent of supply chain data is unstructured data.The organizations are looking for ways to best analyze this unstructured data.

The better a company can perform supply chain analytics, the better it protects its business reputation and long-term sustainability.

An effective supply chain analytics has got following pointers: -

1. Complete: Analytics capabilities must be scaled with data in real time. Insights will be comprehensive and fast. Latency is unacceptable in the supply chain of the future.

2. Collaborative: Improving collaboration with suppliers increasingly means the use of cloud-based commerce networks to enable multi-enterprise collaboration and engagement.

3. Connected: Being able to access unstructured data from social media, structured data from the Internet of Things (IoT) and more traditional data sets available through traditional ERP and B2B integration tools.

4. Cognitively enabled: The AI platform becomes the modern supply chain's control tower by collating, coordinating and conducting decisions and actions across the chain. Most of the supply chain is automated and self-learning.

5. Cyber-aware: The supply chain must harden its systems from cyber-intrusions and hacks, which should be an enterprise-wide concern.

In the current supply chain networks, data analytics is required to become more customer-centric i.e. responding quickly while maintaining accuracy and integrity.

Businesses are striving for supply chain analytics solutions that can quickly analyze huge amounts of data from disparate data sources, including unstructured and natural language-based data. Finally, supply chain analytics is being used to predict an increasing number of supply chain variables which includes external forces such as weather, war, workers and regulations.

Write to us at to understand how Agilytics can become your partner in Supply Chain Analytics solution implementation.

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