Improving process efficiency is an essential part of digital transformation. Process automation is the crucial last part of this transformation. To reap the benefits of that, you must have insight into the process, be able to analyze the data and make objective decisions. Process Mining can help with this.
Particularly, financial departments can profit a lot from automation and robotization because there are typically processes and workflows in those departments that can be standardized. Before implementing automation, you must clearly understand the processes and workflows involved. And there lies the challenge. By interviewing employees to get a picture of those workflows, you do not always get a view of the ‘real’ process’; you often end up with a ‘perceived’ workflow. Mostly, this happens because an employee cannot oversee the entire process but rather just a part of that. You get an interpretation of the workflow instead of the raw data that maps the actual workflow.
Not so lean as you would like
For instance, the ideal workflow for the Purchase-to-Pay or Order-to-Cash processes should be straight and lean: An order is placed, the order is delivered, an invoice is sent to the customer (or received from the supplier), the payment is processed, and the case file will be archived. However, in reality, this is not the case; the workflow is complicated, circular, and can contain a lot of deviations. The issue is that what employees perceive as the actual workflow is often much more complex if you look at the data. If you analyze only the perceived process, you can end up with automation or robotization suggestions based on subjective data. That can make automation less beneficial.
Mapping the real process
Analyzing the raw data is a way to get insight into the actual process. Since a lot of data is present, even in the leanest form of the Purchase-to-Pay or Order-to-Cash process, we think automating the workflow can make a difference. We call it Process Mining. Using specialized software such as Minit, we can map every mutation during the process. This happens because Minit acquires all the data from the ‘event logs,’ data that is being entered or altered whenever there is a mutation in the status of a casefile: delivery confirmation, rejected payment approval, and so on. It also processes the time and data it takes for each action, including times between mutations. The software uses all the data generated by existing systems, like ERP systems. Still, it can also record new data on its own when no data is available through ‘keylogging’ users’ input. With the ‘Plug and Process’ principle of Minit, it is easy to implement it with existing systems, such as the ReadSoft Process Director.
Accessible data, thorough analysis
The data is displayed in a user-friendly, giving users an insight into the actual (natural) process. It lays connections between the different steps in the process, where there are improvement points and opportunities for automation and robotization. You can make more objective decisions because it uses data rather than subjective interpretations. It is also a more efficient way to gather the information needed, rather than taking precious time away from employees by conducting interviews and workshops.
To benefit the most from automation and robotization, you need complete insight into the processes you consider automating. Process Mining will enable it to fully map a method based on real-time data and give you an objective representation of workflows, improvement points, and automation opportunities. If you would like to know more about Process Mining and how it can help you understand your processes and workflows, allowing you to reap all the benefits of automating them, please do not hesitate to contact us.
Process Mining will enable you to fully map a process based on real-time data and give you an objective representation of workflows, points for improvement, and automation opportunities.
