Making RPA and Automation Successful with Intelligent Process Mining Technology

In today’s modern economy, our personal experience as consumers informs the changing expectations that companies have in their B2B interactions. If we can get instant digital experiences and guaranteed on-time next day delivery in our personal lives, why can’t we have that experience at work with our supplier relationships?

In addition, as labor rates equalize, and population growth slows, driving productivity by outsourcing to low-cost labor markets is no longer an option for most businesses. As a result, organizations increas-ingly turn to intelligent automation systems to take advantage of the power of digital technology to scale human efforts. As WorkMarket’s 2020 In(Sight) Report points out, employees and business leaders estimate the potential of automation in their average workday to save as much as three hours per person and day. It is, therefore, no surprise that understanding technology’s impact on strategy and business models (EY Research, Top Priorities for US Boards in 2018) is becoming an increasingly strategic priority for executives and process owners alike.

Automation has traditionally meant complex IT-driven initiatives which modify the workflows in operational systems, and leverage the APIs exposed in these operational systems to tie disparate systems together. In contrast, Robotic Process Automation (RPA) offers an alternative approach to speed the delivery of automation by replicating and scaling the activities of human “end users” through automated scripts. RPA is quickly becoming an ubiquitous initiative for modern businesses looking to drive productivity and efficiency. According to a recent study from Deloitte, 53% of surveyed companies are either implementing or currently running RPA programs to transform internal processes like Accounts Payable, Purchase to Pay, and Order to Cash. All with the expectation of significant savings in process costs, improved speed and quality, fewer errors and thereby improving customer satisfaction.

RPA initiatives have significant potential, but there are equally significant challenges. According to Ernst and Young, half of RPA implementations fail due to lack of adoption. To ensure their process optimization initiatives are successful, many organizations follow the example of Siemens and take a process-first approach to RPA.

„At Siemens, automation rule number one is to take a process-first ap-proach. Process mining gives us total visibility into how our processes are running, and allows us to take a guided approach to RPA implementation and monitoring. RPA can deliver big savings, yet the actual potential for RPA related savings must be preceded by process mining to validate if such potentials can be realized. If so, RPA is a great companion to process mining in the desire to drive further automation.”

Gia-Thi Nguyen, Head of Operational Excellence, Siemens

Business Transformation Realized By Combining RPAand The Celonis Intelligent Business Cloud

To achieve success in maximizing your customers’ experience, while improving productivity, it is imperative to combine the strengths of the Celonis Intelligent Business Cloud for managing business transformation with automation. The Celonis Intelligent Business Cloud adds value at all points in an organization’s automation journey. When thinking about RPA in particular, the IBC contributes to an organization’s implementation path from initial decisions about what processes to automate, to actual robot implementation, to triggering robots intelligently, and finally to monitoring and scaling RPA imple-mentations. Specifically, there are five critical best practices for ensuring RPA success through the use of the Celonis Intelligent Business Cloud:

1. Understand and improve processes first, automate second

Before getting started with an automation initiative, it is crucial to take a step back and assess whether current processes are efficient and scalable. If an organization runs very complex and non-standardized processes, automation can make things even worse. Replicating a complex process with many variants using RPA is typically tedious and requires a significant investment. Moreover, the cost of maintaining and servicing robots could significantly outweigh the expected savings. It is critical to understand the maturity of a process and decide which processes are standardized enough to benefit from RPA and which processes would benefit from harmonization and standardization prior to starting an RPA initiative.

Process mining technology, the foundation of the Celonis Intelligent Business Cloud, helps customers quickly and easily understand the maturity of their processes. By looking at the flow of data through the underlying operational systems, process mining technology allows the Celonis Intelligent Business Cloud to reconstruct, visualize and analyze these processes. Companies can then easily assess the degree of standardization by looking at the deviations present in their processes and identify processes with potential for RPA applications. For non-standard processes, proactive insights about the root causes that drive complexity can be used to standardize first before moving onto RPA.

2. Build a business case

Having standardized a process, the next important step is to uncover and quantify automation potential in that process. Without full transparency, automating some manual activities might look like a perfect match at first but prove to have no significant business impact once implemented. To identify suitable RPA initiatives, the number of manual activities has to be assessed as well as current automation rates. If activities are already somewhat automated, one might be better off starting with another completely manual activity that occurs more frequently.

