Digital Transformation Powered by AVEVA’s Roadmap
Industrial manufacturers are navigating cost volatility, regulatory demands, workforce changes, and supply chain disruptions, according to a new white paper, “A Strategic Guide to Digital Transformation in Industrial Manufacturing,” published by AVEVA, a industrial software company that provides cloud and AI-powered platforms to design, run, and optimize complex industrial operations for global energy, manufacturing, and infrastructure customers.
The paper explains how companies can stay ahead by weaving digital technologies into everyday operations. AVEVA defines digital transformation as a fundamental change in the way industrial organizations design, operate, and maintain assets throughout the value chain.
Matt Newton, Director of Asset Performance Portfolio Marketing at AVEVA, says that “digital transformation is enabling companies to enhance their capabilities, increase their reach and returns across their asset and operations value chains.” AVEVA positions this shift as a response to structural industry change, not just an isolated IT project.
The white paper cites survey findings revealing that 92 percent of respondents believe “success requires digital at business core,” while 90 percent say organizations that don’t embrace digital risk falling behind competitors. AVEVA frames digital as a business model issue linked to asset strategy, operational data, and capital allocation.
AVEVA Digital Transformation Framework
AVEVA structures its white paper around a model that connects strategy, analytics, and asset maintenance. It describes digital transformation as a continuous cycle that links operational data to enterprise decisions.
Matt writes that manufacturers must combine real-time production data with historical operational information to generate insight. He states that digital systems “can help you to design, manufacture, deliver, support and maintain products faster, more efficiently, and at lower costs.” AVEVA connects the capability to cloud platforms, Industrial Internet of Things (IIoT) infrastructure, and analytics tools.
The white paper argues that data without context limits value creation. AVEVA highlights the integration of engineering, operations, and supply chain information into shared environments. By doing so, companies can detect anomalies, identify performance gaps, and act before equipment failure disrupts output.
Matt writes that digital transformation “merges the latest innovative tools and processes with your in-house domain expertise.” He links the integration to closing operational feedback loops across asset lifecycles.
AVEVA outlines three core processes: strategize, analyze, and maintain. In the strategize phase, organizations define performance indicators and connect assets, people, and processes in real time. In analytics and machine learning detect patterns and uncover operational losses. In maintenance, digital systems support predictive and condition-based maintenance to reduce downtime and improve asset utilization.
IIoT and AVEVA Data Integration
The white paper identifies IIoT as a key enabler of digital change. Sensors and connected devices collect operational data that previously remained siloed. AVEVA explains how these technologies extend visibility across ageing infrastructure without requiring a full system replacement.
By linking IIoT streams with hybrid cloud platforms, manufacturers create connected data environments. The white paper explains that integration enables predictive analytics and machine learning applications to identify trends across large datasets.
AVEVA argues that IT and operational technology must converge to remove silos. The white paper describes how digital platforms connect plant systems with enterprise applications, aligning engineering, planning, operations, and supply chain functions. The integration provides a shared operational view across multiple facilities.
The white paper discusses digital twins as part of the transformation architecture. AVEVA explains that digital twins replicate physical assets in software models, enabling teams to simulate performance and test operating scenarios before implementing changes in live production environments. The models allow operators and engineers to assess risk and forecast outcomes using real operational data.
Workforce and investment implications
AVEVA addresses workforce considerations alongside technical integration. The white paper notes that digital tools support knowledge transfer as experienced operators retire and new workers enter industrial roles.
Extended reality technologies, including augmented and virtual reality, enable operators to access contextual instructions during maintenance and inspection. The white paper links these systems directly to live plant data, allowing training and guidance to reflect current asset conditions.
Matt highlights that technology deployment must align with internal expertise. He presents transformation as a coordinated effort between digital platforms and domain specialists rather than a standalone software rollout.
The white paper connects digital adoption to investor perception. It states, “Over the past few years, companies that have embraced digital technologies have been rewarded by investors with higher valuations.” AVEVA includes this reference to highlight financial implications beyond operational metrics.
In addition, the document cites projections from the World Economic Forum estimating that digital transformation could generate up to $400 billion in value for mining and metals, $550 billion for chemicals, and $1.3 trillion for electricity operations. AVEVA uses these figures to illustrate the scale of economic opportunity associated with digital integration.
Case Studies in AVEVA White Paper
AVEVA supports its framework with industrial case studies. The white paper highlights Duke Energy’s SmartGen program, which applies predictive analytics to power generation assets. Duke deploys analytics drawing on data from more than 30,000 sensors and develops over 10,000 models to detect anomalies.
According to the white paper, the program identifies 385 findings over three years and avoids more than $66.6 million in repair costs. AVEVA presents the case as evidence that predictive analytics reduce unplanned downtime and protect capital-intensive infrastructure.
The document further explores how digital twins of enterprise operations allow companies to model plant performance across multiple sites. AVEVA explains that by simulating scenarios, organizations improve maintenance planning and production scheduling without interrupting output.
Throughout the white paper, AVEVA links digital transformation to operational execution. It focuses on integrating systems, capturing data at scale, and translating analytics into maintenance, engineering, and production decisions. Matt frames the shift as structural, indicating that digital technologies are reshaping how industrial manufacturers manage assets across the design, operation, and service phases.
Authored by: Stella Nolan is the Editor of American Healthcare Leader and Modern Counsel Magazine and a regular contributor to Manufacturing Today, all published by Finelight Media Group. With over a decade of experience in senior editorial roles, Stella creates commercially savvy, engaging content for global brands. Based in the UK, she brings sector expertise and compelling storytelling to topics like digital transformation, advanced manufacturing, EV infrastructure, and the impact of AI on industry. Stella’s focus includes DEI, AI, procurement, and telecoms, where she profiles industry leaders and curates essential features for in-house counsel and healthcare professionals.
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