


Application of intelligent technology in supply chain management: artificial intelligence and intelligent document processing technology
Artificial intelligence (AI) has irrefutable potential to improve business operations, but not always in the ways people imagine. For some, artificial intelligence in supply chains conjures up images of robots manning conveyor belts or drones speeding up delivery times. While this may eventually become a reality, the application of AI in modern supply chain management strategies is much more practical.
Supply chains are under intense pressure to deliver on time, whether to other organizations or directly to consumers. This situation is further exacerbated by staff shortages across the country, with fewer employees available for day-to-day business tasks.
AI-driven Intelligent Document Processing (IDP) can replace manual data entry with automated data capture, enabling digital extraction and export of information in minutes, simplifying customs compliance and reducing Backlog. By integrating AI applications to optimize user experience and provide immediate, measurable results, the supply chain industry can streamline daily operations, streamline manual data entry, and save businesses time and expense.
Here are some examples of the best use cases for integrating intelligent document processing into supply chain management operations, and the obstacles this technology can overcome:
Manual data entry errors
Gartner predicts that poor data quality costs businesses an average of $12.9 million per year. Many factors contribute to this statistic, with manual data entry playing a large role. Not only is this time consuming, but it also increases the likelihood of introducing human error. The more errors there are, the worse the data quality is, leading to wrong business decisions. Additionally, manually entering data can leave supply chains with outdated information because employees can’t keep up with the volume of data. Rushing to catch up can get ahead of input data quality, leaving businesses with inaccurate information and outdated data, leading to inefficiencies and poor decision-making.
In 2020, a study ranked manual data entry as one of the most hated office tasks among employees, leading to high employee turnover. Intelligent document processing eliminates manual data entry, allowing employees to focus on high-value tasks. Data quality improves and data processing speeds up, saving businesses money and time.
Data Inconsistency
If the company has a manual data entry position, there is a good chance that more than one person is responsible for this position. Adding more people may reduce the time it takes to log this data into the system, but it may also lead to inconsistencies in the data. For example, each employee responsible for manual data entry may define categories differently and interpret the data differently. As a result, information may be entered correctly but shifted or sequenced inconsistently, thus worsening the quality of the data available to the company. While this can be reduced with proper training, it does not eliminate the possibility of this inconsistency.
Intelligent Document Processing (IDP) provides consistency and quality of data input. The system can read documents like a human, but it does a better job of identifying and sorting content rather than blindly analyzing formats. As AI systems are used more, it will get better at data capture, making all entries more accurate. This can significantly reduce the number of data conflicts in the supply chain.
Continuing Backlog
Backlogs and bottlenecks continue to cause delays in transportation and logistics. This problem at individual companies could have a negative impact on the global economy. Companies can work around this by pausing sales and orders while they work through the backlog, but a continued revenue stream is needed to keep the company afloat. From here, the backlog continues to pile up, exacerbating the problem and frustrating customers and employees alike. As supply chains expand, it becomes increasingly impractical for one person to be responsible for handling these backlogs.
Intelligent document processing greatly shortens the time to deal with the backlog and speeds up the delivery of goods. Invoices will have a faster output, errors in documentation will be identified more quickly, and the system can incorporate real-time error correction feedback. Inaccuracies can be resolved immediately and the need for further traceback processes is eliminated.
Smart file handling becomes even more powerful with the addition of email integration. Imagine being able to proactively keep suppliers in the loop with automated email notifications and status updates. It is now possible to automate notifications and alerts, send payment and invoicing information, confirm receipts, provide status and follow-up updates via email.
According to data released by IDC, the global intelligent document processing (IDP) market will grow at a compound annual growth rate of 23.1% in the next five years. Almost all industries are beginning to recognize the importance of integrating IDPs into their business models.
However, advances in artificial intelligence in supply chains or any industry will not happen overnight. When designing new technology, improvement is always a gradual process. To ensure that the supply chain gets the best AI, AI must be implemented from the foundational level. Intelligent file processing provides the artificial intelligence elements needed to automate and streamline workflows for greater operational flexibility. This technology eliminates tedious manual data entry while providing a portal to the collective future that can support the drones and robots that capture everyone’s attention.
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