The Agile Enterprise

Introduction

The concept of an Agile Enterprise was defined in 1991 as a recognition that Lean Six Sigma would be unable to meet the demands of the 21st-century markets. A decade later, the Manifesto for Agile Software Development introduced the approach to build software applications: “uncovering new ways by doing it and helping others to do it”. Unlike the Enterprise version of Agile Manufacturing, the software version of Agile had a limited understanding of risk and risk management. Risk was perceived as a negative aspect of product development and Agile as a way to minimise or even eliminate them. Twenty-five years later, Agile teams and practices matured, and risk management had become a hot topic among Agile practitioners and enterprise leaders.  Project Management professionals are curious to know how Risk Management evolved in Agile and Enterprise Agile contexts. Is the traditional risk register obsolete? How do teams handle enterprise-level risks?

In principle, according to the Agile mindset, Risk Management in Agile environments should be more continuous, visible, and integrated with delivery than in traditional, document-heavy processes. There is also growing recognition among Agile Teams that Risk Management is not just about avoiding threats, but also about surfacing and seizing opportunities. This blog post explores the unique challenges of risk management in agile enterprises and provides practical recommendations.

Challenges

From Periodic to Continuous Risk Management

Traditionally, Risk Management in large Enterprises has meant maintaining a risk register, reviewing it at set intervals, and producing compliance documentation. Agile ways of working, however, move at a much faster cadence. Teams operate in short Sprints, priorities shift frequently, and feedback loops are tight. This creates tension: how do you maintain meaningful risk oversight without slowing down delivery?

The Risk Register Debate

Forum debates often centre on the role of the risk register. Some argue it is an outdated artifact, while others say it remains useful if it is kept current and directly informs decisions. The consensus is that static, forgotten registers are useless, but evolving, transparent ones can add real value—especially when risks are actively linked to backlog items, sprint reviews, and product increments.

Handling Enterprise-Level Risks

Agile teams are empowered but often have limited boundaries and decision power beyond the scope of their work. What should they do when they identify risks that affect the wider enterprise? Traditional project managers recommend clear escalation paths, portfolio-level reviews, and coordination mechanisms. Systemic risks—cybersecurity threats, regulatory changes, supply chain vulnerabilities—require visibility beyond the team. Without an enterprise view, critical risks can go unmanaged.

Balancing Iterative Planning and Governance

Iterative planning is a core agile principle, but it can seem at odds with formal risk governance, which is usually periodic and structured. Forum users ask: How do we reconcile the need for lightweight, adaptive risk management at the team level with the demands for stronger oversight where the stakes are higher? The answer is nuanced: combine flexible team practices with robust enterprise controls for high-impact risks.

Ethical Challenges: Transparency and Optimism Bias

The PMI Code of Ethics and Professional Conduct stresses honesty, responsibility, and fairness. In practice, Agile teams sometimes fall prey to optimism bias—underestimating risks or failing to surface bad news. Ethical risk management means surfacing risks honestly, even when uncomfortable, and making trade-offs explicit. Leaders must foster a culture where risk is discussed openly, and risk appetite is clear.

Recommendations

Make Risk Management Continuous and Visible

Shift from periodic, document-driven risk reviews to continuous, collaborative risk management. Use agile ceremonies—like sprint planning, stand-ups, and reviews—to discuss risks and opportunities regularly. Tools like lightweight risk boards or digital dashboards can help teams visualise risks in real time, making them part of everyday work.

Keep Risk Registers Dynamic and Actionable

Don’t abandon the risk register, but evolve it. Link risks directly to user stories, features, and product increments. Update risks as work progresses, and make sure mitigation actions are visible and assigned. The risk register is most useful when it is a living document, continuously referenced and adapted. Change its name to ‘risk log’ to indicate that it is a new artefact, and it will be managed differently: by the team, continuously and in conjunction with the product backlog items.

Establish Clear Escalation and Coordination Mechanisms

Teams should have clear paths for escalating risks beyond their scope. Regular portfolio or program-level reviews help identify systemic risks and coordinate responses. Project, portfolio and program standards emphasise the importance of enterprise-level risk identification and response networks that enable rapid, cross-team communication and mitigation.

Integrate Opportunity Management

Risk is not just about threats. Agile enterprises should also manage opportunities—positive risks that can be exploited. During planning and reviews, ask not just “What could go wrong?” but also “What could go right?” This mindset encourages innovation and proactive value creation.

