Start and Scale Intelligent Process Automation with Process Mining
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Fast track Process Discovery

Accelerate process discovery using traceability and transparency.

 

 

Improve visibility into your processes to help you identify the best opportunities for improving your automation, predicting the impact of changes on your key performance factors and ultimately, scaling your business efforts. Unlike traditional process discovery, automated, AI-enabled process discovery helps you identify your processes as they truly are, not as they appear to be, efficiently and error-free using evidence and data.
Quickly and accurately identify your processes and accelerate the time to impact operations with automated process discovery powered by the Apromore process mining platform.

 

Gain data to improve decision making and impact business performance 


Disruption has widened the disparity between businesses and what they believed their operation processes to be. Understanding the differences between assumed and actual 
business processes and being able to spot opportunities for improvement will separate top-performing businesses from competitors as the pace of change continues to accelerate.  

To better understand business processes and the potential impacts of change, it is essential that accurate business process models are created, and process architectures are analyzed. But with shifting employee bases, skills shortages and increasing urgency to repair and rebound, organizations are under extreme pressure to quickly demonstrate progress.  

Traditional process discovery methods no longer meet organizational demands for business process mapping and modeling. Business processes have become too complex and unwieldy, and the urgency to make decisions means businesses cannot wait months to gain an accurate model, during which time the model may be obsolete.  

 

 

 

 

 

 

 

 

Accelerate process discovery and reduce risk, time to action 


Business process modeling
 can only start once there is enough information about existing processes to build an accurate process map. Traditional methods of process discovery have historically involved interview and workshop-based sessions, delivered by an analyst with a business process questionnaire template. Getting the right people together in one place is difficult, but even more of a problem is the complexity of today’s business processes. Traditional interviews can be flawed by:  

  • Fragmented process knowledge: Different tasks are completed by different people. 
  • Case level thinking: Individuals describe specific instances (variations) instead of the larger process. 
  • Lack of business process modeling expertise: Domain experts can miss articulating or asking key pieces of information needed for accurate modeling. 

Alternatively, evidence-based discovery using automated process discovery and process mining speeds the data collection phase of process discovery from months to days and provides an objective, more complete representation of the business process, as well as removes biases in collection methods. Using a systems-neutral approach allows analysts to extend investigation across enterprise systems and construct end-to-end business process models, capturing all variations- a necessity in gaining an accurate perspective.  

These models can be highly detailed and make it difficult to understand critical business processes and leave analysts feeling like they are searching for a needle in a haystack.  

 

 

Identify critical business processes faster


Process mining 
takes event logs from information systems and turns them into process models 

Most systems record timestamped events that correspond to work and may include messages and documents received or other actions a user takes. They can show who performed a task, how long the task took, the cost, or other industry-specific data such as a loan amount, patient health record information or the status of an application. These logs can be extracted from the database of an enterprise system. Simple event logs can be captured in a CSV (Comma Separated Values) file and more complex logs are extracted in eXtensible Event Stream (XES) formats.  

Apromore provides a no-code interface allowing business analysts to define and schedule the automated execution of custom ETL (Extract Transform Load) pipelines using a point & click approach, reducing the burden on technical resources, and enabling analysts to implement ongoing business process monitoring.  

Because event logs can be extraordinarily complex, Apromore is built on some of the most advanced process mining algorithms ever made, yet can be quickly learned, helping analysts and business decision-makers to gain insights with an average of ten hours of training. 

 

 

 

 

 

process mining integration

 

 

 

 

 

 

 

Automatically create effective business process maps 


Convert process maps to BPM (Business Process Management) models in one click, gaining consistency with quality aspects and assurance activities. Apromore’s built-in process modeling tools come with a predefined list of modeling guidelines that can be automatically checked against a model and allow the possibility of custom guidelines.
 

With Apromore, you can easily change the level of detail in the graphs to meet your analysis needs, and review process performance, bottlenecks, and conformance: 

  • Abstract details to gain a big picture view of a large event log 
  • Filter details to dive down and explore a subset of activity in detail 

 

 

Book your free consultation today to learn more about benefiting from exposing your processes as they really are not as they appear to be.  

Book now

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