BPM360 Podcast - Covering Every Angle

Drei BPM-Podcasts, ein Raum, ein Mikrofon: Live von der All About Process Management in Stuttgart ziehen die Hosts Bilanz zur Messe. Dann wird es grundsätzlich. Wird KI das Prozessmanagement überflüssig machen, oder erlebt BPM gerade sein größtes Revival? Die Runde ist sich einig: Prozesse waren nie wichtiger. Nur die Art, wie wir BPM betreiben, wird sich radikal ändern.In dieser FolgeKlassentreffen statt Frontalbeschallung: Was die Messe ausmacht: Workshops, Podiumsdiskussionen, ein Hackathon und viele kleine Anbieter mit frischen Ideen. Dazu eine bemerkenswerte Offenheit zwischen Beratungen, Tool-Herstellern und Wettbewerbern.Fehlt da nicht was? Wird die Messe ihrem Namen gerecht? Kritikpunkt: Ein richtiger Process-Mining-Anbieter fehlte in der Ausstellung.Alle Tools ringen mit KI: Bauen wir das Tool komplett neu oder erweitern wir es? Die Runde fragt, ob etablierte Anbieter, die nur an ihrem Bestand weiter iterieren, noch eine Daseinsberechtigung haben. Ihre Prognose: „Wir werden in den nächsten Jahren noch viele Kodaks sehen.“Was wird aus der Beratung? Wenn die Hälfte der Leute das Doppelte schafft: Wie positioniert man sich, wie stellt man Leistung in Rechnung, und welche Kompetenzen braucht es künftig? Ein Beispiel ist Governance für KI-Skills statt BPMN-Modellierungstraining.FOMO oder echter Shift? Viel Hype, aber auch echte Veränderung. Anforderungen lassen sich heute per Rapid Prototyping erheben statt in 100-seitigen Lastenheften. Ein Beispiel aus der Runde: ein Projekt mit drei Jahren Lastenheftphase.Teure Lektionen: Unternehmen bauen deterministische Prozesse mit KI-Agenten nach und wundern sich über sechs- bis siebenstellige Token-Rechnungen im Monat.Die Fachexperten schlagen zurück: Wer die Spezifikation beschreibt, erzeugt künftig die Lösung. Java wird zum neuen Assembler. Die entscheidenden Rollen werden zwei: der Fachexperte und der Architekt, der das große Ganze sieht.„Prozesse erlebbar machen“: Weg vom Dokumentieren und Abheften in der Klarsichthülle, hin zu Prozessen, die greifbar, sichtbar und messbar im Live-System stecken.Das Revival von BPM durch KI: Prozesswissen, Daten und vor allem Regeln wandern in ein Kontextmodell, also einen Knowledge Graph mit Prozessschritten, operativen Daten und Compliance-Vorgaben. SOPs, die früher nur abgezeichnet und abgelegt wurden, werden endlich nutzbar. Das Fazit der Runde: „Ohne Prozessinformation wird KI nicht fliegen. Punkt.“Ein Agent ist wie ein neuer Mitarbeiter: Er weiß nur, was du ihm gibst. Mit dokumentierten Regeln, Prozessen und Daten liefert er Gutes, ohne sie nur Unsinn.Klein anfangen, wo die Begeisterung ist: Erfolge zeigen, Neid erzeugen, von Push zu Pull kommen, und dabei immer das große Ganze im Blick behalten.Europa vs. Amerika: Langfristiger Qualitätsanspruch gegen „Go fast and break things“. Die Gefahr ist ein neues Daten-, Prozess- und Usability-Chaos durch schnell gebaute Insellösungen.Resilienz: Was passiert, wenn IT oder Energie ausfallen? Business Continuity Management rückt aus der Nische ins Zentrum.