Combine Lightweight Team Practices with Stronger Enterprise Oversight

For everyday delivery, Agile teams should use lightweight risk tools and practices. For high-impact risks (regulatory, financial, reputational), enterprise-level governance is essential. This dual approach combines the best of both worlds: nimble team execution and robust oversight where it matters most.

Foster a Culture of Honesty and Transparency

The PMI Code of Ethics and project management standards remind us that effective risk management is grounded in honesty, transparency, and open communication. Leaders should model these values, encourage surfacing of risks, and make risk appetite and tolerance levels explicit. This helps teams understand boundaries and make informed trade-offs.

Leverage Agile Feedback Loops to Reduce Uncertainty

Agile’s rapid feedback cycles—through reviews, testing, demos, and customer engagement—allow risks to be identified and mitigated earlier. Use these cycles intentionally: treat each feedback opportunity as a chance to surface uncertainty, validate assumptions, and adjust course quickly.

The Bottom Line

Risk Management in Agile Enterprises is fundamentally different from traditional approaches. It is more continuous, visible, and integrated with day-to-day delivery. The most successful Agile Enterprises treat Risk Management as a proactive, embedded practice that combines flexible team execution with strong enterprise oversight. Transparency, honest communication, and a willingness to adapt are essential. Agility improves risk response only if transparency and escalation mechanisms are strong. The ultimate goal is not just to avoid threats, but to actively manage uncertainty and seize opportunities for value creation.

Questions for Readers

1. How does your organisation balance lightweight team risk practices with enterprise-level oversight?
2. What tools or ceremonies have you found most effective for making risk management continuous and visible?
3. How do you ensure that risk appetite and tolerance are clearly communicated across your teams?

Introduction

Agile methodologies have changed, some would say revolutionized, the way product teams collaborate, adapt, and deliver value. At the heart of Agile software development, and in recent years of Agile project delivery, is the belief in empowered individuals, cross-functional teams, and a culture of continuous improvement. However, as Artificial Intelligence (AI) permeates Agile environments—automating roles, analysing workflows, and even facilitating Scrum ceremonies—it may fundamentally alter the human experience in work environments. This blog post explores the nuanced impact of AI on human roles and team dynamics within Agile delivery environments, drawing on principles from the PMI Code of Ethics and Professional Conduct, insights from thought leaders like Ron Jeffries, research articles published on ResearchGate.net, and risk management standards to frame risk management in the evolving landscape of Agile product and project delivery.

Challenges

Dehumanization of Agile Roles Due to AI Automation

The Manifesto for Agile Software Development recommends “individuals and interactions over processes and tools.” Yet, as AI systems take on tasks such as Product Backlog prioritization, Sprint planning, and performance tracking, there’s a risk that team members become seen as interchangeable resources rather than unique contributors. Ron Jeffries, one of the original signatories of the Agile Manifesto, warns against reducing people to “cogs in a machine.” The PMI Code of Ethics emphasizes respect, fairness, and honesty—qualities that can be undermined if automation strips away human judgment and empathy from Agile roles.

Dehumanization occurs when the unique contributions, intuition, and creativity of team members are overshadowed by algorithmic decision-making. Paul Kidd, the author of the first book that introduced the term Agile in relation to product development, notes that organizations must guard against “the tyranny of systems that erode the value of human insight.”

Impact of AI on Scrum Master Responsibilities

Scrum Masters are facilitators, coaches, and guardians of Agile values. With AI-driven analytics and automated workflow tools, some Scrum Master duties—such as tracking team metrics, scheduling ceremonies, and even identifying impediments—are increasingly automated. While this can free up time for higher-value activities, it may also diminish the perceived importance of the Scrum Master’s human-centric skills: conflict resolution, team motivation, and fostering psychological safety.

Research highlights the risk that automation can lead to a “checklist mentality,” where the focus shifts from servant leadership to process compliance. The PMI Code of Ethics urges professionals to “act with integrity and professionalism,” reminding us that technical efficiency should not overshadow the human aspects of leadership.

Job Displacement Concerns in Agile Teams

AI technologies promise increased productivity and efficiency, but they also raise legitimate concerns about job displacement within Agile teams. Automation of tasks like testing, documentation, and even code generation can make some roles redundant or require significant upskilling. Risk Management frameworks mandate that organizations must identify and manage risks—including those related to workforce morale and skills obsolescence.

