This blog explains how Product Goals set strategic direction while OKRs make progress measurable through behaviour focused Key Results. It shows how both tools support evidence based decisions, prevent output driven thinking, and help Scrum Teams stay aligned, learn faster, and deliver value with clearer intent.

What will you get if you invest your time and money in learning AI?! Let's dissect it.

I'm sure you've all heard this one: If a tree falls in the woods and no one is around to hear it, does it make a sound? It seems to me that a lot of organizations lately have changed this question to: If you don’t track your work with a ticket, did it really happen?

Diferentes autores e abordagens falam sobre Product Operating Models de formas distintas, mas todos buscam resolver o mesmo desafio: conectar estratégia, times e aprendizado em ambientes complexos. Este artigo explora onde esses modelos convergem e por que ciclos de valor se tornaram um elemento essencial dessa discussão.

In diesem Artikel gibt PST Simon Flossmann 3 Gründe, warum Scrum Master sich zum Produkt-Coach entwickeln sollten

With your AI transformation, others perceive you differently in your professional network, which opens new doorways for you. But how?!

Stop asking 'Can AI do this?' Start asking 'Should AI do this?'

AI forces organizations to align machine speed with governance and funding. In doing so, it structurally closes Product Ownership's authority gap - distributed decisions, adaptive governance, and outcome funding become unavoidable.

Scrum doesn’t just define events—it places them *inside* a Sprint for a reason. The Sprint is the container that gives coherence, continuity, and consequence to inspection and adaptation. Without it, Scrum Events become disconnected conversations instead of a learning system.

In diesem Blog Artikel beschreibt Mark Rehberg, dass komplexe Probleme keine einfachen Lösungen haben. Scrum nimmt diese Komplexität nicht weg, sondern hilft dabei, sie sichtbar zu machen und Schritt für Schritt damit umzugehen. Scrum ist keine Abkürzung, sondern ein Werkzeug zum Lernen und zur kontinuierlichen Verbesserung.

RSGT2026にて、「EBM実践のカタ」として、エビデンスベースドマネジメント（EBM）を実践する際に気にかけるべき実践的な問いのカタを提案しました。ここではその詳細を解説します。

Teams across digital delivery keep running into the same ten traps, not through incompetence but through comforting untruths that quietly undermine performance. From believing more people will speed things up to treating roadmaps as commitments or assuming AI will magically fix dysfunction, these lies shape behaviour and slow progress. Real improvement starts with recognising the patterns, challenging convenient assumptions, and rebuilding product delivery on evidence, focus, and honest reflection.

Somewhere along the way, when "Agile Consultants" began rebranding the Scrum Master as exclusively a "Coach," the role became dangerously hands-off. The result? A generation of Scrum Masters who are disconnected from the reality of product development.

This case study examines through an Evidence-Based Management (EBM) lens what happens when teams operate on rebuilt technical foundations owned by their investor.

Learn how to gain entry-level Scrum Master experience, build credibility, and prove value without waiting for the job title in this latest post with PST Robb Pieper.

Temporary fixes are supposed to be temporary. That's why Technical Debt should be on the Product Owner's radar.

In my practice, I get the chance to talk to a lot of different individuals from many organizations. Here are some of the things that really stood out to me about 2025.

AI changes what work is visible. It does not change what matters in work.

In diesem Artikel fasst PST Simon Flossmann zusammen, was im Alltag für Scrum Master wirklich zählt.

AI is closing the Product Owner data gap by accident. Revenue accountability finally meets real-time access - but decision rights, funding, and governance still lag. Dashboards don't equal authority.

