Astrid Caviezel – Operational Excellence & Business Process Management | Pragmatica AG https://www.pragmatica.ch/en/author/astrid/ Ihre Boutique Managementberatung seit über 25 Jahren. Wed, 27 May 2026 13:02:17 +0000 en-US hourly 1 https://wordpress.org/?v=7.0 Process Mining and AI: Webinar I & II https://www.pragmatica.ch/en/process-mining-webinar/ Tue, 19 May 2026 15:26:21 +0000 https://www.pragmatica.ch/process-mining-webinar-i-ii/ Many companies know what they are doing - but not always exactly how they are doing it.

Processes run, systems work, teams make decisions. But where do frictional losses occur? Where does reality deviate from the plan?

In our new webinar series, we will show you how you can use data-driven methods to gain clarity about your real processes - and how AI helps to translate this insight into real control capability.

Der Beitrag Process Mining and AI: Webinar I & II erschien zuerst auf Pragmatica AG.

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  • webinar

Data. Processes. AI. - How analysis becomes real control - our webinar series starts soon

Graphic: Event log as a data source for process mining - with the four disciplines of process discovery, conformance checking, performance analysis and process enhancement, extended by AI

Many companies know what they are doing – but not always exactly how they are doing it.

Processes run, systems work, teams make decisions. But where do frictional losses occur? Where does reality deviate from the plan?

In our new webinar series, we will show you how you can use data-driven methods to gain clarity about your real processes – and how AI helps to translate this insight into real control capability.

Webinar I - Process Mining: How well do you really know your processes?

Wednesday, June 24, 2026 | 5:00-6:00 p.m.

Many companies are investing in digitalization and AI – and are finding that the foundation is missing: a clear, data-based picture of their own processes.

Process mining creates precisely this basis. It makes visible what really happens in your processes – not how they are documented, but how they actually take place in the information systems. What does the happy path look like? Where do delays occur? Where is there untapped efficiency potential?

What you take with you:

  • A realistic picture of what process mining is – and what it is not
  • Initial orientation (procedure, process selection, etc.) for a possible business case
  • Practical example from the financial industry
webinar I: Register

Speakers & Moderation

Dr. Stefan Michel verfügt über mehr als 15 Jahre Erfahrung im Finanz- und Bildungsumfeld mit Schwerpunkt auf Prozess- und Datenmanagement. Er ist Certified Senior Data Scientist (Fraunhofer) und Certified Business Process Professional (CBPP) der ABPMP. Seine Dissertation zum Thema Process Mining im Bankgeschäft der SNB unterstreicht seine Spezialisierung im datengetriebenen Prozessmanagement. Mit der Prozesslabor GmbH unterstützt er Organisationen dabei, ihre Prozesse klarer, effizienter und nachhaltiger zu gestalten – als Dozent im CAS Prozessdigitalisierung der ZHAW auch in der Wissensvermittlung verankert.

Dr. Stefan Michel

Speaker
Dr. Stefan Michel has more than 15 years of experience in finance and education with a focus on process and data management. He is a Certified Senior Data Scientist (Fraunhofer) and Certified Business Process Professional (CBPP) of the ABPMP. His dissertation on process mining in the banking business of the SNB underlines his specialization in data-driven process management. As a lecturer in the CAS Process Digitization at the ZHAW, he is also involved in knowledge transfer.
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Astrid Caviezel – Operational Excellence & Business Process Management | Pragmatica AG

Astrid Caviezel

Moderator
Astrid Caviezel has more than 18 years of experience in the financial services sector with a focus on operational excellence, business process management and change leadership. As a certified Lean Six Sigma Black Belt, she has led complex transformation and process optimization projects at AXA, Swiss banks and the Canton of Zurich. At Pragmatica, she advises clients on end-to-end process design, project management and sustainable organizational development.
LinkedIn

Webinar II - From transparency to intelligent control: process mining meets data science & AI

Wednesday, July 08, 2026 | 17:00-18:00 h

In the first webinar, we will show you how process mining makes visible what is really happening in your processes.

In the second part, we go one step further: How can process mining be combined with artificial intelligence to not only understand processes, but to actively control them in a future-proof way?

Structured event log data is only part of the reality. Emails, tickets, free text – unstructured data shapes many processes just as much. New methods from data science and AI are tapping into this potential: they explain why deviations occur, predict what will happen next – and automate where decision logic can be repeated.