“The 21st Century Manufacturing Enterprise Strategy” report published by the Agile Manufacturing Enterprise Forum in 1991 warned that while AI can augment human capabilities, organizations must be proactive in reskilling and redeploying talent. Scientific Agile emphasizes that “change must be managed, not endured.” Open dialogue and transparent organisational change management are essential to maintain trust and engagement.

Over-reliance on AI Diminishes Team Creativity in Agile Projects

Agile thrives on experimentation, adaptation, and collective problem-solving. Over-reliance on AI can stifle creativity and discourage the kind of divergent thinking that leads to breakthrough solutions. Ron Jeffries, co-author of Extreme Programming, argues that teams must “retain agency and the capacity for surprise,” while Rick Dove, one of the Agile Manufacturing Forum experts, warns that “automation should enhance, not replace, human creativity.”

When AI dictates too much of the process, teams may become risk-averse or overly dependent on recommendations generated by algorithms. The PMI Code of Ethics calls for “respect for the individual,” which includes honouring diverse perspectives and fostering an environment where creativity can flourish.

Recommendations

Preserve Human Dignity and Agency

Adhere to the PMI Code of Ethics and Professional Conduct by ensuring that AI tools support, rather than supplant, human judgment. Involve team members in decisions about automation and maintain transparency about how AI is used.

Redefine the Scrum Master Role

Emphasize the uniquely human aspects of Scrum Master responsibilities: coaching, mentoring, and safeguarding team culture. Leverage AI for routine tasks but keep the focus on emotional intelligence and servant leadership.

Proactive Reskilling and Career Development

Use risk management tools to assess the impact of AI on roles and identify opportunities for upskilling. Partner with employees to create personalized development plans that align with evolving business needs.

Foster a Culture of Creativity and Experimentation

Balance automation with practices that encourage creative thinking, such as regular retrospectives, cross-functional collaboration, and spikes and “innovation sprints.” Draw on Ron Jeffries’ advice to “make room for surprise and delight.”

Transparent Communication and Change Management

Communicate openly about the benefits and limitations of AI. Address concerns about job security honestly and involve teams in shaping the future of work.

The Bottom Line

AI is reshaping Agile team dynamics and redefining human roles in profound ways. While automation offers opportunities for increased efficiency and data-driven decision-making, it also introduces significant challenges: dehumanization of roles, shifting Scrum Master responsibilities, job displacement worries, and the risk of dampening creativity. By grounding our approach in ethical principles (PMI Code of Ethics and Professional Conduct), thought leadership, and robust risk management frameworks (PMI Risk Management Standard, ISO 31000), organizations can harness the power of AI without losing sight of what makes Agile teams truly exceptional—their humanity.

This blog post is intended to spark conversation, challenge assumptions, and help Agile and project management practitioners navigate the intersection of human values and technological progress.

Questions for Readers

1. In what ways has AI changed the dynamics of your Agile team, for better or worse?
2. How can organizations ensure that automation enhances rather than erodes team creativity and morale?
3. What steps would you recommend to balance the benefits of AI with the need to preserve meaningful human roles in Agile environments?

Introduction

The pace of industrial change today is breathtaking. Globalization, digital disruption, and shifting customer expectations have forced organizations to question nearly every aspect of how they operate. For decades, Lean Six Sigma (LSS) was the gold standard for process improvement and operational excellence. Yet, in the age of rapid innovation and market Agility, critics now ask: Is Lean Six Sigma too slow and rigid for modern industries? Are its principles outdated in a world shaped by the demands of Agility?

This debate is not new, but its urgency is growing. In fact, the roots of this discussion stretch back to the early 1990s, when the Agile Manufacturing Forum—collaborating with Lehigh University—published the influential "21st Century Manufacturing Enterprise Strategy." Their vision called for companies that could rapidly adapt and reconfigure themselves, prioritizing flexibility and speed over rigid process adherence. Today, as organizations grapple with digital transformation, this vision is more relevant—and contested—than ever.

