Automation generates high profile jobs – and they’re up for grabs
There is a concern and fear among employees regarding automation for obvious reasons. However, there is a real opportunity up for grabs created by automation - high profile jobs.
Computational and data models have gone through a huge change in the last twenty years, from simple client-server models to mobile apps. Despite periodic and rapid changes in technology, enterprises have managed to continue doing business using disparate technology and architecture.
This has driven the need for frequent manual tweaking of IT and business processes, which, in turn, created a large demand for employees who are able to manually intervene in the processes to support the business. These jobs range from manual monitoring of NW, HW, DB, other infrastructure, Apps Server, Webserver, application and business transactions.
The rise in the number of employees required to support, oftentimes, mundane and repetitive activities fueled the need for automation. Currently most enterprises are moving forward with automation programs that limits human intervention in IT and business processes. There are several reasons for this:
1. Quality and Reliability: Human intervention creates people dependency, frequently resulting in low quality due to human error. For critical services, human-based services are not reliable. For example, an alert is given through email / text message, but if the employee has not read the mail / text message, a resolution does not happen.
2. Time: Human-based service delivery is slow when compared with an automated one.
3. Cost: Today, most businesses are becoming available around the clock due to the digital revolution and web-based services. Employees cost more and for services running 24x7, that adds up!
Robotic vs. IT Process Automation
We can broadly divide automation into IT Process Automation (ITPA) and Robotic Process Automation
RPA automates business process service activities by utilizing the presentation layer, which eliminates regulatory compliances violations such as Sarbanes-Oxley (SOX), HIPAA (the Health Insurance Portability and Accountability Act) etc. Most of the RPA tools screen scrape the flow to record the user activities and automate those using scripts at the backend and creates the robot (automation script). ITPA automations the IT layer as show in the image above. ITPA involves connecting the application servers, databases, operating system and other components at the IT layer and automates the process flow and creates the scripts and schedule them at the scheduler in the Orchestrator.
RPA and ITPA are both software development projects which normally use an agile approach. Those wanting to benefit from RPA opportunities must have some level of process knowledge, technical development knowledge of one or two scripts and specialized skill in one or more RPA tools such as Blue Prism, Automation Anywhere, UIPath, WorkFusion, OpenSpan etc.
In ITPA, the automation scripts and software pieces are developed to work within the IT Layer. To ease the process, orchestrator tools are provided by almost all ITSM tools providers such as ServiceNow, BMC, CA, HP etc. Automation of complex IT workflow can be designed with the help of designer studios and schedulers provided by orchestrators. An automation engineer who wants to specialize on ITPA must have the following skills:
· At least some experience in agile application development projects
· Skills in powerful scripting languages, including Python and R
Development of automation software is made easy thanks to powerful scripts such as Python and R and a few tools such as Orchestrators, RPA tools and some artificial intelligence platforms. Python and R have very powerful libraries, which essentially free developers from having to write long codes.
Cognitive Automation: Another level of automation
In RPA and ITPA, there are two levels of automation: rule-based process automation and cognitive automation. In rule-based automation, the process steps to be automated are well defined. For example, consider the following examples:
· Loan Approval Process
· Remittance management
· PO approval process
· Insurance Policy acceptance process
In the above cases, processes are well defined and automated. In other words, we automate tasks by writing the program (code) as defined in the process. This is what we call rule-based automation. However, cognitive automation, like artificial intelligence based automation, uses machine-learning algorithms, that are able to learn from the data and create its own rules. In RPA as well as ITPA, there is a strong focus on using artificial intelligence based approaches for automation. Almost all RPA tool vendors and orchestrator vendors are adding machine learning and intelligent predictive capabilities.
Automation Engineer: Your new career path?
Since automation methods are ever evolving, we usually design the solution based on an agile approach for a quicker and more reliable implementation. In the current set up, it is estimated that there are around 40% to 80% manual activities that will be automated in the next year or two, which is a huge undertaking and will require a large number of automation engineers. But they won’t be working alone; agile project managers, analysts and automation development engineers will also play a big role. The following table shows a summary of other high profile jobs created by automation.
Automation Engineer: Your new career path
|Sl No||Role||Responsibility||Skill Requirement|
|1||Automation Engineer - RPA||Develop, test and deploy Robots using an RPA tool|
|2||Automation Engineer - ITPA||Develop, Test and deploy automation scripts|
|4||Automation Agile Project / Program Manager||Automation projects are planned and delivered in time using Agile approach|
|5||Artificial Intelligence Specialist|
Design the Artificial intelligence based solution for problems
Model the data for training the AI based systems
Automation engineers and others who aspire to get involved with artificial intelligence based automation must understand artificial intelligence, predictive analytics and machine learning. In the next couple of years almost all manual processes will be automated using cognitive approaches, those who learn quickly will be able to enjoy the early bird opportunity. This opportunity has already reached the market and it’s only going to expand. The next couple of years will be an exciting time for automation.
(About the author: Xavier Chellandurai is vice president of group competitiveness and automation at Capgemini. This post originally appeared on his Capgemini blog, which can be viewed here)