Chris Heuer on Rethinking Success Metrics, Building Motivated Teams, and Fostering Innovation in an AI-Driven Workplace
Product State Q&A
Chris Heuer is Managing Director at Team Flow Institute. He’s also Fractional Head of Remote Collaboration at FOAF. He was formerly CEO at Alynd, Founder at Social Media Club, and Social Business Specialist at Deloitte Consulting.
Website / LinkedIn
EC: How should software product leaders rethink success metrics for their teams in an AI-driven workplace?
CH: In an AI-driven workplace, software product leaders should rethink success metrics to align with the unique dynamics and capabilities that AI introduces. They should also take this opportunity to rethink what it means to lead a great product team. Traditional metrics do not fully capture the nuances of team performance and productivity in this new world.
AI's role in our workflows fundamentally reshapes how software development teams operate and how their success should be measured. Traditional metrics, often focused on output and individual performance, are becoming less relevant in a landscape where collaboration, adaptability, and the effective integration of AI are paramount. Software product leaders must embrace a paradigm shift towards more holistic and outcome-based success metrics that capture the nuances of an AI-driven environment.
For a deeper exploration of these evolving dynamics and the need for a more human-centric approach, see our recent report, "The World of Work in 2025 and Beyond".
Rethinking Success Metrics
AI is truly a workforce multiplier for both individuals and teams. It can also be a blunt force object if misunderstood and misapplied, resulting in more damage than value creation. As a tool that augments our human work, I am a big believer in its potential while being cautious of the potential for a dystopian future it might create if we fail to understand it is only a tool, not a human replacement.
A human with AI will always beat either alone if used properly. Of course, the nature of work itself is changing, and the value of generalists like me with a combination of broad interdisciplinary and specialized expertise will be more visible. Especially when looking at the time to produce higher-quality results. The first of which won’t be measured as traditional productivity but progressivity, which we at the Team Flow Institute define as progress towards objectives, the pace of that progress, and the quality of the end result.
It isn’t how many lines of code are produced or even how many hypotheses you can test. That said, our progress through asking better questions and running better tests is invaluable and requires us to rethink how we measure quality today.
In an AI-powered workplace, success metrics should reflect the quality and value delivered to users and the business, the team's ability to collaborate and adapt, the effectiveness of AI integration, and the team's overall well-being. We think one significant factor to consider, which isn’t part of the broader conversation yet, is how well we are working together to produce quality results, not how much work is getting done.
As I’ve recently learned from “Work Here Now” by Melissa Swift, one of the biggest challenges with traditional approaches is that performance management is often about measuring just that - the performance - not the quantity of work being done or its quality. As such, the simple answer to this question is to make that shift with a laser focus on quality and outcome-oriented metrics.
We must prioritize metrics that directly reflect the user experience, such as Net Promoter Score (NPS), Customer Satisfaction Score (CSAT), Customer Effort Score (CES), and user engagement analytics. These metrics provide tangible evidence of whether the product meets user needs and expectations. AI can also play a significant role in analyzing user feedback at scale, enabling teams to iterate more rapidly based on data-driven insights. This requires product managers to put more emphasis on feedback loops and gathering customer verbatims. We suggest embedding the ability to capture audio feedback directly into the product and build a means to store and process that feedback with AI anonymously.
AI can enhance collaboration, but measuring how well teams work together is essential. In particular, we want to better understand and measure the frequency and quality of interaction between team members, especially on cross-functional teams. Metrics include the usage of collaboration tools and the frequency of cross-functional meetings that solve problems and move us toward our shared objectives. How often and how easily do teams share knowledge and resources?
Pace and Productivity
While we seek to shift our focus to outcome and process-focused metrics, we must not abandon all of the core productivity metrics. These help us understand that we are making progress and doing so at a good pace. A pace that also takes into consideration the well-being of the team members. We don’t want to put jet fuel in the engine that is moving our team forward towards its objectives lest it explodes and harms our people.
