One Question. Real Answer | S1 E1: The Biggest Modernization Misconception

sa.global · Beginner ·📊 Data Analytics & Business Intelligence ·4mo ago

Key Takeaways

Discussion on the biggest modernization misconception for service-centric organizations

Original Description

What's the biggest misconception service-centric organizations have about modernizing with Microsoft? Stefanie Richter, Business Development Manager at sa.global, sits down with Jennifer Holman, Solution Architect at sa.global, and Quintin Hunkin, Solution Engineer at Microsoft, to tackle the question that trips up organizations before they even get started. Modernization almost never fails because of the technology. It fails because the operating model didn't change with it. Service-centric organizations tend to modernize system by system, a CRM project here, a billing project there, a reporting project next. But the organizations that get the biggest lift treat the Microsoft cloud as an end-to-end lifecycle platform where sales, delivery, resources, and finance operate in a single flow of data. And replacing your ERP isn't enough either. If project managers are still working in spreadsheets, resource managers won't trust the system, leadership won't have real-time visibility, and all you've done is digitize your old processes. The key takeaway: modernization is a shift in how the entire business operates, not just the technology it runs on. #DigitalTransformation #ERPModernization #MicrosoftCloud #BusinessTransformation #OneQuestionRealAnswer #Microsoft
Watch on YouTube ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Related Reads

📰
Tracking Macroeconomic Indicators with the Finance Toolkit
Learn to track macroeconomic indicators using the Finance Toolkit and understand its importance in global economic trends
Dev.to · Jeroen Bouma
📰
Pydantic for Data Engineering: Schema Validation in ETL & Pipeline Contracts
Use Pydantic for schema validation in ETL pipelines to ensure data consistency and quality
Dev.to · Gowtham Potureddi
📰
Half of Data Engineering Jobs on LinkedIn Aren't Real
Understand the discrepancy between reported data engineering job growth and actual job availability on LinkedIn
Dev.to · DataDriven
📰
Evolutionary Data Through Schemaboi: Achieving Forward, Backwards, and Sideways Compatibility
Learn how Schemaboi achieves forward, backwards, and sideways compatibility for evolutionary data through self-contained schemas in file headers
InfoQ AI/ML
Up next
6-Phase SQL Roadmap 2026 | Data Analytics & Engineering | #shorts
SCALER
Watch →