TL; DR: The Illusion of Velocity
In this article, I explore the pitfalls of ‘The Illusion of Velocity’ in agile contexts, peeling back the layers of traditional metrics as leadership tools. Moreover, I point to the advantages gained from leadership engaging directly with teams.
Understand why servant leadership and practices like the Gemba Walks are crucial for coping with complex, adaptive environments toward actual progress. Moreover, get an idea of how to start flipping outdated hierarchies and embrace the natural rhythm of productivity and innovation.
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The Clash of Paradigms
In the traditional management paradigm, born from Frederick W. Taylor’s scientific management, the goal was efficiency through standardization, predictability, and control. Management sought to deconstruct work into repeatable tasks optimized through measurement and refinement. Workers were seen as cogs in the machinery of production, with little autonomy or need for understanding the broader context of their work.
Contrastingly, agile practices, born from the need to accomplish work in uncertain and complex environments, emphasize adaptability and responsiveness. The core of “Agile” is that the best products and solutions to customer problems emerge from self-organizing, cross-functional teams. These teams are given autonomy and are expected to collaborate with stakeholders frequently to reassess and realign their work according to changing needs. Instead of detailed long-term planning, Agile focuses on short, iterative work cycles, allowing for continuous feedback and adjustment.
From the Illusion of Velocity to the General Misfit of Command and Control
In complex environments where knowledge work prevails, classic management practices rooted in predictability and control fall short for several reasons:
- Overreliance on Predictability: Traditional approaches hinge on the assumption that work is predictable and stable, which allows for detailed long-term planning and certainty in output. However, complex environments are characterized by their unpredictability and the frequent emergence of unforeseen challenges. Insisting on precise estimates in such scenarios leads to unrealistic commitments and, often, failure to deliver value, impeding the building of trust between teams and their stakeholders.
- Misplaced Focus on Output over Outcome: Classical management prioritizes output—the amount of work done—over the outcome, the actual value delivered. This focus often leads to a misguided effort to increase the velocity or speed of delivery without considering whether the work is effective or even necessary. In complex environments, the focus needs to shift to learning what works quickly and adapting based on feedback rather than just doing more of the same faster.
- Individual Performance over Team Collaboration: The traditional model often emphasizes personal achievement, which can undermine the collaborative effort needed in complex problem-solving. Complex environments require diverse skills and perspectives, and rewarding individuals over teams can discourage the collaborative culture necessary for business agility.
- Linear Thinking in a Non-linear Context: Classic management approaches apply linear thinking to problem-solving, assuming that A leads to B in a predictable fashion. Complex environments, on the other hand, are non-linear and dynamic, meaning that the same action won't always produce the same outcome. This unpredictability necessitates a more empirical approach, adaptable and responsive to change, rather than one that follows a fixed plan.
- Control vs. Empowerment: In traditional settings, managers control who directs work and makes decisions. In complex environments, this approach can stifle creativity and responsiveness. Empowering teams to make decisions enables a more rapid and appropriate response to change, as those closest to the work best understand the nuances and can innovate effectively.
- Inflexible Structures Hinder Adaptability: Traditional management often has rigid hierarchies and processes designed for stability. These structures can make it difficult to adapt when change is needed, leading to slow responses to market shifts, customer needs, and technological advancements. Agile environments demand a more fluid structure where change can be incorporated quickly and seamlessly.
- Misunderstanding Complexity: Perhaps the most significant failure is the misunderstanding of the nature of complexity itself. Managers cannot manage complexity through simplification or traditional optimization techniques, such as pattern recognition. Instead, managing complexity requires embracing uncertainty, fostering an environment of experimentation and learning, and valuing adaptability over efficiency.
These classic practices, while effective in stable and predictable settings, prove inadequate in the face of the complexity inherent in modern knowledge work. Agile practices address these shortcomings by recognizing the need for adaptability, valuing individuals and interactions, customer collaboration, and responding to change over following a plan, as articulated in the Agile Manifesto.
Learn more with the following Sources:
McChrystal, S., Collins, T., Silverman, D., & Fussell, C. (2015): Team of Teams: New Rules of Engagement for a Complex World.
Snowden, D. J., & Boone, M. E. (2007): A Leader’s Framework for Decision Making. Harvard Business Review.
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Beyond the Illusion of Velocity: Agile Metrics for Insight and Adaptation
Traditional management metrics, while offering the illusion of control, often fail to provide the insight necessary for dealing with complex, knowledge-based tasks. Agile practices, however, promote metrics that provide meaningful insights into the team’s effectiveness and product value delivery, like burn-up charts for tracking progress, cycle times for understanding workflow efficiency, and team Retrospectives for continuous improvement. These tools are not just about measurement but about fostering an environment where the information leads to actionable insights.
