Efficient and effective with business process analytics

Mr. Kraume, the topic of process analytics is on everyone’s lips. Why is it so important to you?

Karsten Kraume: Analytics in general is important to us for two reasons. On the one hand, we offer our customers analytics solutions. This way we help them to achieve more business and a better customer journey and customer experience, driven by data. We offer them both cross-industry (https://www.future-customer.com/accurate-and-personalized-analytics-at-a-glance/) and industry-specific solutions, for example for airlines. In addition, we use analytical methods ourselves when we improve our own processes. This field is large and ranges from operations to sales and HR to sourcing.

Yet another aspect: the analysis of processes is often followed by their automation. Significant savings can thus be achieved. This is also evident from our study “Customer Service in 2027” on how automation, robotic process automation (RPA), and artificial intelligence will change customer service in the next decade.

Does that mean you’re researching this, too?

Karsten Kraume: Correct. It is essential for us to regularly conduct internal analysis on where we can improve, or to drive innovation and develop new solutions for the market. This applies not only to descriptive analytics methods, but also to predictive ones.

But our activities don’t end at our company door.

We have an extensive research and development network with which we regularly exchange experiences. The European Research Center for Information Systems (ERCIS), through which we collaborate with 28 academic institutions and leading researchers such as Martin Matzner, is particularly noteworthy.

Professor Matzner, how do you define the topic of process analytics?

Dr. Martin Matzner: Business process analytics means applying business analytics to process-related data, and is a field of research in the area of business process management. It is often a matter of providing data on efficiency and effectiveness for process participants, decision-makers, and other stakeholders.

Conceptual and technological differences arise in the time dimension in particular: some methods search for patterns and calculate key figures with the help of closed process instances; others try to observe processes in practically real time. A third class of methods is dedicated to predicting behavior and process metrics. We at the Chair of Digital Industrial Service Systems at FAU are developing new methods and techniques for this purpose, but we are also looking at how organizations can use and implement them.

Can you name some research examples and technology partners for us?

Dr. Martin Matzner: Regarding methods and techniques, “RegPFA” is a good example – a machine-learning method that I developed together with colleagues from Münster. RegPFA learns from past process data and is thus able to make predictions about the further course of process instances. This gives companies the opportunity to control their operational processes with foresight.

With regard to the use and implementation of process analytics in organizations, for example, we are currently conducting a process mining tool survey to support companies in selecting suitable software.
It is also important to us that the topic is embedded in the teaching at FAU. Big users like Siemens are desperately looking for young, talented employees familiar with the topic. We therefore offer a Master’s lecture on business process analytics as well as seminars in the field of process analysis and automation.
Partners include solutions providers like the software supplier Celonis and operators like Siemens AG. In addition, as part of the RISE_BPM research project, we work together with the ten leading research institutes in the field of business process management in Europe and companies such as Arvato CRM Solutions.

Mr. Kraume, which providers do you work with?

Karsten Kraume: First of all, we work together with several providers. Quite simply because, as a business process management provider, we have several hundred customers, some of whom have already made tool decisions. But specifically on the topic of process analytics: with Celonis, for example, we analyze purchasing processes. In automation – keyword robotic process automation – we work together with BluePrism, Automation Anywhere, and Contextor, among others. But just as important as performant technology is establishing profiles and integrating them in an organizational way.

How did you set up the organization in the face of more data, and thus a larger basis for analytics and automation?

Karsten Kraume: We have more than 100 full-time staff members working for analytics and robotic process automation. These are close to the use cases, i.e. where processes are analyzed and, if it makes economic sense, automated.

Prof. Matzner, how are other companies you cooperate with proceeding?

Dr. Martin Matzner: It is interesting to see that the organizational embedding in the companies is seeing very different results. For example, Siemens has founded a central department for process mining and now offers the technology as a service for the various business units. Other companies use them specifically in individual specialist areas such as purchasing and sales, in cross-divisional functions such as auditing or internal consulting, which work on a project-related basis. And even more are starting small pilot projects to approach the topic. Here, for example, we cooperate with DATEV e.G. within the framework of the Software Campus, which aims to evaluate the application potential of business process analytics in this way.

All in all, it can be said that a successful deployment requires the interaction of many stakeholders in the company, and it’s important to bring various experts into contact with processes and IT systems.

And what are typical projects on which you cooperate with partner companies?

Dr. Martin Matzner: In most projects, it’s about increasing process efficiency. Of course, the use of business process analytics is expected to lead to savings or other gains in process performance, like “promptness.” As a relatively young chair, we are also in contact with other chairs to identify synergy potentials. For instance, we’ve offered seminars for students in finance – especially tax law – as the topic plays a particularly large role in tax inspection and audits. The focus here is more on issues of compliance than on efficiency.

Overall, our finding was that practice agrees that the topic is highly interesting and important, but there are still many questions. For example, it’s often unclear which data is required, where in the company the application can create the most added value, or what change management should look like in order to convey the sudden transparency of process participants and operations.

What contribution can research make in this?

Karsten Kraume: Research isn’t as far removed from practice as many people think. What’s important is the exchange, and that both sides have a sufficient contextual understanding of the other.

That’s not a matter of course; both sides have to be willing to invest the time. But this deployment does pay off, as good examples like ERCIS, CLAIRE, social media analytics, BPM-Rise at Arvato CRM Solutions show.

CLAIRE is aimed at creating a European network of competence centers for artificial intelligence, for example. The goal is to achieve a similar effect and brand awareness in the field of artificial intelligence as at CERN, the European Organization for Nuclear Research.

Thank you for the interview, Mr. Matzner, Mr. Kraume.

Dr. Martin Matzner holds the chair for Digital Industrial Service Systems in the faculty of Economic Sciences at the Friedrich-Alexander University Nuremberg-Erlangen. He’s also the head of the Service Science Competence Center at the ERCIS and co-author of various studies in the fields of artificial intelligence and digital transformation.

Karsten Kraume is CIO/CSO at Arvato CRM Solutions and represents the company as a committee member at the European Research Center for Information Systems (ERCIS) as well as at research programs such as Business Process Management RISE. He is the co-author of various studies on digitization, automation, and customer experience.

Author: Editorial Team Future. Customer.
Picture: © Silkov – Adobe Stock