Conquering the Myth: Steps to Mature Product Operating Model
This article first appeared in Medium
I have worked across more than five companies and four industries and have yet to experience a genuinely mature product operations model. Is this a myth spun up by the elites in Silicon Valley, only experienced at the FAANG (Facebook, Amazon, Apple, Netflix, Google) companies and modern, unicorn startups who fortuitously caught a tailwind from their inception? A fairytale passed down from generation to generation by “product influencers” around the glow of a social media post? The short answer is “no.” Though many forces indeed perpetuate this myth.
I think there are certainly companies out there who have achieved at least something close to what you’ll read in a Marty Cagen book or countless product “expert” posts. But the fact of the matter is that most of us have yet to experience the ideal, mature product operating model outside of books, social media posts, and whispers in corporate hallways about how other companies have already figured this out.
I bet this is just a fantasy for 80% of us. The other 20% are lucky to have landed at a company that simply started with a mature product management approach or worked at one that figured out how to pivot from a legacy approach to a modern one. Either way, most of us are at companies that, to varying degrees, are struggling with this transition. Indeed, a burgeoning industry focuses on “digital transformation” for legacy organizations, primarily — but not completely — about the product operating model.
This article is for those of us navigating the messy reality of legacy processes and culture in mid to large companies, striving for better but far from the ideal. It’s for the product managers in the trenches and the leaders tirelessly championing customer-centricity, outcome-focused strategies, and data-driven decisions. There is a path forward — a chance to drive real change — but it requires embracing the journey itself rather than fixating on the destination (if one even exists).
Milestones of maturity
Let’s start with the end in mind and describe what we, as product practitioners, aspire to. Many articles offer different perspectives on the “phases of maturation” for product-led companies and the milestones you should look for along the way. As with my previous articles, I will neither re-invent my own wheel, so to speak, nor provide an exhaustive list. Instead, I will synthesize — and simplify — some of the ideas that have resonated most with me.
First, we can identify the main milestones of maturity. These include:
Comprehensive leadership alignment of company goals, product strategy, and metrics
Product operations mindset
Customer-centric
Data-informed decision making
Strategic resource allocation and team structure
Let’s take a closer look and define what each of these looks like inside a mature organization.
Aligned Leadership, Company Goals, Product Strategy and Metrics
A mature product organization demonstrates tight alignment across leadership, teams, strategic goals, and metrics. The product strategy clearly ladders up to the overall company strategy. Employees understand the long-term product vision and how their day-to-day work enables the company vision. Leaders demonstrate alignment with the plan by speaking the same language, establishing a North Star Metric, and emphasizing the link between OKRs at the team level and the bigger-picture vision of what the company is trying to achieve.
Product Operations Mindset
An essential milestone for product maturity is that standardized processes exist and enable — not get in the way of — optimizing product team effectiveness and efficiency. Product ops should support a decision-making architecture with standardized processes, tools, and product management frameworks.
In turn, these processes and tools empower teams to prioritize strategically (and autonomously) by creating customer feedback loops and leveraging data to deliver outcomes that maximize value and minimize unnecessary risk for the business. Product teams are encouraged to strive for frequent, smaller releases. Additionally, the process should be transparent enough for stakeholders to understand how product teams make decisions and launch new features.
Customer-Centric Mindset
A customer-centric mindset is really about culture. It is a critical milestone for product maturity and is, in part, enabled by the product operations milestone discussed above. Companies achieve true maturity — and deliver real value — when they deeply understand their customers’ needs and make those the north star for product development; this has to be baked into your company values. A customer-centric approach involves continuous feedback loops, user research, and empathy, ensuring solutions are feasible, usable, viable, and desirable, not to mention differentiated from the rest of the competition.
Data-Informed Decision Making
Nowadays, most organizations rely on robust data pipelines and analytics to inform decisions, moving away from intuition or anecdotal evidence. However, mature product organizations are clear about what they are measuring, why it is essential, and how it ties to the long-term strategy. What is critical to measure can be articulated from a North Star Metric, One Metric that Matters, or other elevated metrics. Establishing a “measurement strategy” is another way to ensure teams are intentionally coupling the strategy with useful metrics.
Often, mature organizations differentiate between input and output metrics to sharpen the focus on roadmap priorities. Furthermore, a culture of using metrics and data enables teams to test hypotheses regularly and iterate quickly, minimizing guesswork and maximizing the effect on the target metric. Generally speaking, there is more sophistication — and intention — with how data and metrics are used, including using counter-metrics to prevent unintended consequences.
