Importance of Supply Chain Data Analytics for Organizations

Supply chains play a key role in how the success journey of organizations is shaped. Effective management of supply chains is a must-have for organizations given the fact that supply chains have to grapple with disruptions, demand-supply imbalances, and changing customer expectations. Organizations are looking to raise the efficiency bar across their supply chains. And to address the various supply chain challenges across the globe, one area that has grabbed eyeballs is supply chain data analytics.

Supply chain data analytics can play a massive role in driving enhanced efficiency across organizations. Supply chain data analytics can do a world of good to organizations in ensuring access to end-to-end touch point visibility, which always has been a big pain point for organizations. Supply chain data analytics can be an enabler for organizations to deliver an elevated customer experience, reduce operating costs and augment profitability. Given the connected ecosystem of present times, supply chain data analytics will really work well.According to various industry experts, supply chain data analytics assesses supply chain performance and identifies the shortcomings and inefficiencies in supply chain configurations.

For a long period of time, organizations have relied on historical data (inventory data, sales data, lead time data, etc) trends to identify trends and patterns for the future. Such an exercise hasn’t quite delivered the desired results. Historical supply chain data may have helped organizations in the past, but it always fell short of living to the desired expectations of organizations. The problem with historical supply chain data is that it lacks predictiveness and prescriptiveness. To put it in a nutshell, such historical data does not dictate any action that an organization can undertake to fix a particular issue. Such data does not have the advanced analytics quotient such as real-time data based on which organizations can predict future situations and come up with game-changing decisions.

It is not enough for data to underpin the problems and how to go about it to address the problems must be there and this is where Machine Learning-based algorithms can come in handy.

There is no doubt that the importance of supply chain data analytics has been realized by organizations across the globe. Organizations driving supply chain efficiency minus supply chain data analytics would be a futile exercise.