Manufacturers may need to slow down to be ahead in the race to deploy Industry 4.0 since digital changes are notoriously difficult to scale up across manufacturing networks.
In the last five years, a limited group of corporations has begun to accelerate its attempts to deploy Industry 4.0 across their industrial networks. Data and analytics, AI, and machine learning are already providing considerable value to leading manufacturers (ML). However, the majority are still caught in pilot hell, unable to realize the full potential of their transformation initiatives or offer a sufficient return on investment.
While digital reforms are notoriously difficult to scale across factory networks, the stakes are high. Companies in the lead are reaping benefits across the whole manufacturing value chain, including increased production capacity and reduced material losses, improved customer service and delivery lead times, more employee satisfaction, and less environmental impact. These improvements, when scaled across networks, can radically change a company’s competitive position.
With so much at risk, firms are investing substantial time and money in digital revolutions. These expenditures are paying off for some, but most are still unable to expand successful pilot projects or fully use new tools and technology to realize substantial results.
This article will explore some of the regular pitfalls associated with digital transformation and how a strategic and focused approach could help manufacturers in the race to get ahead.
Value across the Factory
Today’s digitally equipped production looks nothing like the leading manufacturing of 10 years ago. Manufacturers may pick from hundreds of different solutions and tech applications to better their ways of working thanks to advancements in data and analytics, AI, and ML, as well as the market’s assortment of technology providers. When implemented correctly, these solutions provide tempting rewards. It is not uncommon to observe 30 to 50 percent reductions in machine downtime, 10 to 30 percent increases in throughput, 15 to 30 percent increases in labor productivity, and 85 percent more accurate forecasts across a wide range of industries.
Digital revolution is transforming all parts of production, affecting not only processes and productivity, but also people. The proper IT applications may result in more empowered decision making, new opportunities for upskilling, reskilling, and cross-functional cooperation, increased talent attraction and retention, and improved workplace safety and employee happiness.
Customers see the benefits of shorter manufacturing lead times, first-time-right launch management, and enhanced customer service and complexity management. There are also the win-win benefits associated with decreased environmental impact, which are made possible by fewer emissions and waste, as well as more efficient energy, water, and raw-material usage.
These productivity, process, and people gains are difficult to achieve, particularly when spread throughout a network of different production locations, each with its own site leadership, IT infrastructure, and workplace culture. It is very unusual to hear about corporations attaining excellent outcomes through pilot projects at a single industrial location only to discover that they are unable to duplicate these local successes across their network.
This was the situation at a multinational corporation. Faced with a significant increase in demand—volume more than quadrupled in three years, resulting in the production of more than 50 million more parts—the company began on an ambitious digital transformation at one facility. The aim was to raise overall equipment effectiveness (OEE) by 10% while lowering product unit costs by more than 30%.
Common Pitfalls of scaling to Industry 4.0
Siloed implementation: Many firms mistakenly establish autonomous delivery teams that are disconnected from business executives, site operations, manufacturing excellence, and central IT by pursuing digital transformations as a theoretical exercise. Others place too much emphasis on reproducing a single site experience, neglecting to recognize the intricacies of a larger network.
Failure to adapt: Manufacturers miss out on the potential to build in the customization and adaptability required to harness the distinct conditions, culture, and values of various plant locations when they choose a one-size-fits-all strategy.
Analytics and Paralysis: A thorough upfront investigation of a whole network might deplete a manufacturer’s resources before a transition can begin. Instead, a well-developed extrapolation process can yield solid, accurate-enough conclusions.
Technology Value Driven: Solutions are provided without a clear relationship to actual value possibilities, business constraints, or competency requirements in a technology-first deployment. As a result, critical buy-in from those in charge of making deployment work is undermined.
Manufacturers miss out on the shorter time-to-impact provided by a proven and pragmatic minimal viable architecture by waiting until a full-fledged, ideal-state data and IT/OT (information technology/operational technology) architecture is defined and implemented before rolling out Industry 4.0 solutions.
Re-grouping around a new, more targeted strategy aimed at maximizing the value
Regardless of where a firm lies on the archetypal spectrum, there is significant benefit in slowing down and regrouping around a new, more focused strategy geared at maximizing the value of a digital transition.
How the few firms that have succeeded in scaling digital breakthroughs began their impact journey is an essential lesson. Before diving into procurement and implementation, the most successful organizations spend time defining the full potential of Industry 4.0, identifying high-leverage areas across the entire value chain, and architecting a laser-focused digital-manufacturing strategy and deployment road map.
The first part of this method comprises a network scan to identify the value at stake as well as a prioritized list of technological use cases that take data, IT/OT, and organizational maturity into account. On this foundation, an associated road map may be built, detailing the deployment strategy and targeted locations for initial distribution, followed by a network-wide rollout plan to achieve scale.
Investing time in advance to undertake a network scan to identify chances for large wins and fast wins may generate substantial momentum for a digital transformation. As manufacturing sites begin to capture financial and operational value, not to mention the benefits of improved organizational capabilities, workforce satisfaction, customer service performance, and environmental impact, these returns can create a virtuous feedback loop in which programs become self-funding and initiatives translate more quickly into competitive advantage.
Following a Strength-Upward Approach
The company must be able to duplicate the network scan method throughout the rest of its production network and grow to other business sectors after implementing a solid value-capture deployment plan and strategically investing in the relevant skills. They should essentially write game-plans for how to scale this into other sites and are making significant progress in these places—not only across downstream supply chains but also within upstream factory processes, leveraging digital to reduce human intervention strategies and increase compliance.
Seven golden principles – Mckinsey
Communicate: Create an effective engagement strategy and maintain regular communication with key senior stakeholders, site leaders, and a cross-functional core team.
Focus: Focus on genuine business needs and existing performance difficulties, and use a "strengths upward" strategy, building on solutions that have already performed effectively at particular sites and can be pragmatically pushed out across the network.
Segment, select, and syndicate: Divide the manufacturing network into segments and choose sample sites for an initial network scan. Publish the extrapolation process in advance to demonstrate how targeted insights will be scaled to produce a network-wide analysis.
Formalizing Value: Describe the real value at risk at each assessed site by connecting the most suitable Industry 4.0 solutions or use cases with current digital readiness, data availability, and IT/OT architecture.
Developing a Vision: To unite business executives on the objective and develop a compelling change story for the entire company, describe the overall value at stake from prioritized bundles of use cases. A visually appealing portrayal of the primary solutions might aid in engaging the larger company with the vision.
Digital Manufacturing Road-map: Create a prioritized deployment plan that includes a clear scaling strategy and articulation of the value to be captured over time, as well as data enablement and IT/OT architecture, as well as resourcing needs, capabilities, and change management.
Syndicate the vision and secure leadership buy-in: Circulate the business case and requirements to key stakeholders, aiming for a clear mandate from top leadership and close participation from site leaders on target setting and execution.
Companies might grow disheartened and disillusioned when they are stuck in pilot purgatory or under increasing pressure to generate returns. Companies may expedite their Industry 4.0 transitions and chart a clear path ahead for the next several years by taking only one or two months to slow down and build a comprehensive manufacturing strategy and deployment road map.
Author : Animish Raje