Deploying new technology such as IIoT in manufacturing is challenging largely because of the unknown – threat to impact jobs, finding right data to make decisions, unclear return on investment, security concerns, … So what are the guiding principles to introduce IIoT?

1. Don’t fall for the shiny-object syndrome. Fundamental factors for success include a clear focus on a pain point where your proof of concept can create immediate value rather than a place where digitalization is simple to implement.
2. Proving return on investment. Find a balance between fast and risky implementation and slow and missed opportunities. One needs a combination of agile business case planning and a frugal implementation journey to scale where value can be created.
3. Have an innovation portfolio strategy. Make quick, informed decisions about what initiative to stop, continue, and accelerate. Not only address transformation for optimization but also include transformation that creates value through new services or new business models.
4. Use the lean innovation mantra: plan big, start small, and scale fast. Once an impactful project identified, scale that proof of concept to a larger area where additional value can be created. Follow step-by-step experimentation.
5. Engage all stakeholders. Include operators in the design, pilot, and scaling phase. Provide sufficient training to get acceptance and success. Involve all stakeholders so they co-own new developments. Change management is only thriving if rooted from the bottom. Invest in communication.
6. IIoT is an end-to-end play. It is a complex interworking between devices, edge and cloud infrastructure, the right data, an analytics capability (AI), and the appropriate security infrastructure.
7. The right data. Data needs to be structured to make the right decisions. Explain what data is gathered and how it is used by AI systems (explainable AI). Ensure privacy is understood and maintained as sensors gather data on the workers.