Automation of Enterprise Business process & IT, Is it relevant in the current Pandemic context?
Pandemic has changed Enterprise organization’s automation approach and CEOs and CIOs are leveraging Business Process and IT automation using RPA (Robotic Process Automation). Enterprises are focusing to reduce manual task and automate workflows to bring operational efficiency. It is very important to understand about automation and RPA’s relevance during the current challenging pandemic situation. This blog will discuss about different automation options that is available for organization to leverage.
Why do we need Automation?
Primary value of automation is replacement of manual tasks, their associated expenses / errors with software robots. Automation helps in Improving Efficiency, Reducing cost and Preventing errors.
Classification of Automation Based on IT landscape
- IT Automation (Automating IT processes)
- Application Development automation (e.g. DevOps — Application development process, Software Testing)
- Business Operations automation ( Business process automation )
- Robotic Process Automation
- Cognitive automation
- Conversational automation
What is Robotic process automation?
Robotic Process Automation (RPA) is the application of technology that allows employees in a company to configure computer software or a “robot” to capture and interpret existing application for processing a transaction, manipulating data, triggering responses ad communicating with other digital systems.
- The automation software is called Robot
- It will need to be configured to automate your process
- It will communicate with existing IT system, typically via the same Graphical user interface (GUI) used by employees
- The tasks it can complete are repetitive and easy to understand
RPA handles the screens of application systems to process work, and execute tasks just as people execute them. With no application integration required, simplified training, scaling and auditing, RPA offers low-risk, high-value automation.
What is Cognitive Automation?
Cognitive Automation uses machine learning techniques to automate more complex or subjective work which is difficult or slow to codify otherwise. This means work that depends on interpreting and processing data like transactions, documents, images and audio, much as people do. Natural language processing (NLP), image recognition, sentiment analysis, decision / action alternative generation, and similar capabilities enable Cognitive Automation to tackle complex business problems.
What is Conversational Automation?
Conversational Automation utilizes machine learning techniques to extend automation into the realm of conversational interactions. This means that email exchanges, chats or voice conversation can be automated, thereby deflecting inbound or outbound inquiries from manual processing.
IT Automation
Information Technology (IT) Process Automation entails two broad areas of IT service. One is “Run Book Automation”, which offers integration and workflow capabilities. IT Process Automation automates multiple tasks that, when taken together, handle some necessary IT operation. Unlike RPA for Business Operations Automation, generally IT organization professionals implement IT Process Automation.
Examples of IT operations include Running backups , Checking system configurations, Provisioning new IT users during on-boarding operations, Help desk automation
While conceptually similar to Business Operations Automation, note the key differentiators for IT Process Automation that include:
- It is purchased by the IT organization rather than the business
- It targets workflows in the IT organization
As a result, IT Automation tends to be implemented and used differently from Business Operations Automation and different software vendors dominate the space.
Remember that IT Process Automation focuses on IT operation automation, as opposed to the automation of business processes, or application software development.
Types of Automation Based on complexity
- Office Automation
- Attended (Robotic Desktop Automation)
- Unattended
- Virtual Assistant
- Artificial Intelligence
Office Automation
Office automation can be further classified as Front office and Back Office. Front office is typically Customer facing services like Sales, Marketing, Customer support etc.
Back office is the back end operations supporting the customer. e.g. HR, Inventory management etc. Back Office automation is about replacement of manual tasks with technology and automation with End user computing. Examples include insurance policy servicing and reporting, claims processing, and new hire on-boarding.
Attended Automation
Automation of repetitive tasks at Desktop is called Attended automation. This helps augment end user activities, save’s time and improves accuracy of processes which cannot be fully automated.
Unattended Automation
End to End Automation with no user involvement is called Unattended automation. This will include automation of repetitive and clearly defined tasks. Typically those tasks that are time consuming and complex for users to perform will fall in to this category.
Virtual Assistants
Interaction with text or speech using Natural Language is called Virtual assistants. Bots can be as simple as handling FAQ or handling complex transactions. Virtual assistance can “humanize” the interaction with end users.
Artificial Intelligence
Using Machine learning and processing unstructured data, Intelligent automation can be provided combining RPA and AI.
Most of the implementations of RPA in the industry is typically on the Attended and Unattended automation where repetitive tasks with defined process is automated to gain efficiency and save cost. But the market is moving towards Intelligent Automation combining Cognitive and AI capabilities with RPA. Intelligent automation is more relevant now because of the following reasons
Big Data: Data to inform automation is now more available
Cost-effective Infrastructure: Cloud resources make processing of that data much cheaper at scale
Artificial Intelligence (AI): Dramatic advances in AI enable no-code system development. Now, automation is a practical, manageable and scalable asset for organizations.
Below pictures depict how the industry is progressing towards automation from “DO” > “Think” > “Learn”. i.e from Process driven to Data Driven leveraging AI & ML.
Now we will get to the point of discussion as to pre-validations that needs to be done before choosing RPA.
- Are there end user computing automation tools already in use?
- Have existing IT systems introduced automation into their latest release?
- Do you have access to automation through an existing vendor ?
- Does your process use digital systems for input?
- Can you automate the tasks using scripting tools like Shell scripts, python, Java, Macros etc.
- Are there other SaaS solutions that can be used for this process / purpose?
- Is Low code / no code development options can be considered for this process (RAD)?
If there are available alternatives to automate instead of using RPA the same can be considered. There is license cost involved for using RPA bots (Task centric automation) and when the ROI (return of Investment) is good we can go in for RPA implementation.
There are good RPA automation vendors like Blue Prism, Automation Anywhere, UI Path, Work Fusion etc providing capabilities to automate. There are many new vendors entering the space delivering specialized services either in the vertical or specific automation segments like Back office, front office, Attended, Unattended etc.
Roadmap of the RPA industry is moving towards Cognitive computing and AI to be included as part of RPA to support both Structured and Unstructured data. Future is going to be usage of more bots (Task oriented automation) and Digital workforce (Augment Human workforce in handling end to end Business processes). With effective implementation / integration of ML/AI into RPA, Industry is moving towards Augmentation of Humans work. Usage pattern of Digital Business process can be captured by ML / AI and automation tools can learn continuously working with Human. Once the RPA + AI (SPA — Smart process automation) starts having more data, complete process can be automated without or with very less human intervention. With the investments towards this direction by many of the vendors / industry, this is coming to reality now and will have broader implementation across industries in couple of years.
Organizations will have to choose the right automation approach for their needs establishing Automation COEs. This will help guide teams in the implementation and will also help them scale automation across the organization.
With the above summary of Automation landscape, we will have to choose the right automation approach based on the business needs. RPA is not a silver bullet for all automation problems.
