As the amount of data companies need to process in day-to-day operations becomes larger and larger, business processes get more sophisticated and intelligent automation needs gain urgency. There are many competencies that companies have to possess to keep pace with these requirements. Digital transformation is the overall framework which can be defined as the process of using digital resources to improve existing business models and culture or creating new ones.

Intelligent Automation as a Part of Digital Transformation

One of the main goals of digital transformation of an organization is to automate operations and processes. This not only about getting faster or more profitable, but also getting able to make better decisions and becoming more strategic.

Overall, we conclude that digital transformation is a more complex type of technology-enabled business transformation, which needs to address the strategic roles of new digital technologies and capabilities for successful digital innovation in the digital world (Yoo et al. 2010). We define it as the process through which companies converge multiple new digital technologies, enhanced with ubiquitous connectivity, with the intention of reaching superior performance and sustained competitive advantage, by transforming multiple business dimensions, including the business model, the customer experience (comprising digitally enabled products and services) and operations (comprising processes and decision-making), and simultaneously impacting people (including skills talent and culture) and networks (including the entire value system).

Digital Business Transformation and Strategy: What Do We Know So Far? by Mariam H. Ismail, Mohamed Khater, Mohamed Zaki

With this perspective in mind, we can understand why intelligent automation is such an important stage of digital transformation. It is so important because it is impossible to digitize processes and operations without utilizing intelligent automation tools. Companies need to free their employees from manual work as much as possible. So that employees can become more productive and focus on high value tasks instead of repetitive, time-consuming jobs.

Handling Data with Data Extraction

As we mentioned above, the amount of data companies need to handle is getting larger. It is not easy to process such a big amount of data, especially when it is generated through many types of documents. When data is arrived in various formats and mostly unstructured, we need a solution to extract, interpret and validate data. Data extraction tools are built to meet this demand and OCR technology has been enriched by AI assets.

Since it is possible to run intelligent automation only after proper data extraction from documents, it is critical to choose a well-developed data extraction solution.

What are the Stages of Intelligent Automation?

Although requirements and KPIs for intelligent automation differ from industry to industry, there are some common principles and methodologies to be used as a guideline.

  • Data Extraction: This is the first step towards successful automation. OCR and ICR engines working through AI based software, make it possible to extract data in various formats, from any type of document.
  • Data Processing: Once data is extracted and digitized, second step is processing it. Machine learning technologies come in help at this stage. Data validation and classifying is ensured with high accuracy.
  • Data Distribution & Automation: As a final step, structured and validated data should be distributed to relevant authorities and core systems. Integration to ERP or DMS software is undertaken at this stage and final automation tasks are completed.

Too many companies and business leaders believe that using automation technologies is one of the smartest ways of gaining competitive advantage and profit. They are completely right; however, they overlook the human component frequently. When you run business automation technologies (RPA, process automation, intelligent document processing, data extraction etc.) within your organization, obvious benefits occur: reducing costs, speeding up operations, minimizing human error, getting more control and transparency.

All these benefits create great business results yet they can help to achieve something else, which is equally important: employee upskilling and satisfaction. If a company is able to use automation technologies to bring out the best in people, then it will take advantage of a lasting transformation of organizational structure and corporate culture.

How Does Business Automation Help Employee Upskilling?

In a recent Deloitte survey of more than 11,000 business leaders, more than 60 percent of respondents said they actively redesign jobs around artificial intelligence (AI), robotics, and new business technologies.

Robots, machines and business automation software can execute repetitive tasks much faster and more precisely than humans. Nevertheless, there are many critical skills such as innovative thinking, creativity, ethical judgement, responsibility, intuition which can be performed by only your human workers. And when people find room and time to use their skills, it is shown that they feel much better and engaged to work.

According to a recent survey, daily stress level of employees is getting higher. Intelligent automation can also help employees to cope with stress. When people have proper tools to use, they feel more secure and comfortable in terms of finishing their jobs on time and with success. 89% of employees believe that automation helped them to be more efficient on work.

Where to Start Intelligent Automation From?

It is always better to start simple. First, define what you need and specify bottlenecks of your processes. Listen your workers and involve them in decision making. Afterwards you can start looking for alternative solutions. Try to go step by step, but never miss the big picture. If you need an invoice extraction tool, for instance, be sure that it can integrate to your existing ERP or is able to streamline with a proper intelligent document processing framework.

