Process Mining and RPA for Quick Time to Value

Going digital is no longer an option but a necessity in business. Nowadays, digital performance is a crucial business success factor, empowering brands to dominate various niches, optimize production costs, manage regulatory compliance, and do much more.


The business world is more digital today than it’s ever been. Entrepreneurs across all industries are keen on digitizing business processes, as indicated by the rapidly-growing digital transformation market forecasted to reach USD 6.78 trillion by 2029. And according to McKinsey and Company, the enterprise digitization rate is already several years ahead due to the accelerated digital adoption trend we saw during the COVID-19 pandemic.


Automation is a particularly intriguing area of digital transformation—and for good reason. Business process automation streamlines workflows by speeding up tasks, minimizing errors, and cutting costs. With today’s readily accessible and sophisticated robotics tools, business automation is a no-brainer in the digital transformation checkl


“As we get more and more into that digitization phase, we need to have the technology to help us automate work”— Alexandre Lanoue, VP & Leader, Business Reimagination, SIA.”


However, blending automation and business processes can be a tough nut to crack. Quite a few automation projects fail, which is disappointing given the immense business value of automation. Let’s look at what might go wrong when automating business processes and how IBM Process Mining can help.

Why are Some Business Automation Initiatives Unsuccessful?

Robotic Process Automation (RPA) is a popular form of business automation technology that makes it easy to build and deploy virtual “robots” or software bots, usually without coding. Most RPA solutions, including IBM Robotic Process Automation, are pretty intuitive, and you don’t have to be a programmer to automate even the most complex of tasks. So, why is automation problematic? Well, the tricky part is not the practice but the approach.


Here are five common reasons why your well-meaning automation project may fail to meet its efficiency, ROI, or accuracy expectations:

Lacking Clear Goals

Before building or deploying bots, ask yourself what the endgame is. Do you want to cut costs, speed things up, improve security, or minimize human interaction? Setting your sights on realistic and achievable goals will help you develop an effective automation plan complete with key performance indicators and success metrics.

Automating the Wrong Processes

Understandably, many companies are unsure where to start with automation, especially when looking at complex business workflows and processes. You might focus on the wrong processes or tasks, inevitably leading to disappointing results. While repetitive, frequent, and predictable tasks are prime candidates for automation, infrequent tasks requiring qualitative human analysis may not require automation. The secret to successful digitization is selecting the right tasks for automation, which is easy with guidance from an IT expert.

Losing Sight of the Big Picture

Most enterprise processes are closely interlinked and interdependent. For instance, a particular workflow may involve several departments and resources. This is something you must consider when automating a task or process. Take a 360-degree view of the process in question and measure all its dimensions. A workflow chart is a good way to identify and visualize processes and their dependencies. You must know how automating one task affects the outcomes of other processes. After all, the idea is to automate the entire enterprise.

Using the RPA Hammer

Renowned psychologist Abraham Maslow wrote, “If your only tool is a hammer, it is tempting to treat everything as if it were a nail.” This applies to automation as well. Despite its immense capabilities, RPA technology is not a silver bullet for streamlining all business processes. Sometimes, re-engineering, standardizing, outsourcing, or eliminating a process might be more appropriate than automating. So, analyze the underlying problem before hitting it with an RPA hammer.

Lacking Insight into Potential Automation Outcomes

Another problem with automation is lacking a clear picture of the expected behaviour and outcomes. Successful automation requires extensive testing to analyze all possible outcomes and optimize for the more desirable ones. An automated workflow must also undergo several iterations to ensure it checks all the boxes.

Enter Process Mining

COOs and CIOs now realize that process mining can solve most problems standing in the way of successful business automation. Process mining is an umbrella term for techniques used to plan, implement, and manage business process optimization. But there is more to it than that.

IBM’s process mining solution has three levels of capabilities:

1. Discovery

The first pillar of process mining involves identifying processes, tasks, dependencies, and business rules from readily available event logs and information systems such as ERPs and CRMs. This creates process/task models outlining various end-to-end processes and presents them as intuitive flow charts.

2. Monitoring

Monitoring is more of an analytics and conformance phase focusing on KPIs, costs, compliance, automation, and root-cause analysis. Think of it as setting up guardrails for your processes to ensure governance and results.

3. Optimization

Thirdly, process mining lets you create and test what-if scenarios through simulations to see how different process parameters affect the final outcome. The process mining tool also gives you automation recommendations and calculates the ROI of automating various tasks in real time. This is where the magic of finetuning business processes for maximum speed, returns, efficiency, and compliance happens.


Only about 30% of process mining involves automation. Process mining is mostly about measuring and optimizing processes’ KPIs, constraints (compliance, internal governance, business rules), and costs. Remember, the problem with automation is not the process but the approach.


“You cannot manage what you don’t measure.” — Alexandre Lanoue, VP & Leader, Business Reimagination, SIA.


In a nutshell, process mining helps you understand where you should be automating and the impact RPA will have on your enterprise in terms of value. From there, you can optimize and scale your automation solutions for company-wide adoption. Process mining takes the guesswork out of business process automation while providing transparency and clarity on what’s going on. Ultimately, merging RPA and process mining is an easy, fast, results-oriented, and compliance-cautious way to leverage automation in business.


“Robotic process automation and process mining are indeed the ultimate power couple.” —Richard Theodore, Business Automation Leader IBM.


Adopting RPA without first analyzing your business processes, workflows, governance structure, and compliance requirements is setting yourself up for failure. Like with any digital solution integration, you need sufficient groundwork in order to make the right decisions and see desirable results. Process mining gives you a template for laying out your automation blueprints and roadmap. And when paired with the right RPA tools, you get a vast sandbox to experiment with various automation and process optimization strategies.


Speaking of using the right tools, SIA Innovations is your go-to IT partner for all things digital, from automation and modernization to cloud migration. SIA Innovations is an IBM Platinum Business Partner dedicated to offering its clients the best digital enterprise technologies, services, and solutions. Talk to us and discover new ways to boost your business through digital transformation.


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