The Future: Order Entry with Innovative Automation Solutions

Processing incoming orders is a critical step in the sales process that impacts customer satisfaction and business efficiency. Despite advancing technology, many companies still rely on manual methods to capture orders, which has a negative impact on time, human resources and accuracy. More and more companies that want to ensure their long-term competitiveness are therefore looking at alternatives to manual document processing. This blog post will therefore introduce you to various approaches to automating order entry and explain why the introduction of automation solutions makes sense

What solutions are available for automated order entry?

Level 1 - Optical Character Recognition (OCR): OCR technology enables the digitisation of documents, but is limited in the interpretation of data

Level 2 Template-based systems: These extend OCR with customised templates, but do not allow comprehensive flexibility

Level 3 - Robotic Process Automation (RPA): RPA automates repetitive tasks, but is less suitable for diverse order documents

Level 4 - Electronic Data Interchange (EDI): EDI enables the digital exchange of business documents and rationalises processes, but requires intensive coordination and can still have errors

Level 5 - Artificial intelligence (AI): AI solutions enable an intuitive understanding of documents, are highly customisable and capable of learning. They offer the most comprehensive automation options and can process a wide range of formats and languages

Level 1 - Optical Character Recognition (OCR)

The first step on the way to automated order entry is the use of automatic text recognition. OCR (Optical Character Recognition) technology is changing the way organisations process their documents. OCR technology enables companies to quickly and accurately digitise their physical documents, streamline data entry processes and improve overall efficiency. OCR can extract text from images or documents, analyse it pixel by pixel and convert it into digital text, making the data machine-readable. This makes the information available for transfer to other systems.

Once documents have been digitised using OCR technology, the text is converted into a machine-readable format that enables further processing. This step is crucial to driving digital transformation in organisations. By converting documents into a machine-readable format, companies can unlock the potential of their data, making it easier to search, analyse and use. This not only saves time and costs for organisations, but also improves accuracy and eliminates errors that can occur with manual data entry.

The result of automatic text recognition is machine-readable data. What OCR technology cannot do, however, is interpret the data. Without this interpretation, it remains unclear whether a sequence of numbers is an article number, a tax number or the postcode of the customer's delivery address. As a result, automatic processing of the data is only possible to a limited extent and a human translator is still required to interpret the data in the order entry process.

Thanks to OCR, all content can be selected from the document by humans using the copy & paste process, which can save a small amount of time compared to completely manual typing. However, OCR technology is not a fully-fledged solution for automating order entry. In order to upgrade to a higher level, companies that currently use OCR solutions should plan to switch to higher-quality software, as discussed in the following levels.

In summary, it can be said that OCR technology can help with the digitisation of orders, but is not suitable for the automation of order entry and quickly reaches its limits. Companies can therefore only be recommended not to rely on pure OCR solutions, but to urgently consider the introduction of higher-level systems. Only in this way can the benefits of process automation really be realised satisfactorily.

Advantages of OCR technology: 

• Changes document processing in companies
• Enables fast, accurate digitisation of physical documents
• Streamlines data entry processes and improves efficiency
• Extracts and digitises text from images/documents
• Enables transfer of information to other systems
• Saves time and costs and improves accuracy

Disadvantages of OCR technology: 

• Cannot perform data interpretation
• Automatic data processing is limited
• No fully-fledged solution for order entry automation
• Limited realisation of process automation without higher level systems

Level 2 - Template-based systems:

In this category, conventional OCR technology is enhanced with customised templates to combine automatic text recognition with the interpretation of the recognised data. Templates are the backbone of these systems and provide a structured framework for document processing. The solutions utilise pre-stored layout and format templates that specify where on the document which information is stored. An approximate interpretation of the machine-readable data is possible via the spatial assignment of read-out data with the context information from the template.

To use template-based systems, each customer's specific document layout must be entered into the software. To do this, a template must be created in which the spatial position of certain information on the customer's document is specified, e.g. the delivery address always at the bottom right of the document. The predefined templates allow solutions in this category to be customised to different formats and layouts. The prerequisite for this is the storage of the specific templates in the software. Once the template has successfully interpreted the information extracted from the document using OCR technology, the data field can be transferred to the input screen of the ERP system for order creation. This data transfer can take place without human intervention, enabling order entry to be automated.

The consistency of incoming customer orders and the number of (new) customers are decisive for the success of the software in this category. Even the smallest deviations from the template, such as a two-page order instead of a one-page order, order item lines with page breaks or an additional note on delivery instructions, can mean that the extracted data can no longer be interpreted automatically. As a result, the automatic processing of incoming orders fails and manual processing of the order becomes necessary.

Alternatively, the customer's stored template can be customised. However, this process is usually very time-consuming, which only shifts the workload away from the manual entry of orders to the maintenance of templates or, in the worst case, even increases it. Solutions based on templates are therefore only worthwhile for a limited group of companies or can only be an intermediate step on the way to a high level of automation. To achieve this goal, it is necessary to use solutions from the higher levels.

