Insights

Perspectives on Service, Technology, and Execution
This page brings together perspectives on after-sales, field service, digital transformation, and emerging technologies, drawn from real-world work with manufacturing and automotive organizations. The insights here explore what’s changing, what’s working, and where execution often breaks down, with links to deeper topic hubs for focused exploration.
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Latest Insights
Service Revenue Execution: Why the Levers Matter More Than the Strategy
Service revenue growth in manufacturing doesn’t fail because of weak strategy, it stalls due to execution gaps. This article explains how aligning ownership, incentives, and revenue levers such as contracts, parts pricing, and warranty governance determines whether installed base potential becomes measurable, scalable growth.
KPI of the Month #4: Installed Base Coverage Rate (IBCR)
Installed Base Coverage Rate (IBCR) measures the percentage of assets under active service contract or monitoring within your installed base. For manufacturing and automotive after-sales leaders, IBCR is a strategic KPI that drives recurring service revenue, enables proactive service, and strengthens long-term lifecycle monetization.
Business Case for Agentic AI in Aftersales: Quantifying Incremental Value Beyond Copilots
Most AI investments in aftersales improved productivity but failed to deliver material ROI. This article explains how Agentic AI changes the equation by orchestrating decisions across warranty, parts, dealers, and enterprise systems, unlocking incremental value beyond copilots in aftersales operations.
Sustainability & Aftersales: Why Lifecycle Thinking Is Manufacturing’s Real Climate Lever
Sustainability in manufacturing is decided long after the product leaves the factory. This article explores why aftersales and service execution, and not production alone, determine lifecycle impact, Scope 3 emissions, and customer value. By extending asset life through repair-first strategies, organizations unlock sustainability, margin growth, and stronger customer experience at the same time.
The Fully Autonomous Service Organization: What AI-Led Aftersales Really Looks Like
Aftersales is entering a new phase, one where service decisions are made before customers notice problems. This article explores what a fully autonomous service organization could look like, how AI-led orchestration changes warranty, parts, and dispatch, and why the shift is as much about operating models as technology.
Field Service KPIs for Manufacturing & Automotive: Metrics That Actually Drive Performance
Field service organizations track dozens of KPIs, yet still struggle to improve uptime, customer trust, and service profitability. This article explains how manufacturing and automotive companies should design, structure, and govern field service KPIs as a connected system that drives decisions, manages trade-offs, and scales with service maturity.
Manufacturing & Automotive After-Sales Service: Strategy, KPIs & Digital Transformation
After-sales service is now a strategic growth lever for manufacturing and automotive organizations. This article presents an end-to-end view of after-sales service, covering operating models, KPIs, execution challenges, and the practical role of digital and AI, grounded in real-world service transformation experience.
KPI of the Month #3: Proactive Resolution Rate (PRR)
Proactive Resolution Rate (PRR) is an emerging KPI that measures how effectively manufacturing and automotive service organizations prevent failures before customer impact. As AI, predictive analytics, and condition monitoring scale, PRR connects proactive insights to real outcomes, shifting service excellence from fixing failures faster to preventing them altogether.
Case Study: Improving Field Service Uptime Through Cognitive Technician Self-Service
Dealer technicians often lose valuable time searching for information instead of fixing equipment. This case study shows how a material handling equipment manufacturer improved uptime by 15% by reducing cognitive load at the point of service, using a search-driven technician self-service approach rather than overengineering AI.




