The five factors driving intelligent industry

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Intelligent industry (n): pioneering new ways of designing, manufacturing, operating, and experiencing products and services, powered by data.

The five factors driving intelligent industry

Digital transformation will remain a top priority for companies in 2020 just like it was in 2018 and 2019. And if a firm is involved in manufacturing, its focus will undoubtedly be on Industry 4.0, which has helped manufacturers improve revenue and reduce cost of goods sold (manufacturing, freight costs, etc.) and other indirect expenses while contributing to significant working capital (think inventory) improvements, thereby strengthening corporate balance sheets (pro tip: bringing the CFO on board in Industry 4.0 initiatives increases the likelihood of their success manifold).

So, is there life after Industry 4.0? Though Industry 4.0 has yet to reach its full potential, at Capgemini we believe that it will evolve into its next avatar – intelligent industry. In this two-part blog series, I outline the contours of intelligent industry and talk about the factors driving its rapid adoption. In the next part of my blog series, I will discuss how companies stand to benefit from the intelligent industry wave and share some tips for manufacturers on how to ride it.

Intelligent industry (n): pioneering new ways of designing, manufacturing, operating, and experiencing products and services, powered by data. As the definition states, firms will become insights-driven organizations across both product development (what we call Engineering 4.0) and the entire manufacturing and operations lifecycle. “Siloism” will be shunned, high levels of automation will be reached, and hyper-personalization will be the norm – resulting in highly efficient firms.

So, what are the enabling factors that are making the intelligent industry a reality?

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 (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 situations such as autonomous vehicles or compressors scattered 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 really embraced packaged software – be it ERPs, or 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 vendors 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 the deployment of business capabilities in the form of microservices. This is a significant shift for an industry that is more used to slower change, generally relies on a traditional waterfall approach, and has not fully recovered the cost of long and complex transformations. Such manufacturers have to take the APIfication 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.

Now that we have covered the key drivers making intelligent industry a reality, in the second part of this series, we will discuss what this means for manufacturers (beyond financial metrics) and how they should gear up to benefit from it.

Read more about the Intelligent Industry offer here.

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