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Tackling Supply Chain Woes

Leveraging intelligent automation to face the complexity and instability of the modern supply chain.

For decades, manufacturers outsourced production and assembly of products to multiple contractors often located in many different countries, just as Apple uses dozens of global manufacturers to build the individual parts of an iPhone. These global supply chains require planes, ships and trucks to transport the products and warehouses to store the finished goods. This complex web composed of everything from manufacturers and consumer package goods (CPG) brands to transportation fleets and logistics companies is like a delicate ecosystem that is highly sensitive to disruption. Unfortunately, the pandemic demonstrated that it was too sensitive.

While the coronavirus would spread across the entire world, the initial shut down of Chinese factories and plants resulted in global supply chain consequences. Fast forward, and the demand for goods increased; with people stuck at home, shopping and buying online became a pastime. The new omni channels of today made supply chains even more complex, with the number of channels and journey of goods that retailers need to keep tabs on significantly greater. Not to mention increased reverse logistics, return challenges and inventory management. Likewise, there were already truck driver shortages even before the pandemic, which have only gotten worse with the higher federal unemployment benefits.  


The rise in complex omni channels plus supply chain disruption increased the costs of labor, transportation and logistics. Due to the finite amount of resources, like the number of containers and the limit of manufacturing output, delays, shortages and late fees became abundant. In fact, 38.8% of U.S. small businesses reported supply chain delays. All the while, consumers’ high expectations remained the same. The chaos laid bare the vulnerability of the supply chain for all to see. One report, for example, found that only 6% of companies had full visibility of their supply chains.

Recognizing the need to make their supply chains better, leading retailers and CPG brands underwent projects in flexibility, visibility and resiliency. They understood that they had to improve the speed and accuracy of procurement and sourcing, plus the forecasting and replenishment of stores. Moreover, these companies needed to streamline and automate business processes to react and adapt to volatile markets. Today, intelligent automation (IA) has emerged as a prominent solution. 

IA leverages automation technologies and touches everything from physical robotics to intelligent process management to streamline human decision-making across organizations. IA is heavily reliant upon data, as it is nearly impossible (or irresponsible) to make decisions, predictions or react properly to unplanned events without data. However, don’t be mistaken by the name – IA is not cognitive or truly autonomous. Data-driven, and rules-based, IA can help users make more accurate predictions and quickly uncover actionable insights. Like a voice assistant, IA gives humans all the data they need to make the best decision possible. 

From a supply chain perspective, IA can help retailers keep pace with fast and mutable markets through controllable platforms and predictive technology. It can also reveal shoppers’ habits as accurately as a store-by-store basis, simplify manufacturing processes and improve visibility across supply chains. From enhanced inventory allocation and distribution to precise order placement and cost reduction, IA is becoming the future of supply chain management.

Nevertheless, it is not enough to download IA and… presto – supply chain problems solved. The user must abide by several foundational principles, most notably the four pillars of data-driven intelligent processes management. These four – digitization, sense, adjust and react – proceed from each other and are central to IA functionality.

First, CPGs will need to digitize all their processes to enable greater transparency and control. Next, they will need to make sense of their data. Are processes meeting KPIs? Are there any friction points or problems within processes? Unpacking data allows one to answer these questions and more correctly understand patterns vital to decision making. Then comes adjustment. At this stage, an organization, having designed its processes to be easily changeable, will examine its data to see if certain modifications are necessary for further optimization. Finally, CPGs will strive to be reactive and capable of predicting the best course of action timely. 

 

Experts predict that these supply chain challenges will last roughly a year – maybe more. Globalism – for all its economic advantages – contributed to the spread of the virus and the fragility of supply chains. If retailers and CPGs are to endure another global supply chain catastrophe, they must lean into IA to help them weather the storm.

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