One of the most promising areas for digitization of business is cognitive data capture. Among many applications of cognitive data capture, invoice processing is getting ahead because of fast and effective results that companies get.

In every company, accounts payable department spends most of its time to process invoice data. Invoice processing consists of a series of steps, which must be followed and executed strictly. Data collection, validation, approvals, payment terms and synchronization of all these steps with an ERP or accounting software can easily lead to bottlenecks in any organization.

Instead of putting that much load onto your accounts payable team, you can start using a solution that uses cognitive data capture in order to automate invoice processing.

What is cognitive data capture?

 

Cognitive data capture performs two main functions: Data extraction and data validation/correction. Automation of these two steps are vital for invoice processing, because there are various invoice formats with respect to metadata and you often encounter with several unstructured and non-uniformed data.

As the first step, onVision Invoice Extraction product uses a mixation of OCR and ICR to recognize contents of invoice and extract data with a high level of accuracy. Following this step, machine learning procedure begin to show off its abilities. Each line item of the invoice is analyzed and interpreted by AI. Based on confidince score rating and spatial referencing method, data validation/correction is finalized.

 

5 Benefits of Using Cognitive Data Capture for Invoice Processing

  • Traditional OCR tools can solve some basic problems of invoice processing, nevertheless OCR needs rules and templates to work properly. This means that a human operator needs to define rules and templates for each new invoice format. On the contrary, cognitive data capture is document-agnostic and can learn and operate by itself without any supervision.
  • Automation of invoice processing through cognitive data capturing reduces costs (time, money, energy) and enhances efficiency of the relevant business process.
  • Increased level of control and transperancy is another significant benefit. You can easily prevent fraud, duplicates or any possible malicious attempt, by using cognitive data capture for invoice processing.
  • When you automate invoice processing by cognitive data capture, it works as a catalyst for other enterprise software solutions and business processes. Supply chain management, customer relations will benefit and your ERP system will perform much better.
  • Digitization level of a company depends on the ratio of its paperless and touch-free processes. If you aim at increasing digitization level of company, cognitive data capture is your best servant.

Learn about onVision Invoice Extraction product.

Digital transformation has been around almost for two decades, however there is still lots to do to overcome devastating paper work and manual document processing.  Main reason which lays beneath the fact that document processing (invoice processing, banking and financial document processing, legal document processing etc.) couldn’t reach to a higher level of digitalization is the difficulty of transforming contents of custom and arbitrary documents to structured, standardized data.

According to a recent survey, 92% of business leaders agree that companies need to enable process automation technologies. OCR (optical character recognition) technology plays a vital role in this story. It is still the best method to turn print outs into consistent digital data, which can be processed by computers. And the good news is OCR technology is improving constantly. Nevertheless, companies need more complex, flexible and yet accurate solutions than OCR in order to fulfill their challenging document management and digitalization needs.

How Does Intelligent Document Processing Work? 

 

Think about all of these various types of documents, forms, e-mail attachments, PDFs, invoices, receipts, work orders, bank and insurance statements etc. Tones of valuable data are stored in these documents, yet it needs a great deal of time and effort to reach and use them meaningfully.

 

Intelligent document processing (IDP) can be defined as a bunch of solutions come together to transform unstructured data into usable data and finally to create smooth, productive and cost-effective work flows. Most of IDP tools can be easily integrated with enterprise solutions such as ERP, CRM and DMS.

Components of IDP framework are:

  • Data capture & classification: OCR, NLP
  • Data extraction & interpretation: Deep learning, machine learning
  • Data validation & automation: AI, RPA

What Are the Benefits of Intelligent Document Processing?

 

When you run an IDP platform your business gets into a total boost. Typical and obvious benefits of IDP are:

  • Time and cost savings
  • User friendly processes and efficiency
  • Data accuracy & security uplift
  • Higher satisfaction of employers and customers
  • High quality internal project management

These benefits can be designed for a high variety of use cases in a flexible manner. One of the best assets of IDP is this flexibility, which is built on different levels of technology. For example, a medium sized exportation company can limit the solution for scanning invoices and extract invoice data to transfer to concerning parties in seconds. Besides, a large international enterprise would run AI based intelligent document processing in a multi lingual environment. And also can track, interpret and create each business process through robotic process automation (RPA) integration.