Field Service & Aftersales Insights
Perspectives on Service Growth, AI in Aftersales, Operation and Technology
This page brings together perspectives on field service, aftersales operations, and emerging technology in manufacturing and automotive service, grounded in real implementation experience.
The articles here explore what is changing, what is working, and where execution often breaks down. Topics range from KPIs and AI adoption to dealer operations, warranty management, and the day-to-day decisions that determine whether a transformation program succeeds or stalls.
Pick a topic below to explore further or browse the latest insights.
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Latest Insights
The 2026 Service Blueprint: From Predictive AI to Agentic Operations
2026 marks the end of AI experimentation and the rise of Agentic Execution. As assets become software-defined and margins shift to uptime, service leaders must master Industrial FinOps and ‘teleporting expertise’ to protect Customer Lifetime Value. Discover the five pillars of the 2026 service blueprint.
2025 Aftersales & Field Service Review: From Ambition to Operational Reality
2025 was a reality-check year for aftersales and field service. Demand stayed resilient, but workforce shortages, asset complexity, AI scaling limits, and regulatory pressure reshaped execution. Leading organizations shifted from experimentation to fundamentals, anchoring AI to KPIs, prioritizing productivity over headcount, and treating service as an end-to-end system under real economic constraints across manufacturing and…
KPI of the Month #2: Mean Time to Repair
Mean Time to Repair (MTTR) measures how quickly service organizations restore failed assets to operation. In manufacturing and automotive after-sales, MTTR reflects diagnostic readiness, parts availability, process discipline, and system integration. Used correctly, it highlights structural bottlenecks; used in isolation, it can drive superficial optimization and missed root causes.
Agentic AI in After-Sales: The Missing Execution Layer That Automation Couldn’t Fix
Discover how agentic AI in after-sales and field service is closing execution gaps that traditional automation cannot fix. Learn how agentic systems orchestrate workflows across CRM, FSM, ERP, and service teams, improve technician productivity, enhance customer experience, and enable closed-loop feedback into product design.
Predictive vs Preventive Maintenance: Key Differences Explained
Understand the real difference between predictive and preventive maintenance, and why it’s not just about technology. Learn how manufacturers can master preventive maintenance first, assess readiness, and layer predictive intelligence to drive service-led growth. Explore common pitfalls, readiness checklists, and practical guidance for bridging the gap from reactive repairs to proactive, data-driven reliability.
Service vs. Serving
As after-sales becomes a major profit driver, many OEMs are prioritizing revenue over relationships. This article explores how monetizing service, through inflated parts pricing, opaque terms, and sales-driven KPIs, is eroding customer trust and loyalty across the automotive sector. Learn how transparency, contextual upselling, and a Service-Led Growth mindset can rebuild relevance before disruption arrives.
KPI of the Month #1: First Time Fix Rate
The First Time Fix Rate (FTFR) is one of the most important field service KPIs, revealing how effectively technicians resolve issues on the first visit. This article explains what FTFR really measures, why it matters for cost, efficiency, and customer experience, and how people, process, and technology improvements can drive sustainable performance gains across manufacturing,…
GenAI Hype Is Over: Welcome to Reality
Generative AI hype is fading as organizations confront the reality of data gaps, weak ROI, and integration fatigue. Gartner’s 2025 Hype Cycle shows GenAI peaking while traditional AI quietly delivers results. Learn why mature enterprises are hitting pause, what’s driving this shift, and how to navigate the post-hype era with clarity, readiness, and measurable impact.