How to implement an effective strategy in the 4.0 industry?

This article is based on knowledge insights by Carles Roig

If you're wondering what the Industry 4.0 is, here's how it's defined: it's about developing new technologies and driving forms of intelligence that enhance skills. Companies that want to improve their chances of success can adopt seven recommendations for implementing an effective Industry 4.0 strategy.

In this changing environment, there is a growing need to reindustrialise the Western world. The Industrial Revolution 4.0 poses new challenges and opportunities that companies must seize.

"The complexity of the environment and the opportunities globalisation offers demand the development of new attributes on which to build the industrial future," says Esade Associate Professor Carles Roig.

What attributes should this Industry 4.0 have? According to Roig, businesses that want to thrive in this environment should develop a series of new attributes that target:

1. Speed and flexibility of response.
2. New formulas for collaboration and relations.
3. Greater and better use of databases and sources of information.
4. Implementation and good use of new manufacturing technologies.
    

Industry 4.0 objectives and applications

The definition of Industry 4.0, established in 2011, is often associated with the development and adoption of new technologies that are advancing at a rapid pace. This Industrial Revolution 4.0 is based on automation, connectivity through the Internet of Things (IoT) and Big Data, which drives greater efficiency at all levels of production.

The Industry 4.0 principles include process automation, the use of Big Data for informed decision-making, the Internet of Things, among others. These principles are the basis on which companies can transform their operations, making them more agile, efficient and adaptable to market demands.

Big data in Industry 4.0

The exponential increase in data and the development of advanced software are expanding the possibilities of generating knowledge at the service of decision-making.

You may be interested in our article→ Big Data in business management.

IoT

These are new ways of connecting information and improving the transmission of data in real time to stimulate interaction between humans and technological devices.

Additive technologies

These disruptive technologies, based on robotics and 3D production, are making way for large-scale product customisation and cost reduction.

Task management

Task management in Industry 4.0 has evolved with the incorporation of smart technologies that automate and optimise the allocation and tracking of tasks within production processes. Through advanced tools such as ERP systems, cloud-based collaboration platforms and AI-based applications, companies can coordinate teams more efficiently and in real time.

Automation

Automation in Industry 4.0 involves the integration of advanced technologies such as robotics, artificial intelligence and machine learning, which enable automated manufacturing processes and optimisation of the production chain. This not only reduces the margin for human error, but also improves operational efficiency.

Data analytics

Data analytics in Industry 4.0 is based on the use of Big Data tools and artificial intelligence to process and analyse large volumes of information generated in real time by connected devices. Thanks to advanced analytics, companies can make informed decisions, predict behaviour and optimise production, reducing downtime and improving product quality.

‘The main objectives of Industry 4.0 focus on three key aspects: improving efficiency at the operational level, optimising the design and governance of the value chain and developing new business models,’ explains Roig.

Large companies are already adopting Industry 4.0 strategies, implementing solutions based on IoT, automation, and data analytics. These examples of Industry 4.0 are transforming operations and creating new business opportunities.

New forms of intelligence and competencies

The impact of the Industry 4.0 requires the development of new forms of intelligence that stimulate skills and allow the new challenges of the 4.0 supply chain to be met.

"From a demand viewpoint, this means improving the capacity to interact with customers, that is, including them and giving them a participatory role in production processes in order to personalise the range of products and services offered, and also to develop business models based on customers' needs," says Roig

Industry 4.0 involves developing new forms of intelligence

From a supply point of view, the increased complexity of the supply chain must be compensated by developing business ecosystems equipped with the best instruments for connectivity and information transmission, but in particular by new criteria for recruitment, management and collaboration between their members.

"A swift and personalised response is prioritised over low unit costs, while the capacity to generate dynamic relationships is prioritised over the establishment of static relationships based on long-term contracts."

7 key recommendations on implementing an Industry 4.0 strategy

The research findings outline seven key recommendations that businesses can follow to implement an Industry 4.0 strategy and improve their chances of thriving in this new digital scenario.

1. Plan the scope of your business and align your goals with the company's general strategy. Clearly define what your goals are and prioritise your actions based on: improving your operations' effectiveness, optimising your value chain and evaluating the possibility of creating new business models.
2. Facilitate a work environment that promotes an open mentality oriented towards learning, change and experimentation.
3. Define the competencies that need to be developed, both internally and with external providers.
4. Recruit and manage talent, prioritising multidisciplinary teams and the capacity to turn data analysis into a strong asset.
5. Select a team of providers with tested technologies to start growing the optimal network of partners.
6. Adopt an ecosystem perspective and develop network management abilities.
7. Start with pilot projects, validate results and systematise the learning mechanisms.