ABPM - RPA Exam
What type of data can RPA perform 'if, then, else' statements on?
Structured data
T/F: Only the business side can realize the benefits from a technology solution
True
T/F: Jobs are eliminated with RPA
True, but as jobs are eliminated new ones open up because we are redistributing work to support new innovation
How can we ensure that creating the bot script delivers good results?
1.) Business people create the scripts, not IT professionals (training for proper use) 2.) Have well understood and documented processes 3.) Understand interfaces between applications (how data is transfered) 4.) Test all the time
How can we ensure that the bot delivers over time?
1.) Dedicated bot personnel 2.) Analytics to understand bot performance and automation target 3.) Contingency plan for broken bots
What are the steps in RPA implementation?
1.) Identify candidate process for RPA 2.) Process developer creates the set of steps for the automation bot 3.) Bot is operational and uses software licenses to perform the steps 4.) Bot is centrally monitored for performance 5.) Performance improves
What causes RPA efforts to fail?
1.) Not considering RPA as business-led, as opposed to IT led 2.) Not having an RPA business case and postponing planning until after proof-of-concepts (POCs) or pilots 3.) Underestimating what happens after processes have been automated 4.) Treating Robotics as a series of automations vs. an end-to-end change program 5.)Targeting RPA at the wrong processes 6.) Applying traditional delivery methodologies 7.) Automating too much of a process or not optimizing for RPA 8.) Forgetting about IT infrastructure 9.) Assuming RPA is all that's needed to achieve a great ROI 10.) Assuming skills needed to create a PoC are good enough for production automations
What does a typical RPA Architecture consist of?
1.) Process library of routines/scripts developed 2.) Controller dashboard that allocates work to "bots" 3.)Server-based runtime = pool of bots (allocation options and price vary)
What are some risks in RPA implementation?
1.) Process volatility (rules change over time i.e. flux) 2.) Environment volatility (ongoing system updates, etc.) 3.) managing licenses, security, risks, governance 4.) lack of process documentation/standardization
How do we make a bot operational?
1.) Redesign processes to support both humans and bots 2.) Understand security implications (background checks and credentials for humans and bots) 3.) Understand bot governance and chain of command for bot actions 4.) Have a deployment roadmap
What should a good process candidate have?
1.) Standardized, repetitive tasks 2.) Structured data 3.) Clear decision rules
What are some of the things that we need to consider before everyone can "go home happy
1.) Target revenue generation while reaching for cost savings (avoid focusing on RPA solely to reduce labor costs) 2.) Automation should be a business initiative supported by IT
What are the benefits of RPA?
1.) saves time, costs, labor 2.) increases operational efficiency/capacity 3.) decreases variation & errors
What is attended deployment in RPA?
Attended deployments run on the user's desktop and are invoked by the user to automate routine activities associated with processes
What is unattended deployment in RPA?
Automated activities that do not require human intervention after they are programmed and are activated by a schedule, timer, trigger, call, or can run on demand
Who should be responsible for creating the bots?
Business users
T/F: Scalability is difficult with RPA
False; RPA has the potential to scale quickly and companies can go from a couple of bots to dozens in little time
Should RPA be seen as an IT initiative?
No; only the business side can realize the benefits from a technology solution
What is the difference between RPA and AI/Machine Learning?
RPA is standard and methodical, AI can think and come to conclusions rather than just simply follow instructions. AI can provide meaningful, insightful outputs on non-routine tasks
What is RPA?
Robotic process automation (RPA) is the use of software with artificial intelligence (AI) and machine learning capabilities to handle high-volume, repeatable tasks that previously required humans to perform.