Introduced in 2019 by Gartner, the world’s leading information technology research and advisory organisation, Hyperautomation has taken the world by storm. Read on to explore.
Hyperautomation is an effective approach to identify, vet, and automate as many business and IT processes as possible. This extension business process automation beyond the confines of individual process automation requires the orchestrated use of multiple technologies, tools, and platforms, including Robotic Process Automation (RPA), ‘low-code’ platforms and process mining tools.
Hyperautomation marries tools such as Artificial Intelligence (AI), Machine Learning (ML), event-driven software architecture, RPA, Business Process Management (BPM), Intelligent Business Process Management Suites (iBPMS), Integration Platform as a Service (iPaaS) and packaged software with other types of decision, process, and task automation tools. In doing so it allows for automating any and every repetitive task within a business.
Technologies leveraged in Hyperautomation
Hyperautomation uses an infrastructure of advanced technologies that help an organisation automate its capabilities and scale up.
Some of the technologies used in this are process mining and task mining tools that allow for identifying and prioritising automation opportunities, and automation development tools for reducing the effort and cost of building automations. The latter include RPA, no-code/low-code development tools, iPaaS for integrations, and workload automation tools.
Business logic tools are also used in Hyperautomation as they make it easier to adapt and reuse automations, including intelligent Business Process Management (BPM), decision management and business rules management. Lastly, AI and ML tools are used to extend the capabilities of automations. The range of tools in this area include Natural Language Processing (NLP), optical character recognition, machine vision, virtual agents and chatbots.
Potential use cases for Hyperautomation
Hyperautomation has been instrumental in enabling several businesses in digitising their operations and scaling up significantly. Here are some of the top uses cases from across the industry:
- Enhanced customer service: Hyperautomation can help reduce response time by instantaneously addressing a customer’s concerns and proactively delivering effective solutions across all channels of communication. Additionally, Hyperautomation tools within the system can enable the setup of an initial point of contact for customers where queries are attended to, sorted, and then redirected to the relevant department.
- Prevention and monitoring of money laundering: Hyperautomation solutions like AI, ML, or a combination of RPA bots can monitor early signs of money laundering and send out alerts to avert any possible consequences for business and customers. For example, RPA bots can be deployed to collect and process customer inter-linked data and pass on the records to verify an interaction and conduct post-payment follow up confirmation actions and so on.
- Declutter ‘Accounts payable’ process: Hyperautomation can be used effectively leveraged by ‘Accounts payable’ teams as such solutions simplify the entire process, from receipt to payment, through the use of BPM, OCR, bots etc.
- Streamlined talent management process: Hyperautomation solutions can unburden talent teams by automating the tasks of sorting through spam, spotting potential candidates, and filtering undesirable applications based on pre-loaded parameters
- Seamless technology integration: Hyperautomation can lay the foundation for successful integration of analytical, operational, and storage tools that can make any process comparatively more robust. A hyperautomated setup can also allow any business to communicate effortlessly as well as access and analyse data that has traditionally been inaccessible to gain important organisation-level insights
Implementation of Hyperautomation with Business Process Management (BPM) and Robotic Process Automation (RPA)
Synergy between BPM and RPA
RPA aids in automating repetitive, monotonous, and time-consuming tasks or activities, thus freeing up team to focus on complex business activities. RPA itself is agnostic and based on events or triggers that are elementary, such as mouse or keyboard usage and scraping web pages. It is not focused on or built to optimise business processes; rather, it is a surface-level fix aimed at maximising efficiency of repetitive tasks and minimising human intervention.
On the other hand, BPM is all about streamlining and re-engineering business processes to deliver greater efficiency. It is important to remember that BPM is not a task management or project management tool. Just like RPA, it aims to optimise existing repetitive business processes with predictable patterns. However, its focus lies on automating end-to-end business processes by listing administrative processes or steps for various scenarios, creating an outline of complete workflows, identifying, and focusing on areas where the workflow can be optimised and then amending the workflow to make it more efficient and effective.
Possible scenarios of synergy between BPM and RPA
Handling exceptions: Consider a scenario where an RPA bot is handling a complex logic and encounters something unknown. The bot cannot process this unless it is specifically programmed to do so. BPM can include processes to diligently handle such complex exceptions
Handling bottlenecks: A potential bottleneck in the BPM process, such as manual data entry, which can potentially delay or derail the full cycle can be assigned to an RPA bot to save time and effort
Handling notifications: If RPA-related tasks exceed the expected timeline, they can be handled through the ‘Event Timer’ feature of BPM. The feature enables triggering of automatic notifications to the designated SPOCs to move the tasks towards timely closure
Handling decision task segregation: All decision-related tasks can be segregated into automated (less critical) and human-driven (critical) segments during the modelling phase and can be choregraphed by BPM. The critical tasks can be owned by BPM, while RPA handles the rest
Handling manual activities in a task: RPA can help automate the solution in scenarios where a task includes manual activities that cannot be automated programmatically. For example, legacy CRM/ERP systems which don’t offer an API and require manual data entry
Hyperautomation and architecture
The ‘bridge and adapter’ pattern
An integration between RPA and BPM systems can be achieved through a ‘bridge and adapter’ design pattern. During execution of a business processes, the bridge will initiate and execute robotic automated activities without any manual intervention. It will then go on to connect to BPM and RPA via APIs and communicate through specific adapters.
Such a pattern does not limit the capabilities of either of the systems, acts independently, manages the integration with a single configuration and allows for the separation of concerns between the RPA and BPM. Additionally, this does not impose constraints on the abstraction level of the processes that are to be automated.
Out-of-the-box Integration between BPM and RPA
Several key BPM suites allow for an ‘out-of-the-box’ pre-built integration with the most relevant RPA products. This can be considered a ‘low-code’ solution requiring minimal coding.
Benjamin Hoffman explains this pattern with Camunda, an open-source workflow and decision automation platform and UiPath which makes robotic process automation software.
Camunda makes an API call from the workflow engine to the RPA tool (UiPath) and receives a call back from the RPA tool so that the workflow can continue. With UiPath orchestrator’s REST API, a new work item can be added to a dedicated queue. One or multiple robots can fetch items from that queue and work on those items. The work item itself contains all the context data from the workflow that is needed to complete the task. The Camunda RPA Bridge is a standalone application that allows for such integration.