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Courtesy of Nintex Pty's Paul Hsu, below is a transcript of his speaking session on 'Improve employee productivity during and post-COVID by ...
Process mining is an analytical discipline for discovering, monitoring, and improving real processes (i.e., not assumed processes) by extracting knowledge from event logs readily available in today’s information systems.
Process mining offers objective, fact-based insights, derived from actual event logs, that help you audit, analyze, and improve your existing business processes by answering both compliance-related and performance-related questions.
Process mining is a technique to analyze and monitor processes. In traditional business process management, it is done with process workshops and interviews, which results in an idealized picture of a process.
Process mining, however, uses existing data available in corporate information systems and automatically displays the real process.
A process is a series of actions or steps repeated in a progression from a defined or recognized “start” to a defined or recognized “finish.” The purpose of a process is to establish and maintain a commonly understood flow to allow a task to be completed as efficiently and consistently as possible.
Common business processes include purchase to pay (P2P), order to cash (O2C) and customer service. While nearly every company has some version of these processes as the backbone of their business, there are many others that support a company’s daily operations:
Manufacturing processes
Distribution processes
Logistics processes
Supply Chain processes
Accounts Payable processes
IT service management processes
Accounts Payable processes
IT Service Management processes
Utilities processes
Master Data Management processes
The term process mining originates in the field of data mining. The concept is that you’re “mining” data for insights to answer questions or solve problems. In data mining the search is usually specific to an identified challenge or obstacle.
While it shares some similarities with data mining–in that it analyzes big data to support business decisions–process mining applies specialized algorithms to event log data in order to identify trends, patterns and details of how an entire process runs rather than a singular incident.
The term process mining originates in the field of data mining. The concept is that you’re “mining” data for insights to answer questions or solve problems. In data mining the search is usually specific to an identified challenge or obstacle.
While it shares some similarities with data mining–in that it analyzes big data to support business decisions–process mining applies specialized algorithms to event log data in order to identify trends, patterns and details of how an entire process runs rather than a singular incident.
According to market research firm IDC, not only are most companies unaware of lost potential due to process weaknesses, 20-30 percent of their revenue is lost that way!
Think about all the processes, process steps and people involved in completing a task. Not only are there infinite possibilities for variables, different departments are responsible for different pieces along the way. That means there’s rarely one person or team with oversight of all steps involved. It also means if one area is underperforming it impacts all the others, but it might not be immediately obvious where or how.
It’s important to recognize that processes are not static. Even the best plans have exceptions, and over time these exceptions can become the rule. Dynamic markets also force change: customer expectations, new product lines, acquisitions, changing geographies, outsourcing, different suppliers, competitor moves, rules and regulations, etc.
When everything operates efficiently, a company is agile enough to adapt easily to outside forces, leaving more time to drive revenue through internal innovation, quality improvement and strengthening customer relationships.
In our modern digital economy, companies require flexible processes to be competitive. That flexibility only comes through a deep understanding of how things are working and where shifts are possible.
Which vendor gives you the best chance of meeting a committed delivery date?
Which employees are not following the process?
Which of your channel partners are downselling rather than upselling?
Process mining provides answers to these questions and more.
In addition, process mining allows you to quickly audit your processes, and many companies are using process mining for ongoing monitoring and optimization. That way they can detect potential problems before they have a negative impact, ensuring business operations are cost effective, compliant and several steps ahead of the competition.
Using key process performance indicators (KPPIs), process mining technology can show exactly where there are opportunities to correct or improve processes. By performing root cause analysis on operational system data, it also indicates why things may have deviated from a standard process.
And KPPIs can be connected to a company’s key performance indicators (KPIs) for comprehensive measurement, in-depth analysis, improvement specification and sustainability monitoring all in a single environment.
Back in the day, process mapping had to be completed by teams of people who met together for several days to figure it out on a whiteboard or spreadsheet. In other words, it was a complete slog.
But thankfully, we can leave all that painful people-driven process mapping in the past. Because today, process mining’s powerful algorithms and advanced data transformation make discovering and optimizing your processes fast, data-driven, and complete. And slog-free.
As people and software robots work with corporate IT systems, their activities are captured by those systems.
Process mining transforms this data into an event log—and then creates visualizations of the end-to-end process, along with insightful analyses.
So you’ll have the facts you need to understand, improve, and monitor how things get done… anywhere they’re getting done.
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