In this live episode from the All About Process Management Conference in Stuttgart, Caspar and Russell welcome Sabine Kaul, Head of Integrated Process and Application Management at the German Cancer Research Center (DKFZ). Sabina shares her journey from administrative coordinator to leading process transformation across 3,500 employees at 20+ sites. She reveals the fundamental reality: 70-80% of critical work communication happens through email and attachments, not formal systems, because people choose the easiest tool available for getting things done.The hosts explore whether AI could mine email communications to extract process patterns that traditional process mining cannot capture—the coordination, decisions, and knowledge transfer happening outside formal systems. While GDPR constraints complicate this, the conversation highlights that digitalization's real challenge isn't technology but usability: when official tools aren't easy enough, people revert to email and spreadsheets as workarounds.Sabine shares DKFZ's innovative process landscape approach: an onboarding portal intentionally removing department names to force cross-functional thinking. HR, for example, appears across management, core scientific (PhD development), and support processes—revealing true organizational interdependencies. The landscape's greatest value is change management, creating awareness that processes exist whether documented or not.5 Key Takeaways:Email and spreadsheets dominate because people inherently choose the easiest tool available, making usability the critical factor in technology adoption.Process management in complex research organizations requires enterprise-wide transformation, not isolated departmental improvements.Process landscapes serve primarily as change management and onboarding tools, creating organizational awareness rather than just documentation.Effective landscapes remove department names to reveal cross-functional processes and true organizational interdependencies.AI could unlock valuable insights from email communications capturing coordination and decisions outside formal systems, if GDPR constraints were resolved.If you have suggestions or questions, please reach out to us via [email protected] you enjoy our content, please like, rate, subscribe… we do appreciate that…

In this dual-guest episode in German from the All About Process Management Conference in Stuttgart, Caspar and Russell welcome Sven Schnaegelberger (founder of BPM-O and AI startup leader) and Markus Wolf (co-founder of bpExperts). The conversation centers on how BPM consulting must transform beyond time-and-materials billing as AI reshapes the industry. Sven notes that while toolmakers have advanced substantially, they still face technical challenges embedding AI meaningfully. Crucially, process mining, modeling, and workflow disciplines are converging around "context"—fundamentally reshaping how BPM professionals deliver value.The hosts trace consulting's twenty-year evolution, revealing that pressure to shift to value-based models has long existed but consistently failed because customers lacked internal capacity for the prerequisite organizational changes. Consultants demanded full mandate; customers couldn't deliver. This impasse perpetuated traditional billing despite universal recognition of its inadequacy.Three forces now align to make value-based models viable. First, consultants must invest time in AI capability building and junior training—not just billable customer hours. Second, customers increasingly recognize AI requires value conversations ("What is this worth to our business?") rather than simple ROI calculations. Third, pioneering firms like Tanaka deliberately reject traditional licensing tiers, instead having genuine value dialogues with each customer about worth and impact. This shift toward ambiguity and collaboration, while initially disorienting to procurement departments, represents market maturation. The hosts conclude that industry-wide dialogue through conferences is essential for practitioners to share experiences and collectively imagine sustainable consulting models for the AI era, perhaps through consultant-only barcamps focused on business model evolution.Time-and-materials to value-based consulting becomes viable when consultants invest in AI capability building, not just billable hours to customers.Process mining, modeling, and workflow disciplines converge around context, fundamentally reshaping how BPM professionals create value.Customers and vendors must engage in genuine value dialogues about technology worth rather than relying on fixed pricing or guaranteed ROI.Consulting business models are evolving across billing structures, staffing approaches, and how professionals measure and account for their contributions.Industry-wide dialogue through conferences is essential for consultants to share experiences and collectively design sustainable models for the AI era.If you have suggestions or questions, please reach out to us via [email protected] you enjoy our content, please like, rate, subscribe… we do appreciate that…

