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Professor Seiter, how do cloud computing, big data, and other digital developments influence management accounting?
Digitalization is leading to a profound transformation of all areas of the economy and society. This not only creates unprecedented potential for process optimization but also lays the groundwork for new business models. Consequently, this development also has an enormous impact on management accounting and requires corporate management to adapt to these new, digital realities.
A solid foundation is certainly achieved through the most extensive process automation possible. To this end, a homogeneous system landscape and centralized, automated data management, among other things, are necessary. In this context, we are seeing an increase in the provision of controlling applications by cloud providers.
Under the umbrella of “Big Data,” companies are gaining access to large volumes of structured and unstructured data. At the same time, digitalization—combined with the use of advanced statistical methods and quantitative models—enables the meaningful analysis of this increasingly complex array of data. This allows patterns to be identified and decision-making to be optimally supported. The result is a highly automated, analytics-driven, and integrated real-time corporate management system.
In summary: The digitization of controlling processes leads to cost savings, time savings, and improved quality.
In which controlling processes is digitization taking place? What has already become firmly established?
In self-assessments, many companies report having achieved only a moderate level of digitization in controlling so far. At the same time, the need for digitization is growing. While digitization as an overarching concept is still difficult to grasp, several key areas are already emerging.
For example, process automation technologies such as Robotic Process Automation (RPA) can drive efficiency and effectiveness gains in reporting by reducing turnaround times and error rates. Intelligent automation technologies such as chatbots or digital voice assistant systems can also help to increasingly simplify and accelerate controlling processes.
Thanks to the digitization of manual interfaces, complex planning and analysis will be possible in real time in the future. Furthermore, new data sources and volumes of data can reveal previously hidden insights using business analysis methods. In this context, innovative controlling tools not only provide significantly more detailed insight into corporate management but also enable faster and simpler planning.
Examples of innovative controlling tools include multidimensional performance measurement, driver-based planning, and Objectives and Key Results (OKR). This is leading to the growing importance of dynamic planning applications that can simulate business developments using algorithms, thereby reducing the planning effort involved in budget planning. Driver models and algorithms are also increasingly being used in forecasting within digitized controlling.
Efficiency-enhancing technologies are also finding their way into controlling. What impact does RPA have on controlling?
Robotic Process Automation is particularly well-suited for repetitive, rule-based, and standardized processes that involve system silos. Here we can already see the connection to controlling: Many processes converge in controlling, and information from the individual business units is made available through various systems.
When aggregating this data—a task that controllers previously performed manually—RPA can deliver real efficiency gains. This frees up resources for the strategic aspects of controlling, which are more important than ever in times of crisis. It also dramatically increases the frequency with which reports can be generated. The basis for decision-making is available virtually at the push of a button, enabling new, more agile management systems within companies.
What challenges do you see in the implementation of RPA in controlling?
In our research projects, we’re currently seeing that RPA is being gradually adopted in companies of all sizes. Whereas some time ago there was still a need for support in identifying processes suitable for RPA within companies, there is now a consensus on this in both academia and practice.
One challenge we currently see with the implementation and operation of RPA in companies is employee acceptance. Employees’ work environments are changing dramatically; tasks they previously performed are being automated and eliminated. Whether employees accept such a change depends not only on their personality but also, for example, on the software’s performance: Can I rely on the automation, or do I have to constantly correct the software robot’s errors? Training sessions prior to the implementation of RPA can help break down barriers to employee acceptance.
What distinguishes subscription business models from traditional business models?
At their core, subscription business models revolve around an ongoing service relationship between the customer and the provider. Instead of ownership, the customer merely acquires access to a service and pays based on an agreed-upon time frame or volume of service.
A key aspect is the provider’s access to customers’ usage data, which allows them to better understand customers’ needs and improve the service in a targeted manner. This is also what distinguishes subscription business models from traditional subscription models. Digital offerings are particularly well-suited to this model, as intangible goods can be provided flexibly and with consistent quality. Consider, for example, the many successful streaming services. However, we are also seeing an increasing number of use cases in the manufacturing industry. Here, the terms “pay-per-use” or “equipment as a service” are often used. This brings additional risks into play. Depending on the model, in addition to the investment risk, the provider also assumes the customer’s utilization risk and the machine’s quality risk.
This creates new challenges for corporate management, such as higher revenue volatility and a changed cash flow profile. In this context, the use of business analytics methods for better forecasting is particularly promising. Overall, subscription business models thus represent a veritable paradigm shift in the manufacturing industry, yet they offer significant opportunities for new value creation and growth.
Imagine a company wanted to—or had to—restructure its controlling function. How would you staff the various roles, and why? What skills would you require?
On the one hand, management accounting faces the challenge of continuing to support novel business models with appropriate control mechanisms. On the other hand, controlling itself must be digitized to keep pace with organization-wide developments. Accordingly, we are observing a shift in the controller’s role from that of a mere provider of information to that of a full-fledged business partner who acts as an enabler for the development and implementation of innovative business models.
In this role, the controller is responsible for both helping to shape the innovation process and developing new management concepts and key performance indicators. This entails the task of actively supporting revenue and profit growth and identifying opportunities for development. Furthermore, controllers should proactively engage in business model innovation and support management through their knowledge of methods and tools, as well as their analytical skills.
Prof. Dr. Mischa Seiter is a lecturer at the Frankfurt School of Finance & Management. He developed the Certified Digital Controlling Specialist certificate program, which he also teaches.
His research focuses on business analytics and performance measurement, the acceptance of intelligent systems, the development and management of digital platforms, and use cases for new technologies in a business context.
