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Upgrade your Business Performance with Process Mining: Successful Process Transformation and Continuous Improvement
Because processes are dynamic and complex, process optimization is not a one-time endeavor, but an ongoing task with strategic relevance for your commercial success. In order to provide our powerful solution MPM ProcessMining with the necessary strategic framework for your continuous process excellence strategy, we work closely with strategic partners like Capgemini Invent. We are excited to partner with Capgemini in the upcoming webinar to share how you can successfully and sustainably transform your processes to achieve new levels of operational excellence and competitive advantage. Let process analysis capabilities become part of your business DNA and make smart decisions.
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Achieving Operational Excellence. Gaining Competitive Advantage. Improving Business Performance.
Optimizing processes is at the top of many companies' to-do lists - surely this applies to you as well? This is good and important in order to be able to withstand competition or, ideally, to be one step ahead. Because processes are dynamic and complex, process optimization is not a one-time endeavor, but an ongoing task with strategic relevance for your commercial success. In order to provide our powerful solution MPM ProcessMining with the necessary strategic framework for your continuous process excellence strategy, we work closely with strategic partners like Capgemini Invent. Capgemini Invent combines strategy, technology, data science and creative design to address even the most complex business and technology challenges. We are excited to partner with Capgemini in the upcoming webinar to share how you can successfully and sustainably transform your processes to achieve new levels of operational excellence and competitive advantage. Let process analysis capabilities become part of your business DNA and make smart decisions.
Agenda
The Power of Digital Data Traces
Learn about the automated process analysis technology Process Mining. Realise the power and value of digital data traces.
Jan Birkholz, Process Mining Expert & Business Development Engineer, MEHRWERK
How to ensure Value Creation?
Get to know ESOAR™ – A unique and straightforward transformation methodology.
Elsa Duberg, Process Mining Consultant, Capgemini Invent
From Spaghetti to Happy Path
How can you find optimisation potential in spaghetti diagrams? Watch an exciting live demo in the Process Mining application.
Elsa Duberg, Process Mining Consultant, Capgemini Invent & Jan Birkholz, Process Mining Expert & Business Development Engineer, MEHRWERK
Register for the eSeminar now FREE of charge
Take the opportunity to get smart for free with a look at the Process Mining Tool
YOU DON'T KNOW PROCESS MINING YET?
DEFINITION
Process|Mining
[ˈprəʊ.ses ˈmaɪ.nɪŋ], the; (Business Process Discovery)
Automated business process analysis - with all relevant key figures - based on digital traces in IT systems. Process knowledge contained in data, implicit and otherwise hidden is visualized and thus tangible and transportable.
WHY PROCESS MINING
Achieve operational Excellence
Increase Efficiency despite Complexity
We live in a world of business processes that are supported digitally. These processes leave their mark on IT systems. People are connected through IT systems (e.g. SAP®, Microsoft Dynamics® etc.), whereas machines are linked by MES systems (Industry 4.0). Complexity is increasing. Flexibility must be maintained. Costs should be reduced. Process Mining gives you complete transparency:
- What is happening daily within your processes?
- Where do deviations, inefficiencies, compliance issues occur?
- What potential improvement may result from this?
WHY QLIK-BASED PROCESS MINING
Process Mining with Qlik DNA
The philosophy of the market-leading BI platform Qlik® is that " data is the key to the success of your business". Renowned experts such as Prof. August-Wilhelm Scheer also know that the efficiency of the central core processes is a prerequisite for succeeding on the market. The logical consequence: Business Intelligence meets Process Mining.
There are often separate "standalone" BI and process mining solutions based on similar source data. However, there is an exciting development in the Qlik® universe that has arisen from the understanding that process performance indicators (PPIs) should not form their own analysis clusters in addition to classic indicator analyses. On the contrary: the special features of the modern "Agile BI" pioneer Qlik® are "inherited" by process mining analysis and offer a unique added value. A real win-win situation for Qlik® users. But also for Qlik® newcomers this presents Process Mining of a special kind.
In the webinar we will demonstrate the Process Mining solution with Qlik®-DNA ...
AGILE
In contrast to dedicated process mining solutions, agile process mining takes place in convenient, flexible analytical applications. Expanding the data space is possible "on-the-fly".
We'll provide you with an insight into the agile world of analysis!
CUSTOMER-CENTRIC
In contrast to traditional process mining solutions, self-service Process Mining is possible. Business analysts and professional users can independently create sophisticated data and process visualizations as well as customized analyzing applications.
We'll show you how easy it is to create individual apps!
TIME-SAVING
80 % of expenditures regarding BI & Process Mining projects are related to data preparation.
In contrast to traditional process mining solutions, the processing of data does not take place in the source system - all thanks to integrated ETL & mining algorithms. Consequently, the processing performance is significantly higher.
We'll show you how highly performant and simple data preparation can be.
DATA GOVERNANCE
Data governance is one of the most important success factors for digital transformation and plays a decisive role in the success of data analysis and big data projects. Qlik-based process mining offers reliable data quality.
Learn how Qlik® ensures the highest standard of data quality across multiple data sources.