To summarise, it can be said that template-based systems are a first step in the direction of automated order entry. These systems are particularly suitable for companies with a small customer base that changes little and remains consistent in its orders. However, companies with growth ambitions or with a large customer base should refrain from introducing template-based solutions and instead turn to solutions from higher levels in order to be able to satisfactorily implement automation of the order entry process and realise the benefits.

Advantages of template-based systems:

• Automated text recognition and data interpretation
• Structured framework for document processing
• Adaptability to different formats and layouts
• Automation of order entry
• Suitable for companies with a small, consistent customer base

Disadvantages of template-based systems:

• Time-consuming input of specific document layouts per customer
• Problems with deviations from the template
• Only suitable for a limited group of companies
• Restrictive for companies with growth ambitions or a large customer base

Level 3 - Robotic Process Automation (RPA)

Robotic process automation (RPA) represents a refinement of template-based systems. With RPA, repetitive, manual, time-consuming or error-prone activities can be taken over and automated by so-called software robots (bots). When processing documents, these bots can automatically read out individual data points. Once the order data has been read, it can be translated into a standardised data record and forwarded to the ERP. RPA enables companies to streamline their workflows, resulting in greater effectiveness and employee satisfaction. The beauty of RPA is its ability to perform repetitive tasks, allowing people to focus on value-adding tasks and ultimately increasing productivity.

The bots act based on rules (if this, then that). By automating repetitive tasks, RPA allows employees to devote their time and energy to higher priority tasks that require human expertise. However, it should be noted that RPA has its limitations when it comes to decision-making tasks that require human support.

RPA solutions are somewhat more flexible than template-based systems due to the large number of mappable options. In order to be able to process the widest possible range of formats and cases, a larger set of rules is required, which of course also increases complexity. The RPA approach works excellently for processing standardised documents. In order entry, however, such a system quickly reaches its limits, as a large number of different order documents often have to be processed with a wide variety of rules. This significantly reduces the accuracy of RPA and requires constant manual maintenance of all the customer-specific rule sets.

The cost aspect of RPA software should be critically scrutinised. Work is often shifted from commercial employees to specially trained RPA programmers in the IT department, which leads to increased costs and can cause bottlenecks in IT. Low-code solutions also give users from the specialist department the opportunity to automate processes using RPA. However, the coordination required to standardise processes and create complexity should not be underestimated. Before introducing RPA solutions, companies should scrutinise whether they want to jump straight to the highest level of automation and use high-quality AI software for this purpose. Companies that already use RPA software should critically evaluate how resource-intensive the maintenance and servicing of these systems is. In order to achieve an even higher level and sufficient future viability for the process of automated order entry, switching to adaptive AI-based solutions is a worthwhile alternative.

To summarise, it can be said that RPA solutions are well suited to the automation of standard processes. For processes such as order entry, which are characterised by a pronounced diversity, the comprehensive mapping of all possible process variants and special cases can become very complex and time-consuming in terms of maintenance. 

Advantages of RPA systems:

• Automates repetitive and error-prone tasks
• Increases effectiveness and employee satisfaction
• Increases productivity
• Enables focus on prioritised tasks
• More flexible than template-based systems

Disadvantages of RPA systems:

• Limits in decision-making tasks
• Increased complexity due to multiple rules
• Reduced accuracy with multiple documents
• Constant manual maintenance of rule sets required
• Cost and IT resource expenditure
• Costly maintenance for complex processes

Level 4 - Electronic Data Interchange (EDI) 

With the introduction of electronic data interchange (EDI), the automated processing of order documents can become a reality. EDI enables the digital exchange of business documents between companies in a standardised electronic format. By eliminating the need for post, fax and e-mail, documents can be seamlessly transferred from one application to another for immediate processing across company boundaries. This automation not only saves time, but also reduces the risk of errors that can occur during manual data entry. By utilising EDI processes, companies can streamline their operations and focus on more important tasks at hand.

In order to use EDI transmission, point-to-point connections must be established between two business partners. The companies involved must agree on a specific EDI standard and a specific version when setting up the direct connections for the exchange of EDI messages. All EDI messages sent and received must then comply with this agreed standard format so that error-free processing is possible in the systems of both business partners.

The benefits of using EDI for automated document processing are numerous. It not only simplifies and speeds up business processes, but also increases data accuracy and improves overall efficiency. Standard EDI formats ensure data quality and proper process management. The direct connection of the other company to your own ERP systems via EDI is particularly useful for business partners with high trading volumes. 

The disadvantage of EDI is the high level of effort required for each individual EDI connection. A standardised format must be agreed with the business partner for each connection, which often requires a great deal of coordination. In addition to the initial agreement, the format must also be adapted individually each time one of the two partners changes the formatting or the structure of a data field. In addition to the high time and cost involved in harmonising the format, additional software costs for process integration solutions are often required to set up the EDI connection. Furthermore, the EDI connection does not protect against one business partner transmitting invalid order data that runs into errors in the other business partner's ERP system and requires human verification.  