In this fourth episode of their context mini-series, recorded live from the All About Process Management Conference in Stuttgart, Caspar and Russell explore performance baselines and anomalies as critical dimensions of process context for AI systems. They begin with a compelling analogy: in fully automated dark warehouses, there are two variants—hard-routed robots following predetermined paths (pure automation requiring no AI), and autonomous vehicles that must navigate unpredictable encounters with other vehicles (where AI becomes essential). The discussion reveals that AI's greatest value lies not in executing happy paths but in handling exceptions, deviations, and anomalies that cannot be fully predetermined with rules. Russell explains that while standardized processes aim for complete determinism with no choice, more flexible case-management-style processes require AI to provide intelligent orchestration when reality diverges from plan.Russell shares a powerful real-world example from his procurement optimization work: process mining revealed that 80% of purchase orders fell below 100 euros, yet every order incurred 35-115 euros in administrative costs. He proposed eliminating approval steps for purchases under 100 euros based on risk analysis—the savings would remove 80% of workload while jeopardizing only 1% of total spend. This exemplifies the crucial role of context: understanding what is normal (80% of orders are small), what threshold is acceptable (100 euros), what risk appetite exists (1% risk is tolerable), and what guardrails are appropriate (trust people at this level, use sampling checks). The conversation connects this to AI, asking: if we can risk-trust humans below a certain threshold, how far can we risk-trust AI with appropriate context and guidance?The episode concludes with a sobering discussion about the Hugging Face incident where an AI agent, when given the right prompt, was willing to hack into the system. This reveals a fundamental challenge: AI is trained on everything humans have created, including criminal behavior, deception, and manipulation—the entire Machiavelli playbook is in the training data. The hosts emphasize that providing context to AI isn't just about positive guidance toward desired outcomes; it must also include risk assessment around worst-case scenarios and clear guardrails that distinguish between trusted decision space and prohibited actions. This multidimensional approach to AI context—combining positive aspiration, risk tolerance boundaries, and explicit constraints—represents the real work ahead for organizations deploying AI.5 Key Takeaways:AI's greatest value is handling exceptions and anomalies that cannot be predetermined with rules—the happy path requires only traditional automation.Context must define normal performance baselines, acceptable thresholds, and risk tolerance to enable intelligent AI decision-making within appropriate boundaries.Risk-based approaches to process optimization reveal how much work can be eliminated by trusting people within defined thresholds; the same logic applies to AI.AI training data includes everything humans created, including criminal behavior and manipulation tactics, making it essential to provide explicit guardrails and prohibited actions.Effective AI context requires multidimensional guidance: positive aspiration for desired outcomes, realistic risk boundaries, and clear constraints on what AI should never attempt.If you have suggestions or questions, please reach out to us via [email protected] you enjoy our content, please like, rate, subscribe… we do appreciate that…

In this special guest episode, Caspar and Russell welcome Jonathan David Lewis, president of McKee Wallwork, a brand strategy firm specializing in marketing operations and organizational identity. Jonathan brings a unique lens to BPM and change management: that process adoption failures aren't fundamentally about bad processes or inadequate tools, but about a mismatch between the identity and story of the change leaders and the identity and stories of the people expected to adopt them. He reveals that BPM professionals are typically attracted to the ideals of efficiency, streamlining, and control—yet the people they're trying to change are often driven by entirely different narratives rooted in fear, shame, scarcity, or wrongness. Understanding these competing stories is the critical first step to designing adoption strategies that actually work.Jonathan introduces his framework of four limiting mental models that drive human behavior: fear ("something bad will happen"), shame ("I'm not good enough"), scarcity ("there isn't enough"), and wrongness ("something is wrong with me or this situation"). These stories operate beneath conscious awareness and shape how people respond to new processes, technologies, and organizational changes. He emphasizes that most adoption initiatives fail because they address the logical problem (the process or system) while ignoring the psychological and narrative foundations of resistance. Jonathan argues that we need to stop trying to remove suffering through perks and flexibility; instead, leaders must bring meaning to the suffering by framing organizational work as a relational quest—giving teams a sense of adventure, a clear enemy to defeat, treasure to gain, and people worth fighting for.The conversation explores how modern workplaces have eroded the tribal feeling and sense of meaningful purpose that characterized earlier decades of employment, replaced by transactional, futureless, and suffering-oriented work environments. Russell shares poignant examples of burnout driven not by workload but by disrespect for the meaning and identity people brought to their projects. Jonathan concludes with a powerful reframe: instead of operating in a hyper-efficient, dehumanizing AI era, leaders should actively reconstruct the story of work as relational rather than transactional, future-oriented rather than futureless, and meaningful rather than suffering—creating the conditions where humans can thrive alongside technology.5 Key Takeaways:Process adoption failures are fundamentally identity and story mismatches between change leaders and the people expected to adopt new processes.Most BPM professionals are attracted to efficiency and control, but frontline workers are driven by deeper narratives rooted in fear, shame, scarcity, or wrongness that technology alone cannot address.The four limiting mental models (fear, shame, scarcity, wrongness) operate beneath conscious awareness and shape how people resist or embrace organizational change initiatives.Leaders attempting change should not remove suffering through perks and flexibility, but rather bring meaning to suffering by framing work as a relational quest with clear purpose and human value.Rebuilding the story of work requires creating relational (not transactional), future-oriented (not futureless), and meaningful (not suffering) environments where humans can thrive, especially in the age of AI.If you have suggestions or questions, please reach out to us via [email protected] you enjoy our content, please like, rate, subscribe… we do appreciate that…