The IT landscape and legacy systems are among the most significant reasons automation projects and intelligent in-motion software implementations fail, serving as the “silent” killers that are often underestimated.

When the IT landscape comprises multiple legacy and new systems connected through numerous interfaces, issues such as lag, disconnects, synchronization problems, and frequent downtime arise; you have effectively awakened your own personal Frankenstein’s monster that clashes with your new foundations.

1. Shit-In-Shit-Out

Intelligent software requires reliable, accurate data. If your data sources are inaccurate or in bad shape, you will fail.

2. Real-Time Data

Older systems often use batch processing that is not real-time. When intelligent software uses in-motion data for task synchronization, the data must be real-time; otherwise, you will fail.

3. Technical Debt

Technical debt is the historical shortcuts that become barriers to overcome. Instead of investing in innovation, you spend most of your IT budget on maintaining Frankenstein’s monster.

4. Blindness

Intelligent software fails to automate when you try to automate a mess. Undocumented processes and a complex IT landscape often prompt operators to create workarounds and “shadow processes.” These unofficial workflows disrupt automation deployment and will cause you to fail.

When deploying intelligent software and AI to digitize and automate your operations, there are two fundamental considerations to keep in mind.

• SOFTWARE. You need software built on subject-based execution, real-time data, and location awareness (X/Y/Z).
• PEOPLE. You need people with holistic supply chain experience to automate your end-to-end operations.