To summarise, EDI has become an indispensable tool in the way key business partners communicate with each other. Especially for business partners who exchange high volumes of trade, the direct digital exchange of information can help to automate order entry. Due to the high level of coordination and costs involved, an EDI connection is often not worthwhile for customers who order irregularly or only very small baskets of goods.  

Advantages of EDI technology:

• Accelerated document processing
• Time savings through automation
• Reduced risk of errors
• More efficient business processes
• Improved data quality and efficiency

Disadvantages of EDI technology:

• Complex set-up and coordination
• High customisation requirements
• Additional software costs
• Risk of data transfer errors
• Not always advantageous for smaller customers

Level 5 - Artificial Intelligence (AI)

Software solutions that use artificial intelligence (AI) to extract, interpret and process order documents and the information they contain provide the highest level of automation for order entry. AI enables an intuitive understanding of documents, as would be the case with human processing. Intelligent Document Processing (IDP) offers high-speed processing that allows large volumes of documents to be processed with ease. In addition, IDP is characterised by easy setup and commissioning, making it a user-friendly solution that can be implemented quickly and seamlessly. This not only saves time, but also reduces the risk of human error.

Software that uses AI is much more flexible when processing documents with different layouts than template-based systems or RPA solutions. Thanks to a high degree of customisation, AI solutions can be adapted to the individual needs of companies. In order to be able to reliably process a wide variety of document formats, AI solutions are trained using a large data set of documents. In this data set, all data points relevant to order processing are annotated in a training data set of documents. Based on this labelled information, the AI develops a generalist understanding of the documents and can interpret them in a similar way to a human.

The AI is thus able to recognise the data points it is looking for in the documents largely independently, regardless of the layout or language. Even layouts that were not included in the training data can be extrapolated and processed very reliably with sufficient training. The variety and number of documents in the training data set, as well as the quality of the labelled data, are decisive for the performance of an AI. For this reason, solutions that work with a centralised data set for a diverse customer base have a particularly generalist and flexible understanding of documents. If new order documents to be processed are continuously added to the training data, the AI learns about them and is able to find the required information more and more reliably.

Unfortunately, missing or incorrect data on order documents is the rule rather than the exception: outdated or incomplete customer and article numbers, unclear article descriptions and a wide variety of date, number and quantity formats. The formatting and normalisation of incoming data in different source formats, such as dates, units and addresses, into a desired target format is easily possible thanks to individual configuration options. AI systems are able to utilise additional data sources beyond pure documents in order to validate and expand document data. By integrating customer and article master data, the data points recorded can be checked for accuracy. This also enables the automated enrichment and correction of data. AI solutions with this type of functionality significantly increase the effectiveness of order entry automation.

A further and decisive advantage of modern AI software programs for automated order entry is the possibility of machine learning by the system. Intelligent systems can learn from patterns and trends on documents as well as from human feedback, such as the data input of the clerks. In this way, implicit knowledge that is only in the heads of employees can be transferred to scalable systems over time and secured in the long term. AI software is designed as a self-learning system that continuously learns and evolves over time without the need for active intervention or training. This means that the system becomes smarter and more efficient over time, further increasing its performance.

To summarise, it can be said that AI solutions take the automation options for order entry to a whole new level. A wide range of formats and languages can be processed automatically without having to set up and maintain a complicated set of rules. Simple set-up and continuous learning also make AI software economically attractive. Due to the increasing speed of innovation in the field of AI, further progress and leaps in the effectiveness of the solutions can also be expected in the coming years.

Advantages of Artificial Intelligence:

• High-speed processing of large volumes of documents
• Easy setup and implementation
• Flexibility in processing different document layouts
• High degree of customisation to individual company requirements
• Ability to recognise data points regardless of layout or language
• Continuous learning and improvement of performance over time
• Utilisation of additional data sources for data validation and enhancement
• Automated enrichment and correction of data

Disadvantages of Artificial Intelligence:

• Dependence on the quality and variety of training data
• Challenges in processing missing or incorrect data on order documents
• Requirement to constantly update the training data set with new order documents

Conclusion

The processing of incoming orders is a crucial aspect of administrative processes in sales. In many organisations, order entry is still done manually, which can be time-consuming, error-prone and costly, especially when orders are received in different formats and structures. These manual processes are at odds with today's customer expectations for fast response times and first-class service. In times of a shortage of skilled labour and rising customer expectations, the automation of order entry is essential to remain competitive in the long term. The holistic integration of sales, production and logistics for smooth processes can significantly improve the customer experience and promote long-term customer loyalty.

It is important to understand the different levels of automation, from OCR technology to AI-based processing. Each level offers different advantages and disadvantages, depending on a company's individual requirements.

Overall, the benefits of implementing order entry automation software are numerous, including increased productivity, reduced labour concerns, managing seasonal fluctuations and supporting business growth. However, organisations should carefully consider what level of automation best suits their needs and invest in quality solutions to ensure long-term success. The future of order entry undoubtedly lies in automation and the use of modern technologies such as AI to optimise operations to the highest level and meet the demands of an ever-changing business world.

If you have any questions about automating your order entry with the help of AI software, we will be happy to advise you in detail about the Workist solution. Arrange an expert appointment today!