Business processes often involve multiple stakeholders performing different parts of the process and relying on multiple applications and siloed information systems to run them. This fragmentation of people and information systems involved translates into a lack of visibility on the end-to-end process, which ultimately makes it difficult to understand how processes actually run and to check whether they are in compliance with their expected behavior.
Traditional approaches to business process design and modelling rely on qualitative and subjective data – such as interviews and questionnaires – to map and analyze current state business processes and involve, often, expensive consulting services. Process audit common practices also rely on limited data – e.g. audit sampling – to assess process compliance. As a result, traditional approaches to process discovery and conformance checking are suboptimal and expensive.
Process mining provides a new bottom-up, transactional data-driven approach to business process discovery and conformance checking that overcomes the limits of the aforementioned traditional approaches. Mining the event logs data stored in the information systems used by the process’ stakeholders, process mining allows you to automatically generate a dynamic model of the As-Is process that is objective and comprehensive of all process variants. Not only the model has no observer’s bias, it also takes less time to be created and is less expensive.
The more advanced the process mining solution used, the more accurate the dynamic model of the process that can be achieved and the analysis that can be performed. myInvenio leads innovation in the field, being able to mine process decision rules – e.g. in an accounts payable process myInvenio can infer automatically that above a certain amount an invoice requires some approval activities – and being able to map processes with many to many relationships in a single comprehensive process. The latter capability, referred to as Multi-Level Process Mining, allows you to analyze complex processes such as Procure to Pay or Order to Cash while treating them as single end-to-end processes without having to deal with biased statistics, data divergence and convergence issues. Without Multi-Level Process Mining, P2P subprocesses – purchasing, ordering, invoicing, payment – would have to be analyzed independently, losing visibility on the end-to-end P2P process.
The As-Is process model discovered with mining enables you to analyze the process along different dimensions, which include control flow, time, costs, resources involved, and process instances. These analyses are a big support to process improvement initiatives, providing unprecedented fine grained visibility on the end-to-end process for its assessment.
A second important application of process mining is to monitor the conformance of the actual process against its reference model. An example is the model developed on BPM solutions such as iGrafx. This capability of automatically identifying deviations between how the process is supposed to work and how it actually works empowers business and regulatory compliance monitoring, especially when compliance monitoring is implemented in real time – with all the benefits that derive from spotting deviations as soon as they occur.
Given the aforementioned discovery and conformance checking capabilities that process mining brings to the table, it is easy to understand how process mining enables and accelerates an RPA strategy:
Facing increasing customers’ demand for tools to enable RPA strategy and to monitor process and RPA’s compliance, myInvenio and iGrafx are developing integration between their two solutions to seamlessly integrate mined data into iGrafx and augment iGrafx’ GRC capabilities. These capabilities are now available to the public as part of iGrafx’ RPA Accelerator offering, whose description can be found here.