The ability to learn and adapt quickly is a hallmark of high-performing teams in any era, but it's especially crucial in the rapidly evolving field of AI. Measure the time it takes to move from insight to deployment, reflecting the team's ability to incorporate feedback and iterate quickly. Track the number of experiments conducted and the insights gained together, not just the number of experiments.
We can also evaluate how readily the team embraces new AI tools, development methodologies, best practices, and AI-specific metrics. In doing so, we should be mindful not to spend too much effort measuring, as that is another form of performative work that takes away from the actual work needing to be done. Where possible, we can use our digital exhaust with AI to gather and analyze these measures of success – ideally in a conversational manner with the team in a facilitated feedback session – a new kind of after-action review with questions focused on these issues I’ve referenced in this article.
Of course, we also must measure the performance of the AI itself, with metrics like accuracy, precision, and recall being essential for evaluating the effectiveness of AI models, which impacts the selection of AI tools. Then, we can look at how well we integrate AI into our workflows, measuring factors like the percentage of tasks automated by AI, time saved through AI assistance, and the impact of AI on decision-making. Taking this even further, you might also look at what we are now able to do instead of the things we have automated as another quality/outcome metric.
Considering the shift towards outcome-oriented, collaborative, and adaptive development in an AI-driven workplace, sprints in an AI-driven workplace should be shorter, more iterative, outcome-focused, and data-driven, emphasizing collaboration, learning, and delivering demonstrable business value. The metrics used to assess sprint success should reflect these priorities, moving beyond traditional measures of output to encompass a more holistic view of quality, progress, and value creation.
It is time to get real. At the Team Flow Institute, we think that for too long, managers have been paying lip service to the idea that our people are our most valuable assets, and it is time to treat them like that. To become a true human-centric leader AND organization, we need to care about our people and their well-being. We need to ensure psychological and sociological safety within and between teams – a healthy, motivated team is more likely to be productive, innovative, and adaptable – to produce higher quality results with less effort and less impact on their physical, mental, and emotional well-being.
Ultimately, software product leaders must adopt a balanced scorecard approach to success metrics in an AI-driven workplace. This involves a shift from a narrow focus on output and individual performance to a more holistic view that encompasses outcomes, collaboration, learning, adaptability, AI effectiveness, and team well-being. By embracing a culture of continuous improvement and empowering teams with the right tools and metrics, leaders can foster an environment where teams thrive, innovate, and deliver exceptional value in the age of AI. The role of leadership is not just to define these metrics but also to create a culture that embraces them as tools for growth and improvement rather than simply evaluating performance.
EC: Given rising disengagement among employees, what can product leaders do to build high-performing, motivated teams?
CH: The current climate of economic volatility and organizational change has fueled an even more concerning rise in employee disengagement than when Gallup first identified this challenge in 1998. Reversing this trend requires a fundamental shift in our approach to leadership, moving from a purely task-oriented management style to one rooted in genuine care, shared purpose, and individual empowerment. Product leaders are uniquely positioned to foster this change, building teams that are not only high-performing but also deeply motivated and resilient.
The core of the solution lies in a seemingly simple yet profoundly impactful principle. While there are many variations of the saying, the essence is captured accurately by author Simon Sinek: "You can't teach someone to care. Caring is a human feature and it comes from how we treat each other". This statement is the cornerstone of building engaged teams.
Product leaders must demonstrably care about their teams and each of its members, both as individuals and as contributors to their collective endeavor. Caring isn't a soft skill; it's a leadership imperative that translates directly into performance. It's about understanding individual motivations, aspirations, and challenges to create an environment where people feel valued, supported, and empowered.
From my perspective and through the lens of our Team Flow Model, this type of caring manifests in several key ways:
Cultivating Collective Ambition: High-performing teams are united by a shared vision, a common purpose that transcends individual tasks. This "collective ambition" embodies a compelling mission, a clear understanding of why the team exists and what it aims to achieve. Shared values animate it – the principles that guide the team's behavior and decision-making. This is strengthened by the interpersonal connections between team members, which also must be cultivated regularly both inside and outside of work where possible.