In vielen Unternehmen hängen die Werte und Prinzipien des Agilen Manifests (wenn überhaupt) irgendwo an der Wand – zwischen Vision-Statement und Kaffeeküche. Gelebt werden sie selten. Stattdessen wird Scrum eingeführt wie ein neues Prozesshandbuch: Meetings ersetzen Denken, Jira ersetzt Verantwortung, und „agil“ wird zur Ausrede für operative Hektik. Kundenfeedback? Zu aufwendig. Selbstorganisation? Zu riskant. Veränderung? Bitte erst nach dem nächsten Quartal. Was übrig bleibt, ist ein leeres Ritual: Scrum ohne Mut, ohne Vertrauen und ohne echtes Lernen. Nicht Scrum ist gescheitert – sondern der Wille, die agilen Prinzipien wirklich ernst zu nehmen. In diesem Artikel möchte ich beleuchten, warum die Agilen Prinzipien bei der Umsetzung von Scrum essentiell sind...

New Years is a time to pause and reflect - and that applies to Scrum Teams as well. So why not plan a New Years-themed Retrospective this year?

Government is losing digital talent not through lack of skill, but through pay structures that cannot compete with the private sector. Specialists leave, return as costly contractors, and capability drains away. Without market-aligned pay, consistent DDaT allowances, and smarter supplier use, government will keep renting back its own people.

Scrum talks about *adaptation*—but not the kind driven by opinions, pressure, or discomfort. True adaptation only happens after transparency and inspection. Without learning first, teams don’t adapt—they drift. This post challenges how Scrum Teams really use adaptation.

The Scrum Guide is short—but every word is packed with intent. In this series, we explore its language one post at a time, connecting each phrase to real-world professional Scrum practice. You’ll never look at “collective intelligence” or “relationships and interactions” the same way again.

This blog clarifies the distinction between Scrum Master accountability and the execution of Scrum Master activities, emphasizing that Scrum requires clear accountability but not a formal role or job title. It explains how mature Scrum Teams can delegate activities based on skills while preserving a single point of accountability and maintaining Scrum effectiveness.

Many organizations bought Microsoft Copilot and “turned it on” without changing how they actually work. In APOM terms, Copilot is stuck inside a project‑centric operating model. This post shows how treating “Copilot enablement” as a product with its own Agile Product Operating Model can turn licenses into real, measurable value.

Singapore ranks 4th globally in innovation, yet teams hesitate on experiments. The paradox? The system is pro-innovation, but individuals can't afford visible mistakes. Here's what research reveals about risk aversion and true agility in Singapore.

All the first steps you need to know to start your AI journey in product management.

In diesem Artikel erklärt PST Simon Flossmann, worauf es im Aufbau einer Online-Community ankommt.

If the same problems return Sprint after Sprint, something in the team’s learning is not working. Action Learning strengthens Scrum by turning inspection into disciplined learning and adaptation into deliberate action.

Product leaders own revenue, but many companies still run feature factories—leaving Product Owners accountable without the authority, data, or stable teams to deliver. Fixing it requires outcome-based governance and Evidence-Based Management measurement.

Muchos equipos Scrum miden su productividad en base a tareas terminadas, puntos de historia o cosas entregadas, y luego toman los promedios para establecer líneas base de productividad que impulsen métricas estandarizadas de control a cumplir, pero entonces: ¿Dónde queda el aprendizaje y la mejora continua? En este post exploramos formas de mejorar la capacidad de aprendizaje de los equipos Scrum.

In Scrum, inspection isn’t just “looking carefully.” It’s comparing reality to intent — the bold act of confronting what 'is' versus what 'should be.' Each Scrum Event offers that mirror moment, but only if teams dare to look without filters.

AIが多くの産業や市場を変革し続ける中、多くのチームが過度な期待、「不確実性」、そして「認知的過負荷」という『霧』の中で行き先を見失っています。「AIセンスメイキング」ワークショップは、確立されたセンスメイキングの原則に基づき、方向性を明確にすることで、この複雑性を乗り越えるための解決策を提供します。 このワークショップでは、チームが「次に何が起こりうるか」を共同で議論し、その結果に基づいて、変化への適応確率を最大化しつつリスクを低減するための行動を決定します。本記事では、AIが引き起こすディスラプションをナビゲートする方法を概説し、チームの対話と意思決定を円滑に進めるための具体的な手法を提案します。 （執筆：フォンテーヌ・グレゴリ／Scrum.org Professional Scrum Trainer）

As Artificial Intelligence reshapes the many industries and markets, many teams find themselves lost in a "fog" of hyper, uncertainty and cognitive overload. The "AI Sense Making" workshop offers a solution to navigate this complexity, drawing on established principles of sense-making to clarify direction. This workshop helps teams collectively discuss what might happen next. Based on that, they take actions to maximize chances of adapting successfully and reduces risk. This blog post outlines how to navigate the disruption caused by AI, and proposes a concrete way to facilitate team discussions and decision-making.

