Manufacturers Face Multiple Modernization Challenges

Manufacturers are facing growing demands for a fast transformation. More and more, digitalization is becoming a competitive imperative. Technological advancements are disrupting business as usual. Traditional manufacturing is drifting into the past as environmental policy and consumer expectations shift. Manufacturers are revamping their production facilities to meet new sustainability goals and market demands.

The effort to modernize traditional manufacturing with increased efficiencies and sound sustainability practices is ultimately a positive. Yet companies struggle with the challenge. According to IT company, Capgemini, the ability to successfully adapt to changing needs – from production to customer experiences – can become a major competitive advantage for manufacturers.

Capgemini – a French IT services company that helps businesses use technology to manage operations and transform – has spelled out three critical areas manufacturers need to address to successfully traverse the path to technological transformation:

Transformation Strategies: Major manufacturers in the US are strengthening production capacities with cutting-edge technologies and addressing the transition to more sustainable energy sources.

New Technologies: The adoption of digital technologies, like AI, is impacting the quest for talent, streamlining production, and enabling companies to meet supply chain demands.  

Consumer Expectations: Manufacturers are meeting evolving consumer needs by shifting to more data-centric innovations that are also sustainability-oriented.  

We caught up with Khalid Sebti, EVP and managing director at Capgemini, to get insight into how manufacturers can successfully manage these three challenges.

Transformation Strategies

What can manufacturers do to strengthen production capacities with new technologies while also transitioning to more sustainable energy sources?

Khalid Sebti: In today’s manufacturing landscape, it’s not enough to just be efficient. Businesses must adopt sustainable practices that reinforce production capacities and contribute to long-term sustainability goals. In fact, our research shows that 57% of executives across industries report that they are in the process of redesigning their business and operating models to be more sustainable (up from 37% in 2022). 

Overwhelmingly, 60% of organizations believe that technology can help them fast-track their ESG goals. For example, artificial Intelligence (AI) is playing a pivotal role in enhancing the efficiency and reliability of clean electricity grids for manufacturers. AI can optimize energy distribution, reduce waste, and ensure the stable supply of renewable energy for critical manufacturing operations that rely on consistent power sources.

Manufacturers are also leveraging advanced supply chain intelligence by incorporating real-time tracking and traceability as well as sophisticated data analytics and monitoring systems, allowing them to gain insights into their product lifecycles, identify inefficiencies, and implement more sustainable practices. This approach helps in managing Scope 3 emissions, which are indirect emissions that occur across a company’s value chain and are often the most challenging to measure and reduce. Effective management of these emissions is essential for achieving comprehensive net-zero targets.

A prime example of digital transformation in manufacturing is our collaboration with the BMW Group to implement an innovative change and enablement program, strengthening their sustainable supply chain practices. This initiative involved over 1,200 stakeholders, focusing on decarbonization, environmental standards, and circular economy principles. The program successfully increased awareness and commitment to sustainability, setting a benchmark for the automotive industry.

By focusing on both production efficiency and energy transition, it is possible to achieve significant advancements towards net-zero goals, contributing to a more environmentally conscious industrial landscape.

New Technologies

How are digital technologies like AI impacting workforce issues, streamlined production, and supply chain demands.

Khalid Sebti: The introduction of automation, data-driven processes, and AI has introduced greater complexity for many manufacturing jobs, creating a more competitive environment for highly skilled workers. Positions that normally required physical or manual skillsets now require an understanding of the digital landscape. The demand for skills such as programming and data analytics are creating a narrower candidate pool across industries.

Additionally, businesses must consider adopting a strategy of workforce augmentation, not replacement. While AI has successfully streamlined many manufacturing processes, it cannot replace human talent. Businesses must invest in training employees to manage these new technologies and collaborate alongside AI.

AI and automated tools are also making waves in supply chain and production processes by providing business leaders with the resources to support the navigation of an increasingly complex landscape. The transformation from traditional to intelligent supply chains can address declining visibility and mitigate risks by implementing comprehensive monitoring and analysis capabilities for all processes. This allows businesses to increase the reactivity, speed, accuracy, and reliability of all related decisions.

For example, AI capabilities are prompting innovation in the automotive industry as its leaders navigate aging production sites and new complexities and requirements associated with the production of electric vehicles. Specifically, AI and automated tools can make assembly lines smarter, generate vast amounts of data, reduce throughput time, and limit dependencies on manual processes.

Consumer Expectations

How are manufacturers using data-centric innovations and sustainability-oriented practices  to meet the ever-evolving consumer needs. 

Khalid Sebti: In the digital era, with digital-first customer expectations, every company, including manufacturers, must navigate ongoing software transformation. A 2023 survey found that one in three (33%) of high-tech manufacturers already considers themselves to be a software company. More than half (64%) of these manufacturers believe software transformation makes them more competitive, helping them deliver new value to customers through intelligent and connected products and services. Software transformation also helps companies develop new business and operating models, which can unlock new revenue streams and reduce costs. Time to market and operational efficiency are only one part of the modern customer expectation equation, however.

The evolution of consumer expectations in the new eco-digital era is creating an increasingly complex environment for businesses to operate in. Consumers are looking for top-notch products and low prices while prioritizing commitments to ESG initiatives. For example, Capgemini found that  63% of consumers want brands to play an active role in their education around sustainable products, and 55% believe that the greater a brand’s sustainability effort, the more positive the consumer perception of that brand.

Manufacturers are uniquely positioned to educate their stakeholders and meet consumer needs, since they touch integral processes throughout the value chain. For example, implementing sustainable procurement can be a key step in meeting decarbonization goals. Furthermore, unlocking access to quality data will drive effective management of carbon reporting. This level of transparency is necessary for the modern organization to succeed under pressures from consumers and regulatory agencies to reduce greenhouse gas emissions.

By leveraging AI and automation, manufacturers can also identify inefficiencies and refine operations by improving forecasting and resource allocation, optimizing inventory, and streamlining shipping times, all while using intelligent, customizable tools to avoid costs associated with operational bottlenecks. These data-centric improvements enable manufacturers to analyze real-time data, predict demand, and enhance decision-making processes, ensuring that products meet consumer standards and remain competitively priced.

In the consumer product and retail (CPR) industry, for example, AI can use real-time data and predictive analytics to identify in-demand products and support efforts to develop them and bring them to market more swiftly. Improvements to existing products can also be made with the help of AI tools that make it easier to accurately prioritize customer preferences. Additionally, data-centric innovations such as digital twins, IoT integration, and visual renderings of products enhance sustainability by enabling precise monitoring and management of resources, reducing waste, and minimizing environmental impact.