Why frugal innovation is a force multiplier for India’s next manufacturing leap

India has long been shaped by a distinctive advantage: frugal innovation—the discipline of achieving more with less. It is visible in landmark national achievements executed with uncommon cost efficiency, and it is even more evident in the agility of millions of small manufacturers who routinely innovate under constraints. This "do more with less" mindset is not a cultural footnote; it is a competitive capability—one that can become the blueprint for India’s manufacturing expansion in the coming decade.

Yet the manufacturing model that carried India this far is under pressure. As the country advances its manufacturing priorities under programs such as Make in India and Atmanirbhar Bharat, traditional industrial automation approaches look increasingly misaligned with what the market now demands. Heavy upfront capital expenditure, rigid architecture, deep dependence on highly specialized labor slow transformation, limit adoption beyond large enterprises, and make it difficult to respond to volatile supply chains and high-mix production environments. In short, the legacy model cannot deliver the speed and breadth that India needs.

A more practical model is emerging—one that brings together cloud-native Manufacturing Execution Systems (MES), AI-enabled operations, and data-centric execution across plants and supply chains. In this context, Plex MES is positioned as an embodiment of frugal innovation applied through modern software: cloud-built, scalable, mobile-first, real-time, and designed to be AI-ready—while remaining accessible to a broad base of manufacturers, including MSMEs. The central idea is simple: world-class manufacturing capabilities should not require world-class budgets to begin.

The cloud imperative: shifting from CAPEX shock to OPEX control

For India’s manufacturing ecosystem, the first barrier to digital maturity is often not intent—it is economics. Traditional automation programs typically demand major upfront investments: infrastructure, servers, storage, licenses, upgrades, and dedicated IT overhead. MSMEs—forming a large backbone of India’s industrial capacity—are particularly constrained by these CAPEX-heavy commitments. Cloud-native MES changes that equation by shifting the model toward subscription-based OPEX, reducing the need for on-premises hardware, eliminating routine maintenance burdens, and enabling continuous feature updates. The result is not only affordability; it is predictability—an attribute that matters deeply in cost-sensitive, margin-conscious environments.

The cloud advantage is not only financial—it is operational. Traditional MES programs can involve long implementation cycles and extensive customization. By contrast, a cloud-native approach is designed to accelerate time-to-value and reduce the operational drag created by upgrades, patching, and version-lock issues. When manufacturers can deploy faster, learn sooner, and iterate continuously, digitization becomes a capability rather than a one-time project. This is frugal at the system level: minimizing waste in deployment effort, technology overhead, and organizational energy.

Agility for India’s “always-changing” factory reality

India’s manufacturing floor is defined by change—fluctuating supply chains, high product mix, rapid engineering adjustments, and evolving demand cycles. Policy initiatives can create surges in production and investments, while sectoral shifts—particularly in automotive and EV ecosystems—force faster line changes and tighter quality expectations. In such conditions, the goal is not merely automation; it is agile automation. Cloud-native Plex MES supports that agility through rapid rollout across sites, scalability as production grows, and unified real-time visibility across plants. The bigger point is strategic: agility is no longer a nice-to-have; it is the cost of competing, especially when manufacturers must deliver speed, quality, and resilience simultaneously.

The operational prize is enterprise-wide coherence. A plant can only optimize so much in isolation; across a multi-plant network, leaders need comparable metrics, aligned workflows, and consistent data. Integrated MES platforms can unify manufacturing-site data into a single operational view, enabling real-time decision-making across networks. That kind of visibility is what allows companies to shift from reactive firefighting to proactive control—whether the objective is throughput, quality, inventory, or delivery reliability.

Artificial intelligence: turning complexity into usability

AI in manufacturing is often discussed as breakthrough technology. In practice, its highest value may be more pragmatic: reducing complexity and making advanced systems usable for a broader workforce. Practical scenarios include conversational interaction to retrieve metrics, interpret machine signals, trigger workflows, and generate reports. This matters because manufacturing transformation is constrained by skills gaps and change fatigue. When AI reduces friction in how operators and engineers interact with systems, adoption improves—and the benefits of digitization compound.

AI also strengthens quality systems, especially where manual inspection is costly or inconsistent. AI-powered machine vision and image-based quality control are gaining traction in sectors such as electronics and pharmaceuticals, improving defect detection, and strengthening export competitiveness. While the technologies differ by process and industry, the direction is consistent: quality becomes more repeatable when intelligence is embedded into inspection workflows, rather than dependent on manual checks alone. For manufacturers striving for stringent global standards, intelligence can lower the barrier to compliance and reduce the cost of quality.

DataOps: the backbone that makes digital manufacturing scale

If cloud MES provides the system of record for execution, and AI provides the usability layer, DataOps provides the backbone that makes transformation sustainable. Without DataOps, many organizations remain trapped in familiar pain points: siloed machine data, weak ERP–MES connectivity, lack of contextualized OT data, and no dependable single-source of truth. Under those conditions, even advanced MES or AI solutions can underperform—because data feeding them is fragmented, inconsistent, or incomplete.

A modern DataOps approach—integrated with MES—delivers a unified information model, contextualized operational data, seamless OT–IT connectivity, reusable datasets for analytics and AI, and enterprise-wide dashboards updated in real time. The practical impact is best understood through shop-floor outcomes: benchmarking OEE across plants in real time, detecting spoilage trends early in batch environments, or spotting micro-stoppages across multiple lines within seconds. These are not abstract analytics use cases; they are operational controls that prevent losses, improve yield, and raise asset performance.

Why Plex MES fits the frugal innovation model

The frugal innovation lens demands a hard test: does technology deliver depth without demanding complexity? Plex MES is positioned to do this through several characteristics: it is built for cloud delivery (not merely migrated), it provides real-time production visibility (including OEE and SPC), it includes integrated quality management within workflows, it is mobile-first without added cost, and it is configurable in ways that support scale without brittle custom code. In addition, end-to-end traceability—material genealogy, operator touchpoints, machine data, quality results, routing adherence, and lot/serial records—is increasingly essential for audits, compliance, and recall risk reduction.

Just as important are the governance guardrails that matter in enterprise adoption: enterprise-grade security, multi-region delivery considerations, and a model that continuously evolves through feature releases rather than periodic disruptive upgrades. When manufacturers can modernize without repeatedly “starting over,” transformation becomes compounding—each improvement builds on the last.

India’s advantage is not just cost—it is design discipline

India’s opportunity is not simply to digitize factories. It is to define a manufacturing operating model that is affordable to start, fast to adopt, resilient in volatility, and scalable across an ecosystem that includes both global enterprises and Micro, Small, and Medium Enterprises (MSMEs). Frugal innovation is the mindset that can make this possible—but it needs a technological counterpart that reduces friction rather than adding to it.

Cloud-native MES platforms such as Plex, amplified by AI and anchored by DataOps, offer a coherent pathway toward that future: real-time visibility, integrated quality, mobile execution, traceability, and enterprise-wide intelligence—delivered in a form factor that supports sustainable scale.

In the end, the most meaningful measure of progress is not how many pilots a manufacturer runs, but how quickly it can replicate value across lines, plants, and partners. That is the flywheel effect: once the core system is in place, every new insight, workflow improvement, and quality enhancement becomes easier to deploy everywhere. For India’s manufacturing transformation, which is not just a technology story—it is a competitiveness story.

By Murali Manohar, Regional Leader, Enterprise Software Business, India and Southeast Asia, Rockwell Automation

(Disclaimer: The views expressed in this article are those of the author and do not necessarily reflect the views or editorial position of Dataquest or CyberMedia.)