An audacious, well-crafted OKR (Objectives and Key Results) can be a powerful catalyst for this collective ambition. A truly inspiring OKR isn't just a set of metrics supporting a well defined outcome; it's a rallying cry, a challenge that ignites passion and encourages individuals to push their boundaries, both for their own growth and for the success of their teammates. The feeling of "we're in this together," of shared struggle and shared triumph, is a potent antidote to disengagement. It creates a sense of unity, a powerful force that binds individuals together, especially during uncertain times.
Aligning Personal and Team Goals: To foster deep engagement, we turn to a central element of the Team Flow model, making the direct connection between an individual’s career goals, and the team’s goals visible. When individuals see how their daily work contributes to their personal growth and the team's success, genuine engagement flourishes because they are invested in the outcome. This involves understanding each person's individual "why." What drives them? What are they hoping to achieve in their career? What skills do they want to develop?
Regular one-on-one conversations are crucial for uncovering these individual motivations. Product leaders should use these conversations not just to review performance but to actively explore how the team's work can contribute to each individual's growth and fulfillment. This alignment is a core condition of team flow. When individuals see a direct connection between their personal goals and the team's success, their engagement levels soar. They're no longer just completing tasks but investing in their future while contributing to a larger purpose.
This alignment should extend beyond one-on-ones and be woven into everyday interactions. Leaders should consistently connect individual activities and contributions to the team's goals and, by extension, to the organization's overall mission. This creates a clear line of sight, demonstrating how each person's work matters and contributes to the bigger picture. This makes the work more meaningful while making the worker feel valuable AND valued.
Creating a State of Flow, Individually and Collectively: When individual aspirations align with team goals, and a collective ambition unites the team, the conditions are ripe for achieving a flow state. At the individual and team level, flow is characterized by deep engagement, focused concentration, and a sense of effortless action. Individuals are challenged but not overwhelmed, their skills are fully utilized, and they receive clear and immediate feedback. Teams in flow exhibit remarkable levels of collaboration, creativity, and productivity.
The product leader's role is to create an environment that facilitates flow. This includes:
Setting clear goals and expectations.
Providing the necessary resources and support.
Removing obstacles and distractions.
Fostering a culture of psychological safety where team members feel comfortable taking risks and sharing ideas.
Celebrating successes, both big and small.
Providing consistent and thoughtful feedback at regular intervals.
Addressing employee disengagement in today's challenging environment requires product leaders to prioritize genuine compassion, cultivate a strong sense of shared purpose, and actively align individual aspirations with team goals. By fostering these conditions, leaders can unlock the full potential of their teams, creating high-performing, motivated units that are resilient, adaptable, and capable of achieving extraordinary results, even amidst uncertainty.
EC: What leadership traits will be most critical for software product leaders to foster innovation and resilience in their organizations?
CH: To foster innovation and resilience in their organizations, software product leaders must cultivate specific leadership traits beyond traditional management skills. These traits are crucial for navigating the complexities of an AI-driven workplace, addressing employee disengagement, and ultimately unlocking the full potential of their teams to deliver extraordinary results. These traits are not merely "nice-to-haves"; they are the foundational elements that differentiate true leaders from managers and enable the creation of high-performing, flow-state teams.
The following traits will be most critical in this evolving work environment:
Authentic Empathy and Care: As previously discussed, genuine care for team members is paramount. Leaders must demonstrate empathy, understanding individual motivations, aspirations, and challenges. This goes beyond superficial gestures; it requires actively listening, seeking to understand, and creating a supportive environment where individuals feel seen, respected, and valued.
Visionary Leadership: Leaders must articulate a compelling vision and inspire a shared sense of purpose (what the team flow model refers to as collective ambition). This involves clearly communicating the "why" behind the team's work, connecting it to the broader organizational goals, and painting a picture of the future that motivates and excites the team.
