An increasing number of businesses are using process mining to adapt to a new world of remote work and stay ahead of market shocks with more agile and resilient processes. In fact, research by Deloitte found that 63% of global companies now use process mining, while many more plan to use it soon.
Process mining is a way to see how business processes are carried out inside the organization. It is a set of techniques that gathers the data from event logs, analyses it, and identifies the inefficiencies and bottlenecks within information systems. Process mining is one of the top ways to identify automation opportunities and a catalyst for robotic process automation (RPA.)
To discuss this topic, Workfellow CEO Kustaa Kivela joined Dave Dabbah on the Robocorp and Beyond podcast. The two experts shared their experience and views on a rapidly changing and growing software.
The Birth of Workfellow
Before founding Workfellow, Kustaa was an RPA solution consultant. A big part of his job involved traveling around the world, helping companies understand where to implement new technology. Kustaa used Google Translate to read Polish process maps. He knew he’d need to truly understand what was actually going on in processes and operations before attempting to improve them.
Hoping there would be an easier way to figure out what’s happening in business operations, Kustaa explored process mining technologies to help him in his role. But no technology that could give a rapid, objective understanding of the as-is state of operations existed. So, he created Workfellow. Today, Workfellow’s Work API offers a faster, more holistic understanding of operations and helps pinpoint automation targets in end-to-end processes. But Work API isn’t driven by process mining alone.
The Rise of Process Intelligence in Digital Transformation
Process intelligence helps digital transformation by giving a deep understanding of new technology and where it fits within an organization during the implementation phase. This helps companies ensure they are getting the most from their investment and ensures everyone is using it as planned.
Using process intelligence is also easier than ever. Previously, analyzing huge chunks of data required the help of internal or external professionals. Today, self-service enables all employees – with or without technical knowledge or experience – to view ready-made insights in an easy-to-understand model.
A Holistic View of the “Small Stuff”
But it’s no good having lots of data you don’t know what to do with, which is why many companies are adopting automation platforms for time-saving benefits.
At Workfellow, we can detect copy-pasting between two different systems in process flows. When you multiply every person involved in that process, you get 100 copy-pastes a week. This means the entire team produces 5200 copy-pastes a year. Ineffective systems cause bigger companies bigger amounts of money. Often, fixing so-called “small issues” in one system fixes a series of problems for companies and employees such as low projectivity and high spending.
COVID and the Rise of Shadow Processes
Shadow processes became a common issue during and after COVID because companies very quickly implemented more digital tools to survive. Because of this, many process flows and workflows were born but never documented, leaving companies with processes they don’t understand and cannot improve.
In this era of remote work, it’s more important for businesses to identify what their processes are and how they are conducted. Adopting process intelligence solutions is a good idea, as it helps workers understand what could be improved by mapping out processes.
The Bottom Line
The way we work has changed dramatically over the past few years and is still rapidly evolving. Thankfully, the industry is one step ahead. Now you don’t need to develop big projects to get started with heavy-lifting specialist tools. Many young and innovative companies have developed tools to give businesses a real-world view of their data in just a few days, so getting started is easier than ever.
