process mining and process bionics


The Enterprise as an Organism: From Process Mining to Process Bionics

Evolution of the process towards holistic analysis and optimization

Is data really the raw material of the future? If so, then it is the last call for companies to collect this asset as well. Process Mining is a new, powerful tool for this "raw material utilization" and offers an innovative digital approach that combines data mining and process optimization. Supported by real data, it provides valuable, detailed insights into a company's decision-making processes and points out ways of improving them. But the ambition goes beyond the known: with the new Process Bionics concept, Deloitte is extending Process Mining to a holistic digital management approach. It aims for a dynamic, continuous application of the insights gained right across the company. This visionary model follows the paradigm of natural processes such as neural networking, AI, adaptation, and evolution. Companies can already benefit from this today. Process Mining allows you to really understand what is going on in your company. Realized by starting with the extensive digital data on actual events, decisions and process paths in the business. Concrete approaches can be derived from analysis, e.g. recommendations for action that save costs: a precisely defined return on investment that can be implemented in real time.

Deloitte supports companies in implementing this technology – and expanding it to Process Bionics. With this extended approach, optimization becomes a core element of corporate DNA. From this perspective, the spectrum of process paths is understood as an organically grown landscape. Change and improvement must therefore themselves take place as an organic, evolutionary process. Process Mining opens up the potential to analyze and handle "special cases" that are difficult to capture using traditional methods. Process Bionics expands the principle: being in constant evolution, process optimization becomes the "normal state".



Insight is the first step towards improvement: the huge potential of digital insights

Thanks to rapidly advancing digitalization, Big Data and the like, companies today have completely new analytical possibilities with regard to their business processes. In fact, almost every process is documented in data records. Anything that has a timestamp can now potentially be combed through by Process Mining applications. This makes comprehensive transparency, real-time control, and adherence checks against defined target processes possible. Specific decision-making processes which take place in the company become comprehensible – and where the causes of the problems that arise actually lie. They can then be solved precisely and sustainably in the real event context. This may be through one-off measures, organizational changes, or intelligent digital tools such as robotic process automation, and the use of software-based "robots" for the dynamic automation of tasks.

Despite all the revolutionary possibilities, however, Process Mining is not a revolution, but rather an evolution. Historically, companies and consultants have been working for a long time to improve structures and processes through approaches such as lean management, Six Sigma and so on. However, the consultants’ proven expertise is now being transformed into a more holistic and empirical depth. Existing techniques such as interviews and workshops will be supplemented by digital access directly into the heart of operational processes. Of course, all of this is being done while maintaining the operational and legal regulations such as data protection and privacy.

This new data-driven form of process discovery permits an unbiased, "agnostic" view of even uncomfortable truths in the business. In addition to that, it is very efficient because it ties up few resources (such as interview partners or workshop participants). In this way, process models can be developed on the basis of the master- and transactional data plus process logs. If these already exist, Process Mining compares the actual data with the model in a further step based on the process logs (Conformance Checking). Finally, on a third level, Process Mining can change and improve the model itself through a feedback mechanism (Model Enhancement). Ideally, in the sense of company-wide "Continuous Evolution", as it underlies the holistic claim of Process Bionics. In terms of access, Process Mining is almost total and in the analysis as fine-grained as desired. The user can zoom in on the smallest details of the process steps - or back out again at will, to get the "big picture".


The informational value of the outliers: Process Mining brings to light the previously hidden

What is attractive about this approach, however, is not just the holistic perspective, based on data points or the wide variety of information. What makes Process Mining even more exciting is that it enables navigation through undiscovered regions of the process landscape. Thanks to this approach, it is also possible to investigate precisely those processes that have so far fallen by the wayside: atypical extreme cases, outliers, inefficiencies and other patterns. In fact, these are particularly interesting. In process optimization, the middle way does not always lead to the final objective. Instead of statistically overlooking special cases, it is precisely these that have to be searched for and scrutinized.

The main variant of a process can be theoretically as well defined as you like, but if problems occur in practice they can be analyzed much better by looking at the exceptions. Only then will it become clear what deviations and bottlenecks exist, and how they occur. Is it the process itself, the employee or the location? In a certain company, for example, it is found that production starts up again and again even though there is no official order (yet). What is the reason for such an unusual, irregular workflow - mere technical or human errors? Or are the processes justified by the context? These questions can be answered more precisely with the tool. The areas of application in the company are extremely diverse. Process Mining is a true end-to-end approach - a comprehensive increase in efficiency across all business areas.


Requirements, applications, hurdles: Process Mining in practice

All this sounds compelling - but also a little abstract. How does Process Mining work in practice? And what are currently the main sectors for its application? Today, the prerequisites for this are universally met, since ERP systems or databases (e.g., ticketing and service systems) digitally record almost all processes in the company. Time stamps, event semantics and process instance IDs enable the extraction of data from logs. And the analysis of these data is attractive in just about all sectors. Process Mining is currently the trend, especially in highly regulated industries. A large number of software providers are now present on the market, from Germany, for example, the market leader Celonis or the newcomer Lana Labs (other tools include PAFnow, SNP, Aris, Processgold, Disco, Signavio). In the media, too, aspects of the trend are being discussed more often. Most of the time, however, the focus is on limited areas such as finance, where strict regulations make fine-grained process monitoring particularly important. The same applies, for example, to pharmaceutical companies with highly specific production processes. But it also applies to supply chain logistics in general and non-financial processes. The modern supply chain, just like almost every other operating process, benefits from optimization based on real data. In the working capital area, payment flows are optimized. The purchase-to-pay process can be digitally analyzed and improved.

