In an exclusive interview with Industry Outlook Magazine, Deepak Patil, COO of Group Legrand India, offers feasible solutions for manufacturers to tailor their offerings to the demands of the consumer. He also offers pointers on how output from existing data can be maximized by leveraging AI and IoT technologies. He has over 24 years of experience in Manufacturing Operations Management and has executed numerous mega projects successfully.
How is the adoption of Lean Six Sigma methodologies influencing leadership strategies across the manufacturing sector, and what trends are emerging in their implementation across diverse industrial sites?
Lean manufacturing is crucial in today's market due to its dynamic demands. These demands aren’t just about fluctuating quantities from customers; they reflect rapid shifts in customer preferences and choices. To keep up, we must design our manufacturing operations to be agile, flexible, and lean while also ensuring precise quality. In today’s market, we simply can’t afford to meet any gaps in quality expectations.
Beyond just meeting quality standards, we also need to align with the perceived expectations of the customer. This involves two main aspects of any product. First, functionality—does the product perform as expected and meet the customer's requirements? Second, perception—how does the customer feel about the product's aesthetic value or perceived worth?
This means focusing not only on the product’s functionality but also on its fit and finish. Even if the product isn’t highly visible, aspects like packaging, appearance, and color significantly impact customer satisfaction.
Now, translating these customer requirements into our manufacturing process means being incredibly precise. Ensuring 100% quality requires a commitment to Six Sigma principles in our manufacturing operations. Additionally, we operate in a competitive landscape, so our products must be competitively priced. Achieving this level of cost efficiency and timely delivery requires us to be lean and agile.
In short, to succeed, our entire manufacturing ecosystem needs to be lean, agile, flexible, and precise—ultimately providing customers with quality products that meet both their functional needs and their expectations.
How are leaders addressing the challenge of workforce skill gaps in different industrial sites, especially with the increasing complexity of advanced manufacturing technologies?
To provide a broader perspective on this topic, the issue isn’t unique to any one industry in India; it's a challenge faced globally. While we do have a large labor force, the main hurdle is securing the right skills at the right place and time, which has become increasingly complex. This challenge arises largely from an insufficient infrastructure or ecosystem for training people in line with industry needs.
Although we have technical schools, polytechnic institutes, and engineering colleges, the training is often unstructured and doesn’t fully align with specific industry requirements. This gap, in turn, leads to a skills shortage—not in numbers, but in relevant capabilities. For example, skilled labor might be available in one region of India, like the West, while a company operates in the East, creating a regional mismatch. Additionally, the availability of labor doesn’t always match demand cycles. Companies often need extra hands during seasonal production peaks, like festivals or specific climate conditions, but there’s no system in place to adjust the labor supply to these cycles or manage surplus labor when demand falls.
To address these issues, our industry has analyzed our specific skill and labor needs and studied our production patterns. This approach has led us to create localized solutions, including training our workforce within our facilities to meet our unique demands. For example, we have set up experiential, structured training areas, ensuring that new employees are properly prepared before they begin their roles. This structured onboarding boosts engagement and motivates our local workforce.
However, on a larger scale, both the government and the industry need to collaborate to build a robust ecosystem for skill development. This includes ensuring a steady, regionally appropriate supply of skilled workers across different industrial zones in the country.
How does data-driven decision-making shape leadership strategies across multiple manufacturing sites, particularly in ensuring data integrity amid real-time operational challenges?
With today’s digitalization, we indeed have access to an extensive amount of data across our operations. For instance, at Legrand, we have eight manufacturing sites throughout India, where we've implemented numerous Industry 4.0 projects. These systems provide data from various operational areas, such as energy, maintenance, and quality management, allowing us to capture and refine accurate and relevant data.
However, while this data offers valuable insights, decision-making can't solely rely on numbers. Effective leadership involves balancing data-driven insights with vision, intuition, and anticipation of future trends. Data serves as a foundation, but leaders also need to forecast and adapt to emerging technology, evolving demands, and shifts in the industry ecosystem.
It’s essential to view data as one piece of the puzzle, not the entire picture. Overreliance on data can sometimes constrain decisions, as real-world complexities and changing dynamics don’t always align perfectly with historical data points. Leaders must use a blend of data, foresight, and experience-driven intuition. For instance, even with real-time and precise data, unexpected factors might require a spontaneous, “impulsive” decision based on situational awareness and industry knowledge.
