Recently attending an industry event, we got talking with a CPO about the inevitability of Product people ending up managing frameworks of the moving parts that will make up your business outcomes. Sooner or later this Market & Engineering partnered department has to get its operational ducks in a row to streamline down the right data; all for product strategy to get its chance to create a growing rate of revenue.
Companies have started to figure out that Product Managers can’t actively lead their own cross-functional workflow and the product’s development at the same time. One predicates the other for success, which is how ProductOps has started to seep into job listings. The popularity of the role varies across continents – North America leading, with China behind and Europe hiring only around 15.5% of global ProductOps roles.
There’s a knowledge gap about the role, its function and clear separation from a classical Product Manager role as 73% of product leaders still can’t clearly define what ProductOps actually does. The disconnect creates a massive opportunity gap. While product teams struggle with data fragmentation, tool sprawl and cross-functional misalignment; the companies that crack ProductOps are scaling efficiently and outperforming competitors by significant margins.
Introduction
This comprehensive holistic guide reveals how ProductOps can transform a product organisation from reactive ad-hoc coordination to strategic consistent execution. Creating an in-built scaling machine as your company expands.
In this article we’ll discuss:
- This Product department’s operational backbone that can enable 40-60% higher ROI through systematic process optimisation
- How, with this implementation framework for ProductOps, organisations can reduce time-to-market while maintaining quality standards
- Real-world case studies from companies achieving measurable product-led growth acceleration by deploying ProductOps roles
These insights will help you advance the organisation’s competitive position by implementing ProductOps as a strategic operations differentiator rather than waiting for it to become a necessity to keep streamlining the operations without major breakdowns.
Why ProductOps matters in today’s Product landscape
The current Product Management team responsibilities and complexities have massively expanded over the last five years. An average product/engineering organisation uses up to 20-30 different tools, coordinates across multiple time zones and processes customer feedback from dozens of channels simultaneously. Add in the growing prevalence of automation and AI agent tooling, the job descriptions look more like “Where’s Waldo?” picture than Scandinavian minimalism.
Challenging data silos
The modern Product Manager is an umbrella term for a long list of jobs that need to be done to get the product on the market. The success for that is measured in the business outcomes – crediting the skill of strategy and insight, but not the materialisation of those values. Product Managers can have an abundance of tools, but it’s not the problem of having enough data – it’s the pipelining of that data in the right context. Customer insights arrive fragmented—some buried in support tickets, others locked in interview transcripts. While behavioral and performance data sits across several analytics platforms. This information chaos forces product leaders into a reactive cycle where 60% of their time vanishes into administrative archaeology for metric artifacts, translating different data sources into insights and manually stitching together customer signals that (in the operationally efficient world) should flow unobstructed.
Operational crises emerge when teams hit the 20-person threshold. What worked as informal coordination among a handful of people – suddenly fractures into competing priorities, misaligned timelines and communication gaps that multiply with each new hire. Cross-functional alignment that was a row of hallway conversations and shared context degrades into lengthy status meetings and email chains that create more bottlenecks than they resolve.
Such managerial conundrums lead to a lot of different stories that are being told across the organisation about the product, which lead to miscommunication and disagreements on how to lead that product. Every single person in the company is developing and selling a different story in their head. Development cycles that once moved with startup velocity now drag under the weight of decision-making untransformed. Or worse – turning into bureaucratic machines, where Product Managers lose the autonomy yet keep the responsibilities.
Market trends of AI agents and automation
The convergence of AI automation and product operations represents a fundamental shift in how organizations scale their product capabilities. While 58% of product teams already report positive impact from dedicated operational support, the real transformation emerges when agentic AI systems begin handling the repetitive coordination tasks that traditionally have consumed Product Managers’ time. These AI agents don’t just automate reporting—they actively manage data pipelines, synthesize customer feedback from multiple channels and maintain real-time alignment dashboards that eliminate the manual stitching together of insights.
