NEW YORK & MUNICH--(BUSINESS WIRE)--HFS Research today published a study1 commissioned by Celonis and IBM Consulting that shows approximately 90% of surveyed enterprise leaders are suffering from supply chain disruption, and more than 75% cited the volatile market conditions marked by inflation and recession as having a major impact on their businesses. The study also highlights process intelligence as the most effective way to weather these macroeconomic challenges.
The findings show that process intelligence, specifically process mining adoption, is driven by customer service (56% in production or scaled up), IT (53% in production or scaled up), and supply chain (55% in production or scaled up).
Further data from the research demonstrates that businesses believe in the power of process intelligence:
- Process intelligence is the #1 emerging tech investment expected to impact process transformation today
- 88% of enterprise leaders expect increases in process intelligence investments despite the harsh economic climate
- More than 95% of organization leaders see combining visibility into cross-functional operational performance and monitoring as a game-changer
- About half of enterprise leaders are still exploring ways to become more predictive with their data
Process transformation for efficiency, productivity and lowered costs
Process transformation efforts have come to the forefront for many organizations, who are focusing on bottom-line metrics - specifically efficiency and productivity gains, as well as cost reductions. The study findings highlight that process intelligence has become the #1 way to address process debt, and that ERP, alone, cannot do it.
ERP modernization has often been hyped as the prescription for every ailment related to business processes, but roughly only a third of organizations (36%) believe it is essential today. Designing and running business processes that can thrive despite uncertain macroeconomic conditions will require enterprises to address their process debt, which HFS Research sees as a corollary to technical debt. Process debt is the creation of awkward (and often manual) processes that are designed to buttress aging technologies and that must be redesigned and modernized to improve business operations.
“While migrating to cloud-based ERP certainly has a role to play in operations modernization, enterprises must revisit the design and execution of their processes to have a bigger impact,” said Reetika Fleming, Executive Researcher Leader at HFS Research. “Our study with Celonis and IBM Consulting finds that many organizations are turning to process mining as the primary way to tackle these challenges. The majority of enterprises have already gotten their feet wet with initial projects and the research shows the high potential for this set of technologies to rapidly drive radically new sources of insight and business value.”
Infusing intelligence and predictability with digital process twins
Process intelligence has been a good starting point for diagnostics and addressing process problems or process debt. The study shows that process intelligence, implemented atop digital process twins, can deliver multi-functional data and insights. This will help business leaders predictively manage business uncertainties through digital command centers.
Digital process twins (also known simply as “digital twins”) enable multi-process and multi-function visibility, as well as blend multiple datasets, augmenting process intelligence which was traditionally more focused on impact on individual business functions. Digital twins enable scenario modeling and planning, as well as stress-testing and simulations - allowing for better future-planning and addressing uncertainties.
And with the latest advent in process mining - specifically object-centric process mining (OCPM) - digital twins are made even more valuable. With the release of Process Sphere at its annual Celosphere conference in November 2022, Celonis launched this revolutionary new technology that enables the analysis of interrelated business objects and events involved in business processes. Events are connected to objects instead of a single case, making it possible to easily and quickly view complex and interacting processes from all perspectives.
Whereas traditional process mining allows you to analyze a single process (like accounts payable), the analysis becomes extremely powerful when it is capable of understanding and optimizing interconnected processes. Object-centric process mining provides a 3D-view of how numerous processes work and interact (think: procurement’s impact on production), and thus enables optimization across interconnected processes. If traditional process mining is an x-ray of a single process, then object-centric process mining is an MRI, providing a 3D-view of a company’s interconnected processes.
“Process mining provides unparalleled visibility into how a business runs, uncovering value opportunities hidden by complexity within and across processes,” said Prof. Dr. Wil van der Aalst, Chief Scientist at Celonis. “Process mining, particularly object-centric process mining, is foundational for analyzing a digital twin. With digital twins building on OCPM, teams can analyze multiple processes simultaneously. Digital twins can effectively be used to enable quick wins, advanced simulation and expert decision-making, and - in an uncertain macroeconomic climate - help organizations to look forward and prepare for any kinds of uncertainties through a digital command center.”
New horizons: External exchanges
According to the study, the potential for external collaboration with shared process data exchanges is on the horizon for ambitious businesses that want to seek entirely new sources of value. An example of this might be a CPG company or a retailer exchanging inventory and payment data for mutual decision-making and action-taking benefits - in other words, looking for new sources of value through data exchanges.
Methodology
HFS Research conducted a study, sponsored by Celonis and IBM Consulting, in which they reached out to 260 enterprise leaders (including Global Business Services (GBS) leaders, shared services heads, and CXOs) spanning various geographies, industries, company sizes, and other demographics across goods-producing industries. The goal of the study was to document through research the uses, benefits, and financial value of using digital twins in multi-process environments, especially in shared services operations.
About Celonis
Celonis enables customers to optimize their business processes. Powered by its leading process mining technology, Celonis provides a unique set of capabilities for business executives and users to continuously find improvement opportunities within and across processes, and execute targeted actions to rapidly enhance process performance. This optimization yields immediate cash impact, radically improves customer experience, and reduces carbon emissions. Celonis has thousands of implementations with global customers and is headquartered in Munich, Germany and New York City, USA with more than 20 offices worldwide.
© 2023 Celonis SE. All rights reserved. Celonis, Execution Management System, EMS, Process Sphere and the Celonis “droplet” logo are trademarks or registered trademarks of Celonis SE in Germany and other jurisdictions. All other product and company names are trademarks or registered trademarks of their respective owners.
About HFS
Insight. Inspiration. Impact.
HFS is a unique analyst organization that combines deep visionary expertise with rapid demand-side analysis of the Global 2000. Its outlook for the future is admired across the global technology and business operations industries. Its analysts are respected for their no-nonsense insights based on demand-side data and engagements with industry practitioners.
Read more about HFS and our initiatives on: www.hfsresearch.com or follow @HFSResearch
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1 The study, “Infusing intelligence and predictability with digital process twins”, surveyed 260 enterprise leaders (including GBS leaders, shared services heads, and CXOs) spanning various industries, company sizes and other demographics across goods-producing industries.
