How Smart Factories Unleash Value Across the Manufacturing Ecosystem

The smart factory, defined by its digital production model, is gaining traction. The factors driving smart factories forward are diverse. They include global disruptions, supply chain issues and client demands for digital experiences. That last point is particularly important. Organizations often prioritize production optimization and cost reduction in digital transformation, but true success lies in transforming value delivery to customers.

Such success, unfortunately, isn't guaranteed. Certainly, some organizations have achieved operational efficiency through smart factory initiatives. But many remain in "pilot purgatory" due to barriers ranging from leadership gaps, cultural resistance and workforce readiness to legacy systems and cybersecurity risks.

Nor is a Smart Factory an all or nothing proposition. Manufacturers are using smart factory elements, such as Manufacturing Execution Systems (MES) for visibility, real-time data for planning and augmented reality for maintenance. But a holistic smart factory approach impacts the entire enterprise and ecosystem and should be central to an organization's digital transformation strategy. The strategic significance of smart factories is clear. Early adopters already report increased agility and profitability. Such benefits fulfill some of the priorities manufacturers rate as high today. A survey by NTT DATA and Oxford Economics revealed manufacturers' priorities include revenue growth, cost reduction, resiliency and innovation. This article explores key considerations, maturity models, and use cases for smart factories.

4 key considerations for Smart Factory success

1. Data mastery and analytics
Data mastery is a key element of smart factories, involving using data and analytics to gain insights for efficiency and new business opportunities. It encompasses structured and unstructured data flowing through processes to enable data-driven decision-making across the enterprise. But obstacles to data mastery abound in everything from accessing to aggregating to analyzing data. A diversity of sources, such as smart sensors, MESs and databases, create additional hurdles.

Successful data mastery lies in creating a common data framework to manage data from the factory floor and channel it to an AI data pipeline. For example, artificial intelligence can contextualize data and generate a digital twin of the factory. Real-time analytics further support best practices such as predictive maintenance, process optimization and more. The combination of technology creates effective contextualized dashboards that present actionable information for the enterprise.

2. Cybersecurity
Connecting IoT devices to networks increases potential attack surfaces and risks from compromised devices. Those risks are a shared burden. Device manufacturers share responsibility for security with those deploying the devices. But businesses often implement Operational Technology (OT) networks hastily, creating risks that may be unknown or unassessed. Manufacturers, therefore, need a holistic approach to cybersecurity that encompasses lifecycle assessment, implementation and management.

3. Digital technologies
Smart factories will typically integrate functions beyond the factory floor. Their focus spans across operations, quality, sustainability, safety compliance and technology risk mitigation. But it also integrates with the ERP, CRM, PLM and other value chain applications. The ecosystem and sustainability issues also play a prominent role in the evolving set of digital technologies and smart manufacturing priorities.

4. Leadership, organization, culture and people
Smart factory initiatives need a particularly higher level of engagement to manage change. This is because smart factories call for data-driven decision-making, breaking down traditional corporate silos and adopting collaborative, agile value-chain ecosystems. Managing change at scale requires both top-down and bottom-up approaches. That is, it requires prioritizing support not only from leadership but also from ground-level teams to gain buy-in and adoption. Teams with diverse skills in engineering, data management, analytics, edge and data science are essential. Upskilling and reskilling employees, along with ongoing support and learning, are critical for long-term success as the smart factory evolves.

Building skills facilitates solution acceptance while also supporting employee adaptation and fostering continuous learning. As digital technologies transform employee roles, however, upskilling becomes challenging. Organizations should explore alternate talent models. These include collaborating with universities and leveraging partner ecosystems to attract and motivate young talent in manufacturing.

Execution approach: think big, start small, scale fast

Smart factory investments often begin by targeting specific opportunities. For example, achieving the goal of "Lights Out" operations requires a crawl, walk, run approach. It's best to start small, pilot concepts and scale after learning. Successful solutions can expand to more assets, lines and factories, creating exponential value. Companies must tailor their strategies to address unique issues and unlock value through smart factory solutions. Customization of those solutions is key to making sure the smart factory aligns with organizational needs.

Pilot site plant maturity assessment and transformation framework

Before starting a transformation, it's wise for organizations to assess the maturity of its people, processes and technology. The World Economic Forum's Smart Industry Readiness Index (SIRI) offers frameworks and tools for manufacturing transformation, though no global standard exists. The World Economic Forum has also reported some of the top use cases implemented by the Global Lighthouse network companies. Assessment findings rely on sharing organizational practices and self-reflecting on improvement areas. Preparatory work should include a roadmap outlining current maturity, a readiness index, improvement levers, required capabilities, next steps and transformation recommendations.

Digitally infused operations drive productivity

Smart factories benefit all aspects of manufacturing: operations, quality, sustainability, safety, compliance and technology risk mitigation. As a result, use case benefits vary. Often, though, they include productivity increases, cost reductions, energy efficiency, inventory reduction, lead time reduction and improved throughput. The World Economic Forum's Global Lighthouse network of companies demonstrates how digitally infused operations drive productivity and sustainable growth. For example, digital machines and management applications increase output. But at the same time, new business models and unlocked capacity optimize resources and empower workers with digital applications. These measures enhance infrastructure and minimize environmental impact without massive capital investment.

Various approaches to smart factory deployment offer valuable lessons. These include people-centric experiences such as change management and skill diversity, as well as operational and technological considerations. Success will likely come to manufacturers that continuously move forward. Surveys and research show a broad consensus on the "Smart" future of manufacturing, with empirical results from global lighthouse factories supporting the smart model's value. To drive sustainable value, starting small with specific objectives. For those already on the journey, acceleration and scaling are crucial. And for those contemplating how to start, now is the time to begin or risk falling behind.

If you’d like to discuss any aspect of the smart factory, please don’t hesitate to contact us.

^{This blog is a condensed version of an article originally published on the Manufacturing Leadership Council site.}