In this fast-paced world, we need Scrum more than ever. From the transparency created by artifacts to incremental delivery that keeps us on track, Scrum gives organizations a way to adapt and thrive. AI is a powerful tool, but instead of replacing Scrum, it makes the framework even more essential. Here are five reasons why Scrum is more relevant than ever.

Viele Meetings versanden in Konsensfloskeln statt in konkreten Vereinbarungen. Als Scrum Master kannst du das ändern: indem du vage Aussagen konsequent hinterfragst, kleine Schritte statt großer Lösungen priorisierst und mit einfachen Werkzeugen zu viel klareren Entscheidungen führst: Klartext statt Konsens!

In diesem Artikel teilt PST Simon Flossmann 3 Einsichten, wie er seine Liberating-Structures-Workshops in Zukunft verbessern wird.

AI is tremendously helpful in the hands of a skilled operator. It can accelerate research, generate insights, and support better decision-making. But here’s what the AI evangelists won’t tell you: it can be equally damaging when fundamental AI risks are ignored.

このブログでは、スクラムがプロダクトレッドグロース、マーケティングレッドグロース、セールスレッドグロースといった異なる成長戦略にどう適応するかを解説します。スクラムの基盤である「利用可能なインクリメントの提供」と「成果の検査と適応」は変わりませんが、価値の証拠、関わるステークホルダー、フィードバックループは成長モデルによって異なります。組織の戦略にスクラム実践をどう整合させ、効果と価値を最大化するかを学べます。

Many leaders I meet tell me the same story: “We’ve tried Agile. More than once. It never worked the way we were promised.” These conversations often lead to the bigger question of why Agile fails at scale—why the same methods that work well for small teams often break down when applied across an entire organisation.

One without the other? You’re either dreaming or gambling. Here’s how combining iterative and incremental turns Scrum into a value-delivery engine.

Organisationen scheinen bei ihrer KI-Transformation an denselben Mustern zu scheitern, an denen auch ihre agilen Transformationen gescheitert sind.

Is your Scrum team just going through the motions of Scrum without using it to focus on continuous improvement? Then coach the "fluffy" Scrum values to help turn them into a team focused on value.

Sometimes Scrum gets a bad rap. When I ask why an organization struggled with Scrum, I almost always hear something like “there was too much overhead.” But when I dig deeper, I usually find that the organization had imposed extra rules—rules that have nothing to do with Scrum. In other words, when Scrum “doesn’t work,” it’s almost always because the team wasn’t actually using Scrum well.

Wanting to collaborate better, gain control over an overloaded annual plan, increase job satisfaction and, in turn, reduce staff turnover: these are challenges almost every organization in every sector faces. However, the cultural industry differs significantly from the business world. It has its own unique challenges, working methods, and goals. That’s why Curious Culture, together with Scrum Facilitators, developed a two-day Professional Scrum Master training specifically tailored to the cultural sector. We spoke with Ziryan Salayi, owner of Scrum Facilitators, about what Scrum is and why it can be so effective for organizations in the artistic field.

AI Agents can take over repetitive tasks to free up our time for strategic work. However, we should learn what it is, how it works, and how we can build them. This blog shows you the starting step.

Many Scrum Teams fall into the trap of assuming there will always be another Sprint. This mindset leads to delay, complacency, and missed opportunities. Treating each Sprint like it could be your last helps teams focus on outcomes, improve continuously, and deliver real value, while they still can.

In Scrum, one of the most common misunderstandings is the difference between the Definition of Done and Acceptance Criteria. In this blog, PST Robert Pieper explains the key differences and how your team can avoid confusion.

The secret to a high-performing team lies not just in its processes, but in the ability to understand each individual. During a recent Professional Scrum Master training, we were introduced to a powerful concept from Process Communication®: the Energizer/Rebel personality type. This profile is a game-changer for team dynamics. When well-supported, these individuals are a true catalyst for collaboration and innovation. Their humor, spontaneity, and creative energy can significantly boost an entire team's engagement. However, if not properly guided, their strong personalities can also disrupt a group’s balance. For managers and Scrum Masters, understanding this profile is a unique opportunity to: Boost engagement and initiative Empower the team toward self-management Strengthen collective agility Discover how taking personality styles into account can transform your team's performance and help you fulfill the core responsibilities of a Scrum Master.

This blog explores how Scrum adapts across different growth strategies — Product-Led, Marketing-Led, and Sales-Led. While Scrum’s foundation of delivering usable increments and inspecting outcomes remains the same, the evidence of value, stakeholders, and feedback loops shift depending on the growth model. Readers will learn how to align Scrum practices with their organization’s strategy to maximize effectiveness and value.

