Productization of a System 06.2021


Amongst digital products, systems are most commonly considered as internal services that are created to support, scale or distribute the organization's product offering. By this definition, systematic processes are inherently invisible to the end customers and their direction is tightly coupled to the roadmap and the needs of the products that consume them.

To offset the upfront infrastructural cost of a system 1, architects tend to abstract the system’s functions to be as horizontal as possible 2. This approach allows systems to stretch across the boundaries of multiple product verticals within the organization, and if the abstraction is sufficient to support similar functions for products outside of the same company.

Productized systems

When systems have the opportunity to serve external customers, their productization becomes necessary. As products on the open market, they face a set of challenges and requirements which did not exist when they were operating as internal services.

In addition to being sufficiently abstracted to solve non-specific problems tied to the context of a single company (e.g. a system that is designed around a proprietary workflow or technology), the process of building a system-product largely overlaps to the one of building any other product, with some key differences.

In the early stage of their development, all products go through a process called “the fuzzy front end” 3, which helps identifying business opportunities and market fit. Since system-products can be incubated inside of an existing organization, they are able to validate these concepts quickly and at no cost, which allows them to focus immediately on problem solving.

We know that abstracted systems last longer and function better 4.
System-products take this axiom to heart and build on a set of loose foundational assumptions based on user or market needs. For example, CircleCI is built on the idea that businesses in a competitive market need to build products at speed, and continuous integration can help them be more efficient. It's also a product which must integrate with existing engineering and deployment environments with little cost.

These foundational statements should be simple and scoped enough to allow the system-product to focus on its core mission without distractions. The Pareto principle 5 can be applied for a broad strokes guidance to identify which areas of the product are able to deliver the most amount of value. Pareto is not only useful from a product management standpoint to identify which 20% of the product drives 80% of the engagement, but also as a guiding principle for prioritization and sequencing of engineering practices, where 80% of the product design and code can be created in 20% of the time. Establishing these areas of opportunity early on prevents systems-products from working on areas that have flat or diminishing returns.

A Pareto-inspired system-product is also able to reach its customers faster than a competitor. Time to market is a lead indicator of the success of a product since it allows product owners to validate their assumptions early, directly with their customers and to begin growing their user base sooner.
It not only provides unique insights which can help steer the product's direction, but it reduces capital risk by allowing resources to be re-allocated at shorter intervals instead of taking larger, longer bets which minimizes the opportunity cost 6 of every investment.

The development of Git began on 3 April 2005 Torvalds announced the project on 6 April and became self-hosting the next day. The first merge of multiple branches took place on 18 April.
Key dates from the iterative Git timeline

Successful system-products are built iteratively with customers and incrementally by growing in their feature set over time.
As we learned, an agile approach allows a lean product to capture market opportunities in a timely manner. A notable example of that is the rise of Git. Since 2002, Linus Torvalds and his team had relied on BitKeeper, a development tool which was provided for free in support to the project, to track code changes for the Linux kernel.

Three years later, BitKeeper announced that they would no longer offer their software for free and that the team would have to pay costly licensing fees to access their proprietary solution 7. Unwilling to pay for a license, and left without any other viable alternative to manage their workflow, Linus created an open source, distributed version-management tool called Git, specifically to source-control the Linux kernel project. Git started on April 3rd 2005 and just seventeen days later 8 Linus publicly released the first version of the software.

There are other reasons beyond its incredible velocity to market to why Git’s history is an exemplary system-product. The project was founded on a limited set of goals, which helped contain the complexity of the product 9 and allowed for a faster development cycle. Speed itself was in fact one of the core attributes of Git since it’s inception:

  • Patching should take no more than three seconds
  • Follow the Concurrent Versions System
  • Support a distributed workflow
  • Include safeguards against corruption, either accidental or malicious

Today, sixteen years and over forty incremental releases later, Git is the most widely used version control system in the world, and it is at the core of services like GitHub, GitLab and Bitbucket.

Learning organizations

In addition to starting small and shipping early and often, the ability of an organization to deliver value to its customers is directly proportional to its ability to learn. Learning is unequivocally a vector of positive change, and is fundamental for the growth of any system-product.

As organizations aim to reach customers faster, they must adopt processes which promote frequent evaluation of progress and consequent adaptation. These agile processes prescribe a linear set of steps in addition to a validation loop, which can be executed multiple times.

The validation loop is designed to accept or reject a solution hypothesis through direct experimentation with customers, and has the goal to incorporate the results of these tests into the final product. Evaluating the outcomes of each experiment is part of the analytical process that characterizes a learning organization.

In his book The Fifth Discipline, Peter Senge defines learning organizations as institutions

where people continually expand their capacity to create the results they truly desire, where new and expansive patterns of thinking are nurtured, where collective aspiration is set free, and where people are continually learning how to learn together.