Specifically designed RPA Assessment Apps available in the Celonis Intelligent Business App Store scan the existing processes and leverage the full capabilities of Process Analytics to enable business users to identify and prioritize RPA initiatives and their economic impact with just a few clicks. This allows customers to build and validate business cases and select the right activities early on.

3. Maximize the inputs to building an RPA automation

RPA robots cannot think for themselves; rather, they follow a strictly predefined set of rules. It is crucial, then, not to make any mistakes when implementing a robot. Implementation usually starts with recording a small number of user’s actions, and process experts are consulted to serve as a blueprint for the robot configuration. All too often, implementations focus on the most common scenarios, and important specific scenarios are missed. As they move into production RPA robots often start throwing errors and cannot operate at full efficiency. Lengthy maintenance and revisions are required and prevent organiza-tions from realizing the expected benefit.

By leveraging the Celonis Intelligent Business Cloud customers get full visibility into the actions of every user in a business process because process mining technology provides visibility into the full detail of the underlying business process. In addition, it is possible to combine operational system data with desktop analytics click-path data to provide full visibility into what actions a user takes at each step in a business process. As a result, the most repeatable patterns in a manual activity can easily be found and prioritized by their impact.

4. Make robots “think”

The big advantage of robots--strictly following predetermined rules to automate manual activities with 100% accuracy-- also comes with a downside: They are not able to adapt and deviate from their initial configuration, even if that would result in a more favorable overall outcome.

Linking RPA robots to an intelligent system that runs in the background and actively controls their activity avoids robots running actions blindly and significantly enhances the robots’ performance. The Celonis Intelligent Business Cloud’s Action Engine does just this. Capturing real-time information from all systems in an organization ( not just the ones the robots are working on) and learning from past process data, the Action Engine is able to work with probabilities to identify the right action at the right time. Triggering robots automatically through the Action Engine ensures robots are working in the most efficient way possible to always lead to a beneficial process outcome. At the same time, being able to consider the effect of a robot’s activities further down- or upstream in a process also opens up completely new use cases for deploying RPA that were not possible before.

5. Monitor and scale your automation initiative

Monitoring robots and evaluating their performance might seem very straightforward as one can sim-ply count a robot’s activities and compare that to the previously manual human labor. Things are more complicated in reality because automated activities may not be optimal when considering the full end-to-end process. Robots simply perform their prescribed actions, without accounting for the impact and problems their actions may cause further downstream in the process. Add the fact that robots might be misconfigured, system changes or updates in desktop systems might lead to incorrect entries. The robot might also simply not be suitable for a certain new workflow that is performed by your human workforce, and the risk is that RPA-automated activities tend to become less efficient with time.

The Celonis Intelligent Business Cloud brings data from operational systems together with data about automation rates and robot execution rates to give a full end-to-end analysis of the impact of automa-tion and RPA on process improvement and efficiency. As a result, process owners can keep track of a robot’s impact on the overall organization and react early on should the robot deviate from its intended purpose. At the same time, achievements can be quantified and further automation potential prioritized for scaling up the RPA initiative. With a growing number of bots deployed, monitoring the whole fleet becomes a must and increasingly important as customers scale.

In summaryCelonis’ Intelligent Business Cloud enables real business transformation across all dimensions of pro-cesses, people, and technologies. Working with some of the leading organizations in the world like Siemens, Vodafone or Merck, automation--and RPA in particular--is oftentimes an invaluable tool when it comes to process optimization.

When thinking about RPA, the Intelligent Business Cloud is not only capable of easily identifying and prioritizing automation potential, but also offers more sophisticated RPA integrations to build and monitor the best robots possible. Leveraging the full power of the Intelligent Business Cloud’s Action Engine, robot activity can also be triggered intelligently depending on what action results to the best real-time outcome for the organization.

Celonis is the New York- and Munich-based leader in business transformation software, turn-ing process insights into action with the process mining technology it pioneered. Its Intelli-gent Business Cloud allows organizations to rapidly understand and improve the operational backbone of their business. Companies around the world including Siemens, GM, 3M, Air-bus and Vodafone rely on Celonis technology to guide action and drive change to business processes, resulting in millions of dollars saved and an improved experience for their custo-mers.

www.celonis.com