The modern industrial landscape is increasingly dynamic, competitive, and complex. This new landscape is being shaped by a number of ongoing trends that are affecting every aspect of business, including new product design, manufacturing, logistics, supply chains, and even the ways in which products are sold and serviced. For example, embedding computing power, sensors, connectivity, and other smart features into products of all kinds has become widespread in response to growing demand. Smarter products can support more sophisticated functionality and provide greater value for the user, but are also more complex, costly, and more difficult to engineer. On top of this, companies are striving to bring these new and advanced products to market as fast as possible with the hope of being on the forefront of innovation and faster than the competition.
As products become more complex and the push for innovation intensifies, companies are also working towards the realization of global climate goals through both internal policies and by complying with new regulations that call for the progressive reduction of carbon and carbon-equivalent emissions. Moreover, companies in all industries are designing, testing, and building increasingly advanced products in less time, with fewer resources, and while minimizing emissions.
Among these trends, the rapid growth of complexity is particularly disruptive because it manifests in several ways throughout an organization. Products of all kinds – from cars to consumer electronics, appliances, industrial machinery and more – are becoming smarter, more sophisticated, and thus more complex. These products are comprised of various components and subsystems including electronics devices, electrical networks and wiring, software, and mechanical systems that all must integrate into a single robust system. As this complexity grows, the challenge of product development also increases. At the same time, modern customers have come to expect a high degree of intelligence and customization in products, driving requirements for flexibility or modularization back into product development. These demands add further complexity to product development as engineers must find ways to create systems that are flexible, customizable, reliable, and that can outperform the competition.
Growing product complexity has follow-on effects throughout the organization. Manufacturing systems are also growing in sophistication and intelligence as they must become more efficient, flexible, and connected to produce the advanced products being developed on pace with the rapid cycles of today’s industry. Consumer demand for product personalization can drive the potential number of unique product configurations into the thousands. As a result, production facilities are quickly trying to become more modular and more flexible to support such a vast number of possible product configurations. Simultaneously, manufacturers are working on connecting machinery to the industrial internet of things (IIoT) to gather and analyze data from the factory floor, enabling process optimizations, machine monitoring, and predictive maintenance activities to maximize the uptime of production lines. Growing connectivity and intelligence in the factory is certainly valuable, but it also adds layers of complexity to an organization.
Furthermore, connectivity is an ever-more widespread fact of modern life; it is not limited to any one industry or context. All kinds of products are being connected to the cloud, creating a vast network of objects that can collect data for processing and analysis (i.e. the Internet of Things). As with industrial machinery, connected products allow companies to capture immense amounts of data from actual product utilization in the field and harness it to drive optimization of product design, manufacturing processes and more. The difficulty is in making the most of the immense amount of data that is produced by connected machines and products. It’s one thing to collect terabytes (or even petabytes) of data from the manufacturing lifecycle and the product in the field, and another to analyze the data and intelligently apply it to enhance the product and production processes.
For many companies, the future holds a two-pronged challenge. They must adapt to the needs of tomorrow by developing advanced products, adopting connected design and manufacturing processes, connecting to the cloud, and by managing complexity rather than being buried by it. At the same time, companies cannot ignore the needs of their customers and business today. With the future fast approaching and complexity already on the rise, how can companies solve both problems at once? The answer is digital transformation. Digital transformation is the widespread digitalization of processes, data flows and methodologies, and it provides a holistic data-centric view of the world instead of being limited to the application or domain-centric silos of information. Through digital transformation, companies can facilitate integrated engineering across traditional domains such as mechanical, electronics, and software, manage and organize data across the product and production lifecycle, and connect to cloud computing and the IoT to incorporate lessons learned in the field back into the product development and production processes. Companies that engage in digital transformation will be able to turn complexity into a competitive advantage instead of letting it slow them down.