For many organizations, the issue is the way systems and processes have built up over time.

A finance team may work from one view of performance, while sales or operations use another. Service teams may hold useful client information that never reaches planning. Supply chain updates may arrive too late to shape decisions. And when reports do not align, teams spend time chasing and checking the data instead of acting on it.

Common challenges include:

Teams working from different versions of performance data
Data arriving too late to support fast decisions
Information trapped across ERP, CRM and other systems
Spreadsheets filling gaps between processes
Manual reporting taking time away from higher-value work
Inconsistent governance across data sources

These challenges may feel operational, but their impact is strategic. Leaders lose time chasing clarity. Teams duplicate effort. Governance becomes harder to maintain. And the business becomes less responsive at the moments when speed and confidence matter most.

For a deeper look at why AI initiatives stall before they scale, explore Avanade’s infographic: When AI ambition meets operational reality

Why more data is making organizations slower