Using Process Mining Technology to Deliver Successful Digital Transformation Programmes

Today, the digital footprint of business processes has never been larger. The breadcrumb trail of clicks, updates, messages and interactions, flow through an organisation’s systems to support front and back office operations. This digital footprint need not merely be the interaction of employees with the systems, but increasingly we see the application of ‘digital workers’ through Robotic Process Automation (RPA) and the addition of low code automation and integration (PAAS) technology also contributing. As a result, the complexity of processes, especially amongst larger organisations, compounds the risk of digital transformation initiatives; initiatives which the ongoing COVID-19 situation seems to have accelerated the need for. Thus, with the impetus on many organisations to do so, process mining technology can help us better understand and visualise current process execution, automation, workarounds, process interdependencies and much more. This lends itself to helping organisations embark more successfully thereafter on a digital transformation involving business critical systems.

Digital Transformation Due Diligence

Software has brought digital standardisation to many processes and, in conjunction, many companies developed global process templates to streamline and standardise ways of working on new software. At the time of initial implementation, ‘as-designed’ reflected ‘as-executed’ as the gap between requirements gathering and software implementation was smaller. Yet over time processes usually change to meet the needs of new externalities. We get a divergence of as-executed away from the original process templates, often created through the support of external consulting firms. Now faced with a digital transformation project, years or perhaps over a decade in some cases, after the original software was implemented; how can we accurately understand our ways-of-working today to better prepare for a transformation to new or improved processes?  how can we quantifiably understand the level of change management that will be needed?

Historically this exercise has been qualitatively completed with external support. These take the form of lengthy and costly whiteboarding and interviews, with many emotive and unconscious biases affecting the output. Process mining technology can shorten these exercises by visualising actual ‘as-executed’ processes based on the process’s digital footprints. Eschewing the biases of interviews and modelling based methods, extracting data directly from underlying applications instead, the technology quickly highlights variations in process, root causes and impacts of executed activities across large datasets. Owing to the extensive enterprise software use over the last decade, data coverage is generally very high, even from legacy systems such as older ERP systems from Oracle, Microsoft and SAP. This generates a much more quantitative starting point to digital transformation. It allows individuals to discuss process execution in a more constructive and evidence-based manner.  Crucially also, it visualises how data is being used through a process thanks to the relational data models inside the process mining technology.

Process mapping, sketching and whiteboarding through interviews skews towards ‘as-designed’ process and does not reveal the true picture of process execution. Photo Credit: Unsplash

As a capability that is relatively nascent when compared to other software technology such as ERP software, there have been plenty of digital transformation programmes executed without the use of the technology. However there have been several high-profile failures especially concerning business critical systems. It is certainly the case that using process mining technology, an organisation embarking on a digital transformation programme can reduce the external cost of lengthy interviews and start instead with a clear data-driven insight of their processes. This creates a far stronger platform with which to embark upon a digital transformation than has previously been the case.

Process Mining as a Catalyst for Process Improvement Culture

Some changes to enterprise software architecture have greater risk and change to an organisation than others. For instance, implementing a new HCM or ERP technology is often colloquially referred to a ‘brain’ or ‘heart transplant’. Conversely the implementation of a targeted point solution, such as sourcing and procurement tool or sales commission management software does not carry the same level of business continuity risk. Yet in both cases, for an organisation’s employees, these new tools bring about a requirement to change ways of working and adapt to new processes. Equally the blind application of software is not a successful method to resolve underlying process issues in an organisation.

Process mining insights can help an organisation into transformative frame of mind by acting on inefficiencies discovered in the processes or to reduce the amount of process variations. Ultimately this serves two clear benefits; root causes of inefficiency are acted upon, delivering working capital, income statement and efficiency benefits. Secondly the organisation is better prepared for change, having delivered ‘quick wins’ and being in a more streamlined state for change. This increased agility and a more informed enterprise is one of the key advantages of process mining capability; quantifiably understanding the contribution of process activities to improvement or degradation in KPI performance.

Much to Gain, Little to Lose

Process mining technology represents a lower risk entry option compared with immediately starting a sourcing process to upgrade or migrate legacy software. As we have explored in this article, the results not only better prepare an organisation for digital transformation but also result in the improved sweating of existing software assets and delivering financial improvement to the income and cashflow statements. Especially in the current delicate economic environment, the risk vs. reward profile of applying process mining technology ahead of more fundamental software changes is skewed exceedingly in favour of the player than that of the house. This case is underlined by the remarkable number of companies and recognisable brands now adopting this technology.

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