Data Silos

What Are Data Silos?

A data silo is an isolated repository of data that is controlled by one department or system and not accessible — or not easily accessible — to the rest of the organization. Silos exist when systems can’t communicate with each other, when data isn’t standardized across teams, or when departments protect their data as a source of organizational power.

The result: the same business reality is represented differently in multiple systems, requiring manual reconciliation to produce any unified view.

Why Data Silos Form

Data silos aren’t the result of bad decisions — they’re the natural byproduct of how organizations grow:

Systems are bought to solve point problems: A manufacturer buys an ERP for accounting, a separate system for production scheduling, a third for inventory management, and a fourth for CRM. Each was the best tool for its purpose at the time. None were designed to talk to each other.

Acquisitions bring legacy systems: Every acquired company comes with its own technology stack. Standardizing systems takes years — in the meantime, silos multiply.

Departments build local workarounds: When the central ERP can’t answer a question, departments build their own Excel models, Access databases, or shadow systems. These become the authoritative source for their data — and another silo.

IT prioritizes stability over integration: Connecting systems carries risk. IT teams rationally prioritize keeping existing systems running over building integrations that could introduce failure modes.

The Finance Impact of Data Silos

For finance teams, data silos are the root cause of nearly every major pain point:

“We have our ERP, we have our MES, we have our PLM, we have our aircraft maintenance and management system. None of these talk very well together.” — COO, Aerospace

Manual reconciliation: Finance teams spend 40-60% of their time doing Excel ETL — manually extracting data from each silo and forcing it together in spreadsheets.

Delayed financial close: Month-end close takes weeks instead of days because data must be manually gathered from each silo before reconciliation can begin.

Conflicting numbers: When sales, operations, and finance each maintain their own data, they often disagree. “Three sets of numbers” is a common complaint — and a trust-destroying problem in executive meetings.

Invisible operational problems: When finance can’t see operational data, variance analysis stops at the financial symptom. The root cause — which lives in the operational silo — remains invisible.

P&L uncertainty: One CFO estimated he was “80% confident” in his P&L because the operational systems feeding it were disconnected. Off by $2-3M in profitability — in a business where that gap matters enormously.

Types of Data Silos in Mid-Market Companies

System Type	Common Tools	Data It Holds
ERP	NetSuite, SAP, Dynamics	GL, AP, AR, inventory, purchasing
Production/MES	Various	Production orders, routing, machine data
CRM	Salesforce, HubSpot	Customers, opportunities, orders
HR/Payroll	ADP, Paylocity	Headcount, compensation, labor hours
3PL/Logistics	Various	Shipments, freight costs, delivery
Project Management	MS Project, Procore	Job status, labor allocation
Spreadsheets	Excel	Everything that doesn’t fit elsewhere

Breaking Down Data Silos

There are three main approaches:

Replace systems with an integrated suite: Consolidate onto one ERP that handles everything. High risk, high cost, rarely achieves full integration in practice.

Point-to-point integrations: Build direct connections between each pair of systems. Creates a web of brittle integrations that break when either system changes.

Centralized data integration layer: Connect all systems to a central platform that handles extraction, transformation, and delivery of unified data. Preserves existing systems while eliminating the silo problem at the reporting layer.

The third approach is typically the fastest and lowest-risk path for mid-market companies.

How Go Fig Breaks Down Data Silos

Go Fig connects to the systems where your data lives — ERPs, production platforms, CRMs, databases — and builds a centralized data layer that gives finance and operations teams a unified view without replacing any underlying system. The result is a single source of truth that eliminates manual reconciliation and makes the data from every silo available to the people who need it.