There’s no shortage of training and frameworks on decision-making, prioritization, or time management. But what if the real issue lies elsewhere? What if the challenge is not a lack of knowledge, but a cognitively overloaded leader? This article, based on a workshop I delivered to the Agile community in 2025, explores how leaders make decisions under pressure and how they can approach it differently. The topic fascinates me, and leadership happens to be my daily work.

Even in 2025, the difference between the Product Owner and Product Manager is misunderstood. Is it a career path? Is the PM a step up from the PO? Are they the same? This article puts this discussion to bed in an easy and straightforward way.

In diesem Artikel beschreibt PST Simon Flossmann, wie sich Liefertermin einhalten lassen.

Why Today’s Failures Look Uncannily Like Yesterday’s “Agile Transformations,” Or: Why This Time Won’t Be Different Either.

Across industries, teams are experimenting with Copilot, GPT, and automation. The result? Local productivity gains. But the big initiatives that matter for customers and strategy still stall. Why? The existing org design is not AI-ready and limits performance.

This AI-generated video shows you how far you can go with AI to step into a new level of productivity. So, learn and leverage it.

Scrum’s lean thinking isn’t about doing *everything* faster—it’s about focusing only on what truly matters. Learn how to cut through backlog bloat, process clutter, and competing priorities so your team’s energy fuels real outcomes, not busywork.

Scrum is all about creating a Done increment that generates value for its users. However, you might come across teams that do almost everything in the name of Scrum except creating a Done Increment. Spillovers almost every Sprint. Sprint Goals not achieved, at times they are not even defined.

One of the key aspects of Scrum is that each Sprint should result in a Done, usable increment of product. But what happens if your team struggles to achieve this? Here are ten practical ideas that your team may consider adopting to help improve your ability to get to Done.

AI is reshaping product management, and Product Owners can no longer ignore it. Building on the six preferred stances, the Orchestrator emerges as a seventh stance: treating AI as a digital colleague that automates repetitive tasks, reduces cognitive load, and frees time for strategy, vision, and customer value. Far from replacing judgment, AI amplifies the Product Owner’s impact across all stances — from Visionary to Influencer. Adopting this mindset shift allows Product Owners to focus on what matters most: delivering value with clarity and intent.

Discover the two critical decision types—One-Way and Two-Way Doors—that can transform how you tackle decision paralysis in agile teams. Packed with practical tips, coaching questions, and insights into empirical product development, this article from Pawel Rola empowers Product Owners and other Scrum professionals to drive innovation and agility.

In diesem Artikel erklärt PST Simon Flossmann, wie er 3 typische Probleme in hybriden Meetings löst

Digital.ai releases an annual 'State of Agile' report which I am eagerly anticipating. While I wait for the 18th report to be released, I want to take a moment to look at how we have talked about Agile has changed over time.

Many confuse operating models with organization design. Operating models, as defined by Jeanne W. Ross focus on daily operations, resources, governance, planning, performance but are too narrow to shape the whole org-design. Organization design, shown in the Star Model by Jay Galbraith, aligns strategy, structure, processes, rewards, and people. Confusing the two causes local fixes without systemic change — and culture quickly eats strategy when the system stays the same.

Waste hides in “the way we’ve always done it.” In Scrum, Lean thinking is about spotting waste—whether it’s defects, overproduction, bloated backlogs, or wasted talent—and making it smaller, less important, or gone. Here’s how to see it, reduce it, and free your team’s focus.

Mixing SAFe and LeSS inside one product does not work. LeSS is not just a framework but a full organizational design that demands deep structural change. This article explains why SAFe and LeSS conflict and when it is possible to pilot both in the same company.

A modern, agile approach to transforming legacy software, which is often too risky for a complete rewrite is possible. The strategy combines three key elements: the Strangler Fig Pattern, an incremental method of building new services around an old system; AI-powered code generation tools like Blitzy and Claude, which automate the bulk of the coding work; and the Scrum framework, which provides the framework for managing this complex, iterative process. I emphasize that this approach not only mitigates risk but also redefines feedback loops in product development, turning them into a source of creative input and personal growth rather than just criticism.

Pricing is a hypothesis about value, willingness-to-pay, and customer behavior. In this blog, we explore TAP’s pricing formula and show how Scrum Teams can run lightweight experiments, fake doors, A/B tests, and packaging trials, to validate pricing early. Treating pricing like backlog items ensures empiricism guides not only what we build, but also how we sustain value.

Warum agile Praktiker perfekt für das KI-Zeitalter aufgestellt sind.

This blog post introduces a survey about the Agile Product Operating Model (APOM). Dave West explains that Scrum.org is investing in APOM due to challenges organizations face with Product Ownership and the limitations of project-based approaches for managing digital assets. Many organizations, despite calling themselves "product organizations," still operate within a project culture, leading to misaligned and disempowered product teams. APOM aims to provide a unified set of ideas, bringing together Scrum, Nexus, EBM, and modern product thinking to help organizations align, fund, and operate their "products" more effectively. The author emphasizes that APOM is not a prescriptive methodology but a framework of ideas that organizations must adapt to their own context, and encourages participation in the survey to further develop this body of knowledge.

