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Top 5 Use Cases for Automation in Supply Chain Management in 2023

CoCo Pierce

The pandemic may be mostly behind us, but that doesn't mean supply chains are back to normal. In fact, other geopolitical and economic events continue to exert pressure on these highly complex but critical supply networks. 

The COVID-19 pandemic highlighted the fragility of global supply chains. Previously stable supply chains suddenly faced heightened demand, trade restrictions, rising freight rates, and factory closures. And some of these issues persist today. 

And then there are the new challenges. Around the world, the logistics industry is struggling to hire skilled workers. And while the US and the EU are feeling the squeeze here, some countries are feeling it even harder. For example, the UK has a shortage of 90,000 to 100,000 haulage drivers. The Russia-Ukraine conflict is also compounding an already bleak global supply chain crisis due to trade restrictions and rising fuel costs. And then there are disruptions due to COVID-19 lockdowns in China as the country presses forward with its controversial "Zero-COVID" policy. 

Unfortunately, we will see supply chain disruption for the next several years. However, that doesn't mean we have to resign ourselves to defeat. 

We can dramatically boost productivity, efficiency, and accuracy with supply chain automation. With this in mind, let's look at the top 5 use cases for supply chain automation in 2023. 

Robotic Process Automation in the Supply Chain

Robotic process automation, or RPA, automates and accelerates repetitive, rules-based tasks usually performed by humans. You'll also see RPA bots referred to as smart bots, especially when the bot performs complex tasks or leverages artificial intelligence. 

RPA can use optical character recognition (OCR) to extract text from images and documents or use other scripts to handle repetitive, rule-based digital tasks such as filling in the same information in multiple places, reentering data, or copying and pasting data across locations. 

So, that's RPA, but what about supply chains? Supply chains are networks of companies, resources, and people involved in producing and delivering products. Some vital components of supply chains include retailers, vendors, producers, warehouses, transportation or logistics companies, and distribution centers. 

Supply chain automation, therefore, uses RPA to make supply chain processes lean and efficient. Unfortunately, many supply chain tasks are incredibly time-consuming and error-sensitive when done manually, leading to inefficiencies and costly delays. Smart bots solve these problems. There are a vast number of use cases for RPA in the supply chain, and we can't get into all of them here. However, we can look at some of the most impactful ways RPA revolutionizes the supply chain. 

RPA Use Cases in the Supply Chain

RPA has numerous applications across the supply chain, so let's get into some of the most popular ones. 

1. Integrated Data Transmission

Condition monitoring is an excellent example of this use case in action. Just delivering a product isn't enough. Logistics companies also have to ensure it arrives unbroken or unspoiled. This usually means keeping the product at the right temperature and humidity, ensuring it can sustain shocks, and ensuring it is only opened if it's supposed to be. 

To achieve these goals, companies use IoT devices to collect and transmit data about products while in transit. This data not only provides a useful snapshot of current shipments but can be used for future analysis to improve the supply chain. 

RPA can help with the data handling and analysis side of things here. IoT devices generate vast amounts of data that contain valuable insights. However, to unlock these insights, you must ensure the data is formatted and stored appropriately and can reach the right computer systems when required. Smart bots can extract all the necessary information, store it in an appropriate place, and send it to data analysis software for crunching. 

2. Order Management

Order management is a crucial part of the supply chain and is where much of the complexity in supply networks come in. Here, order management refers to everything related to tracking, capturing, fulfilling, and managing customer orders. For example, the company must confirm received orders, process payments, ensure warehouse personnel pick up the item on time, and ensure it's properly packed and shipped on time. 

Essentially, the order management process contains many repetitive steps, making it a prime candidate for supply chain automation. RPA can handle complex workflows. It can save time by verifying orders, pulling data from multiple systems, and eliminating duplicate orders, all without human input. In addition, the datasets involved in order management are often large, and handling this manually can result in errors that either delay the shipping process or lead to poor customer experiences. 

Critically, smart bots can work 24/7, ensuring that orders are managed effectively even when workers are not in the office. RPA for order management helps boost efficiency in order fulfillment, provides reliable data for further supply chain refinement, and reduces time wastage in troubleshooting problems in the order fulfillment process. 

3. Shipment Status Management

Often, customers want an update on the status of their shipment - Has it left the warehouse? Is it already in transit? How long will it be until they receive the item?

When done manually, the process looks like this:

  • The customer emails the company asking for an update.
  • An employee at the company will open the email and copy the order reference number. 
  • They then paste the order number into the ERP system to find the order status. 
  • Report back to the customer. 

This process is time-consuming for employees and can sometimes result in customers waiting several hours or even days for an update during hectic periods when employees may be busy working on other tasks. 

Luckily, RPA solves this problem. RPA can handle the end-to-end process of updating customers on their order status, and it can do it in a fraction of the time as a human worker. 

Smart bots can also update various companies in the supply chain about any delays or changes to the shipping schedule. By providing this information in real-time, every entity in the supply chain can ensure they are prepared for when the package arrives. 

4. Invoice Processing and Payment Management

Companies that rely on manual invoice creation often encounter delays, errors, and discrepancies. This can hamper the company's delivery speed, and reputation, and potentially lead to fewer opportunities to collaborate with other companies. 

Invoice management is one of the top use cases for RPA across sectors, and with good reason. Invoicing and payments involve a lot of necessary but tedious steps. So, by deploying automation, companies can increase their employees' productivity by boosting accuracy and reducing the time spent processing invoices. 

Invoicing robots can download invoices, scan or read paper invoices using OCR, capture data from emails, validate invoices, monitor payment deadlines, and streamline invoice acceptance. For example, the RPA bot could log into any vendor's online portal to download invoices or identify emails with invoices and extract the information from the attached files. It could also compare invoice data with internal company records and Purchase Orders to validate the information. 

Smart bots can also help with payment execution, ensuring that approved payments are automatically scheduled and sent out by the given date. 

5. Supply and Demand Planning

Supply and demand planning is tricky. Companies must accurately forecast customer demand and ensure the inventory supply meets the forecast targets. Accuracy is key here. And for accuracy, we need reliable data. 

This is where RPA comes in. With smart bots, companies can collect, store, and extract crucial data needed for accurate forecasting. The bot can collect data from anywhere - any system, emails, market intelligence reports, sales teams, vendor data, and so on, to provide the most accurate picture of the current climate. Moreover, RPA bots can prepare this data for analysis, ensuring that any erroneous or duplicate information is removed before the data moves to the next system in the chain. This is crucial because inaccurate data leads to inaccurate forecasting and, potentially, wasted inventory. 

Final Thoughts

With supply chain issues set to continue over the next few years, companies must optimize their processes to maximize efficiency, flexibility, and resilience. Supply chain automation is the most effective way to achieve these goals. RPA bots help boost productivity, save time, eliminate human error, and reduce overhead.

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