What you take with you:

  • What data science and AI can do for processes
  • Practical example of a root cause analysis with ML
  • Concrete picture of new possibilities for your processes
webinar II: Register

Speakers & Moderation

Porträtfoto von Fredrik Moeschlin, Founder und Senior Advisor bei moe & company

Fredrik Moeschlin

Speaker
Fredrik Moeschlin is an advisor and generalist in data science, AI/ML and digitalization with a background in engineering physics and economics. As a former Senior AI & Data Science Manager at the Volvo Group, he has driven data-driven initiatives in predictive maintenance and automated root cause analysis. With moe & company, he now advises companies from data strategy to concrete ML implementation - with a focus on data-driven processes and AI-based applications.
LinkedIn
Astrid Caviezel – Operational Excellence & Business Process Management | Pragmatica AG

Astrid Caviezel

Moderator
Astrid Caviezel has more than 18 years of experience in the financial services sector with a focus on operational excellence, business process management and change leadership. As a certified Lean Six Sigma Black Belt, she has led complex transformation and process optimization projects at AXA, Swiss banks and the Canton of Zurich. At Pragmatica, she advises clients on end-to-end process design, project management and sustainable organizational development.
LinkedIn

Both webinars - a holistic picture

Both webinars stand alone – and unfold their full effect together. Those who attend both will get the full picture: from a data-based understanding of actual processes to future-proof, AI-supported control. Two perspectives, one goal: keeping your processes under control.

Questions about the webinar series or a specific project?

Contact us

Further topics

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Process Mining and AI: Webinar I & II

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Do I really need AI?

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Third Country Intercept: How secure is your data in the cloud?

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Name
Über welche Services im Bereich Prozess Optimierung & Digitalisierung möchten Sie mehr erfahren?

Der Beitrag Process Mining and AI: Webinar I & II erschien zuerst auf Pragmatica AG.

]]> Do I really need AI? https://www.pragmatica.ch/en/do-i-really-need-ai/ Sat, 22 Nov 2025 00:15:05 +0000 https://www.pragmatica.ch/do-i-really-need-ai/ A modern digitization project without AI - is that even conceivable or justifiable?

The answer is as sobering as it is liberating: YES!

Many current problems can still be solved effectively with classic process automation. While companies invest considerable resources in AI initiatives, the return on investment of which often takes years to materialize, proven automation approaches can deliver measurable results within months.

The key challenge lies not in the technology itself, but in the correct allocation: which approach addresses which problem most effectively? This article guides you through the strategic decision-making process and highlights the differences between classic process automation, intelligent process automation (IPA) and autonomous AI agents.

Der Beitrag Do I really need AI? erschien zuerst auf Pragmatica AG.

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Do I really need AI?

  • FOCUS TOPIC

A modern digitization project without AI - is that even conceivable today?

The answer is as sobering as it is liberating: YES!

Many current problems can still be solved effectively with classic process automation. While companies invest considerable resources in AI initiatives, the return on investment of which often takes years to materialize, proven automation approaches can deliver measurable results within months.

The key challenge lies not in the technology itself, but in the correct allocation: which approach addresses which problem most effectively? This article guides you through the strategic decision-making process and highlights the differences between classic process automation, intelligent process automation (IPA) and autonomous AI agents.

AI or classic process optimization - the fundamental differences

The three automation approaches differ fundamentally in terms of functionality, area of application and requirements:

Classic process automation

Classic process automation executes rule-based, predefined processes precisely and repeatably. The technology is ideal for stable, high-volume processes with low variability – such as invoice processing, data capture or report generation. Its strengths lie in complete traceability, reliability and scalability. The maintenance effort for complex sets of rules and the lack of adaptability to unforeseen situations mark the limits of this approach.

Intelligent Process Automation (IPA)

Intelligent process automation (IPA)orchestrates various processes with the integration of AI components. Systems in this category analyze context, make data-based decisions and dynamically adapt process flows. Typical applications include document classification, intelligent ticket distribution or intelligent customer service (chatbot / voicebot). IPA offers seamless system integration and anticipates potential bottlenecks, but requires high-quality data and API-enabled systems.