In managing multiple factories that operate in different ecosystems and manufacture various products, leadership requires the bandwidth to interpret data as a reference while leaning on broader insights, future projections, and often unquantifiable qualities, like experience and instinct, to make well-rounded decisions.
Given the rise of supply chain disruptions, how are leaders enhancing resilience and adaptability in their manufacturing processes across different sites?
In the post-COVID world, supply chains across industries faced significant disruptions, and stabilizing these networks took one to two years, depending on the specific materials, industry requirements, and geographic reach. For companies like ours with multiple factories—each producing various products with diverse raw materials and components sourced both locally and internationally—supply chain management is inherently complex.
To navigate these challenges, robust forecasting and planning processes are essential. This includes the ability to sense potential problems early, assess their gravity, and take preemptive actions. For instance, recent geopolitical tensions, such as those in the Red Sea, highlight the need for leaders to recognize the potential impact on supply lines. This means, where possible, securing critical raw materials, adjusting production schedules, or advancing shipments to mitigate risks.
Inventory management becomes a crucial buffer in these cases. Creating stockpiles of essential materials and adjusting inventory levels provide a cushion against supply chain disruptions, even though these proactive measures may not always prevent every issue.
The dynamic nature of the global supply chain often presents unforeseen disruptions that require immediate, reactive actions. A strong Sales and Operations Planning (S&OP) process combined with advanced forecasting methodologies is essential. In practice, leaders must strike a balance between reactive and preventive measures—responding to immediate challenges while proactively preparing for potential future disruptions.
With the growing complexity of integrating IoT and AI, ensuring data interoperability across diverse systems is a challenge. How is the industry addressing this to improve real-time performance monitoring?
Ensuring data interoperability across diverse systems is a key challenge, especially when aiming for real-time performance monitoring and decision-making. In our industry, we've made strides by establishing robust digital systems across all factories, which connect our machines, equipment, and processes to gather extensive data through IoT and Industry 4.0 systems. However, collecting data alone is not sufficient; the true value lies in how we analyze, synthesize, and extract actionable insights from it.
To maximize data utility, we focus heavily on developing secondary systems dedicated to data analysis and synthesis. This involves creating processes to modulate the raw data, analyze it in real time, and derive logical, meaningful information. The goal is to drive precise, data-driven actions, making the data collected genuinely impactful.
In every Industry 4.0 or digital project, we consider not just data acquisition but also the end-to-end process of transforming that data into strategic, actionable insights. By emphasizing systems for data interpretation, we ensure that our digital investments translate into improved operational efficiency, informed decision-making, and enhanced responsiveness. This integrated approach—combining data collection with robust analysis systems—enables our teams to drive meaningful actions that contribute to our long-term performance and adaptability.
As sustainability becomes a critical focus in manufacturing, what key leadership strategies do you foresee becoming essential for achieving excellence across multiple industrial sites over the next decade?
Sustainability has become foundational for building a competitive edge and ensuring longevity in any industry. Reducing the carbon footprint is central to this effort, involving a focus on energy efficiency and a commitment to renewable energy sources, like rooftop solar panels and wind energy. Companies must actively work to reduce energy consumption across their operations, transportation, and supply chains.
Equally important is a commitment to effective water and waste management. Implementing strategies to minimize water usage and reduce both hazardous and non-hazardous waste generation is essential. Establishing a clear roadmap for waste reduction helps companies streamline operations while reducing environmental impact. Additionally, sustainability efforts should emphasize circular economy practices, including using recycled materials—such as plastics and metals—and reusing production scrap and other waste materials.
Another aspect of sustainability is extending the lifespan of products and machinery, which helps conserve resources. For example, companies can upgrade equipment rather than replace it, maximizing utility while reducing the need for new resources. Practicing responsible business is also essential, particularly by maintaining high health and safety standards across all business activities, from protecting employees and customers to ensuring the safety of products.
A diverse and inclusive workforce is equally vital to sustainability. Companies should embrace differences in gender, geography, and culture while actively promoting inclusion, particularly for early-career professionals. Bringing in fresh talent can introduce new perspectives, drive innovation, and create a more balanced, dynamic organization.