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How to Combine Supply Chain with Artificial Intelligence

Artificial Intelligence has been finding numerous use cases in the Supply Chain industry. Surveys from Gartner indicate that 64% of the market leaders have already implemented AI solutions in one form or another, with 31% of them using it to automate decisions. If you are planning to explore the revolutionary possibilities that AI puts forth for your Supply Chain, here is a roundup of what you can expect in either of the two categories of AI - Augmentation or Automation.

1. Automated Decision Making

Artificial Intelligence can reinvent business models by revamping the way in which you look at future trends. AI has the ability to analyze the patterns of today’s operations to predict the possible outcomes of tomorrow’s scenarios. This can be used to automate lower-level decision-making and balance the supply with the forecasted demand. Managers can thus indulge their skills in high-level decision making and strategizing.

2. AI in Procurement

The Deloitte Global CPO Survey of 2017 gives an overview of how AI is being implemented in Procurement today.

AI was initially confined to automating the process of collecting, classifying, and analyzing organizational expenses. But today, the technology is finding extensive usage as companies are leveraging cognitive procurement advisors (CPA) and virtual personal assistants (VPA) that deploy AI functions such as Natural Language Processing and Natural Language Generation.

VPAs have the capability to improve the experience of end-users. They can also guide people to relevant purchasing tools. On the other hand, CPAs can provide consolidated summaries and advice about multiple processes in the complete Procurement cycle. This can involve supplier assessment, performance management, risk management, and even compliance.

3. Algorithmic Breakthroughs

Artificial Intelligence has the ability to unearth insights and patterns in the Supply Chain to find correlations that escape the purview of the human mind. For instance, future availability of resources in your organization can be determined to calculate the approximate time frame of deliveries. Historical data can be used to understand the probable demand in the future and accordingly make relevant decisions.

Companies like Amazon are already implementing this by analyzing copious amounts of data to produce an endless loop of forecasting and adjustment by collecting and analyzing data related to real-time sales.

4. Supplier Relationship Management

Sourcing from the right supplier is key for a sustainable supply chain. AI can help in this regard to drive the best possible scenario for supplier selection and reduce the associated risks during every single supplier interaction. Data sets generated from SRM actions such as delivery performance, audits, evaluations, and credit scores are actively analyzed to make informed decisions about every supplier.

Machine Learning can turn your current passive data gathering activities into active and provide you with multiple ‘best supplier scenarios’ based on the parameters that you choose.

5. Chatbots

AI-powered chatbots in the Supply Chain, such as Procuebots, are also finding immense popularity. You can use them for a range of daily tasks such as:

     Interacting with the suppliers during trivial conversations.

     Automatically placing purchase requests.

     Handling actions related to governance and compliance materials.

     Researching and answering queries about the procurement process or suppliers. Receiving, reviewing, and filing documents related to invoices, payments, order requests, and more.

     Effective handling of procurement emergencies.

6. Logistics

The right combination of AI and Machine Learning can also provide you with visibility over the real-time movement of goods. This keeps you in complete control and reduces the chances of theft or pilferage during transit by sending proactive alerts at every stage of the movement. At the same time, by crunching real-time data about the environment, the estimated time of delivery can be accurately predicted. Such data would also help to optimize the routes to identify the bottlenecks and determine the most optimum schedule for the delivery.

 

Conclusion

We are closer than ever to the imminent truth today - the future of your business is closely tied with your ability to leverage new-age technologies. Artificial Intelligence is set to change the Supply Chain Industry as we know it and can soon be the key that determines the market leader. Companies relying on manual methods may not be able to keep up with the pace of the technology.

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