Analytics Pillars Create Information Asymmetry by Design

There’s a logic to organizing analytics resources around business functions. Finance gets its analysts, CX gets its analysts, Operations gets its own. The ownership is clear, the domain expertise is concentrated, and every business unit has dedicated support.

The problem is that this structure consistently produces the opposite of what it promises.

What you’ve actually built is a system where the people with the most context on what the business needs have the least ability to act on it. Your product managers can see the full competitive landscape, the cross-functional opportunities, the places where two capabilities combined would create something neither could alone. The analysts they need to act on any of that are controlled by functional leads whose mandate, incentives, and visibility are all bounded by a single pillar.

The person with the most information is disempowered by the person with the least. That’s not a coordination failure you can fix with better quarterly planning. It’s structural.

What this looks like in practice

Your CX Analytics Lead controls headcount and roadmap prioritization for CX analytics. That’s a rational response to the org design. They will optimize for CX outcomes. When a product manager sees an opportunity that requires combining a CX initiative with an operational capability, they have to negotiate across pillar boundaries to staff it. By the time they’ve worked through that process, the window has usually closed or the energy has gone somewhere easier.

This produces a few predictable consequences.

Analysts sit underutilized in one pillar while another is constrained, because the capacity isn’t fungible. The waste is hidden inside what looks like clean accountability.

The most valuable insights tend to come from the seams between business functions. A pillar structure makes those cross-functional bets difficult to place because no one is positioned to see them and fund them simultaneously.

Your best product managers eventually leave. They were hired to read the full situation and make informed decisions. A structure that requires them to spend significant time negotiating for analyst access is a slow form of disrespect for what they’re actually capable of.

What to build instead

The answer isn’t a center of excellence layered on top of the existing structure, or a collaboration framework designed to smooth over the coordination problems the structure creates. Those are workarounds that add overhead without fixing the underlying problem.

The question to ask is: who controls analytical resources, and what can they see from that position?

If the people controlling resources have siloed visibility, the work will be siloed. If analytical capacity can be directed toward the highest-leverage opportunity regardless of which business function owns the problem, the work will reflect the actual priorities of the business.

This requires a few deliberate decisions. Analytical resource allocation needs to be centralized enough that cross-functional bets are possible to staff. The data leader needs real-time visibility into the full investment portfolio across all functions. And the organizational design has to make cross-functional work easier, not harder, to initiate.

Most analytics dysfunction traces back to org design, not talent. In the pillar model, the talent is usually fine. The structure is working exactly as designed. That’s the problem.