What's a Silo? (and why they ruin everything)

If you've seen enough conference presentations, you've likely come across the following image (original photo credit to Doc Searls) along with statements like "Silos are bad" or "Get rid of Silos." Usually, the presenter will then move quickly to another topic. Rarely do we get much analysis on what Silos actually are and why they are so destructive.

silos are bad

So what exactly is a silo?

The term “silo” is bit of jargon that was born in the Lean manufacturing movement and popularized by the DevOps movement. Some people mistakenly think "teams = Silos", but in reality, Silos don't have much to do with organizational structure and have everything to do with how a group works.

In simple terms, a group is said to be ‘working in a silo’ when its members find themselves working in a disconnected manner from other groups. Look for groups that are working in a different context from other groups, work is coming from a different source (i.e., different backlogs), and working under different incentives or priorities (and often a different management chain). It is almost certain that group is working in a Silo and you will find the usual "Silo Problems" around it: bottlenecks, slow handoffs, miscommunication, tooling mismatches, delivery errors, excess rework, and conflict (usually the finger-pointing type).


silos illustrated

Of course, teams don't set out to work in Silos or suffer from the consequences of Silos. It is usually the natural byproduct of the human urge to "optimize" large-scale efforts by sorting people according to functional specialization and grouping like-with-like.

Problematic handoffs (too slow, incorrect, lots of rework, etc.) are the most commonly cited problem attributed to Silos. While this is probably true in most organizations, it is good to unpack that a bit and understand the common causes of handoff problems.

  • Information mismatches – The parties on either side of the handoff are working with different information or are processing the information from different points of view, leading to an increase in errors and rework (i.e. repeat work due to previous errors).
  • Process mismatches – The parties on either side of the handoff are following either different processes or processes that are nominally the same but take a different approach and produce results not expected by the other party. Timing and cadence mismatches between parts of a process that take place in different silos also lead to an increase in errors and rework.
  • Tooling mismatches – An increase in errors and rework is seen when different parties on either side of silo boundaries are using different tooling or tooling that isn’t setup to connect seamlessly. When the work needs to be translated on the fly by a person moving information and artifacts by hand from one tool to another, delay and variance are bound to be introduced into the process.
silo mismatches



Ticket-Driven Request Queues 

On the surface, request queues seem like an orderly and efficient way to manage work at organizational divides. However, if you look under the surface you will find that request queues are a major source of economic waste for any business. They are often the manifestation of Silos and a leading indicator that you are going to start seeing Silo effects (if you haven't already).

Why are requests queues a major source of economic waste? Let us look at the list created by noted author and product development expert, Donald G. Reinertsen.

Queues create:

  • Longer Cycle Time – Queues increase cycle time as it takes longer to reach the front of a large queue than than a small one. Even small delays can exponentially compound within a complex interdependent system like an enterprise IT organization.
  • Increased Risk – Queues increase the time between request and fulfillment which in turn increases likelihood of context of the request changing. If a problem does arise, the requester is now in a different mental position (often working on something else) from where they were when they made the request.
  • More Variability – Longer queues lead to high levels of utilization and higher levels of utilization amplify variability. This leads to longer wait times and a higher likelihood of errors.
  • More Overhead – Queues add a management overhead for managing the queue, reporting on status, and handling exceptions. The longer the queue, the more these overhead costs grow in a compounded manner.
  • Lower Quality – Queues lower quality by delaying feedback to those who are upstream in the process. Delays in feedback causes the cost of fixing problems to be much higher (e.g. bugs are easier to fix when caught sooner) and often means that additional problems of a similar origin have been created before the first negative feedback arrives.
  • Less Motivation – Queues have a negative psychological effect by undermining motivation and initiative. This is due to queues (especially longer queues) removing the sense of urgency and immediacy of outcomes from the requestor’s work. If you don’t feel the impact and don’t see the outcome, it’s human nature to grow negatively disconnected from the work.
request queues cause


Of the various economic wastes created by managing your work through ticket-driven request queues, perhaps the easiest to communicate to the business is the idea of "cost of delay."

For every delay introduced into a company’s processes, there corresponding effect of reducing how quickly the business can react to market signals and how quickly the business can deliver. While the impact of each delay can be almost imperceptible, in an organization full of request queues the delays add up (and compound) quite quickly.

cost of delay

The downward spiral of silos and ticket-driven request queues

The stronger the Silo effects, the longer the requests queues become. The longer the request queues, the stronger the Slio effects become. These adverse effects reinforce each other and drive organizations into a downward spiral of bottlenecks, waste, and management overhead.

As the downward spiral continues, organizations find themselves in the dreaded position where "everyone is working beyond capacity, but nothing seems to be getting done." This is a frustrating way to work, and it leads to talent drain ⏤ which just further feeds the downward spiral.



How to get rid of the Silos and ticket-driven request queues

There are two parallel strategies to achieve this:

1. Get rid of as many silos as you can

Forward-thinking organizations are focusing on creating “cross-functional teams” or “market-oriented teams” that can handle as much of the lifecycle as possible (without needing to hand off work to other teams). It is very difficult for silos to form if you don’t have handoffs or breaks in context and everyone is working from a single backlog with common priorities.

cross functional


2. Apply the Operations as a Service design pattern

In the many cases, especially in the enterprise, you won't be able to avoid functional specialist teams. Silos will want to form, but with the right tools at hand, you will be able to mitigate any adverse impact and counteract the Silo effects as they arise.

Operations as a Service does just that by enabling both the definition and execution of operations activity to be delegated throughout a broader organization and across traditional organizational boundaries. Wait time will be eliminated, feedback loops will be shortened, breaks in context are avoided, tooling is aligned, and labor capacity is improved.

cross functional and oaas



To read more about Silos, Ticket-Driven Request Queues, and the Operations as a Service design pattern, I recommend you check out the book "Operations as a Service:Rethinking IT Operations to Solve Today’s Challenges." You can read it online (or grab the pdf to share or read on the go).