In practice, traditional metrics like velocity, often used to extrapolate future performance with tools like Excel, are less effective in environments filled with complexity and unpredictability. These classic metrics are derived from a desire for predictability and control, a relict from management practices of the industrial age. However, they regularly fail to provide the necessary insights for truly adaptive and responsive practices, which prove to be suited to deliver progress in complex environments:
- Velocity Obscures True Progress: Velocity is typically a measure of the quantity of work delivered, often quantified in story points. It’s a unidimensional metric that doesn’t account for the value delivered or the qualitative improvements in the product. In complex environments, providing features quickly doesn’t necessarily translate to delivering the right features or doing so suitably.
- The Fallacy of Extrapolation: Using velocity to predict future performance assumes a stable environment and tasks of uniform difficulty, which is never the case in complex projects. Extrapolating story points with tools like Excel may create an illusion of precision, but it fails to accommodate the inherent uncertainty and variability in creative and knowledge work.
- Flow Metrics Offer a Clearer Picture: Flow metrics, on the other hand, are designed to provide a more granular and real-time view of the work process. These include:
- Lead Time: The time it takes for a work item to move from initiation to completion. It’s a direct measure of efficiency in the workflow.
- Cycle Time: The time a task spends in the actual development process, which can highlight process inefficiencies or blockers.
- Throughput: The number of work items finished in a specific time frame, indicating the actual work rate of the team.
- Work in Progress (WIP) Limits: A way to manage flow by limiting the number of tasks being worked on at any given time, promoting focus, and reducing context-switching.
- Flow Efficiency: The ratio of work time to lead time, indicating the amount of idle time in the process.
These flow metrics are not just about measuring; they are about understanding and improving the workflow. They help identify bottlenecks and waste, enabling teams to adapt their processes to become more efficient and responsive to change.
By focusing on flow metrics, teams can shift their attention from the output (velocity) to the outcomes (value delivery and quality). They can better manage workloads, prioritize tasks more effectively, and create a sustainable pace of work that maximizes value delivery without overburdening the team.
Switching to flow metrics requires a mindset shift from output to outcome, from task completion to value realization. This shift allows management to understand the team’s effective capabilities, adjust expectations, and ultimately align business goals with agile practices for a more responsive and resilient organization.
Leadership Proximity and Decision Making
In the realm of agile practices, traditional hierarchical structures and decision-making processes often inhibit the flexibility and responsiveness essential in complex, unpredictable environments. In contrast, a model where leadership immerses itself in the operational context of teams—where the leaders come to the work rather than the work being reported up the chain—is critical for success:
- Servant Leadership: Agile environments benefit from leaders who serve their teams rather than command them. These servant leaders offer support by removing impediments, from processes to tools to training opportunities, facilitating growth, and promoting a culture of empowerment.
- Flattening the Hierarchy: In complex contexts, decision-making needs to be rapid and informed by real-time information. Flattening the hierarchy doesn’t mean eliminating leadership but redefining it to be more about mentorship and support rather than command and control.
- Bringing Leadership to the Information: This approach encourages leaders to become intimately familiar with the projects. Instead of waiting for filtered reports, leaders engage directly with the work environment, leading to more informed decisions and a stronger connection with their teams. (The Sprint Review in Scrum is a good example of the practice.)
- Gemba Walks: This practice, derived from Lean management, involves leaders going directly to where work is done (“the real place” in Japanese). By observing the work process in its natural setting, leaders gain firsthand insights into the workflow, challenges, and opportunities for improvement.
- Contextual Decision-Making: When leaders are close to the work, they can provide the necessary context for their teams. They help connect the day-to-day activities with the broader organizational goals, ensuring the teams can align their work with strategic objectives.
- The Big Picture: By engaging with teams on the ground, leaders can help workers see beyond their immediate tasks, understanding how their work fits into the larger scheme of things. This approach enhances motivation and can improve overall performance and satisfaction.
This transition from “bringing information to leadership” to “bringing leadership to the information” signifies a profound change in the culture of an organization. It embodies a commitment to agility and responsiveness, fostering an environment where knowledge flows freely, decisions are made swiftly and accurately, and the organization as a whole is more adaptable to the complexities and uncertainties inherent in today’s business landscape.
Food for Thought
Consider the following questions to help your organization to move beyond the illusion of velocity and embrace agility fully:
- In what ways might the fixation on velocity metrics detract from more qualitative aspects of team dynamics, such as innovation and creative problem-solving?
- How can organizations balance the need for some form of measurement with the recognition that not all valuable outcomes are quantifiable?
- Considering the principles behind the Gemba Walk, what cultural shifts must occur in traditionally managed organizations to adopt this practice effectively?
Conclusion
For organizations mired in traditional measurement paradigms, the path to agility involves a fundamental mindset shift. It requires valuing learning and responsiveness over predictability, embracing cross-functional collaboration over siloed departments, and recognizing that actual effectiveness in knowledge work comes from the ability to adapt rather than from the repetition of optimized tasks. Leaders must cultivate an environment that empowers teams, values empirical evidence over speculation, and promotes a culture of experimentation. Ultimately, they need to quit the illusion of velocity.
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