Three Uses Of Automation Within Supply Chain 4.0

The increased availability of advanced technologies has revolutionized the traditional supply chain model. Supply Chain 4.0 responds to modern customer expectations by relying heavily on the Internet of Things (IoT), advanced robotics, big data analytics, and blockchain. These tools enable automation and thus give organizations a chance to close information gaps and optimally match supply and demand.

Industry giants like Netflix, Tesla, UPS, Amazon, and Microsoft rely heavily on automation within their supply chain to lead their respective industries. Let us take a closer look at three powerful automation use cases.

1. Managing demand uncertainty

A painful aspect of supply chain ecosystems is the demand uncertainty and the inability to accurately forecast demand. Generally, this leads to a set of performance issues, from increased operational cost to excess inventory and suboptimal production capacity. Automation tools can forecast demand, remove uncertainty from the equation, and thus improve operational efficiency at each step along the supply chain.

Big data analytics is an established tool that helps organizations manage demand uncertainty. It consists of data collection & aggregation infrastructure combined with powerful ML algorithms, designed to forecast demand based on historical (or even real-time) data. Modern storage solutions (such as data lakes) make it possible to aggregate data from a variety of sources: market trends, competitor information, and consumer preferences. 

Machine learning(ML) algorithms continually analyze this rich data to find new patterns, improve the accuracy of demand forecasting, and enhance operational efficiency. This is the recipe that Amazon uses to predict demand for a product before it is purchased and stocked in their warehouse. By examining tweets and posts on websites and social media, they understand customer sentiments about products and have a data-based way to model demand uncertainty. 

The good news is that such powerful analytics tools are not restricted to industry giants anymore. Out-of-the-box solutions (such as Amazon Forecast) make such capabilities widely available to all organizations that wish to handle demand uncertainty. 

2. Managing process uncertainties

Organizations operating in today’s supply chain industry need to handle increasingly complex logistic processes. The competitive environment, together with ever-increasing customer expectations make it imperative to minimize uncertainties across all areas of supply chain management

3. Synchronization among supply chain partners and customers

Digital supply chains are characterized by synchronization among hundreds of departments, vendors, suppliers, and customers. In order to orchestrate activities all the way from planning to execution, supply chains require information to be collected, analyzed, and utilized in real-time. A sure way to achieve a fully synchronized supply chain is to leverage the power of automation. 


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