By Walid Gomaa,
CEO Omnix International

Assembly line manufacturers, competing in the global marketplace, with millions of components to be fitted into a final product, understand the importance of conforming to a process. The closer the conformance to an ideal process, the better is profitability and return on investment.

This approach changes wildly inside an enterprise where millions of components are replaced by hundreds and thousands of human workers. umans are not machines and do not like to conform. They enjoy flexibility, innovativeness, and originality. This tends to affect how a workflow or usiness process progresses inside an enterprise

As regional enterprises adopt automation an important starting point for them is identifying which processes to automate. Processes that rerepetitive, that can be described precisely, that can be replaced easily by oftware robots are a good starting point.

But the key inhibitor usually is to identify those processes and complete the description of those processes accurately so that the starting point, ending point, and all the other intermediate points are identified. Team members nvolved in those processes will describe all the variations of the processes that they have been following and process improvement managers at this stage are usually stumped as to how to progress

This fundamental challenge has led to the emergence of process mining solutions that can help capture how business processes are being actually followed, rather than how they should be followed. This elps to quantify the time taken, resources involved, the exact path followed, and most importantly where deviations and bottlenecks occur.

According to Gartner, process mining is a technique designed to discover, monitor and improve real processes, by extracting readily available knowledge from the event logs of information systems.

A Forrester report indicates that 37% decision-makers report delays to their digital transformation initiatives due to misunderstood processes, and it is normal for people to approach the same task in different ways.

While in itself human ingenuity is not a negative for business fundamentals, over a period of time this leads to increasing variations and deviations to the process, which finally impact the quality or specifications of the final outcome.

Today’s ERP and CRM enterprise applications provide an audit trail of their transaction processes, and their log data is accessible. Processmining solutions extract this data from enterprise applications and recreate the process as it is followed inside the enterprise. This represents the most accurate picture of the process as-is.

Algorithms built into process mining can now reduce the time taken to analyze these data logs and identify the root cause of deviations from the ideal planned workflow path.

Once initiated inside an enterprise, there are three fundamental stages in process mining.

In this stage, data logs from enterprise applications are used to ecreate all the processes that exist in the enterprise. No other influence is used to rebuild these processes and it is assumed that no other processes exist other than those for which there are data logs.

At this stage, the description of the process being followed by team members is compared to the process that is being followed according to the data logs. From this comparison it is easy to identify the deviations that are happening in real-life with team members inside the enterprise.

In this stage, additional inputs are brought into the process to accelerate ecision making and remove bottlenecks and to take the final outcome of the process much closer to what is anticipated and desired. These additional nputs can help to optimize the process at various stages for team members, which may not have been happening previously.

Process mining benefits the enterprises in multiple ways:
• By identifying bottlenecks in the workflow, it helps to improve the quality of the final outcome.
• It can reduce the cost of time and people that are involved the bottlenecks.
• It can help to redefine outdated job roles and responsibilities thereby optimizing human resource costs.
• By uncovering better variations to the process, this actually boosts innovation.

To efficiently automate the enterprise, decision makers must have
complete and authentic visibility into their processes. Process mining is a necessary stage to reach this level of confidence. In other words, they must know where their processes are today, where they want their processes to be in the future, and the transition path from one stage to the other.

Once these conditions have been established inside the enterprise, implementing robotic process automation and hyper automation are the next levels of progression.