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The next phase of transformation: Intelligent industry

Abdelmajid BOUTAYEB

Manufacturers everywhere have been focused on Industry 4.0, which has helped them improve revenue, reduce cost of goods sold, and minimize indirect expenses while contributing to significant working capital. Though Industry 4.0 has not yet reached its full potential, the next focus for manufacturers will be on what we at Capgemini call “intelligent industry,” or, in other words, a focus on pioneering new ways of designing, manufacturing, operating, and experiencing products and services, powered by data.

With intelligent industry, companies will become insights-driven organizations across both product development and the entire manufacturing and operations lifecycle. “Siloism” will be rejected, high levels of automation will be reached, and hyper-personalization will be the norm – resulting in highly efficient operations.

So, what does it look like when an organization has embraced intelligent industry? These are the key elements:

  • Intelligence at the edge:Sensors continue to become cheaper, more rugged, and therefore ubiquitous. This, combined with edge computing, makes it possible to not only monitor every asset and process parameter – which is the traditional value proposition of IoT and IIoT – but also to build decisioning capability and intelligence closer to the point of execution. This is invaluable in low-latency scenarios such as autonomous vehicles or compressors located along long hydrocarbon pipelines.
  • Secure and speedy data transfer:With improvements in cybersecurity and communication infrastructure, industrial companies are slowly but surely putting their data on the cloud. This will go a long way towards reducing data silos and lead to enterprise-wide efficiencies. Moreover, 5G, with its ability to provide high data transfer rates and make connections between the factory floor and the cloud more feasible, is a potential gamechanger.
  • Insights from data: Progress on the data front is really where maximum value is being created. Most firms have built up capabilities in acquiring, cleansing, and managing huge stores of IT, OT, and unstructured data. ML and AI, when brought into the mix, dramatically improve decisioning and create a platform on which true automation can be built. Think of warehouse robots, or automated borers in mines, or even supply-chain forecasts and you start to truly see the potential of data.
  • Cloud-based industrial platforms:The manufacturing industry has already embraced packaged software, be it ERPs, warehouse management systems, etc. A similar trend is playing out with the adoption of cloud-based platforms that have the functionality to acquire, analyze, and decision various types of data for IoT operations. These platforms make building apps and capabilities across the three technologies we discuss above painless and quick. Cloud and automation vendors are investing heavily to build capability and drive universal adoption.
  • The way software is constructed: Recent years have seen the rapid adoption of agile and DevOps methodologies and the deployment of business capabilities in the form of microservices. This is a significant shift for an industry that is used to slower change, generally relies on a traditional waterfall approach, and is working to recover the costs of long and complex transformations. Such manufacturers have to take the API-fication route along with agile transformation to stay in the intelligent industry game. This approach will transform operations and make business truly agile.

In addition to these factors, collaborative technologies, which allow supply-chain partners to interact and collaborate, and blockchain, with its ability to create trusted transactions between varied participants, are also becoming mainstream enablers.

To get going, it’s best to start small with a specific use case and build from there.