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Industry 4.0 is coming. The increasing digitisation of manufacturing is already happening, through a combination of technologies, including the Internet of Things, big data, analytics, and next-generation applications.
The development of smart factories with secure, flexible and scalable manufacturing processes will bring a raft of benefits that will take companies to a new level with their operations. McKinsey Global Institute predicts that the annual economic impact of operations and equipment optimisation through the use of IoT will range between $1.2T−3.7T in 2025.
Among the new and powerful capabilities that Industry 4.0 promises are the identification of faults before they develop; increased efficiency and productivity; optimised product development and supply chains; and improved health and safety (e.g. by utilising remote access to take people out of potentially hazardous environments).
Realising these benefits will require a significant shift however, not only in terms of how organisations use the data they create, but also in terms of how they share that data across traditionally siloed business departments. This is uncharted territory for the manufacturing industry, and whilst the rewards are significant, the challenges are also numerous.
One fundamental barrier preventing organisations from moving towards and industry 4.0 model lies in the way they are structured. To create products and get them to customers, manufacturers perform a wide range of activities, which generally take place in a standard set of functional units: research and development (or engineering), IT, manufacturing, logistics, marketing, sales, after-sale service, human resources, procurement, and finance.
Before products became smart and connected, data was generated primarily by internal operations and through transactions across the value chain—order processing, interactions with suppliers, sales interactions, customer service visits, and so on.
The responsibility for defining and analysing data tended to be decentralised within functions and siloed. Though functions shared data (sales data, for example, might be used to manage service parts inventory), they did so on a limited, episodic basis. By combining the data, companies knew something about customers, demand, and costs—but much less about the functioning of products.
Now, for the first time, these traditional sources of data are being supplemented by another source—the product itself. Smart, connected products can generate real-time readings that are unprecedented in their variety and volume.
This data has inherent value of its own in the production cycle, yet its value increases exponentially when it is integrated with other data, such as service histories, inventory locations, commodity prices, and traffic patterns. As the ability to unlock the full value of data becomes a key source of competitive advantage, organisations are looking at ways to break down traditional siloes and turn vast quantities of unstructured data into powerful insights.
Occasional cross-departmental collaboration and data-sharing is no longer sufficient. Intense, ongoing coordination becomes necessary across multiple functions, including design, operations, sales, service, and IT.
A unified data lake
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