AI agents

AI agents makeautonomous decisions, learn continuously and pursue defined goals independently. Multi-agent systems are particularly effective in complex, strategic processes with numerous variables and dependencies – for example in autonomous customer advice, dynamic price optimization or self-learning quality control. The challenges lie in non-transparent decision paths, unexpected system behavior and an increased need for control.

The strategic recommendation

Classic automation as the foundation, selective use of IPA for decision-making processes and AI agents where autonomy and continuous learning generate real added value.

The key questions for the right solution

The decision-making process can be condensed into five central questions:

What does the process look like?

  • Stable, rule-based processes require classic automation.
  • Processes with decision points and context dependency benefit from IPA.
  • Complex, variable scenarios that require learning justify the use of AI agents.

What decisions need to be made?

  • Deterministic decisions are suitable for rule-based systems.
  • Contextual evaluations – such as urgency assessment based on tone, content and history – require intelligent automation.
  • Autonomous goal pursuit with adaptive strategies requires autonomous agents.

How high can the degree of autonomy be?

  • Classic automation offers complete control.
  • IPA enables monitored autonomy.
  • AI agents act largely independently within defined framework conditions.

The governance requirements increase considerably as the degree of autonomy increases.

How much time & budget is available?

  • Classic automation can be implemented comparatively quickly and delivers the first measurable results within a few weeks to months.
  • IPA projects require a higher initial outlay for data integration and AI training, which means that the implementation phase takes several months.
  • AI agents are the most complex category – it typically takes 12-18 months or longer from conception, training and testing to productive use.

Are the basics ready?

Technical infrastructure, data quality, available expertise and readiness for change significantly determine the probability of success. Without these foundations, even technologically mature solutions will fail.

A critical self-analysis based on these dimensions prevents costly bad investments and unrealistic expectations.

Prerequisites for successful AI implementation

Successful AI projects are based on robust foundations that go far beyond technological aspects:

Data quality as a critical success factor

AI systems are only as good as the data they work with. Inconsistent, incomplete or low-quality data inevitably leads to suboptimal results. Systematic data cleansing and structuring is essential.

Technical infrastructure

API-enabled systems, clean interfaces and MLOps capabilities form the technical basis. Without this infrastructure, even the most sophisticated AI solution will be ineffective.

Organizational competence

A basic understanding of AI/ML mechanisms within the team is required. Not every project requires specialized data scientists, but a sound basic knowledge enables realistic assessments and effective management.

Governance and compliance

GDPR compliance, compliance with the AI Regulation and clarification of liability issues are not optional. Governance structures must be established from the outset, not added later.

Change management

Technological excellence does not guarantee success if the organization does not go along with it. Creating acceptance, building skills and constructively addressing resistance is crucial for sustainable effectiveness.

Before making significant investments in AI solutions, it is advisable to first systematically establish the organizational structures and technical requirements.

Conclusion: Technological sobriety as a success factor

The relevant question is not “How quickly can AI be introduced?”, but “Which solution addresses the problem most effectively?”

Contact us for a use case sparring session

We would be happy to help you find the right approach for your use cases and support you in building an AI-capable organization.

Whether classic automation, intelligent process automation (IPA) or autonomous AI agents:

The trick is to choose the right technology for the respective challenge and maturity level. Because not everything that is technically possible also brings real added value.

contact us

Our decision matrix helps:

AI decision matrix
download matrix (pdf)

From the introduction of RPA in customer communication to intelligent portfolio optimization, we support you pragmatically and effectively.

What we bring with us:

  • Process analysis with AI readiness assessment –not every process is ready for AI
  • Vendor-neutral advice –the most suitable solution for your goals
  • Pragmatic roadmaps – from quick win to strategic transformation
  • Change management –empowering and developing people
  • AI governance frameworks –integrating compliance right from the start

Do you want to find out what your AI potential is?

Then get started today and contact us for a free joint use case sparring session.

Contact us

Further topics

,

Process Mining and AI: Webinar I & II

to the article ➞

Self-services in digital banking

to the article ➞

, ,

FINMA Risk Monitor 2025

to the article ➞

, ,

Generative AI

to the article ➞

, ,

From cost pressure to the efficiency revolution

to the article ➞

,

Do I really need AI?

to the article ➞

,

Switzerland in the crosshairs of foreign intelligence services

to the article ➞

, ,

Resilience in our supply chains: How the shifting threatscape demands comprehensive security risk management

to the article ➞

,

UBS Data Leak via Chain IQ: Third Party Risk & Supply Chain Security Lessons

to the article ➞

,

Third Country Intercept: How secure is your data in the cloud?

to the article ➞

Der Beitrag Do I really need AI? erschien zuerst auf Pragmatica AG.

