Industry 4.0 benefits and challenges across all three business model elements in social dimension of sustainability
| Business model dimension | Benefits | Challenges |
|---|---|---|
| Value creation | Enhancing the user experience by developing innovative, personalised and safe products. Improving access to healthcare services and promoting smart agriculture, providing the growing population with a food security | Ethical implications associated with robots and AI technologies replacing humans in work, which shows high potential for social disruptions. IA algorithms can inherit biases from the data they are trained on, resulting in biased decision-making and unfair outcomes |
| Value delivery | Greater control and visibility over the supply chain by using data to track product conditions and monitor system failures to predict customer needs, meaning companies can deliver products and services faster and with better quality | Data collection and analysis raises concerns about individuals’ privacy and data protection. Organisations must prioritize ethical data practices, ensuring that consent is obtained, data is securely stored and used for legitimate purposes |
| Value capture | New revenue streams through innovative products and subscriptions of digital services. Lower costs through greater automation and better visibility allow savings to be passed on to customers | Balancing the technological unemployment in manufacturing routine and non-routine tasks, and start investing on high skill education for more knowledge-based jobs is a long-term investment |
| Business model dimension | Benefits | Challenges |
|---|---|---|
| Value creation | Enhancing the user experience by developing innovative, personalised and safe products. Improving access to healthcare services and promoting smart agriculture, providing the growing population with a food security | Ethical implications associated with robots and AI technologies replacing humans in work, which shows high potential for social disruptions. IA algorithms can inherit biases from the data they are trained on, resulting in biased decision-making and unfair outcomes |
| Value delivery | Greater control and visibility over the supply chain by using data to track product conditions and monitor system failures to predict customer needs, meaning companies can deliver products and services faster and with better quality | Data collection and analysis raises concerns about individuals’ privacy and data protection. Organisations must prioritize ethical data practices, ensuring that consent is obtained, data is securely stored and used for legitimate purposes |
| Value capture | New revenue streams through innovative products and subscriptions of digital services. Lower costs through greater automation and better visibility allow savings to be passed on to customers | Balancing the technological unemployment in manufacturing routine and non-routine tasks, and start investing on high skill education for more knowledge-based jobs is a long-term investment |