Supporting the development of this capability is the unique work environments of remote and hybrid work. Pandemic has accelerated adoption of self-service analytics and standardized communication protocols out of hallway chats in the past five years. Unintentionally the perfect foundation for agentic AI adoption was created. In 2024, only 19% of companies had automation in five or more departments. Now, that number has nearly doubled to 37%. Companies with automation in three and four departments have increased, while companies with automation in one and two departments have decreased. Notably, this data also highlights that 74 percent of teams are leveraging enterprise automation in more than one business team, and 52 percent in four business teams or more.
Which ProductOps frameworks to buy into
Exemplifying the Product Operations vs Product Management differences
What exactly is ProductOps in 2025 organisations?
By widely accepted definitions – it serves as the department’s operational backbone that enables product teams to work effectively. By building up flexible processes that can scale, providing data insights through tooling and analysis, and removing friction from aligning with stakeholders. Unlike Product Management, which needs to focus on development strategy and customer value creation, ProductOps optimises the systems and communications that support PMs strategic execution.
Think of the Product Managers/Product Operators dynamic similarly to Sales/Revenue Operators – one is there to make the money, the other is there to make making money as easy as possible. It’s a partnership for the movies as Product Managers can offload a lot of the operational challenges to someone whose role gives them the leverage on the organisational level that PMs struggle with. Allowing Product Managers to focus on sharp delivery on these KPIs.
Still as a fairly unutilised role, the common misconceptions include treating ProductOps as project management or administrative support. If the organisation is placing their Operations teams to execute on external value creation, the role is well misguided. The discipline requires deep product knowledge combined with operational expertise and strategic thinking capability to build from the inside out. Exactly what is ProductOps’ goal – to bridge this gap by enabling rather than controlling, and providing better information without adding friction.
The ProductOps responsibility implementation matrix
Thought-leaders like Jenny Wanger have suggested their own frameworks in an attempt to introduce a clean-cut version of what it means to have an integrated ProductOps role. Wanger provides a proven structure for comprehensive implementation as following:
Data and Analytics
ProductOps establishes single sources of truth for product metrics, building self-service analytics capabilities and ensures data quality across teams. This includes implementing access points that remove obstacles between PMs getting their hands on data and someone needing to give them that.
Customer Understanding
ProductOps’ main responsibility is to get the right info to the Product Manager. That includes systematising user research processes, creating shared insights repositories and automating feedback collection from multiple channels. Ongoing customer testing is a heavy-infrastructure effort, but crucial for Product Managers to be able to learn directly from users.
Cross-functional Coordination
As the Product Manager needs to receive the inputs from their users, they also need to be able to work through standardised communication protocols to establish shared accountability with other departments. ProductOps creates the frameworks, and builds organisational bridges between product, engineering, design, marketing, and sales teams.
Process Excellence
A successful product organisation prevents alignment breakdowns while maintaining team autonomy. ProductOps maps and optimises key workflows for common activities like quarterly planning and product launches; and implements quality assurance mechanisms via ownership structures, taking the load off PMs once more.
The common denominator to all of those ProductOps functions is tooling and automation. Management activities need to be processed seamlessly to ensure an effective profitable organisation. Creating excessive waste in the daily operations directly affects the overhead and the longevity of profit indirectly.
Real-World ProductOps success stories
Spotify’s global scale management
From this case study by Asana, Spotify’s Revenue Engineering team transformed their stakeholder request management. Done using the Asana product suite for centralising intake through forms and systematic triage processes, a step up from the previous spreadsheet and informal chats. Revealing visibility gaps and expensive coordination between teams, a big operational red flag.
ProductOps approach involved creating automated task assignment based on request type, establishing master projects for transparency tracking and integrating with JIRA for technical development output. By using custom fields to indicate feature status, the stakeholders were kept informed throughout the product cycle through automated notifications.
Specific metrics and measured changes included elimination of large group status meetings, status reporting through automated updates and stronger stakeholder relationships by means of consistent communication. The system was now handling high-volume feature requests while maintaining development team focus.
Key lessons Spotify can teach here is a demonstration how stakeholder-friendly processes break down barriers between technical and business teams. Single sources of truth for project status create an opportunity for asynchronous communication across time zones which reduces coordination overhead. A follow-up study on how their Product organisation benefitted from this process change in the long term.
