Successfully Driving Continuous Enterprise Transformation with Data-Driven Business Process Management

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CxO and senior management

Change in market and business conditions and environments is constant and requires organisations to (be able to) continuously evolve. This is where business process management comes into play to ensure alignment between strategy and operations under changing conditions. Yet, manual efforts required to monitor, analyse and re-design business processes on an ongoing basis have been a barrier to adoption in the past. Fortunately, the broad availability of digitised business data is changing the game. Vendors are pushing capabilities for data-driven business process management to assist organisations in understanding their business (the past), monitoring and managing ongoing executions (the present), and adjusting their ways of working (the future). Besides reducing manual efforts, data-driven business process management drives transparency, objectivity, resilience, continuity, and maturity. So, do not miss out and get started now to be prepared for what lies ahead.

Change – A Constant in Life

Change is, always has been, and will continue to be omnipresent and constant. Just in the last decade, climate change, the COVID-19 pandemic, geo-political conflicts, advancements in mobile and cloud computing, big data, and AI have significantly impacted private and corporate life. Organisations that want to persist and grow in such an environment must continuously adapt their strategy and transform their enterprise. In this context, business process management offers a means to ensure that people, technology, and data jointly deliver an organisation’s services and products, and ultimately realise its evolving strategy.

Business Process Management? We’ve done that before!

Undeniably, many organisations have adopted some form of business process management. Yet, they have primarily done so through one-off process improvement initiatives that redesign ways of working on rare occasions mostly from a system’s perspective, e.g., when rolling out a new ERP. However, the scope of business process management is much broader. It offers a rich set of methods and tools that helps organisations in continuously monitoring, analysing, and re-designing processes to incrementally improve the business – at system, operational, and organisational levels! While manual efforts required to adopt such a continuous approach to business process management have presented a barrier in the past, the broad availability of digitised business data is changing the game.

Data – The Enabler for Reshaping Your Transformation

Over the last decades, digitisation and digitalisation have been important levers for the improvement of business processes and performance. Instead of exchanging information over phone or on paper, internal and external communication is now backed by information systems, which can automate the coordination and execution of processes based on digitised data. A side effect of this development is that organisations establish archives of their business transactions and operations. Extracting digital process footprints from those archives allows organisations to comprehend how individual process instances were executed and to derive valuable business insights. As the data are constantly updated with every new transaction, organisations can utilise the data to establish ongoing transparency into their operations. Moreover, through data aggregation insights can be obtained at system, organisational, and operational levels. Both, ongoing transparency, and insights into different process levels, are key enablers for successful continuous improvement.

Making it Happen: Exploiting Data for Enterprise Transformation

As shown in the figure below, organisations can exploit their business data for business process management and enterprise transformation in all phases of the transformation lifecycle. That is, data do not only enable the discovery and analysis of the past, but they also provide a basis for forward-looking activities like process re-design and implementation as well as for activities focused on the now such as process execution and monitoring.

1. Process Mining

Process mining is a set of techniques for analysis of business data with the goal of understanding how processes are currently executed. To this end, process mining provides insights into (i) the actual way in which processes are performed, (ii) key performance characteristics, (iii) patterns that drive those performance characteristics, and (iv) changes in the organisational behaviour. While process mining is often viewed as a problem-centric activity focused on revealing and prioritising pain points, it is indeed solution-oriented and reveals opportunities for elimination, standardisation, optimisation, or automation of activities. Moreover, process mining does not need to be a one-time activity. Once a process mining tool is connected to an information system, digital process footprints can be extracted and utilised on an ongoing basis with minimal effort. This lays the foundation for repeating data-driven process analysis regularly and for embedding data into enterprise transformation efforts.

2. Process Simulation

In contrast to process mining, process simulation is a future-oriented activity. It supports the investigation of what-if scenarios during process design and implementation to test how different process designs would behave under varying conditions. To ensure that simulation results are reliable and reflect process behaviour under realistic circumstances, digital process footprints are used to inform the creation and validation of simulation models.

3. Real-time Monitoring

In addition, the footprints can also be used for real-time monitoring. At the process level, organisations can track the development of key performance indicators. This establishes transparency and accountability, allowing management to sustain and reinforce change. Moreover, the footprints can also be used to oversee how individual cases are handled. That is, the conformance of actions to internal and external rules, laws, contracts etc. can be pro-actively monitored and (manual or automated) actions for any unwanted deviations can be triggered before problems occur.

No more excuses! Get started now!

Over the last years, vendors have significantly invested in the development of tools that enable data-driven process management. As a result, there are many mature and advanced tools available in the market. Ignoring those capabilities and not adopting a data-driven approach to enterprise transformation does not only imply that you will not realise the benefits of data-driven business process management, as summarised in the figure below. It ultimately means that you accept the risk that you and your business will not be able to evolve with changing conditions and environments. So, do not miss out and get started now to be prepared for what lies ahead.



Manager – Enterprise Transformation | Corporate Experience

Dr. Christopher Klinkmueller

Christopher is a manager within the corporate experience team within Capgemini Invent. He is a business process management, process mining, and data science specialist with 10+ years experience. He has worked in collaborative environments with and for high-profile organizations and renowned research institutes, both nationally and internationally. He contributed to numerous engagements taking on various responsibilities including process analysis, process modelling, process mining and intelligence, process improvement and design, proof of concept delivery, and data management and analysis. He is a member of the international business process management and information systems research community, having published in and reviewed for the top-tier conferences and journals in the field.


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