Just a decade ago, IT and business process decision makers were actively discussing the pros and cons of business and IT process automation. Today, the discussion over the topic is no longer taking place and attention has turned on how to move to the next level of automation, typically termed as hyper-automation. Gartner estimates that 69% of routine work done by managers globally will be automated by 2024.
Automation in the form of using programmed bots to take over repetitive, human intensive tasks, also termed as robotic process automation, has moved forward. The demands today are a process of continuous process discovery, continuous process improvement, and continuous process automation. There is now a relentless push to automate more and more IT and business processes and to improve the level of performance and returns from automation.
To reach these levels of performance, hyper-automation is using a combination of process mining, Process discovery, Natural Language Processing (NLP), AI-powered OCR in addition to robotic process automation. The end goal is a fully automated, end to end, self-improving enterprise.
A key minimum condition to achieve these deep levels of successful, end to end automation is complete visibility and understanding of every business and IT process inside the enterprise.
Inside any organization, every business and IT process is the sum of how the workers and systems involved in the process execute their operations. While a business process can be defined by the head of its business, the actual execution by its workers tends to differ. Every worker has their own way of executing their part of the operation and those nuances can seldom be captured by the head on the top of the business operation. The same analogy applies for IT processes.
Moreover, while the starting and ending point of a business process remains the same, the course of the processes can change and does keep changing.
In fact, as organization adopt automation, the first hard-fact of reality that they realize early enough, is that there is no such thing as the perfect process and there is no such state as the continuously static process.
Processes are derived from the needs of a business to deliver based on the internal and external market conditions and the workers who are part of the process. Since these are not fixed nor static, a business process will also not be fixed and static and will keep changing over time.
According to Forrester, 37% of decision-makers report delays to their digital transformation initiatives due to misunderstood processes across the enterprise.
The newly emerging best practice of process mining now allows enterprises to track every step of their business and IT operations and ensure these are aligned with the requirement of business as it exists today and tomorrow. Productivity of an enterprise is centred around having complete control and visibility into every single business critical process and operation.
Discovering the reality of an organization’s business processes, also termed as process mining is not as big a challenge as it used to be previously. Every business application captures how its processes work and saves this data to be accessed through select tools. How long does a process take; who is involved in the process; and at what stage does a worker enter and exit the process.
Previously, the usage of legacy systems and legacy platforms could not make this rich trove of user data visible and available. Process mining tools built on digital platforms, now provide this transparency. Process mining accesses the digital footprint of a process across business applications and makes it visible to decision makers and process architects.
By leveraging the event data of a process, process mining can help to indicate which parts of the process are ready for automation and which parts of the process need to be improved and reengineered. Process mining helps to indicate which parts of a process are impacting customer engagement, customer experience, and customer satisfaction. Using process mining, enterprises can enter a loop of continuous improvement, both internally and externally.
Benefits of process mining
These can be summarised as:
• Provides a comprehensive view of enterprise business processes, allowing them to identify inefficiencies, bottlenecks, and opportunities for optimization
• Provides real-time insights into process performance, allowing organizations to quickly identify and address issues as they arise
• Helps to continuously monitor progress of automation and ROI being generated
• Identifies which parts of a process are the most valuable for automation
• Generates business benefits by aligning best practices and automation
• Converts into an audit tool since it saves history of processes before and after automation
According to McKinsey, the opportunity to automate work is $3.6 trillion opportunity. Forrester adds that the opportunity of automation will create 15 million new jobs by 2027. In the regional market, automation is a huge opportunity for specialist partners offering hyper-automation solutions and services for their valuable enterprise customers.