Challenges: LSS in a Rapidly Shifting World

The Problem of Speed

Lean Six Sigma’s backbone is the DMAIC (Define, Measure, Analyse, Improve, Control) methodology. It demands careful measurement, rigorous root-cause analysis, and methodical improvement cycles. While this approach has delivered billions in savings and quality improvements, its pace can seem glacial compared to the iterative, experimental cycles of Agile methodologies. In fast-moving industries—like tech, consumer electronics, and even advanced manufacturing—months-long Lean Six Sigma projects may miss the window of opportunity, while agile teams launch, learn, and pivot in real time.

Forum Debates and Historical Parallels

The Agile Manufacturing Forum, which helped shape the "21st Century Manufacturing Enterprise Strategy," envisioned companies that could form and reform teams, build partnerships on the fly, and rapidly adopt new technologies. Their call for Agility was a direct response to the era’s economic uncertainty and technological disruption. Now, online forums echo similar concerns: Does Lean Six Sigma’s structure help or hinder in this new world?

Forum participants share stories of Lean Six Sigma projects that delivered impressive results—eventually. However, they also recount missed opportunities. One engineer posted, "We spent so much time on measurement and analysis that a competitor launched a new product line while we were still in the ‘Define’ phase."

Complexities in Modern Enterprises

The 21st Century Manufacturing Enterprise Strategy recognized that manufacturing would shift from mass production to mass customization, requiring unprecedented flexibility. Today, organizations face even more complexity: supply chain volatility, workforce shifts, and relentless technological change. In this context, Lean Six Sigma’s methodical pace is sometimes seen as a liability, especially when customers expect instant responses and markets change overnight.

Regulatory and Quality Demands

Not all industries can afford to abandon rigor. In pharmaceuticals, aerospace, and automotive, regulatory requirements and safety concerns demand the discipline Lean Six Sigma provides. The challenge, then, is not simply about speed versus quality, but about finding a balance appropriate to each context.

Recommendations: Navigating the New Landscape

Embrace Hybrid Approaches

The wisdom emerging from both historical and current debates is clear: Agility and discipline are not mutually exclusive. The most successful organizations blend the best of both worlds. For example, teams can use Lean Six Sigma’s data-driven root-cause analysis within Sprints, applying just-in-time documentation and focusing on the most critical metrics. The result is a more responsive, learning-oriented improvement culture.

Revisit the 21st Century Manufacturing Vision

The 1991 strategy emphasized cross-functional collaboration, networked partnerships, and rapid information flow. Modern organizations should take inspiration from this vision by breaking down silos and empowering multidisciplinary teams. Rather than forcing every improvement project into a traditional Lean Six Sigma mold, leaders can encourage experimentation, rapid prototyping, and the sharing of lessons learned in real time.

Rethink Metrics and Success

Process improvement should not be an end in itself. The goal is to create value for customers and stakeholders. Organizations should continuously ask: Are our process improvement efforts helping us move faster, deliver better quality, and meet changing needs? If not, it may be time to modify or blend methodologies.

Invest in Skills and Mindset

The 21st Century Manufacturing Enterprise Strategy warned that technology alone would not create Agile Enterprises—people and culture matter most. Organizations should invest in developing both process improvement expertise and agile mindsets. Training, coaching, and leadership support are key to enabling teams to navigate uncertainty and change.

The Bottom Line

Lean Six Sigma is not dead, but it must evolve to stay relevant. The lessons of the Agile Manufacturing Forum and the 21st Century Manufacturing Enterprise Strategy are more vital than ever: Flexibility, speed, and cross-functional collaboration are essential for success in the 21st century. As organizations confront the challenges of rapid change, those that blend the discipline of Lean Six Sigma with the adaptability of agile will lead the way.

The future of process improvement is not a binary choice. It is a dynamic, context-driven journey—one that honours the rigor of the past while embracing the possibilities of the future.

Questions for Readers

• In your experience, can Lean Six Sigma and Agile coexist effectively in a single organization, or do they inevitably clash?
• How has your organization adapted its process improvement strategies to keep pace with rapid change?
• What lessons from the 21st Century Manufacturing Enterprise Strategy do you think are most relevant today?

Introduction

Agile transformation is a journey that many organisations undertake to become more adaptive, responsive, and efficient in delivering value to their customers. However, a common pitfall is to rush into changing team frameworks, such as adopting Scrum, without first understanding the current flow of work and information. Value Stream Mapping (VSM) is a powerful tool that enables organisations to trace the end-to-end flow of information and materials, illuminating bottlenecks, delays, and inefficiencies. By leveraging VSM before altering team structures, organisations can ensure that their Agile transformation leads to meaningful, sustainable improvements.