Defining product in Scrum is a fundamental choice. A narrow scope gives focus but risks local optimization. A broad scope brings adaptability and customer-centricity but may blur priorities and vision. The right balance turns Scrum into a true driver of business transformation.

アジャイルマニフェストの最初の一文――「私たちは、ソフトウェア開発の実践、あるいは実践を手助けをする活動を通じて、よりよい開発方法を見つけだそうとしている」――は、しばしば見過ごされがちですが、その核心には謙虚さと好奇心があります。「アジャイル開発」は完成したレシピではなく、探求のマインドセットです。今日、多くの組織は「ベストプラクティス」に固執し、フレームワークを固定化してしまいます。しかし、複雑な課題に必要なのは経験主義――仮説を立て、実験し、振り返り、次を決めることです。実際に、スクラムを一時的にやめてみたチームが「スプリントゴールの価値」を再発見した事例や、製薬会社の部門が小規模チーム構造を試し、効果を確認した事例があります。アジャイルは、組織運営においても継続的な実験と改善を求めています。

The first line of the Agile Manifesto—“We are uncovering better ways of developing software by doing it and helping others do it”—captures the humility and curiosity of its authors, yet it is often overlooked. Agile was born as a mindset of exploration, not a recipe of fixed practices. Today, many organizations confuse “good practices” with “best practices,” clinging to frameworks like Scrum, SAFe, or the “Spotify model” instead of running experiments to discover better ways of working. Complex problems such as delivering customer value or organizing teams require empiricism: forming hypotheses, running experiments, reflecting, and deciding what to do next. Two real-world stories illustrate this—one where a team paused Scrum to test Kanban and rediscovered the power of Sprint Goals, and another where a pharmaceutical department experimented with temporary small teams and learned that size and structure matter. Organizations thrive when they embrace curiosity, empiricism, and continuous experimentation.

The belief that working in parallel through silos is efficient is a myth. It doesn’t speed things up; it throws up walls between teams and creates a tangle of dependencies, misaligned priorities, and extra overhead.

In the world of Product Development, there are only two big problems which need to be solved: Are we building the right product? Are we building the product right? There are many approaches that help the developers to build the product in the right way, enabling great quality. However, building the Right Product is often challenging because it is not an issue of capability or technology but more often it is an issue that stems from a lack of understanding or working with assumptions.

In diesem Artikel beschreibt PST Simon Flossmann, wie du in 5 Schritten Scrum Master werden kannst.

Why Knowledgeable Agile Practitioners Are Perfectly Positioned for the AI Era and the Era of ‘Good Enough’ Agile Is Over.

From initial conception through post-launch phases, product managers are responsible for customer research, feature development, and overall product strategy. Think of them as the ultimate jack-of-all-trades in the business world who oversee the entire lifecycle of a product. 

One practice from Kanban that I think is often overlooked is related to the flow of work. Work on the Scrum board should flow from left to right - but it shouldn't flow backwards.

Definir un producto es central a la mentalidad de producto. Hay muchos aspectos a considerar, como la visión de producto, objetivos de producto, métricas, modelos de negocio, entre otros. El siguiente canvas es una idea de cómo enfocar la definición de producto.

The Scrum Guide urges teams to base decisions on what is observed. But what does that look like in real teams, with real complexity? Let’s unpack the word and its impact.

Every product begins with a spark: a frustration, a market gap, or even an accident. But sparks aren’t finished products; they’re hypotheses waiting to be tested. In The Anatomy of a Product, we call this the Spark of Life: the messy, human moment that reveals a problem worth exploring. Scrum gives us the perfect framework to nurture sparks responsibly: observe before you build, frame the problem clearly, and prototype to learn. Not every spark will grow into a product, but every product begins with one.

A Scrum Team thrives when every voice is heard. Facilitators and Scrum Masters play a vital role in making space for quieter team members. With intention and a few well-tested techniques, we can shift the dynamic and bring more perspectives into the conversation. Sometimes the quietest voice in the room has the most important insight. From using silent writing and Liberating Structures to creating psychological safety and embracing silence, these ten approaches empower facilitators to create inclusive environments where all voices are heard. These strategies can help bring forward valuable perspectives that might otherwise go unnoticed, whether you're working with a reflective thinker or someone hesitant to share.

Verwenden Sie keine LLMs mehr für Probleme, die korrekte, reproduzierbare Antworten erfordern; KI liefert weder die erforderliche Genauigkeit noch die Reproduzierbarkeit.