6 trends driving digitalization in the manufacturing industry

A major challenge facing manufacturing CIOs lies in pinpointing exactly which digitalization trends will both support their business strategy and integrate into existing processes. In this article, you’ll find out the biggest trends and technologies influencing digital transformation in the manufacturing industry, and the key topics for CIOs to watch.

When asked which technologies they were most likely to have implemented by 2025, most manufacturing CIOs cited in a recent Gartner¹ survey “AI and ML” — a finding confirmed by numerous other surveys. Other frequently mentioned topics include cloud computing, security, the Industrial Internet of Things (IIoT), Industry 5.0 and automation. We’ve put together a rundown of the trends that no leader should leave off their digitalization agenda.

Artificial intelligence has arrived in manufacturing. In 2021, almost two-thirds of companies in this sector were already using AI in their daily operations² for use cases such as:

Error detection and quality control
AI is able to analyze real-time data to detect and document errors and deviations occurring in production processes. A company using an AI-assisted information management system, for example, can set up AI to automatically gather the relevant information and generate reports that comply with documentation requirements.

Supply chain management
AI-powered automation enhances efficiency and speeds up processes along the entire supply chain: intelligent content automation platforms can automate order-entry and invoicing tasks, deliver a 360° view of suppliers, and make communication and collaboration with suppliers easier. 

Risk management
AI can streamline supplier assessments to mitigate risks both within and outside of the supply chain. One requirement is that all relevant information must be available to the AI algorithm in an electronic supplier file.

Inventory management
Smart warehousing seamlessly integrates the Internet of Things, robotic process automation and AI to enhance productivity, quality and efficiency. And the process doesn’t have to stop in the warehouse: ECM systems connect inventory management with, for example, the finance department to automate the entire purchase-to-pay process.

The hype surrounding ChatGPT from OpenAI is a prime example of how AI and ML are advancing at a rapid pace and steadily gaining traction in the public eye. Content management, too, reaps substantial benefits from AI through better text comprehension and extraction. For example, the Doxis Intelligent Content Automation platform has the following capabilities:

• Recognize and classify an email arriving in the digital inbox as an invoice, extract the essential data, reconcile the invoice with the order and goods received, and even initiate the payment process.
  
  
• Identify and classify another email as relevant for the customer service team, summarize key information and launch the corresponding service process.
  
  
• Smart assistants, or cobots, such as SER’s smart content assistant Doxi, enhance the user experience by giving users relevant information in the right context and offering useful interactive options. Cobots trained using data specific to the company and sector deliver more precise results and enable process optimizations that are tailored to the customer’s use case. 

With new, powerful AI and ML services emerging in ever-shorter cycles, the key is to integrate them into the existing IT landscape with short lead times so as not to potentially put competitiveness at risk. The challenge for CIOs is in migrating oftentimes long-running projects and processes to innovative AI tech. For maximum flexibility, companies should choose software and platform solutions with a plugable architecture that are capable of seamlessly integrating AI and ML as a service without disrupting operations.

A shift to cloud computing is an almost inevitable step in deploying standardized AI solutions — and the reason why cloud technology is still considered a catalyst for digital transformation, with over 80% of mid-sized to large companies opting for a multi-cloud strategy.³ While this allows businesses to cherry-pick the best services from different vendors, at the same time they must be careful not to create data silos that obstruct the necessary flow of information.

Cloud software solutions without APIs for integrating third-party software are not competitive in the long run. Solutions should instead integrate easily and seamlessly into existing processes and business applications. Like Doxis, for instance, which integrates into numerous applications from leading vendors, from SAP and Salesforce to Microsoft, to create a central information management platform and enable cross-area process automation.

With the costs of cybercrime expected to hit eight billion US dollars⁴, IT security is high up on the investment lists of global companies. As hyperscalers like Google, Microsoft and AWS double down on security, experts predict a shift toward greater industrialization and automation in this area — from which businesses will benefit. SaaS platforms, too, can contribute to greater protection by encrypting data and documents and offering intelligent authorization concepts.

The Industrial Internet of Things connects sophisticated objects used in manufacturing and production processes — sensors, devices, embedded systems in machines, etc. — with IT applications like ERP, PLM, or customer order management platforms. These objects and systems usually communicate with each other independently and the information they collect is forwarded automatically.

For companies, the benefits to IIoT connectivity range from less downtime, lower maintenance costs and better workplace security, to the ongoing optimization and automation of production processes, and more besides. The better the interconnectivity between the company’s IT ecosystems, the more other departments outside of production also profit.

This is made possible when the information delivered by the machines and objects is stored in a central repository that serves as a single source of truth. Meaning that if a problem then occurs with, e.g., a product, colleagues in customer service directly find all the information they need via an intelligent content automation platform.

The use of intelligent automation in combination with IIoT and robotics to optimize processes and relieve the pressure on employees is now commonplace in industrial production. But intelligent automation can benefit the organization and employees in ways beyond the production process — through automated customer inquiry processing, in life-cycle management, in the purchase-to-pay process, and in other areas, too. A centralized ECM platform such as Doxis integrates into existing ecosystems, breaks down information barriers, enables end-to-end process automation and provides employees with the right information in the right context.

Industry 4.0 is all about intelligently networking information and communications technologies. Companies are able to use data analytics to gain valuable insights into their huge stores of data to optimize processes and more. Industry 5.0, on the other hand, is not an industrial revolution, but rather the human-centric evolution of new technologies like AI, augmented reality (AR) and virtual reality (VR). Given the colossal volumes of data being generated, a central information management system is an important tool for giving people quick and easy access to information. This requires collaboration between people, and collaboration between people and smart machines.

Continuing to digitally transform business and production processes is an effective tool for overcoming the challenges facing the manufacturing industry. Industrial companies invest over one trillion euros a year in digital solutions, and in more than just new technologies. A recent PwC survey⁵ found that investments in the digital backbone and enabling technologies can also expect solid returns. Not least because good infrastructure and the constant and end-to-end availability of data and information are the basis for successful digital transformations.

In recent years, digitalization projects in the manufacturing industry have tended to focus on cutting costs and enhancing efficiency, achieved mainly through the automation of production activities. This trend has shifted focus to the human element. Elon Musk, CEO of Tesla, has said that in hindsight the excessive automation within his company was a mistake, adding: “Humans are underrated.”⁶

Companies are now increasingly placing employees at the center of their digitalization initiatives with the aim of reclaiming time for them to focus on core tasks. Such efforts can produce a future-proof organization that Forrester⁷ says is not only adaptable, creative and resilient, but also successfully navigates the balance between software, hardware and humans. Information — its creation, analysis and creative use — is at the center of this trifecta. Intelligent content automation platforms with diverse integration capabilities fulfill this central role and support businesses by enabling automated processes, end-to-end information management, a multitude of collaboration features and more.

1. Gartner, 2023 CIO Agenda Insights for the Manufacturing Industry: How your peers are investing in tech to deliver on digital initiatives, 2022

2. Google Cloud-Branchen: Beschleunigung der künstlichen Intelligenz bei Fertigungsunternehmen, 2021 

3. https://www.statista.com/statistics/1245569/multi-cloud-adoption-organization-size-worldwide/

4. https://cybersecurityventures.com/stats/

5. PwC, Digital Factory Transformation Survey 2022, June 2022

6.  https://twitter.com/elonmusk/status/984882630947753984

7. Forrester, Smart Manufacturing: Don’t Forget The People, 2022