Recently, I had the opportunity to present to a group of early-stage
founders about evolving their engineering organizations.
While preparing, I realized that despite my excitement for this topic,
I’ve only written about it indirectly.
The most comprehensive, related piece I’ve written is about running reorganizations.
Reorgs do involve quite a bit of organizational design, but
they’re a difficult environment to demonstrate best practice.
They’re typically implemented in short order and
heavily constrained by business needs, team health and available leaders.
Good organizational design is a directed evolution that balances
the pursuit of a clear destination with the willingness to repeatedly
adjust your path towards that destination.
The algorithm I’ve found effective is:
- Measure what you hope to improve before you make changes.
- Size your organization against your peers, goals and performance.
- Structure into teams and groups.
- Project your organization’s future growth.
- Rest between changes to develop mastery.
Org design is a topic where solid fundamentals go surprisingly far, and
that even the most experienced folks sometimes find difficult.
This framework isn’t a secret formula for organizational design,
but it will guide you towards all the right questions, as well as the
standard answers to those questions.
Not the final word, but a good start.
Organizational design isn’t defined by approaching an ideological ideal,
it’s judged by its effectiveness at solving your current needs.
Measurement is the underpinning of clearly understanding your reality, and
is the first step towards good organizational design.
This first step is skipped surprisingly often, to unquantifiable results.
The biggest reason its skipped is that measuring how well your organization works
is exceptionally difficult.
Some of the measurement approaches that I’ve found effective are:
- Define goals with a clear timeframe and target,
and continue measuring your performance against your goals to
develop confidence in your forecasting.
- Identify proxy metrics that correlate with your goals.
Accelerate’s definition of productivity is
a great example of using proxy metrics.
- Measure your organizational health, looking at metrics like
employee referral rates, employee attrition, and team health surveys.
- Instrument your planning processes to generate productivity metrics
perhaps using task or story points velocity.
While this kind of metric is rarely precise, they are often very useful.
- Model behavior using a systems model, and adjust it parameters
to refine your intuition on how your current organization works.
- Create synthetic metrics that package a variety of signals
into a structure that you can reason about usefully.
You don’t need to do all of these, just focus on one or two
that work for you. As your organization grows,
you’ll incorporate more of these, but there’s no need to go overboard:
pick a couple, remember to use them, and you’re well on the path to good
Once you’re measuring how the current organization,
the next step is to determine your target organizational size.
How far to look into the future will depend on your stage, and
might range from three months for a very small company to
multiple years for a mature one.
The speed of your hiring funnel determines the start of
your planning horizon, and the predictability of your
business determines the horizon’s end.
Once you pick a horizon, say six months, the next comes is to
calculate your organization’s ending size.
Most companies determine their size by merging momentum and hiring velocity
into a projection, but that can create an investment interia
that’s initially quite reasonable and slowly slips into efficiency.
Three more useful sizing strategies are:
Benchmarking against similar companies.
Talk to five slightly larger companies and build a small dataset
of how they’ve sized their organization. Every company is different:
faithfully copying another company’s approach is cargo-culting.
but learning from a handful to identify useful upper and lower bounds
is benchmarking. Benchmarking is a remarkably sound technique to cheaply
determine the range of reasonable solutions,
and I’d recommend it as the initial approach to solving almost any
organizational problem, including sizing.
Project forward through systems model.
Use the same systems modeling techniques you used to measure
your throughput to project future throughput.
It’s particularly important to factor in your
as hiring and training more recruiters usually creates
resistance towards rapidly accelerating hiring,
and having hired recruiters creates a similar resistance
to rapidly decelerating hiring.
Forecast backwards from goals and roadmap.
Benchmarking and modeling both have a tendency to overfit
on your current organization, but sometimes you’re looking
to accomplish something far beyond your current organization’s
capabilities. In that case, take your future targets and
reason about what you’d need to accomplish those, very
studiously ignoring your current configuration.
For example, you might do this purely from a financial projections
perspective, then reason about the kinds and quantities of products
or businesses your company would need to met those, and further from
those products to a company size.
Each approach exposing different gaps in your projections,
which makes your estimates the most powerful when you apply all three together.
Once you’ve satisfied the three perspectives, it’s time to convert
your size into a structure.
An organization’s size is just a number, its structure is how
the pieces fit together and accomplish useful things.
Even the most complex organizations are composed from a handful
of simple organizational atoms.
The three organizational atoms I build with are:
- Teams are groups of six to eight engineers with one engineering manager,
with a shared purpose, a shared oncall, and who work together closely.