Pivotal Software’s Scaling Success
While Pivotal Software didn’t call what they used as ProductOps to scale from 10 to 60+ agile teams, the principles they used in Technical Program Management align with ProductOps functionality. While scaling it was important to preserve core culture and team autonomy. In Pivotal’s case it meant to maintain small, self-governing team structures but push enablement for rapid organisational growth.
They did really well in operationalising best practices rather than imposing standardised processes. They didn’t want scope for changing existing processes, as it could cause ripple effects and have unintended consequences. They stuck to their proven approaches, simply adapting to organisational scale. Creating lean frameworks that supported team effectiveness and prioiritised avoiding friction.
In the end the quantifiable results showed successful preservation of agile principles at enterprise scale, with teams maintaining high velocity and innovation capacity throughout growth phases. The framework enabled structured scaling without sacrificing the startup agility that drove initial success.
Stripe’s Developer-First ProductOps Excellence
Stripe changed the market of online payments by treating their API as the core product experience. Doing so required advanced implementation of ProductOps to maintain connection between the developer and the product at scale. Blake Samic, a legend in ProductOps, led a global team of over fifty professionals who successfully orchestrated and assisted in over 200 beta tests and product launches annually. The company deployed more than 3,200 new versions of its core API in a single year.
Stripe’s ProductOps teams coordinated product launches across multiple countries while managing complex regulatory requirements, local payment methods and currency handling.
Data-driven product development became central to Stripe’s approach, with ProductOps teams building comprehensive systems around the product development lifecycle. The company processed $1.4 trillion in total payment volume in 2024, up 38% from the prior year while maintaining the approachable developer experience that drove initial adoption. Thanks to this systematic approach they now operate in 50 countries and serve half of the Fortune 100, 80% of the Forbes Cloud 100, and 78% of the Forbes AI 50.
How to implement ProductOps in your organisation
Every ProductOps team and practice will be different and there’s no cloneable solution for anyone. However there are core ProductOps principles that can lead the way for successfully integrating within the organisation. Mostly involving a lot of communication through several departments of engineering, design, marketing, sales and finance. Teaching Product Management to coexist and collaborate for shared desired outcomes. The difference between organisations who gain value from ProductOps and those who don’t is defining clearly the expected outcomes and boundaries within the role. Otherwise the basic rules for implementation requires starting small with high-impact areas, building credibility through quick wins and scaling systematically based on demonstrated value rather than theoretical frameworks.
Phase 1: Strategy
Starting out with ProductOps when it has been mainly a Product Manager’s job to deliver the operational outcomes creates a necessity to clearly state what and how ProductOps will be taking as theirs. That also includes stating what they will not be managing.
Define a specific area that the organisation sees as their most immediate operational challenge – go for the low-hanging fruit. Leadership will need a proof-of-concept with the delivery of results instead of theoretical frameworks. Easily achievable, if the initial tasks are set with clear expectations. The more complexity is introduced too early will make it harder to prove the value of the function. And that’s not because the value isn’t imminent and visual – it’s because ProductOps isn’t part of the traditional organisation structure. If you’re doing everything and everywhere, what’s the company stopping from hiring a general consultant with deeper reach?
Operations aren’t about prediction — never is it allowed to assume how a procedure is delivered. Every step relies heavily on Product Management and Engineering established workflows, and it’s well discouraged to implement ProductOps to bring in new processes at first. Process optimisation can be one of the early projects, but process building should come from the depths of experiences within the existing organisation.
However – here’s another way to look at it.
If the organisation has hired an experienced ProductOps practitioner with a comprehensive buy-in from the stakeholders, the strategy should be built from ground up. No seed picking – go straight to the core and become 100% focused on the outcome. Involving in all other departments and mitigating dependencies – that means building up a program that addresses the whole stack of ProductOps to extract the maximum value from your practitioner. It’s better to dedicate a period of time in the organisation for deep change management than try and fix procedures that have no place in the scaled future.
