Ideas on enterprise technology
Practical perspectives on supply chain, retail, data, AI, and quality engineering from the team delivering enterprise programs every day.
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What It Takes to Raise Productivity Across Your Business by 50% or More with Claude AI
How Everest Technologies pairs Claude AI with assessment, change management, team dynamics, and quality engineering to lift productivity across the business.
Your Data Is Connected. But Can Your Business Trust It?
Connecting data is only the beginning. Here's why data quality, governance, and consistent business definitions matter just as much as the pipelines that move data.
How to Improve Your Warehouse Management System: 7 Practical Fixes
Most of the work of improving a warehouse management system sits in data, configuration, integration, and testing before it sits in new software. Here are seven practical fixes, in order, plus a quick check for when to replace the platform instead.
How to Manage Operational Complexity in Beverage Distribution
Beverage distributors rarely fall behind because of one failing system. They fall behind when SKUs, channels, and packaging formats grow faster than the warehouse, labor model, and systems behind them.
5 Retail Inventory Visibility Challenges and the Role of OMS
Inventory visibility means knowing what stock you have, where it is, and how much is already reserved for customer orders. Here are five common retail inventory visibility challenges and the role an order management system plays in solving them.
Your Data Knows What Happened. Can AI Help Predict What's Next?
Cost forecasting is getting harder as supply chain, procurement, and market conditions keep changing. Here's how combining data engineering and AI can help organizations move from historical cost reporting to forward-looking cost intelligence.
In What Order Should You Automate Your Supply Chain? A Practical Strategy Framework
Winning supply chain automation starts with automating the right things, in the right order. That means defining the objective and naming one accountable owner first, building the data and warehouse management foundation second, and adding physical automation third. Most programs get that sequence backwards.
How Much Autonomy Should an AI Agent Have in Your Warehouse?
An AI agent should have as much autonomy as the cost of a wrong decision allows. A three-tier decision-rights framework for warehouse AI agents: what to auto-execute, what to recommend for human approval, and what to always escalate.
Why Your Enterprise Data Isn't Delivering, and What to Do About It
Most enterprises do not have a data shortage. They have a data assembly problem: hundreds of applications holding partial views, and no governed layer that turns those views into one number anyone will act on.