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More Process Efficiency through Data-Driven Decisions – Process Mining as a Game Changer
MARCH, 30 | 3 PM
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DEAR INTERESTED PARTIES
WHAT YOU WILL EXPERIENCE IN THE WEBINAR
Making data-driven decisions. Increasing process efficiency. Whether it's a strategic decision with far-reaching impact or a detail in day-to-day business, your process analytics solution should provide the right impetus for each of your data-driven decisions. Invest 60 minutes of your valuable time to learn how Deutsche Bahn, Siemens Healthineers, STRÖER and other innovative companies use process mining to make their business processes more efficient and continuously optimise digitised products. We are happy to spoil a little: STRÖER has established an automated, user-friendly process key figures and analysis system in a very short time. This provides real-time information that can be used to take corrective and improvement measures in the operational processes.
Not only our customers are convinced, but also Gartner: MPM ProcessMining is listed as a pioneer for BI-based process mining in the Gartner Guide for Process Mining and our technology partner Qlik® has been rated as a "Leader" in the Magic Quadrant for Analytics and Business Intelligence Platforms for the 11th time in a row in 2021. In the eSeminar you will learn why Qlik®-based process mining is a true game changer in terms of process efficiency & effectiveness. Find out more about exciting customer cases and their various application scenarios.
Welcome & Introduction
Using MPM ProcessMining as a game changer in improving process efficiency |
What exactly is process mining and what makes Qlik-based process mining so unique?
From Practice: Customer Success Stories |
Get an impression of the multiple application scenarios of the technology. Find out which different objectives our customers achieve with process mining. We take a closer look at three exciting customer examples.
Deutsche Bahn | Avoiding queues at ticket sales. Optimising vehicle supply. Avoiding delays before the start of a journey. - The wide range of applications of process mining at Deutsche Bahn
Siemens Healthineers | Improving product design and quality with Process Mining. Using IoT-data in computed tomography (ICT) to gain competitive advantage.
STRÖER | Receive real-time information that is used to take corrective & improvement actions in the operational processes (Accounts Payable / Purchase-to-Pay). How Ströer established a user-friendly process key figures and analysis system in a very short time.
Live Demo |
Take a look at the Process Mining Dashboard and learn about powerful features.
Take the word and clarify unanswered questions.
Constantin Wehmschulte, Head of Process Mining at MEHRWERK, provides insight.
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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?
[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 ...
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!
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!
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 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.