The evolving R&D organizational structure
The evolving R&D organizational structure
The evolution of the organizational structure within Research and Development (R&D) teams mirrors the growth trajectory of a company from a fledgling startup to a robust enterprise. This progression is characterized by significant changes in both team configuration and operational processes which are aimed at enhancing innovation capacity, market responsiveness, and scalability as the startup evolves. I’ll cover the changing nature of the R&D organization over three distinct phases: early, mid-stage and growth. I’ll also highlight some of the key areas of focus and challenges within each stage.
Early Startup Stage (0-30 Engineers)
In its early days, a startup operates with a flat organizational structure, typically staffed by fewer than 30 engineers. This stage prioritizes agility, with team members often undertaking multiple roles to drive rapid innovation and establish a strong product-market fit. The streamlined communication and decision-making processes inherent in a flat structure foster a dynamic environment conducive to experimentation and quick pivots.
The R&D organization is typically organized in software development teams of 2-6 engineers. These teams are dynamic, both in terms of their composition and the work they perform. A team might work on a particular area of the product for a period of time and then pivot to any entirely different area once they are done. This dynamism is a function of trying to rapidly respond to market dynamics as the startup tries to attain product market fit.
This phase represents the quintessential startup experience. It is fast paced, with very low bureaucracy. Decisions are rapidly made. Alignment between and across teams is natural. It can be a hectic and somewhat chaotic period, as engineering teams will tend to move quickly and also rapidly change direction. The flat nature of this phase requires individuals who are self-driven and able to unblock themselves - managers might not exist in this phase.
This phase also sees a marked difference between how the organization is structured from a reporting perspective and how it works. The reporting structure is flat, with all engineers reporting directly to the Head of Engineering, who is typically a technical co-founder. On the other hand, the working structure is team-based with ephemeral and dynamic teams.
Early Growth Stage (30-100 Engineers)
As the team grows beyond 30 engineers, the organizational structure evolves to include more layers. Roles become more defined, with the addition of a Managers, Directors of Engineering and Tech Leads to guide the expanding teams. Specialized groups may be formed to focus on specific domains like Infrastructure or QA, reflecting a deeper specialization within the team.
This phase starts to witness the introduction of long-lived teams. Teams are formed with the intent to focus on one area of the product for the long-term. This is in contrast to the earliest stages where teams can move from one area to another in quick succession. Additionally, new teams will be formed during this phase. These teams might not be concerned with developing customer facing features. Examples include an Infrastructure team, a Platform Engineering team and a Data team. These teams are enablers and typically concerned with supporting the wider R&D organization by being responsible for the CI/CD pipeline, tooling, developer productivity, cloud infrastructure and capacity planning and so on.
During that phase, the organizational structure and working structure tend to get closer to a 1:1 mapping. Conway’s Law can become a reality in this phase.
One of the biggest challenge in this phase is the transition from the fast faced and amorphous nature of the earlier stage. Veteran team members might find that adapting to a more structured environment can be difficult, especially if they accustomed to the flexibility of a smaller setup. This phase can start witnessing the departure of some of these earlier veterans who might decide that they are better off working at a much smaller organization. Communication can also become more complex especially between departments that might not have existing in the earlier phases e.g. GTM.
Another challenge in this phase is around resource allocation especially if the startups starts to “take-off” With resources stretched across multiple projects, R&D leaders are tasked with making tough choices about where to invest—balancing the expansion of existing successful projects with the exploration of new, potentially groundbreaking ideas. Hard tradeoffs are the name of the game during this phase.
Growth Stage (100+ Engineers)
Once the team size exceeds 100 engineers, the company typically restructures around specific products or services, with VPs of Engineering leading larger segments. This structure aligns R&D efforts more closely with strategic business objectives and facilitates resource optimization across a larger scale.
The nature of the startup also changes at this stage. Growth is no longer the only area of focus, but ensuring that the startup is scaling efficiently. Therefore, the responsibilities of R&D will no longer just be concerned with building new products or features, but doing that in an efficient manner. This stage might see the introduction of new processes to track and hit targets for key metrics. Examples include the following:
Revenue / R&D head
% time on KTLO vs building new product capabilities
R&D OpEx / head
Gross margins, especially for SaaS companies where R&D will have an impact on this metric
Another notable change during this phase might see the expansion of the R&D team to new geographies, perhaps even the creation of hubs in cities with critical mass.
Talent management can also become a significant hurdle at this stage. The growth phase often necessitates a rapid expansion of the R&D team, which can dilute the quality and alter the cultural fabric of smaller teams. Attracting and retaining top talent becomes a high-stakes game so is onboarding all the new talent needed to rapidly scale the organization and the business.
The changes of the R&D organizational structure along these phases aren’t cut in stone so to speak. I’ve witnessed R&D organizations with 60+ engineers that are still capable of functioning in a similar mode to the early stage structure. I’ve also been at startups that had a more regimented and structured approach at the earliest stages too. I’ve also see hybrid approaches work all too well where a portion of the organization works on long-lived and thematic teams whilst the rest operate in this every changing and dynamic manner. Even though I presented these changes over clear phases, I believe in being pragmatic and introducing these changes if and when they are needed. After all, the organization structure should be used as a tool to facilitate two key outcomes: pushing the business forward and ensuring the productivity and happiness of your team.
Finally, the articles, some from this blog and from other sources below, could be of relevance to this topic: