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The energy industry is faced with increasingly complex processes with a growing number of participants and new billing scenarios. At the same time as customer satisfaction, cost optimization and compliance requirements must be kept in mind.
Process mining makes it possible to reconstruct what actually happened for all processes from the abundant digital data available. The processes are placed in a common context, deviations from the expected and permitted are identified and the causes can be investigated.
With iVIEW .Process Mining, the process perspective becomes available in the context of proven BI-Tools such as Power BI and Qlik Sense, eliminating the need for employees to learn new tools and keeping the effort required to connect to source systems low.
False meter readings
Detect inefficiencies and clearing cases with high manual processing effort
Reduce the cancellation rate
Analyze turnaround times from receipt of meter reading to claim payment and uncover bottlenecks
the increase of the discount rate
the mapping of cost flows in monthly closing processes
Fraud-Detection und Complicance-Checks
In addition, process mining is extremely helpful in verifying the effectiveness of control systems during internal audits!
WithiVIEW.process mining, we now provide you with a function library to turn your existing business intelligence suite – Qlik Sense or Microsoft Power BI – into an intuitive tool for professional process analysis. In this way, you supplement your business-relevant key performance indicators with the process perspective and can thus optimally use the digital transformation to shape your competitive advantages.
Today, many processes are executed with the help of external service providers. Process Mining can be used to analyze the performance of service providers in all areas (e.g. smart metering) in order to make effectiveness, response times and quality of work in different process steps comparable (benchmarking).
In addition, process mining offers ideal support for the automation of processes via Robotic Process Automation (RPA). For this purpose, Process Mining is first used to identify the processes and process steps suitable for RPA. Then the optimal scope and process flow for automation is determined, also taking into account the existing systems.
With process mining, continuous success control is now possible in order to be able to readjust at short notice.
Companies know their business processes - but usually rather theoretically. In fact, there is often a lack of full process transparency.
The reasons are manifold - work processes are perceived subjectively, steps are added unconsciously. And employees usually only know about sub-processes related to their work. In addition, processes change, for example due to new compliance requirements or changed customer needs. And finally, the intended process flow does not always fit, for example in the case of special, non-standard production requirements.
And this is exactly where process mining comes into play, the automated analysis of business processes based on digital traces in IT systems.