The advantages are transferable to just about all industries and are scalable within the company. Whether in retail, OEM or banking, whether in development, sales or compliance: order processes, financial flows and processes, benchmark checks – these topics can actually be improved everywhere. The data-driven approach helps to overcome silo mentality and opens up a comprehensive view across the company's software developments. A direct understanding of the processes and their performance is simplified by visualization on dashboards. Patterns and deviations can thus be grasped intuitively. The traditional, static "table view" converts into a mutual and dynamic process perspective. Another advantage of the mining solutions is the flexible output to industry-specific cockpits that can be tailored to the role – from manager to skilled worker. The plant manager is interested in comparing the actual status with the planned target. The production worker on the shop floor, on the other hand, wants to know whether the individual machine’s processes are running optimally. Intelligent leading tools in the area of analytics, for example from supplier Celonis, make Process Analytics possible.

However, Process Mining is not a plug-and-play technology. Implementation requires a close dovetailing of implementation partners and companies, because not all data are always available in a suitable form from the outset. Extraction and transformation can demand a lot of effort and applications need to be configured. Aggregation across multiple systems can also often present a significant technical hurdle.
Applications developed in-house also represent a further challenge. They often supplement standard solutions in the process flow for the company's own needs. Over time they could potentially turn into undocumented, non-transparent "black box technology". Precisely such extensions and add-ons to standard software often demonstrate the limitations of standard applications in Process Mining. This is because they sometimes present a bottleneck to analysis, for example due to compatibility problems or data extraction limitations. However, with the right approach it is sometimes possible to simulate such areas, which allows them to be integrated into the optimization process.

Productive implementation requires industry-specific expertise. Deloitte's global knowledge pool is a valuable resource here. Moreover, Deloitte maintains close technological collaboration with analytics providers and also offers broad sectoral and technological expertise of its own: important for solving existing problems with the practical implementation. Of course, the cost issue must also be kept in mind. Rather smaller companies may reach their limits here. However, it is not always necessary for the company to own a license. The analysis function can also be booked by the customer as an additional service.

Learning from nature: with Process Bionics, companies grow into the future of process optimization

With Process Mining, companies have a tangible offer at their disposal that provides immediate cost benefits. But that is only the first stage of tomorrow's process management. This approach is systematically expanded and extended at the Deloitte Center for Process Bionics. The leading models are borrowed from nature with reason. After all, the natural evolution of living organisms has proven to be an extremely efficient strategy for adaptation, survival, and growth. If the company is understood as a growing, living organism, then the improvement process itself can also be designed to be organic. Only if the reasons for the emergence of possibly problematic decision-making processes are understood, efficient further development is possible.

Continuous process evolution resorts to state-of-the-art computer technologies. Artificial Intelligence and advanced cognitive models merge the stream of data insights in the manner of neural networks. Machine Learning makes evolutionary, self-correcting processes with feedback directly into the company’s processes possible. The biological models are used directly in the further development of the concepts. Cooperation with universities and a broad interdisciplinary exchange ensure the transfer of new scientific approaches from biology to business.

Even if much of this remains a vision for the time being – the direction is clear and the benefits are obvious. Adapting to rapidly changing circumstances must go beyond one-off, top-down process corrections. Rather, improvement is now permanent. However, this also means that the company's DNA is constantly being evolved to make it fit for new challenges. An evolutionary process, as dynamic and continuous as the real, constant transformation of the business challenges themselves.

Digital Process Optimization: how Deloitte can unlock the potential for improvement in your company

The benefits of Process Mining and Process Bionics are comprehensive, the possibilities complex. Yet access to these management concepts can be very simple. Deloitte offers a three-tier service model with various levels of deployment. It ranges from a test run to a comprehensive technology rollout to a holistic bionics approach:

  • The Healthcheck service provides companies with a comprehensive understanding of the possibilities of Process Mining based on real data from the business. This involves zooming into a selected typical process, which is examined using standard methods and then further analyzed in workshops. The first insights for optimization potentials quickly emerge.
  • The Process Diagnostics offering expands Process Mining – with a focus on quantifiable measures and specific recommendations for action. The goal is noticeable impact and a fast return. Deep Dive analyses shed light on processes across system boundaries. Process landscapes are maintained and developed, potentials for robotic process automation and the reconfiguration of systems (e.g., during migration to SAP HANA) are pointed out.
  • The third stage, Continuous Evolution, aims to embed Process Bionics deeply in the company's DNA. Seamless integration of capabilities, dedicated governance structures and comprehensive training programs lead to a sustainable competitive edge.

No matter the level on which you want to start: with the Deloitte Center for Process Bionics as a partner, companies can take advantage of the direct benefits of Process Mining already today. And at the same time make a start with tomorrow's process management: into a holistic and continuous further development of the company with the goal of a best-in-class process landscape.

Deloitte Center for Process Bionics