Facilitator of Flow: Leaders must actively cultivate the conditions for team flow, as outlined by Dr. van den Hout's Team Flow model. This means modeling open communications, aligning individual and team goals, integrating the team’s skills, creating a culture of accountability, and fostering psychological safety. It also means removing obstacles and providing regular, constructive feedback. They are not directing the work as much as helping their people navigate it, like a white water river guide.
Commitment to Continuous Learning (Growth Mindset): The rapid pace of technological change, particularly with AI, demands a commitment to lifelong learning. Leaders must model a growth mindset, constantly seeking new knowledge, embracing experimentation, and encouraging their teams to do the same. This includes staying abreast of advancements in AI and development methodologies. It also means embracing new leadership best practices like team flow facilitation.
Co-Elevation: True leaders are defined by their commitment to the growth and success of others. They embody the principle of "co-elevation," finding fulfillment in seeing their team members thrive and reach their full potential. This involves mentoring, coaching, providing opportunities for development, and celebrating both individual and collective achievements. This moves us beyond the idea of servant leadership towards a mutual elevation that comes with being in it together and lifting each other up to be our best.
Outcome-Oriented Focus: Leaders must champion a shift from measuring output to measuring outcomes. This requires defining clear, measurable objectives that align with business value and user needs and empowering teams to achieve those objectives. It also means using data and feedback to improve and iterate continuously.
Resilience and Adaptability: In a constantly evolving landscape, leaders must demonstrate resilience and adaptability, navigating uncertainty, embracing change, and helping their teams do the same. This involves being open to new ideas, willing to pivot when necessary, and fostering a culture of experimentation. This requires us to eliminate the fear of failure and embrace a hypothesis-based culture that is constantly questioning, experimenting, and learning.
Measuring what Matters: We get what we measure, so it is important to balance all measures. The holistic framework outlined earlier should guide top software product leaders toward prioritizing both the quality of results and the pace of progress at which quality and impact are achieved. This necessitates a shift away from quantifying activity through traditional productivity measures and rewarding performative acts. Instead, the focus should be on the outcomes the team must produce, the collaborative processes they employ, and their measurable progress toward intended results.
Practicing Gratitude Protocols: High-performing teams and the leaders who guide them, cultivate a culture of appreciation. This involves establishing regular "gratitude protocols" – structured and sincere practices for expressing thanks and acknowledging contributions. These can range from simple shout-outs in team meetings to more formal recognition programs to the regular practice of gratitude circles. The key is to make gratitude a consistent and intentional part of the team's rhythm, reinforcing positive behaviors and strengthening interpersonal bonds. This fosters a more positive and supportive environment, boosting morale and reinforcing a sense of collective accomplishment.
These leadership traits are not isolated concepts but interconnected and mutually reinforcing. They are the essential ingredients for creating a high-performing, engaged, and resilient team capable of thriving in an AI-driven workplace. This is where the Team Flow model and the work of the Team Flow Institute become invaluable.
The Team Flow model provides a framework for understanding and cultivating the conditions that enable teams to achieve a state of flow – a state of deep engagement, collaboration, and peak performance. By focusing on the model's core principles – collective ambition, aligned goals, psychological safety, open communication, mutual commitment, and skills integration – leaders can create an environment where innovation flourishes, resilience strengthens, and individuals are empowered to reach their full potential together.
Ultimately, the difference between a true leader and a mere manager lies in their commitment to these principles. Managers focus on tasks and processes; leaders focus on people and purpose. Managers measure output; leaders cultivate outcomes. Managers maintain the status quo; leaders drive continuous improvement. True leaders, particularly in software product development, understand that their primary role is to create the conditions for their teams to excel, fostering a culture of co-elevation, lifelong learning, and a deep connection to a shared, inspiring vision. This is the path to building teams that survive and thrive in the age of artificial intelligence, consistently delivering extraordinary results and driving true innovation.
“"A human with AI will always beat either alone—if used properly."
— Chris Heuer