- Each team is composed of one or two workstreams, which represent their ability
to parallelize project execution. Generally I’ve found workstreams of three to four engineers work
best, with smaller workstreams often representing a failure to limit work-in-progress.
- Every five teams is then collected into a group, which are a composition of related teams
that work on adjacent work. Each group is managed by a group engineering manager, who supports the
managers on the teams within their group.
- Beyond this point, recursively collect every five groups into another container,
the next of which you might call a pillar, an organization or whatnot.
Each container has an engineering manager, who supports the managers within their container.
You can mostly ignore workstreams during the organizational design phase,
as they are more relevant during roadmap and sprint planning.
I debated if they’re worth mentioning here at all, and decided that they are worth introducing
because they address the primary concerns with establishing such “large” teams of
six to eight. Namely that you need to focus on more projects than you have properly sized teams,
which often pulls folks towards smaller teams: just add workstreams to a proper teams instead.
From atoms to structure
Converting your size into your structure is then a simple process:
teams = size / 8
groups = teams / 5
org = groups / 5
# and so on
For example, imagine you have sixty engineers:
size = 60
teams = 60 / 8 # 7.5 teams
groups = 7.5 / 5 # 1.5 groups
orgs = 1.5 / 5 # 0.3 orgs
Starting with the largest containers first, ususally organizations,
recursively balance the areas of responsibility across the containers.
You need one organizations, let’s call it the engineering organization.
Then you need two groups, perhaps you’d start with the classic product and
infrastructure split. Then each of those groups needs four teams, which you’d
split according to your needs.
Of course , the tree doesn’t have to be perfectly at all times, and most
companies start out weighted towards product engineering.
It’s tempting to invest very, very heavily into exactly how these groups
are defined, but it’s my experience that it’s easy to overoptimize these decisions.
There is no one right way to divide groups, but there are a handful of
useful rules you can use to identify reasonable structures.
Some rules of thumb to consider while you’re identifying scope for groups and teams are:
- Conway’s law argues that organizations
create products that reflect their own structure. Use this to your advantage,
shaping your structure to reflect the products you want to create.
- Minimize cross-team coordination, including the predictability tax,
by making teams as self-contained as possible.
Teams should depend on as few other teams as possible to accomplish their goals.
This is also true recursively for groups, organizations, and so forth.
- A short escalation path allows you to quickly resolve conflict. This is accomplished
by grouping dependent teams as closely together as possible, and by keeping your org tree
somewhat balanced, in particular avoiding long, skinny reporting chains.
- Structure according to company needs, not overfitting on individual preference.
Some companies heavily incoporate senior leaders' areas of interest into their organizational
structure, and this approach accumulates organizational design constraints over time.
You can go surprisingly far with the above atoms and rules for structuring organizations.
More structuring tips in Rules of thumb for org design.
Now that you’ve design your organization for the next year or so,
it’s surprisingly powerful to extend your planning horizon a bit further.
If you just sized and structured for six months, and
then take a stab at projecting out to twelve and eighteen months.
The further out you project, the less accurate your projects, so
the goal for these additional attempts at sizing is to perform
a rough sort of sensitivity analysis to identify breaking points when your
organization will have to undergo major transitions.
Typically these transitions are adding additional layers of management,
which in balanced engineering organizations will occur roughly at 40 engineers,
200 engineers, and further entries in the sequence of
8 * 5^N.
If your projections cross any of those thresholds, then know that you’ll
need to invest disproportionally more time during that period on coaching your team,
redesigning your process and potentially hiring experienced external leaders.
More on adding practices in Best practices on org best practices.
At this point you’ve finished your organizational design, and there
is only one commandment left to master: stop making organizational changes.
Although these changes feel useful, productivity always occurs between
organizational change, not during it.
It’s only after you stop making changes that folks begin to practice working
in the new structure, slowly building mastery in the new paths of production.
The time to acclimitize increases as an organization grows, with small teams
tolerating a couple of changes each year, and larger organizations sometimes
requiring years of stability to rebuild momentum.
As a rule of thumb, if you haven’t been able to update your measurements
before you’ve proposed a new update, then you’re changing too frequently.
Learning takes time, but it’s the only way to consistently improve an organization.
If there is a core belief in my approach to management, it’s that quality management decisions
exert a subtle, enduring and ultimately defining influence on company health and
company outcomes. Following a structured, deliberate approach
to sizing and structuring your engineering organization doesn’t require
unique insight, is learnable, and it works: give it a try.