How process mining accelerates S/4HANA migration
Migration projects are always a moment of truth. This is because they expose the weak points of process landscapes that have developed over years and thus increase the complexity when switching to new systems. Process mining helps to identify gaps in efficiency and potential risks in existing business processes before they become noticeable in the migration process. This means that companies benefit in two ways: on the one hand, the elimination of process weaknesses identified in this way offers enormous potential for savings. On the other hand, the effort required for migration is reduced by implementing process optimisation in advance.
Whether it's the replacement of a central management service, the transition of a software monolith into more flexible services or the relocation of applications to the cloud - the complexity of existing systems and evolved process landscapes along with their individual adjustments, manual workarounds and non-documented changes, is always one of the greatest challenges when it comes to migration projects. This stems from the fact that unidentified deviations from the standard process delay migration projects, increase costs due to complex adjustments or adversely affect the quality of the business processes in the target system.
In a nutshell: if you migrate bad processes to a new system, the weak points remain in the new system. Or, as the former CEO of Telefonica Deutschland, Thorsten Dirks, once put it: "If you digitalise a shitty process, then you have a shitty digital process".
Operation at the heart of the main business processes
One of the largest migration projects currently facing many organisations is the migration to SAP S/4HANA. For hardly any other initiative has such a significant impact on almost all aspects of a company as the migration of the ERP (Enterprise Resource Planning) system to a new solution. After all, the ERP system forms the backbone for a multitude of process flows and any breakdown during the transition could have catastrophic consequences.
According to the manufacturer, companies have until December 2027 to perform this task. At that point, S/4HANA is meant to replace the predecessor Business Suite and its core application, SAP ERP Central Component (ECC). According to the 2030 plan, ECC support will be discontinued.
Identifying the right migration strategy
Whereas in the brownfield approach the existing business processes are largely transferred straight into the new system landscape, the green or bluefield approach relies on completely redesigning some of the processes or only taking selected data with them. The latter have the benefit that the ballast of the evolved legacy systems will not be dragged into the new system and have a negative impact on future performance.
A prerequisite for this, however, is that companies receive complete transparency in the planning phase as to how well their existing processes are working. This involves questions such as: to what extent are departments currently using the system? How much do current processes deviate from target processes? Where are the greatest process inefficiencies? Are the causes of these inefficiencies known?
Although in the past this information had to be collected and documented individually, these days digital tools facilitate the evaluation of these processes on the basis of existing data. This is where process mining comes in.
Process Mining – An X-ray look behind business processes
Process mining software captures event data from a wide variety of IT systems along defined business processes such as order-to-cash or procure-to-pay. By merging and evaluating these "digital tracks", end-to-end process visualisations, including deviations from the standard SAP path, can be generated. Digital tracks not only provide information on the type of process deviation across markets and business units, but also offer a precise breakdown of each occurrence in the period in question, and how long their effects lasted.
The resulting losses in efficiency or potential savings can thus be precisely calculated on a daily basis and thus provide the necessary transparency for generating awareness for process improvements at the decision-making level. This doesn't always just concern the classic gains in efficiency in terms of cost savings, but also the scalability of one's own business during periods when skilled labour is limited, or a strengthening of supply chain resilience.
Deep dive for in-depth problem analysis
Process mining serves as a pre-analysis. In the next step, a further problem analysis is conducted where abnormalities in the process emerge. With the help of interviews with the employees involved in the process, the real causes of the problems are identified and possible countermeasures developed.
Depending on the causes of process deviations, these issues can then be resolved, ideally by using appropriate apps within the new SAP S/4HANA target system. In other cases, providers of process mining software, such as Celonis, offer their own options for creating simple automated workflows based on business rules and logic that trigger automated events based on current data from the same system.
Conclusion: accompany SAP S/4HANA implementation over the entire lifecycle
Process mining provides very quick and intuitive insight into the existing process landscape. The insights from process mining can thus be applied, not only in the run-up to a migration project, but also throughout the entire lifecycle of the SAP S/4HANA implementation, ranging from planning and conception right through to implementation and operational monitoring.
In this way, on the basis of objective data, target functions and other requirements for the new implementation can be prioritised meaningfully during the planning phase and stakeholder acceptance can be reinforced. The new insights from process mining also provide important information in the conceptual phase, for example for the design of new templates in order to avoid undesired process deviations. During rollout, process mining can in turn serve to identify typical user bottlenecks and adapt user training accordingly. Lastly, process mining can also be used for continuous monitoring of key business processes in the post-rollout phase to reliably inform organisations of their performance against the target plan, as well as to enable rapid adaptation to changing market conditions.