This blog post explores the critical role of VSM in Agile transformation, common challenges organisations face, key recommendations for implementing VSM effectively, and actionable insights to drive organisational efficiency.

Challenges

Agile transformation often promises faster delivery, higher quality, and happier teams. Yet, many organisations encounter significant roadblocks when shifting to Agile frameworks. Here are some common challenges:

Focusing on Frameworks Overflow

Organisations frequently leap into new team structures and ceremonies without first understanding their existing processes. This approach can inadvertently replicate old inefficiencies in a new format, leading to frustration and minimal gains.

Siloed Information and Fragmented Processes

As organisations grow, silos can develop between departments, teams, or functions. These silos hinder the smooth flow of information, causing delays, miscommunication, and rework. Without a clear view of how information travels through the organisation, it’s difficult to identify the true sources of waste.

Invisible Bottlenecks and Waste

Bottlenecks in processes are often hidden from view, buried in handoffs, approvals, or outdated workflows. Waste accumulates in the form of waiting, unnecessary steps, or redundant activities—none of which are easily spotted without a holistic perspective.

Resistance to Change

People are naturally resistant to change, especially when the rationale behind new frameworks or processes is unclear. Without data to support the need for change, transformation efforts may face scepticism or passive resistance.

Measuring the Wrong Metrics

Traditional metrics, such as output volume or utilisation rates, may not align with actual value delivery. Focusing on these can drive the wrong behaviours and mask underlying issues that impede true agility.

Recommendations

To ensure a successful Agile transformation, it is essential to first understand how value flows through your organisation. Here’s how Value Stream Mapping can help—and how to get started:

Map Before You Move

Before restructuring teams or adopting new frameworks, invest time in creating a value stream map. Involve representatives from across the organisation to capture the full journey of a product or service, from initial request to delivery.

Involve the Right People

VSM is most effective when it includes stakeholders from every part of the value stream. This includes business analysts, developers, testers, operations, and even customers when possible. Their insights will help create an accurate map and foster buy-in for future changes.

Visualise the Current State

Start by documenting the current state of your value stream. Identify every step, from idea inception to customer delivery. Capture the time, resources, and systems involved at each point, as well as any handoffs or delays.

Identify Bottlenecks and Waste

Use your current state map to pinpoint bottlenecks, excessive handoffs, duplicated work, and non-value-adding activities. Quantify the impact of each and prioritise them based on their effect on flow and customer value.

Design the Future State

Once you understand where inefficiencies exist, design a future state map that eliminates or reduces these issues. Consider how new team structures, automated processes, or improved communication can streamline flow.

Make Incremental Changes

Rather than overhauling everything at once, use your maps to guide incremental, data-driven changes. Pilot new processes with a small team or product, learn from the results, and scale successful changes across the organisation.

Measure What Matters

Shift your metrics to focus on lead time, cycle time, and value delivered to the customer. Use these to track progress and guide further improvements.

Foster a Culture of Continuous Improvement

Encourage teams to regularly revisit and update their value stream maps. As your organisation evolves, so will your processes. Continuous review ensures that you stay aligned with your goals and customer needs.

The Bottom Line

Agile transformation is more than just changing the way teams are structured or the frameworks they follow. It’s about optimising the entire flow of value through your organisation. Value Stream Mapping provides the visibility and insight needed to make informed decisions, uncover hidden inefficiencies, and drive meaningful, lasting change.

By tracing the end-to-end flow of information before leaping into new frameworks, you set the stage for an Agile transformation that genuinely increases organisational efficiency, responsiveness, and customer satisfaction. Remember: It’s not about working harder or faster; it’s about working smarter—eliminating waste, reducing delays, and delivering value where it matters most.

Questions for Readers

1. Where in your organisation do you suspect the most significant bottlenecks exist, and how might Value Stream Mapping help you uncover them?
2. How does your current approach to Agile transformation account for the flow of information and value, not just team structures or ceremonies?
3. What steps can you take today to start visualising and optimising your organisation’s value streams before making further changes?

Introduction

In the fast-paced world of Agile development, Sprint planning is a critical activity that shapes the direction, speed, and success of the team. Product backlog items (PBIs) must be selected and prioritized with care, ensuring that the most valuable and impactful work is addressed first. However, traditional prioritization methods often rely heavily on perceived business value, urgency, or stakeholder pressure, sometimes leaving risk assessment in the background.