Phase 2: Implementation
Dependencies are the first thing ProductOps should start documenting – what’s the point of building an short-cycled Product Management system if the CI/CD infrastructure can’t support it? The organisation has to move in unison, which makes the part of Ops in Product a collaborative effort. It needs to be understood that ProductOps is the most invisible high impact structure – if it’s done well, people will take it for granted because the processes are built into the culture. But if engineering and sales aren’t doing their documentation processes as self-evident, ProductOps faces the reality of becoming Process Police. The biggest no-no for early professional development because the buy-in from leadership might be low. Without any strategic leverage, Process Police will have a short career and the company will continue to suffer.
Before anything is implemented, ProductOps assures buy-in from key stakeholders across Sales, Engineering, Marketing and Customer Success. They will need process integration and development in business activities that the Product department will have no control over. Say it’s standardised tagging of PRs or segmentation in the CRM – if the data coming through to Product doesn’t have the basics down every next step relying on that info delivery will become blocked.
Which is why it’s always easier to start with singular implementations to gain authority for larger pursuits. A common way to approach this would be to have week-by-week action items that begin with stakeholder interviews to identify highest-impact pain points and document existing processes; followed by current tool stack audit and data collection infrastructure setup. Common pitfalls to avoid here is scope creep beyond core functions, imposing processes without team input and trying to solve everything simultaneously rather than focusing on quick wins that build credibility.
Phase 3: Metrics
Performance measurement of the ProductOps team is necessary. Firstly to understand the product and engineering organisation as a whole. Secondly – picking the key metrics to set baselines on will carry the strategy from aspirational to a team that can be taken seriously. For that the baseline metrics can’t be arbitrary – they have to express the P&L for Product; finding the exact reason why ProductOps was brought into the game and being the proof-of-concept at every step.
Some other sources on ProductOps will tell you to measure pipeline speed delivery and team satisfaction, but by an unpopular opinion, I would suggest to view ProductOps success differently. Measuring any speed will fail to look at the underlying functionality of the process, and optimises for the decision-making team to cut corners, which is why it would do well to implement complex metric systems. Here’s what that means –
Having a process-oriented team like ProductOps, it will be tempting to measure their success by single parameter metrics that are only touching the role domain. Example of this would be the speed a feature is streamlined from request to ending up in development. Which essentially doesn’t measure anything else besides the Product Manager prioritising a feature to be developed as fast as possible without considering the value and the impact the feature will have on the business. Especially tempting in large organisations, where feature conveyors optimise for display rather than business results – Instagram introduced the Reel sharing feature by placing the button for it right on the screen next to the Comments. People started to accidentally repost Reels – the mechanism was really punishing as there was no confirmation button, only a temporary Undo button. The only reason to do that would be to have high feature adoption rates to show at executive meetings.
However, it’s up to Ops to push processes through seamlessly via automation. The quantification will act as a guide to understand where gaps exist and create effectiveness assessment through stakeholder feedback for a comprehensive business impact analysis.
How Product Operations supports Product Management’s success
The ProductOps role had its first mentions in the 2018-2019 period, and became popularised during remote work requirements due to covid – creating a critical need for operational infrastructure for decentralised cross-team collaboration. Now ProductOps is going through its renaissance with the accessibility of automation and AI tooling, promising to bring higher efficiency than ever before.
Convincing leadership to invest into efficiency in the early days of the company is unreasonable because the operational overhead is considered a normal side effect of growth. In survival mode, where every salary paid needs to contribute to generating revenue to ensure continued existence, ProductOps can play only the role of substitution. During then, the right operation is the one that makes more money and those operations should become processes that are automated to its teeth.
Ensuring you’re building features that bring revenue can be systematic activity built into the Product organisation – most of that will be behind understanding the markets through data quantitative and qualitative.
Key Takeaways: Mastering ProductOps in Product Management
- ProductOps bridges the operational gaps that emerge when product teams need to expand their knowledge about the market, make decisions based on user research and create efficient decision-making workflows.
- Effective ProductOps focuses on enablement infrastructure rather than process control – building self-service analytics, automated data pipelines and communication protocols that empower teams to build great products.
- AI automation capabilities are bringing a renaissance to the ProductOps field, creating opportunities that require structured data foundations and standardised processes. Positioning organisations to leverage agentic systems for competitive advantage in product development cycles.