Role Of AI & IoT In Customer-Centric Service Lifecycle Management Explained

May 30, 2024

How efficient and effective is your service lifecycle management? Is your organization lagging behind in terms of AI and IoT adoption? Get the thoughts of major players in Blumberg Advisory Group’s report.

Wondering what the future holds for service lifecycle management (SLM)? Want to get the insights of leading industry figures from companies like IBM, Dell, and Nokia?

Read Blumberg Advisory Group's new report on the recent SLM Executive Roundtable:

Digital Transformation

The paper underlines the growing importance of SLM for digital transformation in the field service and aftermarket services industry while exploring the challenges and strategies that look set to define progress in the coming years.

The Roundtable discussion was led by Michael Blumberg – President of the Advisory Group – with participants including representatives from Dell, IBM, Super Micro, Nokia, and Flock Safety among others.

AI & IoT

The report covers the challenges of integrating AI and the IoT for predictive and optimized service delivery, using advanced technology to manage your service's entire lifecycle from inception to retirement.

AI, in particular, can enable your non-technical staff to handle technical problems that were previously beyond their competencies.

Customer-Centric Approaches

Blumberg says that discussions highlighted the need to view SLM through the lens of customer experience and the importance of asset management in supporting a company's financial growth and survival.


Key points raised in the report include the need to align SLM with your broader business objectives and the importance of connecting your service model with product lifecycles. Discussions underlined the need for continuous innovation and the associated investment needed to fund research, development, and adoption of emerging technologies.

Data-Driven Decisions

The shift towards AI-enabled processes exemplifies a global trend toward data-driven decision-making away from traditional digitization. Michael Blumberg notes his organization's prediction that AI in SLM platforms will cut resolution times by 50% by 2027.

While machine learning progress has been rapid in the field service sector, challenges remain in the integration of disparate systems and processes. As Pavan Agarwal from Super Micro elaborated, “Integration isn’t just about technology; it's about aligning people and processes across various silos.” The report highlights how change management requires cultural and organizational shifts – for example, traditionally product-centric organizations transitioning to a service-oriented approach – to successfully integrate AI and IoT into your business model.

“Insights from industry leaders during the roundtable discussion have highlighted the importance of a strategic, data-driven, and customer-centric approach to SLM, “ says Blumberg. “It's essential for companies to adapt to maintain competitiveness and respond effectively to shifting customer and market demands.”

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