It is fairly typical for a consultant or new leader to walk into an organization and see nothing but silos. These leaders regard silos as a barrier to efficiency and make them a target for change. What they often wind up doing is replacing organically formed structures with new ones that look better on powerpoint than in practice.
Why does this happen? Let's start by digging into what a silo is. "Silo" is usually used as a derogatory term to describe a grouping that you don't like. But groupings are important in large organizations because the number of possible point to point connections makes communication too noisy and prioritization too difficult. If everyone is talking to everyone all the time, nothing gets done. Teams naturally form to confront this challenge. Complementary capabilities are assembled and scaled in highly focused work groups. Process is continuously refined because of a tight feedback loop.
To the outsider, trying to navigate these structures is confusing and frustrating. People seem unaware of what is happening outside of their group. They appear oblivious rather than focused. The reactionary impulse is to criticize the duplication of what appear to be identical functions. The ego feels good when you think you see obvious dysfunction that nobody else recognizes. It certainly feels better than having to slog through complexity that everyone else understands.
But there is great risk in introducing sweeping plans to achieve synergy before really understanding how these teams function. Even if the reasoning is valid, it is incredibly disruptive to blow up any working system and make it re-form under stress and uncertainty.
Before eliminating "silos," you need to understand why they formed. Were they imposed from the top down in order to make the organization easier to understand from the top? Or did these structures develop naturally to solve operational problems related to coordination and focus? Can the same benefits be achieved more efficiently?
You can't fix a working system until you fully understand why it is the way it is. You need to understand what is working right now and what obstacles stood in the way from the system naturally adapting to solve its broken parts. When you hypothesize dysfunction, you need to introduce your corrections scientifically and measure the results. But most importantly, you need to find the best parts and figure out a way to expand on them.