How to optimize processes by conjugating RPA & Process mining

How to optimize processes by conjugating RPA & Process mining

According to Gartner cabinet, 40% of large companies will adopt a RPA software by the end of 2020 year in order to automize manual tasks, compared to 10% which have already adopted it. This programmed expansion of processes robotization answers mostly to the needs of reduction of costs, decrease of errors and increase of collaborator’s satisfaction.

Other benefit, collaborators, cleared of repetitive tasks, could be affected to more added value contributions.

However, beware: benefit from RPA will be even bigger than upstream preventions of its deployment would have been big: robots follow rules and apply scripts without intelligence. By applicating those scripts, RPA can extrapolate processes’ variations that have been implemented. In other words, the automation of a dysfunctional process could result in as damaging as unexpected effects. In contrast, application of RPA on activities that are focused on an eligible and mature process (meaning in a stable sense) will maximize gains promised by RPA.

RPA : to robotize only what has to be

Hence the interest of realizing upstream a fine analysis of the eligibility of processes implemented into the organization in order to maximize chances of deployment in a large scale. This analysis is the first step for validating the RPA’s lever’s relevance for optimizing targeted process, and this by having beforehand made sure of dismiss other possibilities of substantive evolutions : organizational, information system’s evolution, process’ simplification (by deteing low added value tasks for example), formation of collaborators (to the optimal use of existing IS available functionalities).

Thus, this step will guarantee to not use RPA improperly, often with the hope of quickly and with less costs for yawning flaws in the organization and execution of process.

Process mining : to know the reality of professions process

Process mining, at the crossroad between BPM and data mining, permits to complete the theoretical and subjective vision of implemented processes in order to bring transparence in their progress. And this on the strength of data and path took by these last inside the information system.

Very often, theoretical and static vision of a process will be beaten in breach by its dynamic execution made daily by professions. For example, the execution of a buying flow is relatively normalized, but beside different practices executed by countries, it is not rare to note important gaps between theoretical schema and the effective progress. It is often necessary to check on the human’s factor in order to identify roots that are issuing variations.

By connecting process mining to information system, the analysis of data and execution steps will permit to give a snapshot on the real progress of the process into the company and to identify crossing ways.

Process Mining and RPA : a permanent and measured improvement

If the analysis of processes is essential before the deployment of any automation, the coupling between process mining and RPA opens the track to a continuous improvement. Concretely, once the diagnosis realized, it becomes possible to analyze process and some actions linked for example to invoicing : delays, orders validations, estimates process etc. At that point, it is important to ask ourselves : why such a path is not optimized ? Answers could be various. It could be the capacity of processing volume of invoices, of bringing together purchase order and invoices etc. Here, RPA can assist for the execution of some actions. By coupling process mining and RPA, the organization will be capable of measure contributions of automation and to target in function of process mining’s returns activities that have to be robotized inside a process. On the strength of fine measures with the help from relevant KPIs, it will thus be possible to reduce the gap between the real procedure and and nominal path. Benefits from the automation will be even bigger than to-be-processed volumes will be important.

A data-driven transformation lever of process

The couple made by RPA and process mining brings an immediate benefit, but provided that on the one hand processes have to be well thought, and on the other hand all eligibility criteria have to be applicated with a factual measure of results. This monitoring of metrics is even more important than processes are not fixed in an ideal, but have to be adapted in function of endogen or exogen criteria for example linked to the evolution of regulatory, normative or legal risks.

In the end, RPA and process mining combination offers a real lever of optimization of processes and opens the way to a new era of operational excellence based on data-driven transformation of professions process.

Sébastien Duprez (Process Mining Director)
& Yanis Khobzi (Finance Practice Director, Axys Consultants)