Thursday, 14 March 2019 11:37

Artificial Intelligence in Supply Chain Management: Improving the Manufacturing Bottom Line

AI and Improving Manufacturing Bottomline Article Image

Change is inevitable. We constantly need to adapt to changes surrounding us to be able to survive in the world and the manufacturing industry is no exception. Many companies have used artificial intelligence to improve their bottom line. Artificial intelligence helps identifying the flaws in the system, suggest purchases to new and returning customers and streamlines the supply chain process. In fact, according to the reports, supply chain is one area today that is leveraging the benefits of AI.

With the growth of manufacturing industries, the volume of data has also increased drastically. Hence, companies are looking for more sophisticated systems to make business intelligence processing more effective. This is the primary reason why manufacturing companies are ldepend on AI techniques to increase their productivity and increase revenue.

AI and Supply Chain Management

The prime responsibility of supply chain management is to respond to customer demands by providing exact supply match as efficiently as possible. There are three important factors that have led to an inability to match demand and supply: -

  • The inability to forecast the real demand
  • Production gaps leading to reduced supply
  • The difficulty in synchronization between different supply chain partners

All these factors lead to failures and losses because our current systems are incapable of providing correct information in a timely manner to manage the demand and supply equation. Any kind of information gap is detrimental to an efficient  supply chain. The big question is how does a company use artificial intelligence to better manage demand and supply.

Enhancing Demand Forecasting Accuracy

It is not easy to function in a supply chain environment if you are unable to forecast the demand. Traditional methods of forecasting included statistical techniques for forecasting. Historical sales data is used to predict demand. These techniques are unable to process large sums of data and have struggled from time to time in providing accurate information. However, with AI in place, it’s easier to provide precise data and improve demand forecast.

Bridging the Production Uncertainty Gaps

While working in the manufacturing industry, machines will break, and you will not always be able to deliver. This will further lead to low output, delayed shipments, and interruption in the supply chain. Artificial intelligence helps in maintaining equipment by continuously collecting information on equipment breakdowns.  Timely repairs can be scheduled based on this information that help in avoiding delays.

Smarter Inventory Management

Managing inventory is one of the biggest challenges for every supply chain manager. However, with AI’s predictive modelling, it’s easier to predict how much stock is needed and decrease or increase production, thereby bringing down the cost of holding inventory.

AI is the Future in Supply Chain Management

Adopting the latest technologies to meet higher consumer expectations and demands is the need of the hour. AI helps throughout the supply chain management process with faster turnarounds for better results. Artificial intelligence will not only make people’s lives easier but also streamline businesses.

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