In this article of the series, we delve into gathering extensive process intelligence. Process Mining is used for optimizing the finance function, and perhaps more importantly, for enabling the finance function to strengthen its performance management and advising role to a business.
Looking beyond Lean Six Sigma towards objective and efficient process improvement
To identify process improvement opportunities more easily and objectively, it is essential to obtain extensive insights into process execution and performance. As the finance function typically has access to most, if not all, of the incoming and outgoing information streams, it has the opportunity to provide insights on the operational performance of the organization. As a trusted business partner, we would argue that it is Finance’s duty to do so. Digitalization has led to vast amounts of data being generated by various systems throughout the organization. This data offers a gold mine from which an organization can derive valuable insights on its processes: how are the processes executed, what variances are there and which bottlenecks arise?
Modern technologies related to process mining have emerged over the past few years, offering the ability to gather and translate raw process data from various source systems and to bring them together. This enables a comprehensive overview of systems and processes, providing deep and detailed data-driven process insights, right down to the level of task execution. It is therefore possible, with relatively little effort, to derive valuable insights based on the vast amount of available data, while previously, such an analysis would have required substantial work and discussion, often at a very high cost.
Target setting is at present typically subjective and not data-driven
Currently, in most organizations target setting, in a regular budget cycle or more specifically as part of a cost reduction initiative, is often a political process requiring lengthy negotiations between leadership and management rather than a data-driven consideration of facts that informs and supports decision-making. It consumes a lot of time, effort and attention within the entire organization. To counteract these time limitations, data analyses are condensed and high-level. Furthermore, financially focused KPIs are selected instead of operational, non-financial KPIs, while the latter usually offer better insights for steering the value drivers of the financial results. This strongly limits the opportunity to really achieve a culture of continuous improvement: the connection between financial performance and operational activities becomes too indirect for teams to adequately appreciate how their actions can really influence the financial outcomes. Value driver trees can help in bridging this gap, but they require an objective quantification in order to provide a meaningful, transparent and accepted application.
For this, a more data-driven approach is needed. Process mining can objectively determine the value drivers that form the basis of the value tree in an automated budgeting and forecasting approach. The process thus becomes data-driven rather than relying on manual input that is based on expert opinions. Once the automated budget and forecasts have been calculated, a further socialization can take place to embrace the aforementioned expert opinion, support acceptance in the business and allow for manual overrides where appropriate.
Process mining can dig deep into the organizational potential and support decision-making
Real-time insights into organizational value drivers can also accelerate an organization’s ability to adapt to external developments and market challenges, helping it to sustain its competitive advantage and value creation process. Analysis of the processes can be run in the background and custom-made dashboards, linking financial and non-financial performance, can provide timely insights into the relevant cross-sections of the organization’s performance through multiple structured systems. These insights can support decision-making at a strategic and tactical level, for example regarding cost-saving potential, productivity improvements, time-to-market acceleration, and working capital optimization.
Another important application of process mining is in internal benchmarking, which can be executed with a greater level of detail and confidence than any external benchmark can provide. The variance analysis can provide valuable input for performance dialogues between leadership and management, and a conformance analysis can compare the real state of process execution against the designed or desired state, which makes it easier to spot and resolve differences and nonconformity.
Finally, internal and external auditors often use process mining for obtaining extensive functional insights into the usage of IT systems and movements of information through the organization.
Process mining can be effectively rolled out within the organization, but outsourcing is also a viable option
To start with Process Mining, a relatively small scale roll-out of a tool can already yield some valuable results. However, organizations soon realize that a multidisciplinary application provides better insights and extend the license to include more users and data availability.
Also bear in mind that successful deployment of process mining requires translating findings into insights, and these insights into value-adding performance improvements. To uncover the true business value of process mining, six key enablers are critical:
A top-down approach is required, based upon clear hypotheses. Strategic goals should be identified to pinpoint where improvements are needed.
There needs to be genuine enthusiasm for learning and adapting to the new way of thinking and working. Strong senior sponsorship is required here. Although this method has existed for over 30 years, the emergence of data and IT solutions now allows for a fresh perspective on the methodology.
It is essential to bring together the relevant staff with data and process knowledge to facilitate analysis with business process owners.
The availability of critical data from IT systems, or through other sources such as RPA (Robotic Process Automation) bots, is a key factor in gauging success.
An enduring culture of continuous improvement is a precondition for getting the true benefits from process mining. Capitalize on the insights by testing ideas for improvement in daily practice or by spearheading innovation projects. This requires an effective change management approach which is mindful of the cultural components that are needed to make it a success.
Clear role definitions and responsibilities need to be defined. Some organizations benefit form having a separate team which is dedicated to process mining. Moreover, the potential for process improvement is often better recognized when an external lens is applied. That is why outsourcing of process mining to third parties is becoming increasingly popular.
