By industry

Process Mining

Process mining analyzes business processes, providing insights for efficiency and optimization.

What is Process Mining?

Process mining is a cutting-edge analytical discipline that utilizes data from event logs to dissect business processes and gain a thorough understanding of their operational flow. It’s a tool that sits at the intersection of data science and process management, scrutinizing event logs to discover, monitor, and enhance real-world processes. A concrete example of its application is within supply chain management, where process mining can analyze the life cycle of a product from manufacturing to delivery, uncovering bottlenecks, identifying process deviations, and providing visibility into the overall functioning of the supply chain.

What are the benefits of Process Mining?

Process mining offers significant benefits, revolutionizing the way businesses understand and optimize their operations.

What is RPA?

Intelligent Process Automation (IPA) is an advanced form of technology that orchestrates the creation, deployment, and management of smart bots designed to mimic human activities within digital interfaces. These bots can astutely perform tasks such as extracting customer information from a database and using it to generate invoices. They are capable of interpreting on-screen data, executing accurate keystrokes, seamlessly navigating through diverse systems, and extracting relevant data. An added layer of sophistication allows these bots to learn from previous tasks, adapt to changes in process, and even handle unstructured data, proving their robustness in handling a vast array of complex digital tasks.

What are the benefits of RPA?

Robotic Process Automation (RPA) presents a revolutionary approach to streamlining business operations, offering significant advantages ranging from enhanced efficiency to improved accuracy.

Process Mining Process Examples

Compliance

Monitors processes to ensure adherence to regulatory standards.

Transparency

Provides clear visibility into actual processes, promoting transparency.

Risk Management

Helps in early detection of process deviations, managing operational risks.

Where can Process Mining be used?

Process mining is making waves across multiple industries due to its potential for transforming operational efficiency. In property management, it is used to track and optimize the lifecycle of rental or lease processes, enabling a more streamlined service. In tax administration, process mining aids in the comprehensive analysis of tax filing and auditing processes, helping to identify bottlenecks and ensure regulatory compliance. The hospitality sector uses it to enhance customer experience by optimizing processes like reservations, check-ins, and housekeeping. It’s also prevalent in industries like healthcare for patient journey mapping, manufacturing for production process optimization, and logistics for improving supply chain management.

Check out in depth what Automation can deliver for Banks in these cases:

Risk and compliance assessments.

These essential components of banking and financial operations, aiming to ensure that banks operate within legal and regulatory requirements and manage various forms of risks.

Yet another
case

These essential components of banking and financial operations, aiming to ensure that banks operate within legal and regulatory requirements and manage various forms of risks.

Yet another
case

These essential components of banking and financial operations, aiming to ensure that banks operate within legal and regulatory requirements and manage various forms of risks.

Yet another
case

These essential components of banking and financial operations, aiming to ensure that banks operate within legal and regulatory requirements and manage various forms of risks.

Yet another
case

These essential components of banking and financial operations, aiming to ensure that banks operate within legal and regulatory requirements and manage various forms of risks.

Yet another
case

These essential components of banking and financial operations, aiming to ensure that banks operate within legal and regulatory requirements and manage various forms of risks.

Yet another
case

These essential components of banking and financial operations, aiming to ensure that banks operate within legal and regulatory requirements and manage various forms of risks.

Yet another
case

These essential components of banking and financial operations, aiming to ensure that banks operate within legal and regulatory requirements and manage various forms of risks.

Yet another
case

These essential components of banking and financial operations, aiming to ensure that banks operate within legal and regulatory requirements and manage various forms of risks.

Yet another
case

These essential components of banking and financial operations, aiming to ensure that banks operate within legal and regulatory requirements and manage various forms of risks.

Yet another
case

These essential components of banking and financial operations, aiming to ensure that banks operate within legal and regulatory requirements and manage various forms of risks.

Yet another
case

These essential components of banking and financial operations, aiming to ensure that banks operate within legal and regulatory requirements and manage various forms of risks.

Yet another
case

These essential components of banking and financial operations, aiming to ensure that banks operate within legal and regulatory requirements and manage various forms of risks.

How does AI make RPA better?

Robotic Process Automation (RPA) greatly benefits from advancements in Artificial Intelligence (AI). While RPA is excellent at following rules-based processes, AI provides the capability for RPA bots to learn, adapt, and make decisions, enhancing their functionality. AI-powered cognitive capabilities like Natural Language Processing (NLP), Machine Learning (ML), and Computer Vision enable bots to understand and respond to text or voice commands, learn from historical data, and recognize images, respectively. For instance, in customer service, AI-powered RPA can analyze customer sentiments in real-time, allowing bots to handle customer complaints and queries more effectively, delivering personalized responses and improving overall customer experience.