Industry analyst IDC predicts that by the end of this year European organisations will spend over 271 billion dollars on Digital Transformation, included within these investment initiatives are Intelligent Process Automation (IPA) technologies. With such huge investments anticipated, it is more important than ever that organisations ensure they truly understand their use case, the outcomes required and the most suitable technologies to deliver against their Digital Transformation strategy.
In many instances, a use case may involve the simple task of moving data from one system or database into another or the processing of structured documents. For these examples, Digital Process Automation (DPA) technologies such as OCR and RPA offer an effective solution. DPA takes the appropriate manual tasks within a process and makes use of computer systems to help organise and perform them more efficiently, eliminating unnecessary repetitive tasks by having the computer carry them out instead. DPA works very effectively when structured data needs processing as it relies on pre-programmed rules to locate data.
The problem for many organisations, however, is that the data they receive is often semi-structured or unstructured, creating a real stumbling block for traditional DPA solutions. For example, when DPA software receives a document that does not conform to the pre-programmed rules, an exception is created. The software will then either need to be recoded to handle the new document template, or it will be passed to a human operator to manually process. At high volumes, this method of handling document exceptions becomes unmanageable and is costly both in resource and time to the organisation.
By applying IPA solutions to document processing, intelligent technologies such as Machine Learning, Natural Language Processing and Cognitive Automation are introduced, and exceptions can be handled within the end-to-end digital process. IPA platforms, such as Celaton’s inSTREAM™, apply Machine Learning algorithms, which have the ability to learn through the natural consequence of processing through the collaboration with operators who teach it about document exceptions in a process called ‘Human in the Loop’. This removes the need for recoding with every new document type received.
The main advantages of applying ‘Human in the Loop’ are:
No Code. No-Fuss - No requirement for reprogramming, coding or technical skill because of ‘Human in the Loop’ Machine Learning, reducing costs and time delays.
Enhanced customer service, quality and experience - Faster processing times free up staff to spend more time with customers enabling elevated service levels. Furthermore, better visibility of data provides greater and quicker access to transaction insights enabling faster resolution times, again improving the customer experience.
Improved workforce and process efficiency– The removal of manual and repetitive labour-intensive tasks (including exception handling) enables faster end-to-end processing.
Boosted employee morale and efficiency – Through the removal of repetitive and mundane data entry tasks, employees can focus on more rewarding tasks such as building relationships, negotiating deals or problem-solving.
Increase data security – Better visibility and access to documents and data ensures compliance with regulations and minimises risk to the organisation.
Business agility - Continual optimisation and scalability with growth or surge periods without the need for additional programming or technical skill.
With so much impetus for organisations to start their Digital Transformation Journey, it is fundamental that businesses look beyond the hype surrounding traditional DPA solutions and spend time getting to know their processes. It is only through doing this, they can achieve real efficiencies and sustainable long-term transformation.