Organizations are facing many challenges and constraints on a daily basis when trying to define and monitor their business processes:
- Processes have to be visualized to have a better understanding of the business
- There is no effective continuous improvement without knowledge of the processes and how they are actually executed in real life
- When we optimize processes, do we rely on facts or instincts?
- What kind of practices does the organization have for process monitoring and measurement in a systematic way?
- Is it possible to visualize, monitor and measure the actual, real life process?
- Are you able to analyze and benchmark the real life process performance by e.g. product line or geographic area?
- The approach of continuous process improvement is usually executed in process development projects that are traditionally organized according to the following model:
This traditional approach allows organizations to evaluate and review/check processes:
- Perform processes simulation based on data estimations and empirical data;
- Plan the process assessment based on how processes are "designed" in drawing tools or in manuals.
Nevertheless, this approach requires an organization’s employees to spend a lot of time performing review/check activities and process simulation.
However, a few months ago, I "discovered" a new approach that, according to my understanding and experience in this area, could enhance the practice of continuous improvement substantially.
Automated Business Process Discovery (ABPD), a practice related to the process mining concept, is based on a set of techniques that allow any Process Department to automatically build a graphical representation of business processes and its major deviations within an organization. These techniques make use of the information in business process systems, in particular data, logs, events, etc.
When analyzing data and the "way" data flows in the information systems, it will be possible in a more objective and assertive way to know, analyze and optimize an organization's business process.
Thus, we can say that, based on the analysis of data residing in information systems, you can:
Understand your processes:
- Know the reality of the implemented process;
- Identify gaps in the business process rules in order to identify possible scenarios that are not being considered;
Analyze and measure process performance
- Assess the durations for all evaluation, approval and decision phases;
- Assess the decision lead times for each level of approval;
- Identify other unexpected bottlenecks in a process.
Without a doubt, with this approach, there will be a better understanding of the process and its real performance which is based on data residing in systems. This understanding allows more assertive actions to be taken to optimize the activities and rules associated with the process.
Automatic Process Mapping should be considered as a complementary approach to traditional analysis and process optimization, enabling you to create a business process model very quickly, effectively and at a lower cost than is traditionally required.
Following this approach, organizations don’t have to spend so much time in meetings to discover the implicit and/or hidden processes in computerized/automated solutions.
So, now that you have read about this new approach… do you still think that it is not important to use the existing data in your systems to improve your processes?