In today’s competitive landscape, companies strive for efficiency and productivity. Celonis, a leader in process mining technology, is at the forefront of this transformation, reshaping how businesses operate. Through its innovative Process Intelligence Graph, Celonis helps organizations identify inefficiencies and seize opportunities for improvement, all while leveraging artificial intelligence (AI) to drive success.

Dr. Lars Reinkemeyer, Chief Evangelist at Celonis, emphasizes that a robust data foundation is essential for enhancing process efficiency across different industries. He explained that the incremental approach to AI in business mirrors the gradual advancements in autonomous driving technology. While excitement surrounds generative AI tools like ChatGPT, practical applications are only beginning to surface in the business realm.

One of the standout features of Celonis’s approach is the Process Intelligence Graph, which serves as a centralized data backbone. This graph integrates various data types, including process data, event logs, and even contextual information about business operations. Dr. Reinkemeyer insists that this integration is key to unlocking valuable insights that can drive operational improvements. For instance, having a unified view of customer orders translating into manufacturing processes ensures end-to-end transparency.

The importance of transparency is underscored by the tremendous success experienced by Celonis clients, including pharmaceutical giant Pfizer and automotive leader BMW. Both companies have reportedly discovered “triple-digit millions of value,” a testament to the financial impact that such transparency and process optimization can achieve.

However, the road to optimizing processes using AI is not without challenges. Dr. Reinkemeyer pointed out that while current AI technologies can handle defined processes effectively, true advancement lies in developing systems that can autonomously predict and manage complex scenarios. The saying “garbage in, garbage out” rings especially true in this context; the quality of AI outputs is directly linked to the quality of input data.

The strategy behind the Process Intelligence Graph, affectionately referred to as “the pig,” illustrates how businesses can foster better decision-making. Dr. Reinkemeyer emphasizes the need to “feed the pig” by continuously inputting more data into the system. This approach strengthens the AI’s ability to deliver intelligent insights across procurement, finance, and supply chains.

A critical aspect of the Celonis philosophy is the transition from data awareness to action. Dr. Reinkemeyer likens this journey to using an X-ray to diagnose a medical condition—while discovering inefficiencies is vital, taking targeted action to resolve these issues is what truly matters. He stated, “Insight without action is worthless,” underscoring that the ultimate aim is to generate tangible results from the insights gained.

One prominent example of this paradigm shift can be seen in Celonis’s collaboration with Siemens. Dr. Reinkemeyer shared how their partnership evolved from analyzing logistics to achieving transparency across 30 million shipped items annually. This initiative has led to a proactive, alert-driven supply chain capable of anticipating disruptions, thereby enhancing customer delivery reliability.

The COVID-19 pandemic highlighted the fragile nature of supply chains, affording Celonis a pivotal role in helping organizations navigate these challenges. Delays and inefficiencies not only dissatisfaction among customers but also implications for working capital. Celonis’s technology allows companies to detect such issues early, fostering an environment where proactive measures can be instituted.

Feedback from clients is often characterized by initial astonishment due to newfound process visibility. “Wow, I wasn’t aware that my process had so many variants and inefficiencies,” is a common response. Nevertheless, the emphasis remains on converting this insight into actionable strategies that create value.

Celonis places significant importance on ensuring the reliability of its AI capabilities. “We don’t overpromise,” Dr. Reinkemeyer stressed, affirming that the technology thrives within well-defined processes backed by a solid data infrastructure. This open ecosystem enables companies like Pfizer and BMW to customize their AI advancements to suit specific operational needs.

The shift towards automation is becoming more pronounced, especially in areas like procurement. As an example, Deutsche Telekom has automated 95% of its standard purchase orders. Dr. Reinkemeyer pointed out that while this may seem intimidating to some, it represents a natural evolution in business processes. “No one enjoys processing 100 purchase orders a day,” he remarked, noting that AI will empower employees to engage in more meaningful work.

This automation trend is particularly crucial in regions facing demographic difficulties, such as Japan, where an ageing population demands heightened productivity. “Having 95% of purchase orders automated is a welcome development there,” Dr. Reinkemeyer added, further highlighting the societal implications of AI in business operations.

The real-world applications of AI-driven process management illustrate the potential unparalleled advantages offered by this technology. For instance, Celonis has enabled Smurfit Kappa to manage inventory efficiently across various locations. Their AI system can identify material availability in different plants and facilitate timely shipments, contributing to manufacturing deadlines.

Ultimately, Dr. Reinkemeyer envisions a future where AI acts as an indispensable co-pilot in organizational operations. “The ultimate goal is to make support processes highly efficient—95 to 98% automated—so companies can focus on their core business,” he stated.

Celonis is dedicated to helping businesses realize value through intelligent process optimization. Its technology provides crucial insights that pave the way for actionable improvements, ensuring that organizations not only see their data but also act on it effectively.