There’s an old expression, don’t gild the lily. It means to try not to over decorate something that’s already beautiful on its own. Sometimes I want to tell a Product Owner that I am working with not to gild the lily by overloading their requirements with solutions.

Scrum has helped teams embrace transparency, empiricism, and value delivery—but the same principles are urgently needed at the organizational level. As Ken Schwaber and Dave West remind us, honesty is a demanding yet essential capability, especially when applied to how we design and evolve our organizations. Our upcoming business novel, 10X ORG, explores this idea through the story of a leadership team uncovering the structural roots of their challenges—with a free preview available now.

Advanced Heat Map for Daily Banking: combining frequency and TCE‑based specificity to design economic boundaries of a product group, decide what to include, centralize or reconsider, and reduce coordination costs.

In diesem Artikel gibt PST Simon Flossmann Tipps, wie Scrum Master die PSM-III-Prüfung auf Anhieb schaffen können.

92% of organizations are increasing AI investment, yet only 1% achieve operational integration - not because of technology, but because they're running AI on industrial-age operating systems designed for stability, not evolution.

Eine User Story ist kein Mini-Pflichtenheft, sondern der Startpunkt für echte Zusammenarbeit. Ihr Wert entsteht nicht durch viele Worte, sondern durch Gespräche, Fragen und gemeinsames Verständnis. Warum weniger Schreiben oft zu besseren Ergebnissen führt, zeigt dieser Artikel.

The Scrum Guide uses “event” 24 times and “meeting” only twice. That’s not random. Scrum events aren’t meant for talking—they’re meant for changing. Learn how to make every Scrum event count.

A Definition of Done should protect the business, not just signal activity. In this blog, PST Robb Pieper explains how a product-level Definition of Done reduces risk, supports real integration, and builds trust in what teams call done.

Business Agility isn’t about speed. It’s about focus and alignment. And it’s what helps teams and organizations maximize ROI, reduce risk, and adapt effectively to change. In this article, we explore what keeps organizations stuck, the building blocks of business agility, and how to get there.

A step-by-step guide for Product Owners on using AI to precisely transfer feature specs to Developers.

In diesem Blog Post beschreibt Mark Rehberg die Missverständnisse die Scrum häufig verursacht. Viele Organisationen führen Scrum mit der Erwartung ein, dass damit automatisch Probleme verschwinden: ineffiziente Prozesse, schlechte Kommunikation, unklare Anforderungen oder unzufriedene Kunden. Wenn sich diese Hoffnungen nicht erfüllen, heißt es schnell: „Scrum funktioniert bei uns nicht.“ Über diesen "Denkfehler" geht es in diesem Artikel. Scrum ist kein Problemlöser. Scrum ist ein Problemanzeiger.

Government delivery keeps repeating the same mistakes because legacy decisions, compliance culture, and risk-averse governance trap teams in outdated cycles. These ghosts of past, present, and future drain value and slow change. Real progress needs adaptive funding, flexible commercial models, stable teams, and learning that actually sticks.

AI is repeating the same mistakes we saw in failed Agile transformations: hype-driven adoption, weak leadership ownership, and poor alignment. This time, the impact is bigger. The AI Strategy Canvas helps leaders take a mindful, problem-first approach and build AI strategies that create real, sustainable value.

One of the most powerful tools Agile leaders have is also one of the simplest: asking great questions. Great questions don’t tell people what to do. They spark thinking. They nudge teams toward self-management. They build confidence and create space for creativity and innovation.