Process Intelligence: Entelgy lidera la transformación digital con Celonis en Lanbide
14 de April de 2025
Entelgy, como socio estratégico de Celonis, destacó en el Foro de Optimización celebrado el 27 de marzo en las oficinas
SOLUTION
Process Mining & Excellence
Controlled and automated processes
Process mining is a technology that discovers, optimizes and automates processes from data by obtaining the digital footprint that processes leave in different systems.
According to Forrester, 61% of decision makers will use process mining to simplify operations
Goals
Transparency in processes.
Identify automation potential.
Process monitoring.
Streamline processes.
Increased agility.
Benefits
Cost reduction.
Improved times.
Improving productivity.
Greater customer satisfaction.
Improving Working Capital.
Higher income.
Our COE
Our Center of Excellence (CoE) aims to centralize knowledge and best practices in the use of Celonis in order to provide the best experience and advice thefore maximize the value of each project.
Contact our expert
Jordi Llobet
HEAD OF DATA & PROCESS
Address:
Transversal 23 #97-73
Office 411. Bogotá
Phone
+57 3 173 656 708
E-mail
info.colombia@entelgy.com
Drones and the revolution in the agricultural sector help our clients grow
Success stories
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Process Mining Components
Process Mining includes different tools to analyze and improve your processes within the following four areas:
Discovery of the process
Digital footprint reading: Companies implement their business processes relying on a variety of systems, which makes full visibility of the process difficult.
All these systems leave a digital footprint that is the starting point of Process Mining.
Process conformity
Using calculation algorithms, Process Mining is able to depict the process flow as it is from the data obtained (data-driven) and compare it with the design defined by the organization.
This way we can detect errors, redundancies, bottlenecks…
Process performance
By obtaining real-time data we can measure process speed, errors, redundancies and bottlenecks by calculating specific KPIs.
We can measure the automation ratio, the % of late deliveries, the average duration of the process…
All these systems leave a digital footprint that is the starting point of Process Mining.
Process improvement
By having real-time data, we can automate action mechanisms using Artificial Intelligence and Machine Learning tools, in addition to harmonizing and redesigning the process to align it with the company’s objectives.
This way we can detect errors, redundancies, bottlenecks…
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