Every year, companies worldwide waste $2.3 trillion on failed digitization projects. The numbers are sobering: According to McKinsey, 70% of all digital transformation initiatives fail to meet their objectives. For digital initiatives overall, Gartner reports a success rate of just 48%.

The problem rarely lies with the technology. Drones work. AI analytics work. What doesn’t work: the path from data capture to business decision.

Where Data Integrity Breaks in Practice

Energy providers, telecommunications companies and infrastructure operators invest heavily in drone technology. Capture runs smoothly. The data exists. But between the memory card and the maintenance decision, a data graveyard emerges.

The core problem: Data integrity is understood as a snapshot, not as an end-to-end process.

Industry experts identify four critical breaking points:

1. Inconsistent Capture Standards

Different pilots, different flight altitudes, different overlap rates. The result: data that’s neither comparable between assets nor across time periods. Without standardized capture, reliable trend analysis is impossible — and neither is objective condition assessment.

2. Isolated Data Instead of Asset Context

Drones deliver thousands of images. But which image belongs to which tower? To which line? To which asset component?

Research on integrated infrastructure asset management identifies data silos as one of the biggest obstacles to effective maintenance. Without automatic asset assignment, data lands in generic folders — unusable for structured analysis.

3. Manual Analysis Bottlenecks

The reality of many inspection programs: Two employees manually evaluate tens of thousands of images. While they work, new inspection orders pile up.

According to Energy Connects, inspection backlogs in critical infrastructure grow daily — and many operators underestimate that it can take years to catch up using traditional methods.

4. Media Breaks During Integration

Findings are manually transferred to Excel lists. Coordinates typed in. Priorities subjectively estimated. Every interface is a risk point.
Experts on inspection databases warn: Isolated information pools accessible to only a few stakeholders prevent timely, informed decisions — even when the data contains critical insights about asset conditions.

What End-to-End Data Integrity Really Means

Data integrity is more than “correct data.” It encompasses four dimensions:

• Completeness and Precision: Gap-free, immutable data with tamper protection
• Contextualization: Information that relates to assets, time periods and conditions
• Accessibility: Relevant data for all authorized roles — without silos
• Traceability: Audit-proof documentation for compliance and audit trails

How FlyNex Ensures End-to-End Data Integrity

Standardized Capture

Automated mission planning with predefined parameters eliminates variability. Every inspection follows the same standards — reproducible, comparable, scalable. Safe flight corridors and complete geo-documentation are standard, not exception.

Secure Data Transfer With Asset Assignment

Encrypted upload processes and automatic asset assignment replace manual rework. Every image is assigned to the correct asset during upload — centralized, structured, searchable.

AI-Powered Analysis

Vision AI analyzes thousands of images in minutes: automatic object detection, damage classification, prioritization by urgency. Objective, reproducible, scalable — without human bottlenecks.

Seamless System Integration

API integration with EAM and CAFM systems enables direct processing. Findings flow automatically into the maintenance system — with full traceability and clear action recommendations.

From Data to Decisions: The Measurable Difference

Companies that implement end-to-end data integrity report significant improvements:

• Drastic reduction in time-to-fix through automated prioritization
• Elimination of manual evaluation backlogs
• Closed decision processes instead of isolated data collections
• Scalable inspection programs without proportional staff increases

The difference doesn’t lie in drone technology. It lies in the workflow from capture to maintenance decision.

The statistics are clear: 70% of digitization projects fail not because of technology, but because of implementation. For infrastructure inspections, that means specifically: because of missing data integrity.

Drones deliver data. Vision AI delivers insights. But only end-to-end data integrity delivers business value:

• Informed decisions instead of gut feeling
• Scalable processes instead of manual bottlenecks
• Smooth compliance instead of audit risks