Failure Modes and Effects Analysis (FMEA) is a systematic technique traditionally used in engineering and manufacturing to identify potential failures in a process, product, or system. By evaluating the potential consequence, likelihood, and detectability of each failure mode, FMEA helps teams calculate a Risk Priority Number (RPN) for each item, enabling more informed decision-making. Integrating FMEA into Sprint planning can help Agile teams prioritize PBIs not just on value, but also on calculated risk profiles — leading to more robust, resilient, and successful deliverables.

Challenges

Lack of Structured Risk Assessment

Many Agile teams rely on subjective judgment or basic risk discussions during Sprint planning. While this approach can suffice for simple projects, it often falls short in complex, high-stakes environments. Without a structured risk assessment, critical issues may be overlooked until later stages, when mitigation becomes more expensive and disruptive.

Overloaded Product Backlogs

Product backlogs are often filled with hundreds of items competing for attention. Determining which items pose the greatest risk, and thus deserve early attention, can be overwhelming — especially when the team lacks a common framework for evaluating risk.

Communication Gaps Among Stakeholders

Risk is a multifaceted concept involving technical, business, and operational considerations. Without a shared vocabulary and process, risk discussions can become confusing, leading to misaligned priorities and missed opportunities for risk reduction.

Balancing Business Value and Risk

Teams are often pressured to deliver features with the highest perceived business value. However, this can lead to the accumulation of technical debt or the neglect of less glamorous, but high-risk, backlog items — such as refactoring, security upgrades, or architectural improvements.

Time Constraints

Sprint planning sessions are time-boxed, and teams may feel there is not enough time to conduct a thorough risk analysis on each backlog item. As a result, risk assessment is often rushed or skipped altogether.

Recommendations

Introduce FMEA as a Lightweight Framework

FMEA does not have to be a burdensome process. Start by introducing a simplified version tailored for Agile teams. For each PBI under consideration, briefly discuss the possible failure modes (ways the item could fail to deliver its intended value), their potential effects, and basic ratings for severity, occurrence, and detectability. Assign an RPN to each item.

Prioritize High-Risk Items Early

Use the RPN values as an additional lens for backlog prioritization. Items with high RPNs may warrant early attention — even if their initial business value seems low — because addressing them early can reduce overall project risk, prevent costly rework, and improve product quality.

Make Risk Assessment a Team Activity

FMEA is most effective when performed collaboratively. Encourage developers, testers, product owners, and other stakeholders to contribute their perspectives. Diverse viewpoints lead to a more comprehensive assessment of potential risks and how to mitigate them.

Integrate FMEA with Existing Agile Practices

FMEA need not replace existing prioritization methods; instead, it should complement them. For example, consider adding risk as an explicit criterion alongside value and effort in your backlog refinement and sprint planning discussions.

Iterate and Improve the Process

Start small — perhaps by applying FMEA to only the top ten PBIs in your backlog for the next sprint. Gather feedback, refine your approach, and adjust the weighting of severity, occurrence, and detectability scores as needed to fit your team’s context.

Document and Visualize Risk Profiles

Maintain a living document or board that tracks the RPNs of backlog items. Visualizing risk profiles can help the team and stakeholders see patterns, track progress, and make informed decisions about where to focus attention in future sprints.

Use FMEA Data for Retrospectives

After each sprint, review how well the team anticipated and addressed risks. Were high-RPN items effectively mitigated? Did any unforeseen failure modes arise? Use these insights to improve your FMEA process and overall risk management strategy.

The Bottom Line

Integrating FMEA into sprint planning empowers Agile teams to make smarter, more resilient decisions about what work to prioritize. By systematically identifying and addressing high-risk backlog items, teams can reduce surprises, lower the cost of change, and deliver higher-quality products. While FMEA requires some initial investment in time and learning, the payoff in risk reduction and improved team alignment can be substantial. Start with a lightweight approach, iterate, and make risk management a natural part of your Agile journey.

Questions for Readers

• How does your team currently assess and prioritize risk during Sprint planning?
• What challenges have you faced in balancing business value and risk when selecting backlog items?
• How might you tailor the FMEA process to fit your Agile team’s culture