Adding AI and machine learning to automation technologies makes them more adaptable and resilient.
Process automation digitises and streamlines business processes using technologies like workflow tools, document scanning, and data entry scripting. Intelligent automation improves the effectiveness and robustness of these tools by adding in technologies like machine learning to improve process decision support, process discovery to increase automation coverage, and data analytics to improve process measurement and insights.
Organisations are focusing on intelligent automation through this more extensive set of technologies as a way to progress from a collection of tactical solutions that handle limited scenarios to a capability that meets a wide range of automated business outcomes.
Document processing, document generation, data entry into application screens, tracking approvals, and forwarding on tasks to the next process participant can often be completed or assisted through the use of the intelligent automation technologies described below.
Processes can progress and complete more rapidly when they are automatically routed to the right people for action along with quick access to the information they need. Combined with the reduced staff effort described above, less time is also needed to action each task within the process.
Providing timely responses to requests, faster location and access of documents, better visibility over processes that span multiple systems and departments, and decision support through richer Data and Insights enables the organisation’s staff to achieve better outcomes.
Automatically creating digital documents and converting inbound paper documents to digital format allows for electronic document management systems to replace the risks and administration effort of managing paper documentation. Automatically capturing data from digital documents into applications also reduces the staff effort and errors in processing inbound documents.
Streamlining business processes and reducing the staff effort on repetitive tasks allows for reduced costs in completing individual transactions. It also redirects staff effort from lower value tasks to more complex work that requires expertise, innovation, and personalised communication.
Intelligent automation contributes to enhanced Customer Experience and Modern Workplace solutions, by digitising and streamlining processes to provide quicker and more consistent responses and task completion. The reduction in human error and variability provides better consistency and process control, while monitoring and analytics enables more timely exception management.
Intelligent automation is an important part of broader initiatives such as Digital Transformation. It provides the transition functionality to migrate from manual processes and paper documents to digital solutions, while also collecting additional data to support better visibility of processes and measuring of actual outcomes.
To streamline business processes and track their progress, workflow and process technologies automate the routing of tasks between different users based on defining specific paths and rules for each process. The data capture and review needed for each task is typically further supported by quick navigation to either customised workflow forms or quick links to specific application screens and data.
This software automates repetitive, rule-based human interactions with computer applications by recording or programming the interactions into re-runnable scripts. The scripts mimic the human’s behaviour with an application user interface to perform tasks like entering data into forms and extracting data displayed on application screens.
Similar to how RPA automates human interaction with computer applications, document processing software can automate capturing information from electronic documents, for example digitising paper-based supplier invoices and capturing the key attributes of each invoice even when different document formats are used.
Many workflows typically require the creation of documents during the process for internal or external distribution. Document generation tools automatically create documents at the required stages using data captured through the workflow and any related systems, also applying any rules-based decisions that determine changes to the documents content and layout.
The rules engine that drives the automated decision making in workflow automation, RPA, and document management can be enhanced through the use of AI. Analysing the organisation’s structured and unstructured data with machine learning and other algorithms can be used to make predictions and dynamically evolve the initial pre-defined rules that support the other automation technologies.
Having tools to document, manage, and communicate business processes provides a strong foundation to then assessing which processes can be automated and also identifying how processes can be removed from organisational or application silos and further optimised. Advanced BPM tools can also manage the organisation’s workflows as a full repository rather than as individual workflow solutions.
BPM can be complemented by using technologies that identify and detail business processes across the organisation. These technologies identify significant events produced by operational systems by analysing server logs, application outputs, database changes, and similar electronic evidence of digitised business activity.
By moving from manual processes to workflow automation and RPA, the organisation can automatically capture a lot more data about the stages, steps, timings, and user interactions that occur with the automation. Using analytics with this data provides relevant insights to the organisation on how to further improve its processes, automation, operating rules, and decision support.
Intelligent automation tools are only as good as their supporting data architecture. When they have appropriate access to the data in the organisation’s applications, they can provide more insights and decision support that is more timely and complete. With access to automatically issue designated requests and progress business transactions, they can reduce the need for data re-entry and manual user actions in end-to-end business processes.
Most organisations have a set of primary systems and applications that provide most of what they need, which typically leave a number of gaps in system coverage across a range of other processes. Low-code and no-code platforms are focused on providing a range of small tactical solutions that reduce the number of these gaps, which supports workflow automation outcomes by keeping task completion and data capture away from manual, paper-based approaches.
Some of the typical challenges around intelligent automation are not knowing where to start; inadvertently collecting a wide range of different and incompatible automation technologies; and getting the workforce to adapt to making use of these technologies as an improvement to their effectiveness and efficiency. That’s why the additional practices which complement the adoption of intelligent automation technology are very important, they will help the organisation evaluate, select, and introduce the technology in an effective way, also focusing on how the organisation’s processes and workforce can be improved and sustained alongside the technology.
The team from Diversus bring their experience and expertise from helping many other organisations select and adopt the intelligent automation solutions that are best for their situation. Our clients have been able to streamline their business processes, reduce their reliance on paper record keeping, redirect staff effort away from repetitive tasks, and empower their workforce to achieve better outcomes with transformation and collaboration.