]]> Process management: target achievement or “New Year effect”? https://www.pragmatica.ch/en/prozess-management-target-achievement-or-new-year-effect/ Fri, 01 Mar 2024 11:59:06 +0000 https://www.pragmatica.ch/prozess-management-zielerreichung-oder-neujahrs-effekt/ Process management: target achievement or “New Year effect”? PROCESS MANAGEMENT Anything is possible at the beginning of the year. New resolutions and goals are set, motivation is high and the year is still long. But how do you ensure that it is a target achievement and not a “New Year effect”? The “New Year effect” […]

Der Beitrag Process management: target achievement or “New Year effect”? erschien zuerst auf Pragmatica AG.

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Process management: target achievement or "New Year effect"?

  • PROCESS MANAGEMENT

Anything is possible at the beginning of the year. New resolutions and goals are set, motivation is high and the year is still long. But how do you ensure that it is a target achievement and not a "New Year effect"?

The “New Year effect” can often be observed in fitness centers, where there are more people than usual at the beginning of the year. Why is that? If you’ve never had the intention to do more sport, here’s an insight: It takes more effort than expected, it requires discipline, the positive effect takes longer than desired, then motivation decreases, the positive effect takes even longer…

Objectives yes - but not without the status quo

Everyone decides for themselves who wants to achieve which goal – whether as a private individual or as a company. However, it is just as important to know where you stand now in order to achieve your goals. Am I just starting out with sport and want to win a half marathon or am I a marathon runner and want to achieve my new best performance this year?

The question of the goal and the current status is also important for companies. This gap determines how you set up your training/measurement plan. This gap also shows how intensive, comprehensive and disciplined you should be in order to achieve your goal.

Does your training/measurement plan match your goals?

Let’s take a look at the whole thing from the perspective of business process management (BPM): The corporate objective is defined and broken down into the various areas. Is the goal simply to achieve process transparency in an area because it is a regulatory requirement? The first stage of development may be sufficient. Many activities are basically not necessary. However, please note that you have laid the foundation with the process documentation in order to now analyze the processes for optimization potential. It would be a shame to miss out on this opportunity.

Illustration: Maturity in process management

Is continuous improvement largely established in your organization? Then congratulations on your achievement, then it is important to maintain your “fitness” in the organization.

You may also find yourself somewhere between these two examples. The aim of many companies is to increase efficiency. This is probably mentioned as often in the process environment as in the fitness center muscle building / weight loss.

What we can learn from fitness instructors

Depending on the goal definition, the fitness instructors will tell you right at the beginning that the desired goal cannot be achieved with 1-2 workouts per week. This immediate statement may dampen motivation, but it is honest and helps the person to set a realistic goal or adjust the measures and avoid a “new year effect”. This also applies to the process world. If the aim is to increase efficiency, but the processes are rarely systematically checked for improvement potential, it becomes difficult.

What do you want to achieve with process management?

Are you sufficiently positioned and equipped to achieve your goals? Use the overview and check your process goals and measures. We support you so that it is not a “New Year effect” but a goal achievement.

Would you like to find out more? Please get in touch with info@pragmatica.ch. We are happy to support you on your company-specific path.

Further topics

,

Process Mining and AI: Webinar I & II

to the article ➞

Self-services in digital banking

to the article ➞

, ,

FINMA Risk Monitor 2025

to the article ➞

, ,

Generative AI

to the article ➞

, ,

From cost pressure to the efficiency revolution

to the article ➞

,

Do I really need AI?

to the article ➞

,

Switzerland in the crosshairs of foreign intelligence services

to the article ➞

, ,

Resilience in our supply chains: How the shifting threatscape demands comprehensive security risk management

to the article ➞

,

UBS Data Leak via Chain IQ: Third Party Risk & Supply Chain Security Lessons

to the article ➞

,

Third Country Intercept: How secure is your data in the cloud?

to the article ➞

Der Beitrag Process management: target achievement or “New Year effect”? erschien zuerst auf Pragmatica AG.

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