Data is the most significant asset for many organizations. As Wil. van der Aalst, Professor at RWTH Aachen University - Godfather of Process Mining said "Data science is the profession of the future because organizations that are unable to use (big) data smartly will not survive. However, it is not sufficient to focus on data storage and data analysis. The data scientist also needs to relate data to process analysis"
Data and analytics are required to drive corporate transformation and optimization through technological innovation. A new generation of smart analytical tools allows companies to use that data to see what is going on in their back-office operations.
Process mining is a new research field that falls between artificial intelligence and data mining on one hand, and process modeling and analysis on the other. Process mining is designed to discover, monitor, and improve real processes by knowledge from event logs readily available in today’s information systems.
These “process mining” tools can rapidly analyze thousands of transactions to reveal the underlying process flows. Provides insights to data analytics professionals that enable faster, smarter decisions and improved performance on the organization's most critical priorities.
The process model should be well-proven, based on available day-to-day operational data also being understood and engaging all process participants will create awareness and valuable insight to overcome future shadow processes. This will be delivering a path to digital operational excellence.
We as Beakwise partner with Livejourney, a process mining company recognized by Gartner, Everest, Quadrant, and ISG. Developing software able to discover, monitor, and analyze any kind of process thanks to its technology and data science.
How does it work?
The process mining task starts with an event log, and each event in such a log refers to an activity related to a particular case. The events belonging to a case are ordered and can be seen as one "run" of the process. So, these logs give you a real-time picture of how your processes are running.
Process Mining collects the transition from one stage to another. Also allows you to analyze process deviations to help you make the right decisions. Finally, Process Mining allows you to focus on one unit of your process to understand the path on the field, the trace.
Machine learning and AI (Artificial Intelligence), make it possible to analyze the history and predict the paths of your units in the future, complementary to the process mining.
The Value of the Process Mining
Processes are vital for businesses that run smoothly. The way that these processes are executed has a direct impact on critical business outcomes.
Data and analytics leaders need the means to reflect on how these modern technology capabilities may give value to the organization and the customer in the age of digital commerce. Analyzing corporate operations, procedures, and customer interactions can reveal how and where these capabilities can be used to generate business value.
Creating operational fluidity
Businesses can use a process mining learning loop to better understand their processes, predict future outcomes, and automate decisions based on continuous learning.
Process Mining Addresses Several Prominent Issues
Increases level of customer
Reduces the operating cost
Mitigate the risk.
Solves the challenge of identifying
the sources of waste, inefficiency, and lost value in company operations with
speed, and analytical power.
Management trends related to
process improvement and compliance can benefit from process mining.
to detect and map all their activity and processes in real-time. It provides a
visible, dynamic, and exact view of how procedures are carried out in the
interview-based process discovery and modeling are costly and time-consuming.
Assists you in identifying
inefficiencies, recognizing abnormalities, deducing fundamental causes, and
converting redundancies into points of optimization and automation at every
level of your company.
Process mining is the detection
of non-compliance in essential processes to avoid deviations. It is a
particularly useful use in the field of cyber-security.
Process models, exceptions, and process instances, as well
as basic frequencies and statistics, are discovered automatically.
Customer interactions, customer journey maps, and related
analyses are all supported.
Assess conformance not just graphically
through overlays, but also through data analysis and gap analysis.
for process model augmentation that is intelligent while using additional data
from recorded logs and events to enhance or extend existing or a priori process
Support for data preparation and purification, as well as
Real-time dashboards with support for continuously
monitored key performance indicators (KPIs) that offer decision support.
Connections to continually
monitored and adapted KPIs in dashboards for specific roles in the company in
real-time or near-real-time.
Capabilities for advanced
analysis that make use of contextual data such as predictive analysis,
prescriptive analysis, scenario testing, and simulation are all examples of
Extends process mining capabilities across processes with
extensive analytic and decision management features, as well as APIs for
developing process mining apps.
Able to create applications, such as financial auditing
solutions, for businesses and partners of process mining suppliers.
Using low-level event data in UI (User Interface) logs to
derive meaningful information. Based on keystrokes, mouse clicks, and data
entries, these UI logs explain the single steps within a task performed by a
user — for example, when using a workstation.
Capabilities range from basic updates to scripts that
support task execution.
Process Mining is not a BI Tool
They have a common interest, yes. Both help business managers make better, more informed, evidence-based decisions. Here is where they differ from each other
BI can tell you something went wrong, and Process Mining can tell you why it went wrong.
Process Mining has an advantage over BI in terms of analysis depth. Both technologies work with KPIs and data at different levels, but Process Mining unveils and visualizes what BI monitors and reports. Process mining outperforms BI in terms of independence from the expert interpretation and ability to comprehend unstructured data, in addition to addressing the elusive question, "why?"
BI requires expert interpretation and assumes processes are known.
Business Intelligence is concerned with and limited by an assumption that processes are known and transpire as intended. BI is good at reporting and monitoring KPIs, but its weakness is in the assumption that all is going to plan.
Process mining, on the other hand, deals with the realities of defective processes, unanticipated causation, and a slew of other issues that might arise at any moment in any pross. Process Mining makes no assumptions about the underlying process's integrity or objectives, and it moves to report into root cause analysis. Process Mining excels at disclosing the genuine 'as is' process, from defective processes that behave in ways that creators are unaware of to fully rouge process stages that remain hidden from user view.
The right use case for the right tool
BI, on the other hand, has a place in BPM. KPI reporting and data monitoring can be turned into a competitive advantage using BI technologies. Marketers utilize business intelligence to track website traffic in real time, which helps them estimate ROI and accomplish optimization goals. Sales teams employ business intelligence to close deals and discover customers with higher conversion potential who, as a result, demand special attention.
Process mining offers a dynamic and living vision of data and processes intrinsically. BI is static and passive, mostly analytical.
The process mining- must adapt to a movement temporal evolution of the processes' functioning in a company that is always moving (workflow evolution), and it must allow interaction with the user who will detect, identify, communicate, and simulate to act and optimize all of this in real time.
The process mining must demonstrate this; it is no more a question of organizing dashboards as if or like that with the sole purpose of analyzing and interpreting, but of providing the user with the ability to test, pilot, scenario, and simulate changes to quantify the instant consequences.
The process mining will be based more and more on the same fundamentals of the gaming universe, offering users the experience of being an active player in operational and collective decision-making to act, act quickly and act collectively!