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Use a management solution with real-time data will allow you to process the large volumes of data required for vital activities like forecasting, safety stock replenishment, planning for peak buying times and more.

Working from a central platform will also create a unity of data and communication across the entire company. By storing information in a central database, sales and marketing teams will be aligned on any important changes to inventory, like increased orders due to promotions and other one-off events.

Implement third-party and automation solutions

There are two dimensions to this point. On the one hand, automation tools can provide real-time feedback and insights for streamlining inventory management.

Do stock reports automatically register in your database, for example? Are orders automatically generated based on diminishing stock levels? Will suppliers update you on late shipments immediately? On the other hand, third-party services can also help you pick between competing players to improve the overall efficiency of the supply chain



AI in Logistics for Demand Prediction

Why is last mile logistics important?

Last Mile Logistics Are Crucial to Modern E-Commerce and Omnichannel Supply Chains. Last mile logistics allow shippers to get more products to consumers faster and cost-effectively, both critical concerns in the e-commerce and omnichannel supply chain.

To improve your supply chain efficiency, you can use artificial intelligence and machine learning in order to predict the demand or improve the demand forecasting. In case you have already tried to do something like that. On the basis of the past experience, you will get a detailed analysis of all the factors which may have an influence on the demand. Using this knowledge, you will be able to make the right business decision.

Clearly, if you are seeking to improve a system's performance, an operational view is really what you are after. Such a view gets at how a forecasting system really works; for example, by what correlation its past output behaviors have generated. It is essential to understand how a forecast system currently is working if you want to change how it will work in the future. Forecasting activity is an iterative process. It starts with effective and efficient planning and ends in compensation of other forecasts for their performance

Artificial Intelligence can be used to improve logistics experience by increasing reliability, reducing the cost of transportation, faster processing, and deciding optimal routes for last-mile operations.

How can AI be used in supply chain?

AI provides the supply chain with contextual intelligence which can be used by them to reduce the operating costs and manage inventory. ... Companies make use of AI along with machine learning to get new insights into different areas which include warehouse management, logistics and supply chain management.
















Alternative Last Mile Delivery Models Disrupting the Industry

The vast amount of inexpensive cloud computing power is bringing a dream to come to life.  Marrying the cloud computing power to the massive amount of data is expediting new solutions involving artificial intelligence.  Artificial intelligence (AI) is “having a moment” in last mile logistics. Previous iterations involving technology were focused on transactional automation.  Today, innovation is focused on cognitive automation, the means of impacting how decisions are made and executed.  These AI solutions learn the inner and outer workings of the business.  The AI solution then uses this knowledge to make recommendations in real time.  It also makes predictions on business outcomes and can facilitate autonomous action.

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