Strategic Resource Allocation and Structure
The allocation of resources — teams, budget, and time — should align with strategic priorities, with clear accountability structures in place. Furthermore, the product team’s “topology” significantly impacts the teams’ ability to deliver effectively against the product/company objectives. Teams must be structured to support durable products and outcomes, not temporary projects or initiatives. A mature organization structures its teams and resources/funding around the desired outcomes, ensuring that teams are empowered to deliver the right capabilities and are focused on the most critical business challenges.
All of the above milestones are, of course, interlinked. For instance, data-driven decision-making is only enabled if (1) strategy and leaders are aligned across the org and (2) the process is designed to maximize how data is used. But truth be told, the reality looks much less linear at most companies. Speaking from experience, I have seen some of these milestones in place while having a significant gap in others. It’s not a linear progression through these but rather an iterative, winding journey.
Start Here: Basic, Practical Building Blocks
Those milestones may seem daunting depending on where your org is on the product operating model journey. As I said above, you need to think more about the journey and less about when you might reach the destination. However, you can use some simple, practical building blocks to start establishing a foundation — and momentum — for optimizing how your company operates in building products. A checklist of these practical building blocks would include:
A simple, easy-to-access product strategy doc: this should be easy to understand and a frequently used artifact in presentations, team meetings, etc. Every individual contributor should be able to reasonably explain how their work supports the overall strategy. More visibility on this artifact will force leaders to be crisp with their communication and ensure they are aligned with their partners.
Consistent t-shirt sizing across teams: Do not underestimate how much this can streamline how your product and engineers work together as well as make prioritization conversations more effective. More importantly, stakeholders and leaders will benefit greatly from a consistent approach that somebody should be able to translate into dollars easily.
Frequent releases: Focusing on smaller, frequent releases is essential for a few reasons. 1. this gets the team thinking about delivering value faster for the business and the customer. 2. It also naturally reduces risk and enables the teams to learn and adjust more nimbly as they progress through their roadmap.
Consistent data analysis and review: Almost every single company emphasizes data and data-driven decision-making. But seamlessly incorporating data analytics into day-to-day processes is where mature companies separate themselves. Integrating data analytics into the day-to-day means that a culture exists where all roles think about and analyze the data as a natural part of their day, establishing a cadence where teams gather to discuss insights from the data.
Methodical roadmap prioritization & scoring: A transparent, objective, and consistent method for prioritizing your roadmap will help your product team mature more quickly, and your stakeholders will appreciate your approach to prioritization. However, note that scoring itself is a double-edged sword. The objective of using a scoring method should be to facilitate and structure conversations about priorities while also connecting priorities to company strategy. Note that product teams should not treat scoring methods as a way to automate decisions.
Product discovery & customer feedback loops: Keeping your customer at the center of your process should be an obvious objective for organizations following a product operating model. However, I am surprised by how many companies still need help establishing processes and routines that enable constant and consistent discovery and feedback loops as inputs to the roadmap prioritization exercises. If this is a gap for your company, this is an excellent place to start.
Product ops process and tools: Product operations do not need to be a formal part of a product org. However, being intentional about the methods and tools that can enable everything listed above is critical to successfully empowering your team to transition to a more mature operating model, especially as your teams begin to scale.
The Great Disruptor — Gen AI
Generative AI is like the white baby elephant in the room. This elephant is present in the room as a curious and hard-to-ignore being. It is also growing rapidly. It’s only a matter of time before this elephant becomes something large enough to alter everything around it. That will be true for the product operating model as well.
The fundamentals of what I described above will remain the same. However, what will change is how we get there. In theory, as companies adopt/adapt to generative AI tools, they should be able to embrace the core tenants of a mature product operating model more efficiently. But as I wrote before, generative AI isn’t just about efficiency — it will also drive more effectiveness for individuals and teams in the product space and beyond.
To support a transition to a more effective and mature product operating model, organizations must include a final category: embracing generative AI to power this move. Letting your employees experiment and identify ways to leverage these emerging tools best is a good place to start. But in doing so, employers and product leaders must be clear that embracing generative AI is about empowering teams to work effectively — not replacing them.
iStock.com/RichardALock
Conclusion
Conquering the myth of a mature product operating model is less about achieving perfection and more about embracing reality — and how to forge progress. It’s about aligning people, processes, and technology to support teams in delivering meaningful outcomes while fostering continuous improvement. Each milestone — whether it’s customer-centricity, data-driven decision-making, or strategic alignment — is a critical step on this journey.
Generative AI, the latest disruptor, adds a powerful new dimension to these steps. By equipping your people with AI-driven tools and embedding them thoughtfully into your processes, you can accelerate the journey toward maturity without losing human creativity and innovation at the heart of great products. Progress may be iterative, but with focus and intentionality, even the most complex organizations can realize the promise of a modern, effective product operating model and turn the myth into a compelling, new reality.
