ThoughtWave with Solution Architect, Tom Blackburn
Brief Introduction of position at Thoughtonomy
Tom Blackburn, Automation Architect in the Research and Development team – focusing on pioneering new methodologies, products and designs alongside development and delivery of Robotic Process Automation projects.
1. How should organizations prepare for deployment of automation?
There are some estimates provided that indicate that almost 50% of tasks or processes that a human performs today can be automated through the use of RPA. If that is true, as your questions suggests, it is important that organizations prepare for this transformational change. As such I believe there are 3 key areas of preparation.
- Evaluation – Evaluating correctly where RPA can be best applied either in distinct business areas, or particular process streams – looking at rule-based processes, especially those with high volumes and low complexity that involve significant amounts of manual activity. These type of processes tend to deliver a sharper and steeper curve to kick-start the delivery of your Return on Investment (ROI)
- Change/Challenge Management – Understand that changes and challenges are bound to come from operational and non-operation sides of the business. Evaluate potential speedbumps to delivery, whether regulatory/compliance challenges or challenges for individual or business areas internally that may delay or become a risk to delivery. Also, it is important to determine the availability of data for each process (test and production) as well as UAT platform or Test Bench availability to assist with the RPA implementation
- Getting Everyone Onboard – A strategic roadmap with long terms goals and achievement milestones can be set out prior implementation of RPA, where RPA can be delivered holistically. Involve the correct individuals for the relevant business areas, including your IT function
2. What challenges have you come across with organizations deploying automation?
I think there are 2 common challenges that I have seen organizations potentially have deploying automations.
The first is choosing the wrong business process to apply automation to.
In the process selection workshops, it is important to ensure that the business process has a solid, stable underpinning manual process that has strict business rules and guidance on how a user, or potentially a Virtual Worker needs to process that task. Initially focusing on this HVLC (High Volume, Low Complexity) model.
The second is to ensure that IT is on-board and have planned the adoption of Virtual Workers servers in the network or connectivity to the remote automation platform.
3. Should organizations consider the deployment of intelligent automation?
Earlier I mentioned that there are indications that around 50% of processes that someone performs today can be automated. The reason that this figure I believe is quite high and actually can be higher almost up to 75% in some business areas is through the use of adding cognitive elements to the RPA implementation.
This is because where previously a business process was considered not viable for automation or – quite importantly, where a particular part of a process is considered not viable which has a ripple effect on the business process as a whole, these can now be included in process selection workshops due to the availability and additional functionality that can be leveraged from cognitive tools that extend RPA’s reach.
As an example using optical and intelligent character recognition technology with a machine learning core may now mean that further business processes that required document understanding and learning are now in automation scope and are viable for automation.
We tend to see that a lot of intelligent automations with cognitive elements being used more so in the front office: classifying customer issues, directing them to the correct person or team, deciding what issues need to be escalated as well as extracting key information in communication.
4. Where do you see intelligent automation in the future?
Certainly, in the chat-bot arena, there are large scale possibilities for automated service desk management that analyses user requests through Natural Language Processing, which can trigger a traditional RPA automation.
But also the ability to analyze previous automation process history and volume fluctuation to apply predictive analysis to better manage the Virtual Workforce, scaling and de-scaling as required.