Improving processes for digital transformation with automated process mining

According to a 2021 CIO report, 77.3% of CIO’s placed digital transformation as their top priority. However, with the immediate need that the pandemic placed on businesses to offer remote working and more online services and products, this should come as no surprise.  Instead, it has simply brought the agenda for digital transformation forward.

Whilst the implementation of digital technologies can also help accelerate progress towards enterprise goals such as financial returns, workforce diversity, and environmental targets by 22% (Deloitte, 2020), it is understandable that organisations are already on or ready to embark on this initiative.

To start these programs is no mean feat, especially considering the cost of delivering such a transformation and the potential cost if they fail.

If we consider the statistic provided by PTC, 40% of executives reported that the top benefit of digital transformation was operational efficiency, but knowing which areas to start with can be difficult.

A long-standing technique to improve operations is to first start by conducting interviews/workshops and mapping processes as they are now and then how you want them to be. Whilst process mapping is tried and tested, this takes time and is open to errors. Have all the necessary individuals been interviewed? Was a key sub-process accidentally overlooked? Before investing heavily in technologies such as AI, RPA and IoT to support these processes, first consider if and how you can select the right processes to transform your business.

While it is stated that 89% of heads of IT increasingly need to rely on advisors to navigate new technologies, processes, and methodologies (CIO, 2020), automated process mining can help address a significant piece of the puzzle.

Process mining tools, such as ProcessAnalyzer from QPR Software, draws data directly from an organisation’s information systems, which is then used to visualise and analyse the process flows that actually take place. This helps organisations to quickly and effectively identify any compliance violations, bottlenecks, and process automation opportunities.

The next step once you have identified what processes are ripe for improvement, is to determine whether a simple fix is available, such as training key staff or tuning schedules and whether there is a technology suitable to transform it. To support this, QPR ProcessAnalyzer also provides unique predictive process analytics and the ability to ‘act’ and trigger email, automation and RPA solutions to avoid potential future problems and embed the planned transformation.

Organisations such as Piraeus Bank have significantly improved their processes and ultimately their customer service by utilising automated process mining. In fact, Piraeus Bank cut its loan application process from an average of 35 minutes to 5 minutes by fixing its process automation problems.