Start with a Solid Process Baseline
Part 3 of a 5-part Series
Enterprise business processes are designed to support operations. But it’s not always easy to understand how well these processes are really performing or where they need improvement. To identify process weaknesses, compliance deviations, and opportunities for optimization, business process owners need complete transparency into how processes are executed.
To measure the efficiency and conformance of business processes, they need to be able to objectively assess how well processes execute. By using data-based process discovery, organizations can identify all process variants and bottlenecks that may increase costs or lead to compliance problems.
Visualizing and understanding the operative processes running within enterprise applications, and distilling large volumes of data about business process execution into intuitive graphical representations, can provide a clear picture of how tasks are being performed, how well they run, and where they consume the most manual effort.
Organizations can also understand how things work and where to remediate inefficient, cost-intensive, and noncompliant processes. By enabling complete transparency into as-is processes, companies can become more compliant, increase efficiency and enable data-based continuous process improvement.
At SAPPHIRENow, SAP Market Influencer Eric Kavanagh recently sat down with Bastian Nominacher, co-CEO of Celonis, to discuss the importance of understanding how and where data is flowing when undertaking a compliance project, or a transformation initiative.
“You need to have a starting point for any transformation or compliance project. You need to have a solid baseline and a way of verifying where you stand, and them optimize based on this.”
Watch the Interview with Celonis
To see the third of the 5-part discussion, watch the video.
Did you miss Part 1?
To see the first of the 5-part discussion, click here.
Did you miss Part 2?
To see the second of the 5-part discussion, click here.
Learn more about process mining.