The Endless Possibilities of Predictive Analytics in Supply Chain

Predictive Analytics has started marking its importance in the field of Supply Chain Management, thereby making the overall process more reliable, accurate, and less expensive. In order to be at the top of the game, businesses are now heavily banking on the advanced predictive analytics.

Essentially reckoned as a large & continuous workflow and an industry projected to be worth more than $9 billion in the next couple of years, the supply chain has been extensively recognized in the terms of:

• Procurement
• Inbound Logistics
• Manufacturing
• Parts Inventory
• Outbound Logistics
• Finished Goods Inventory

Why Predictive Analytics in Supply Chain Management?

Predictive Analytics- the ability to utilize and implement data that can accurately foretell the future activities. It enables forethought and real-time decision making measured on the scale of performance and strategies. The proactive nature of predictive analytics is what embarked its journey in supply chain business intelligence and therefore forging it to become mainstream in the after-sales service.

As a result of this, newer models, optimization techniques, and Hybrid Transactions Analytics Platforms have resurfaced from the dead and are remarkably processing both transactional and analytical queries simultaneously. These new tools mean near zero delay in decoding the current inventory positions, comprehending the inflow of the customers’ orders, and instantaneous supply chain forecasts at all the levels. Here is a list of high-level activities in supply chain management that are greatly benefitted by the applications of predictive analytics.

• Replenishment Planning Analytics
• Finished Inventory Optimization
• Demand Analytics
• Network Planning and Optimization
• Procurement Analytics
• Transportation Analytics

Manufacturing Machine Learning in A Predictive Environment

Machine Learning- a form of Artificial Intelligence (AI) that facilitates the computers with an ability to learn without being programmed explicitly and a part of nearly every possible aspect of our daily lives.

The major growing trend behind this technology is the infinite accessibility of data and there exists a plethora of information in supply chain that fuels the implementation of predictive algorithms. Modern organizations and industries, especially the manufacturers are adjusting in accordance with this predictive environment and are rigorously adapting to the changing user demands.

Forecasting the Predictive Analytics Future

In the wake of these advancements, the manufacturers have started accelerating their pace to mold and reshape predictive analytics in the form of strategic advantage. Here are three active areas in supply chain management where predictive analytics can firmly gain its foothold.

• Predictive Pricing
• Predictive Demand Forecast
• Predictive Maintenance

 

Also Read How Machine Learning Impacts Customer Experience

When compared to the product-side, optimizing the service-side is equally crucial in the landscape of supply chain management for the long-term financial performance of the manufacturers. Predictive analytics, on the other hand, has been greatly contributing to its upliftment and helping the businesses increase their service values.

What do you think about the possibilities of Predictive Analytics in Supply Chain? We will be happy to hear your side of the story as well!