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Why Process Intelligence is a Real Game Changer

Ryan Raiker

October 15, 2019

“The top 5 key areas of focus for 2018–2019 will be leadership and culture strategy, process redesign work, customer-centric process management, change management strategy and process automation”, according to PEX Network Annual Report 2017 : Global state of process excellence.

Process change can radically change the way an organization operates. According to a widely-cited research by Peter Senge , over 70% of all organizational change efforts fail to meet expectations and deliver planned results. That means that only a small few will deliver on their promises to their boss, team, and perhaps even to their customers.

The “future of business” is with RPA and its automation, but Process Intelligence is a real game changer in how organizations will uncover process and plan for RPA initiatives and continuously stay on top of their operations, ensuring positive outcomes.

The future of work will be entirely different from what we know it as today! The tasks employees perform today will see huge change in the next 18–24 months. RPA and process mining will transform the way organizations get work done. Bots will work literally in unison with human workers.

But, how each of us get there is a different story… and could be a major competitive constraint on the business. How is your organization identifying high ROI opportunities for automation? Are you 100% sure that these choices are accurate? How can you derive more actionable insights from enterprise data to help your business partners react faster to new opportunities like RPA? How does your organization find the best process opportunities for automation? Is your organization still performing time and motion studies?

Businesses are generating an overwhelming volume of data. However, most of them are unable to use it effectively to improve productivity and most struggle to understand how their business operates. Intelligent Process Mining can help!

Recreating processes in the form of an understandable timeline of events allows intelligent process mining to depict and analyze processes in the context of the time, people, and related incidents or tasks. When it comes to the process of service delivery, intelligent process mining makes it possible to easily isolate root causes of undesirable or inefficient processes, and risky protocol deviations. Intelligent Process Mining makes it simple to ask the right questions (even ones you never thought of) and get real answers that can help improve the processes and drive RPA initiatives immediately.

As perhaps you know, when used correctly, RPA is a highly effective automation method for repeatable tasks. If the pre-implementation state of the process can’t be bench marked and mapped, or processes are unknown and the wrong (aka not the best candidates; processes that aren’t offering the highest ROI) processes are being automated, RPA results will not be effective and therefore not profitable. Successful Robotic Process Automation implementation leads to cost saving and increased accuracy, compliance, and productivity. The benefits of RPA are undeniable, but are organizations implementing these projects in the most valued areas? Not always, especially when they fail to understand their processes, its deviations, and any possible variations. But that is exactly how Intelligent Process Mining can help.

Process bottlenecks are often hidden. People have a gut feeling what could be wrong or inefficient, but they lack proof. They don’t have the data to back their assumptions. Repeated steps in the process are often left unfound, and many employees fail to realize other parts of the process as organizations are many times siloed with work being performed across several departments and different locations. This is where intelligent process mining can help. One of the main goals is to be able to see the big picture of a company’s business processes then to be able to drill down to the root causes of deviations, bottlenecks, or process variations. We no longer have to settle for averages but can instead dig out the reasons behind unwanted behavior and see the truth behind the problems in our process.

There is huge opportunity to maximize ROI of RPA with Process Intelligence. Robotic Process Automation is one of the most disruptive technologies available today; however, the number of businesses that have implemented RPA at a scale and were disappointed by the ROI delivered is a warning sign to the underlying troubles some are facing. Without the right knowledge, insight, or accurate understanding of as-is processes, RPA ROI promises are short lived and miss the mark entirely, leaving many managers and project leads disappointed. With data-based insights provided by Process Intelligence during the entire RPA lifecycle make it a complimentary solution that will maximize RPA investments and accelerate RPA initiatives. With the combination of these two cutting edge technologies there is tremendous potential in the transformation of business processes and operations.

Although there is promised financial ROI on RPA implementations, here are three metrics, aside from the financial impact, to measure the ROI of a Robotic Process Automation deployment:

Productivity — Measuring the length of time employees spend on a task versus how quickly robots can complete that same task
Quality — Measuring output accuracy before and after RPA deployment
Compliance — Measuring compliance before and after RPA deployment

True ROI from RPA is dependent on how effectively automation is aligned to processes. This is true even when investment costs are low. It’s important not to rush your organization into a big change project implementing RPA without insight. A good RPA implementation identifies and improves in areas of high value. The best way to make change is to know what change is necessary, critical, and of importance to the business. The next step is to gain an understanding of the process at its current as-is state.

Business process discovery can help to define, map and analyze an organization’s existing business processes. This is a critical component for successful business process management (BPM) initiatives and no one should start an RPA implementation without fully understanding their as-is process.

Robotic Process Automation can do repetitive tasks more quickly, accurately, and tirelessly than humans. The term ‘Robotic’ is slightly misleading. In all actuality, RPA is simply software that is programmed to mimic a human user’s work on a computer. Since RPA bots are designated to complete tasks that continuously need to get done it provides human employees with more time to complete more important complex tasks that can help further success within the organization.

Benefits of process mining within the RPA lifecycle include:

Provide a complete overview of all processes end-to-end
Identify high ROI processes suitable for RPA implementation
Determine the best-case process flow/process path
True Process Intelligence will then be able to provide ongoing process monitoring to detect problems, alerting, and ensuring continuous improvement for sustainable process excellence of RPA in the post implementation phase.

The combination of process mining and RPA is especially important for a company attempting to implement a Robotic Process Automation program into their organization. No matter how much of an improvement an RPA bot makes, if you are unable to see the process path that the bot follows you will not know if there are more efficient, timely and less costly paths that you could program it to take. Process mining gives you the other half of the puzzle by being able to see each and every path that has been taken and gives you an end-to-end view that you can dig deep into the data and uncover things that you would not even know were happening if you only implemented RPA. Heck you wouldn’t even know if you picked the best process for highest ROI. It is time we start improving on facts, not what we think is right, but the truth from the data. It is time to start using Intelligent Process Mining with RPA .

Artificial Intelligence (AI) Enterprise Robotic Process Automation (RPA)

Ryan Raiker

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