Senge's analysis describes the five key disciplines that organizations must be skilled at in order to master learning: systems thinking, personal mastery, mental models, shared vision and team learning. Before they can master any of these practices, organizations must develop a set or pre-requisites that are foundational to effective learning. The three skills that companies must practice in order to be successful at learning are intellectual honesty, transparency and adaptability. Let's take a look at each one of them in detail.

Intellectual honesty

Intellectual honesty 10 is the practice of leading with integrity and fact-based evidence. It grounds the organization in heuristics and data and promotes the scientific method as the center of the decision making process. In larger organizations, it also provides the perspective needed to evaluate how each individual decision impacts the large picture, without being distracted by internal narratives or by goals that don't accrue to the core value of the product.

Intellectual honestly is tightly coupled to systematic problem solving and learning from past experiences, and combined to other skills can lead to profound change. As we see more and more companies take an introspective look to solve cultural and product problems, intellectual honestly is the first step in acknowledging what the organization is great at and what are its areas of opportunity. As with any journey centered around an entity, the sharper the introspective analysis is, the more tactical and actionable the outcome will be for the company.


Effective communication is fast and transparent and it’s the second skill needed to facilitate learning. Successful systems allow information to flow freely between the actors that are involved in creating and using the product and create channels of communications between workers and customers that allow each to share information in a bidirectional manner.

An example of transparent communication is ”building in public”: it consists in creating products by connecting companies and customers directly through tools like public roadmaps and feature requests. Users are invited to actively contribute to the future of the product by engaging with the company backlog, upvote their favorite product features, and request new functionality directly to the organization.

On their end, companies like Buffer and GitHub share their public roadmap with their customers, giving visibility into which features are being worked on in at each given moment, and what will be up next, as a mean to validate their service attachment and keep create a sense of co-ownership with their customers.


Adaptability is at the core of every learning organization. For learnings to be put into action, they must first become a vector of change inside the company; and the organization's ability to implement those changes successfully impacts the likelihood of better performance in the future.

As the old adage goes “it’s difficult to steer a cruise ship”. We discussed how smaller systems have inherit benefits towards enacting change 11 but an organization's ability to adjust to new circumstances is not always correlated to its size. During the 2020 Covid crisis, a number of large manufacturers across the world were able to pivot their systems to begin producing hospital supplies masks and ventilators 12,13 at record speeds. These companies responded to a global crisis with extreme agility both by repurposing existing production lines and retooling their production plants to produce what the medical community needed the most at the time, in a concerted example of worldwide adaptability.

The ability of a product to evolve based on learnings is an infrastructural and cultural investment that companies should pay attention to early on. When adaptability is a core value of an organization, the cost of change becomes minimal and the opportunity that the change brings is maximized.

Competitive systems

As system-products become available on the open market they need to bolster their resilience against similar products. Through the productization process, systems need to develop one or more differentiating factors to attract more customers. This unique value proposition can take many forms, and most commonly it consists of a combination of competitive features, differentiated brand and an aggressive time to market strategy. The more competitive the blend, the larger the advantage the system will have on the market.

Competition is a positive force that drives continuous change into a healthy market and puts pressure onto companies to improve their products. Learning organizations are inherently more competitive because of their ability to pivot quickly and capture market opportunities that other companies are not able to go after. This behavioral skill set can lead to disruptive innovation in dormant market sectors and generate interest that can re-energize the market.

Amidst many, Uber is a notorious example of a system-product (on-demand ride hailing) that was able to expand across and innovate multiple industries. From transportation to food delivery, the company was able to capitalize on a single conceptual innovation by being introspective in regards to their performance, creating tight communication loops with its users, and adapting their existing model to specific market verticals.


  1., Systematism Beyond Design Systems, Do I need a System?. ↩︎
  2., Separation of Concerns in Systematic Design, Transversal Separation. ↩︎
  3. Wikipedia, Front End Innovation. ↩︎
  4., Systematism Beyond Design Systems, Abstracted Systems. ↩︎
  5. Wikipedia, Pareto Princple. ↩︎
  6. Investorpedia, Opportunity Cost. ↩︎
  7. Forbes, A Setback for Linux. ↩︎
  8. Linux Kernel Mailing List archive, Linux 2.6.12-rc3. ↩︎
  9., Separation of Concerns in Systematic Design, Scale. ↩︎
  10. Wikipedia, Intellectual Honesty. ↩︎
  11., Separation of Concerns in Systematic Design, Conclusion. ↩︎
  12. The Verge, How GM and Ford switched out pickup trucks for breathing machines. ↩︎
  13. Triple Pundit, 15 Companies Retooling Their Operations to Fight COVID-19. ↩︎


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