Launching RPA in an Enterprise

robotic photoRobotic Process Automation (RPA) is the latest technology to mature in the area of digital transformation and cost optimization for companies. Before launching RPA in your organization, it is important to develop a strategy that best leverages the software to deliver tangible results tailored to your organizational priorities. Most organizations prefer to experiment with RPA in contained areas before driving an enterprise-wide launch. When organizations are serious about launching an RPA program, this proof of concept or pilot approach can work best if you model sample areas that model common scenarios across the organization.

Before launching RPA, the best practices the companies can inculcate for the preparation and then operations of RPA include working actively with your IT team to install RPA software successfully and constructing the platform controls for enterprise automation, training human capital for effective adoption of ‘bots, creating a ‘bot “manufacturing process” for defining, configuring, designing and testing automated processes and monitoring the RPA platform for ongoing improvements.

Once you have begun defining how RPA will roll out across the enterprise, it is important to identify the candidate pipeline for automation and, ideally, frame up an intake, prioritization, and governance process to qualify candidates. These days there are many best practices that help define RPA ‘bot success factors – such as processes that are rule-based, well defined with repetitive steps, require minimal human intervention, etc. More on that later, but the goal is to discover all qualified processes to realize the ROI of RPA while avoiding the distraction of those processes that will not deliver comparable value through automation.

To that end, performing an analysis of ROI is an important step in launching RPA. It is advisable to calculate all kinds of costs both non-monetary and monetary along with the time taken for completing processes and compare it with the cost optimization offered by RPA – just as would be required of any company initiative. In addition to creating structured intake and governance, launching RPA also involves putting infrastructure in place and procedures required to develop then support the ‘bot development. Lastly, enabling the tracking the results is also crucial in this new paradigm of “snackable” or bite-size projects called ‘bots. We need to take the investments seriously and realize that the success of RPA in your enterprise requires a system that can systematically identify, approve, deliver, and perform at a high-volume, granular level.

Launching RPA can work efficiently for your enterprise if you take the proper steps to prepare, organize, launch, and then track specific results to the business.       

RPA: The Good, The Bad, The Ugly

Robotic Process Automation (RPA) is the maturing trend in the businesses because well, it involves robots and robots are awesome! As fascinating as the concept sounds, it may be that “all that glitters is not gold” in some situations. The main idea of RPA is introducing software that handles repeatable human interactions and mundane tasks with software application instead of humans.

The Good

The good side is, of course, it reduces the human effort, and therefore cost, in un-important areas of business management. RPA deals with various applications performing tasks such as opening email attachments, filling e-forms, recording data, re-keying information, etc. eliminating long hours of copy-pasting and data entry stuff. It is especially useful while dealing with the old legacy applications creating the continuous flow of digital data instead of accumulated large data pools in corporate sectors and it is definitely money-saving as well.

The Bad

The downside however of RPA is based on the fact that it automates the same rules and repetition of processes and is not able to adjust like humans. If there is any change in the application’s data, user interface, or some other aspect of the business process, the deployment of a “’bot” is faced with major complexity and ultimately is broken down. The downstream and upstream mutations can considerably delay the process even in the duration of bot configuration. The truth remains that even the slightest of changes that could easily be dealt with the manpower can cause months and months of lagging in the corporate infrastructure.   

The Ugly

Then there isrobot photo the economics. While change management and adaptive capabilities are challenges for RPA (and its robot army), there is the cost and effort of buying a software stack, building human capabilities and culture around RPA, and pointing automation in the right areas of the business to drive results. These dimensions are all part of the business case that must be considered for RPA.  Simply put: RPA is not point and shoot.

And The Good

RPA still offers quite a bit of value in large organizations and/or across processes with high volume, repeatable steps. The mantra remains: free up your expensive resources (labor) to focus on high-value work like exceptions or innovation.

Also, companies are already enhancing the RPA systems with Artificial Intelligence (IA) – also described as RPA systems with cognitive abilities i.e. CRPA (Cognitive Robotic Process Automation). This software is more resilient and smarter than the ordinary RPA, detecting changes, and making intelligent decisions. But the debate remains the same as some cons outweigh the pros in this situation too. The CRPA technology is still not mature and is functioning in its early days where you cannot rely on it completely for your corporate data. The fact that RPA makes use of the UI (User Interface), can make it brittle to use. Some modern apps are offering APIs (Application Programming Interfaces) which makes RPA somewhat resilient to the changes but this capability is still emergent in the market.

RPA technology is recommended if you are dealing with legacy system-driven processes but need to succeed in the modern digital world.  RPA can provide a valuable bridge to keep these legacy business processes moving while both re-focusing knowledge workers and preparing for more strategic automation of a digital enterprise.